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Chemical engineering education

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Title:
Chemical engineering education
Alternate Title:
CEE
Abbreviated Title:
Chem. eng. educ.
Creator:
American Society for Engineering Education -- Chemical Engineering Division
Place of Publication:
Storrs, Conn
Publisher:
Chemical Engineering Division, American Society for Engineering Education
Publication Date:
Frequency:
Quarterly[1962-]
Annual[ FORMER 1960-1961]
quarterly
regular
Language:
English
Physical Description:
v. : ill. ; 22-28 cm.

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Subjects / Keywords:
Chemical engineering -- Study and teaching -- Periodicals ( lcsh )
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serial ( sobekcm )
periodical ( marcgt )

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Citation/Reference:
Chemical abstracts
Additional Physical Form:
Also issued online.
Dates or Sequential Designation:
1960-June 1964 ; v. 1, no. 1 (Oct. 1965)-
Numbering Peculiarities:
Publication suspended briefly: issue designated v. 1, no. 4 (June 1966) published Nov. 1967.
General Note:
Title from cover.
General Note:
Place of publication varies: Rochester, N.Y., 1965-1967; Gainesville, Fla., 1968-

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University of Florida
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All applicable rights reserved by the source institution and holding location.
Resource Identifier:
01151209 ( OCLC )
70013732 ( LCCN )
0009-2479 ( ISSN )
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TP165 .C18 ( lcc )
660/.2/071 ( ddc )

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Chemical Engineering Documents

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chemical engineering education




VOLUME 33 NUMBER 4 FALL 1999




GRADUATE EDUCATION ISSUE


SFeature Articles...
SGetting the Most Out of Graduate School (pg. 258), Rajagopalan
K | A ChE Graduate Course in Materials Design (pg. 262), Mitchell
SA Survey Course In Particle Technology (pg. 266), Sinclair
Experiences With an Experimental Project in a Graduate Control Course (pg. 270)
Gatzke, Vadigepalli, Meadows, Doyle

Essay: Universities...Why? (pg. 288)
"i IHaile
Particle Technology on CD (pg. 282)
SRhodes
SHow to Lie With Engineering Graphics (pg. 304)
" Vesilind
* I Computer Simulation of Tracer Input Experiments (pg. 300)
i .8 Conesa, et al.
t Designing a Petroleum Design Course in a Petroleum Town (pg. 322)
SYarranton, Svrcek
Activities to Enhance Understanding of the Mole and Its Use in ChE (pg. 332)
Fraser, Case
. I A Phenomena-Oriented Environment for Teaching Process Modeling (pg. 292)
a Foss, Geurs, Goodeve, Dahm, Stephanoloulos, Bieszczad, Koulouris
5 AActive Learning vs Covering the Syllabus and Dealing With Large Classes (pg. 276)
it a Felder, Brent
I Class and Home Problems: Beware of Bogus Roots With Cubic Equations of State (pg. 278)
S I Pratt
SIntroducing Process Control Concepts to Senior Students Using Numerical Simulation (pg. 310)
.4 o |Aluko, Ekechukwu
S Using a Cogeneration Facility to Illustrate Engineering Practice to Lower-Level Students (pg. 316)
Hesketh, Slater
Low-Cost Experiments in Mass Transfer: Part 5. Desorption of Ammonia from a Liquid Jet (pg. 328)
Baird, Nirdosh

W-1999 Awards: ASEE ChE Division (pg. 287)









Index

to

Graduate Education
Advertisements


can be found on

pages 336-337













EDITORIAL AND BUSINESS ADDRESS:
Chemical Engineering Education
Department of Chemical Engineering
University of Florida Gainesville, FL 32611
PHONE and FAX: 352-392-0861
e-mail: cee@che.ufl.edu
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T. J. Anderson

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Colorado School of Mines

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Colorado School of Mines
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University of Texas at Austin
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Chemical Engineering Education

Volume 33 Number 4 Fall 1999


> GRADUATE EDUCATION
258 Getting the Most Out of Graduate School, Raj Rajagopalan
262 A ChE Graduate Course in Materials Design, Brian S. Mitchell
266 A Survey Course in Particle Technology, Jennifer L. Sinclair
270 Experiences With an Experimental Project in a Graduate Control Course,
Edward P. Gatzke, Rajanikanth Vadigepalli, Edward S. Meadows, Francis J.
Doyle, III

> RANDOM THOUGHTS
276 FAQS. II: Active Learning vs Covering the Syllabus and Dealing With Large
Classes, Richard M. Felder, Rebecca Brent

> CLASS AND HOME PROBLEMS
278 Beware of Bogus Roots With Cubic Equations of State, Ronald M. Pratt

> CURRICULUM
282 Particle Technology on CD, Martin J. Rhodes
322 Designing a Petroleum Design Course in a Petroleum Town,
H.W. Yarranton, W.Y. Svrcek

> ESSAY
288 Universities...Why?, J.M. Haile

> CLASSROOM
292 A Phenomena-Oriented Environment for Teaching Process Modeling: Novel
Modeling Software and Its Use in Problem Solving,
Alan S. Foss, Kevin R. Geurts, Peter J. Goodeve, Kevin D. Dahm, George
Stephanoloulos, Jerry Bieszczad, Alexandros Koulouris
300 Computer Simulation of Tracer Input Experiments,
J.A. Conesa, J. Gonzdlez-Garcia, J. Iniesta, P. Bonete, M. Inglis, E. Expdsito,
V. Garcia-Garcia, V. Montiel
310 Introducing Process Control Concepts to Senior Students Using Numerical
Simulation, Mobolaji E. Aluko, Kenneth N. Ekechukwu
316 Using a Cogeneration Facility to Illustrate Engineering Practice to Lower-Level
Students, Robert P. Hesketh, C. Stewart Slater
332 Activities to Enhance Understanding of the Mole and Its Use in ChE,
Duncan M. Fraser, Jennifer M. Case

> ETHICS
304 How to Lie With Engineering Graphics, P. Aarne Vesilind

> LABORATORY
328 Low-Cost Experiments in Mass Transfer: Part 5. Desorption of Ammonia from
a Liquid Jet, M.H.I. Baird, I. Nirdosh

> 287 1999 Awards: ASEE ChE Division
I 336 Index of Graduate Education Advertisements


CHEMICAL ENGINEERING EDUCATION (ISSN 0009-2479) is published quarterly by the Chemical Engineering
Division, American Society for Engineering Education, and is edited at the University of Florida. Correspondence
regarding editorial matter, circulation, and changes of address should be sent to CEE, Chemical Engineering Department,
University of Florida, Gainesville, FL 32611-6005. Copyright 0 1999 by the Chemical Engineering Division, American
Society for Engineering Education. The statements and opinions expressed in this periodical are those of the writers and
not necessarily those of the ChE Division, ASEE, which body assumes no responsibility for them. Defective copies replaced
if notified within 120 days of publication. Write for information on subscription costs and for back copy costs and
availability. POSTMASTER: Send address changes to CEE, Chemical Engineering Department., University of Florida,
Gainesville, FL 32611-6005. Periodicals Postage Paid at Gainesville, Florida.


Fall 1999








Graduate Education


GETTING



THE



MOST



OUT



OF



GRADUATE



SCHOOL


RAJ RAJAGOPALAN
University of Florida
Gainesville, FL 32611-6005



Raj Rajagopalan is Professor of Chemical
Engineering at the University of Florida, where
he has been since 1996. His research activi-
ties focus on colloid physics and complex flu-
ids. In addition, he maintains an active interest
in teaching, at both
undergraduate and
graduate levels. His
educational activi-
ties include the co-
author-ship of a
textbook on colloids
and the develop-
ment of other in-
structional materi-
als.


Copyright ChE Division of ASEE 1999


What you learn in graduate school can be the foundation for a life-long
learning experience and a successful career, but it takes more than a
good undergraduate preparation and a desire to get an advanced de-
gree to get the most out of graduate school. The following are some bits of advice
and recommendations based on my own experience-as a student and as a faculty
member-and on what I have learned from my students.
Although my comments are addressed largely to graduate students in science
and engineering, many of the observations should be of use to all graduate
students regardless of the discipline. Some of the books in the list of annotated
references at the end of this article have detailed guidelines on specific issues you
may face during your studies and beyond. One of the books, by Carl Djerassi, a
renowned chemist, is a fictionalized account of the competition and personal,
professional, and ethical issues faced by graduate students and faculty involved in
day-to-day research. Another, by James Watson of the DNA fame, is a real-life
story that reads almost like fiction. I have included these two books so that you
have more than a list of dry, self-help books. These two books may possibly teach
you more than all the other books put together.
ATTITUDE MAKES A DIFFERENCE
The first and foremost factor is the attitude one brings to one's life. A major part
of how successful we are in what we set out to do in life often depends on our
attitude. Someone who feels like a "winner" is more likely to be a winner; one
who feels like a victim is likely to end up being one. Most people I have talked
with recall their student years as among the best years of their lives, but how much
you get out of school, professionally and otherwise, depends to a large extent on
what expectations, commitment, and discipline you have and how much you
demand from yourself. Here are some points to ponder:
First, know what to expect from graduate school and what commitments and
responsibilities are expected of you.
Do not postpone learning essential professional skills and basic "life skills"
until you get a job or leave graduate school. For example, I have known many
students who have, either consciously or subconsciously, postponed learning
good communication skills, social skills needed for teamwork, and building a
network of peers-only to regret it later.
As a research student, you are a junior research colleague of the faculty. This
is a privilege, but one that comes with certain responsibilities and account-
ability. Be aware of them.

LEARN GOOD WORK HABITS
Discipline Matters
> Graduate research is about generating or implementing new concepts. It is not
a nine-to-five job. Most successful students I know put in at least seventy
hours a week. Expect to work hard, and expect to spend long hours.
- Keep good laboratory notebooks. Divide them into sections, e.g., one for
research papers you read, one for your own work, etc. When you read a
research article, write down the full reference in your research notebook, cut
and paste a xerox copy of the abstract into the notebook, summarize the salient
Chemical Engineering Education









Graduate Education


points and major results, cut and paste key figures and
tables (along with your own annotations), summarize
major questions of interest to you, and make a list of
important cross-references. (You may also want to write
down the dates to make the research notebook a "jour-
nal" of your thoughts and progress.) You'll appreciate
the value of this habit when you are ready to write up
your results for publication or when you write your the-
sis. If you are copying something verbatim from a publi-
cation, make a note that it is a verbatim record, to avoid
later using it inadvertently in your own work without
giving proper credit to the original source. (See my com-
ment later on plagiarism.)
> Spend at least one day a week in the library. It is your
responsibility to keep up with the literature. (It is your
research and your thesis.) Do not expect your research
advisor to do it for you. Take ownership of your project.
- Attend seminars and learn from the experts. Observe
what techniques the speakers use to make their presenta-
tions engaging and understandable. Also observe what
mistakes they make and avoid them in your own presen-
tations. Attend the seminars even if the talks are not on
your research topic-you never know what connections
you can make to your own work or how what you learn
from the talks can help you later in your career.
- Stay focused on your research, but learn about areas
other than your own. The market is fluid, and a typical
employer often wants someone who has a broader back-
ground than the one defined by your specific work. Do
not expect to work on the same problem you studied for
your MA, MS, or PhD when you go into the workforce.
Remember that graduate school is about "learning to
learn" on one's own.
- If your stipend comes from a research grant to your
advisor, learn about the expectations and deadlines the
funding agency places on your advisor. Understand what
pressures your advisor faces in keeping the funds flowing.

Form Networks: Learn from Others
- Take the initiative and form a "journal club" or "research
colloquium club" with other graduate students who have
similar interests. Conduct regular discussion meetings to
learn from each other (and to develop presentation skills).
Use the journal club and similar activities to form a
collegial network of your peers. You never know when
you might need the help of one of your schoolmates!
> Get to know the faculty on your thesis committee and
others from whom you have taken classes. In general,
get to know as many faculty members as possible from
within and outside your department. Make it a point to
meet with them periodically to seek their advice and to
learn from their experiences. Not only do you broaden


Fall 1999


your experience by doing this, but you also create a pool
of faculty members who know you well enough to write
meaningful letters when you need one.
> Form a "global network." If you have questions about a
paper you are reading, write to the authors. Most authors
are pleased to respond. Do not, however, be discouraged
if you do not hear from them-the world is not perfect.
- Attend a few national or international professional meet-
ings in your discipline, even if you have to pay for the
expenses. It is an investment in your future and money
well spent. Use your attendance to meet and to get to
know experts from outside your institution.
> Seek balance in what you do. If you are doing theoretical
work, learn the relevant experimental issues. If you are
an experimentalist, try to get a perspective on the theo-
retical issues. Remember that "theory" does not neces-
sarily mean "dealing with equations." Mathematics is a
language and a medium to achieve an end.
- Seek education beyond the classroom or your research
work. Learn to observe and listen. If you have the right
attitude, you can learn from everyone and from every
experience, positive as well as negative.
College life offers you an opportunity unmatched by any
to broaden your horizon. Break the barriers. Attend talks
or seminars in disciplines very different from yours. For
example, if you are in the "hard" sciences, attend some
seminars in cultural anthropology, art criticism, linguis-
tics or the like. Learn how scholars in the "soft" sciences
approach their research.

Deal with Difficulties Head On; Strive to Stay Positive

> Research is a solitary activity. Do not always expect
others to get excited about what you find exciting. You
can minimize the "isolation" if you build a network of
interested individuals as I suggested earlier.
> Research is full of ups and downs (more downs than ups,
normally), and the key to success is to learn to bear with
or overcome the downs. Try hard to stay motivated. If
you are feeling down, take a break, do something you
enjoy, and then return to your work. If you think you
need someone to cheer you up or urge you on, talk to one
of your friends or see your research advisor and ask
for advice or help. Divide your work into manageable
portions, and make sure that you make progress in at
least one of them on a regular basis. Even incremen-
tal progress is better than none at all and will keep
you motivated.
0 Take a course on "time management." Most people
can use one.
If you feel that you are constantly under stress and have
259










Graduate Education


difficulty coping, deal with it head on. Talk with a sym-
pathetic friend or with your research advisor or a faculty
member. Take a course on stress management. There are
many self-help books available on both time- and stress-
management, and they can be useful. Most universities
provide professional counseling for students with prob-
lems and run seminars on time-management (among
other things, such as public presentation, interpersonal
skills, and conflict resolution),
usually free of charge. Take TA
advantage of these. References and Web S
- It is not unusual to have differ-
ences of opinion with your ad- Books
visor. You may even "dislike" Alley, M., The Craft of Scie
your advisor sometimes. It is Verlag, New York, NY (1
r Booth, W.C., G.G. Colomb,
natural. It is only human. But Research, University of C
you'll find that in the end the (1995)
overall positive experience will Brusaw, C.T., G.J. Alred, al
Technical Writing, 4th ed.
overcome difficulties you face NY (1993)
along the way. It is how you Day, R.A., How to Write an
respond to setbacks that deter- ed., Oryx Press (1994)
mines your success and the Dodd, J.W., ed., The ACS S
Authors and Editors, 2nd
quality of your life. Washington, DC (1997)
SMatthews, J.R., J.M. Bower
Pay Attention to Ethics Successful Scientific Writii
- Research is a human endeavor Cambridge UK (1996)
and is not always an objective Strunk, Jr., W., and E.B. W
ed., Allyn and Bacon, Bos
search for the truth, but do not
let that discourage you or make Technical Writing Internet
you bend the rules. Strive for Online Writing Lab, Purdu
the highest standards. http://owl.english.pur
Grammar Hotline Directory
0 Pay attention to professional http://www.tc.cc.va.u
ethics. Make sure you are Strunk & White's Elements
aware of the rules of author- http://www.columbia
WWWebster Dictionary
ship of publications. Acknowl- http://www.m-w.com,
edge in your publications those WWWebster Thesaurus
who have provided assistance http://www.m-w.comr
in your work (be generous, but *Technical Writing: Books a
http//www.interlog.cc
get their permission). htwww.
- If you use ideas or results of others, do not forget to cite
the relevant (primary) references. If you use someone
else's writing verbatim, follow the copyright require-
ments. Do not forget to give proper credit. When you are
writing your thesis or papers, it is easy to transfer sen-
tences you may have copied into your notebook from
other sources without attribution. In our profession there
is no greater sin than plagiarism, i.e., trying to get, even
unintentionally, credit for someone else's ideas.

MASTER COMMUNICATION SKILLS
Our profession is about generating ideas and communicat-
ing them to others. You fail if you are poor in either; that is,
you can fail even when you are good at what you do, but are


unable to communicate your achievements to others. I have
known many individuals who have advanced rapidly in their
jobs largely due to their communication skills.
- Do not underestimate the importance of writing effec-
tively and elegantly. Reading only technical articles or
articles in your own profession tends to decrease your
verbal skills and vocabulary. Make it a habit to read, on
a regular basis, the works of authors known for their
command of the language. If you
E 1 are in the sciences or engineering,
rn Technical Writing read well-written popular science
articles in magazines (e.g., Discover,
The New Scientist, Scientific Ameri-
Writing, 3rd ed., Springer- can, etc.) to learn how professional

.M. Williams, The Craft of writers avoid jargon and communi-
Press, Chicago, IL cate complicated concepts in an en-
gaging style. Identify also some
E. Oliu, Handbook of well-known authors of non-techni-
lartin's Press, New York,
martins Press, New York, cal material and read their works

lish a Scientific Paper, 4th periodically so that you keep your
verbal skills honed.
ide: A Manual for c Good writing requires clear think-
ing. Practice writing short summa-
R.W. Matthews, ries of long articles or scholarly es-
imbridge University Press, says at a level accessible to a novice.
e E s of 3 Table 1 contains a list of books and
he Elements of Style, 3rd
IA (1979) internet sites on effective writing.
Try to be gender-neutral in your
ersity, West Lafayette, IN writing. It is not a matter of being
lu/ fashionable or being "politically cor-
rect." It is a matter of recognizing,
:ent/gh/index.htm respecting, and encouraging the par-
yle
cis/bartleby/strunk ticipation of both sexes in our pro-
fession.


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Chemical Engineering Education


t.ntm Learn to make oral presentations
rus.htm effectively. This includes knowing
ference Sources how to organize your thoughts logi-
oltys/twritres.html cally and how to prepare effective
viewgraphs and knowing the proper
body language. If you need help, join a public presenta-
tion group such as the Toastmasters Club (see http://
www.toastmasters.org). Make periodic presentations to
your research group and ask your friends and advisor to
criticize your presentation (constructively).
0 In your presentations, focus on your work but present
your results in the context of the broader scope of your
research group and those of others elsewhere. Doing so
is much more impressive to, for example, a prospective
employer, for it shows that you understand the broader
context of your work and that you have the initiative to
learn the broader context of whatever you are assigned.
> Learn to be effective in a group setting. Learn the social


u
s










I Graduate Education


SOME USEFUL REFERENCES

E[ Careers in Science and Engineering: A Student Planning
Guide to Grad School and Beyond, National Academy Press,
Washington, DC (1996)
(A planning guide for students considering entering graduate school
or in graduate school. Gives real-life examples of career paths of
scientists and engineers. Contains short case studies of different
career paths and lists of "action points." You can read this book in
the electronic reading room at www.nap.edu.)
E[ On Being a Scientist: Responsible Conduct in Research,
National Academy Press, Washington, DC (1995)
(Advice on professional, personal, and ethical issues that a gradu-
ate student or a beginning researcher faces. Presents a number of
hypothetical, open-ended scenarios designed to draw attention to
ethical issues one may face in research. You can read this book in the
electronic reading room at www.nap.edu.)
E Feibelman, P.J., A PhD Is Not Enough: A Guide to Survival
in Science, Addison-Wesley, New York, NY (1994)
(A concise and easy-to-read volume on what it takes to be success-
ful, especially in an academic career.)
E Medawar, P.B., Advice to a Young Scientist, Basic Books,
New York, NY (1981)
(Advice from a Nobelist to graduate students and scientists in the
early stages of their careers.)
E Watson, J.D., Double Helix: A Personal Account of the Dis-
covery of the Structure ofDNA, G.S. Stent, ed., W.W. Norton,
New York, NY (1980)
(An engaging record of the author's perspective of the competition,
the excitement, and the human side of science in action, written
almost like a racy novel. This special Norton edition, edited by
Stent, a well-known molecular biologist himself, has a number of
critical reviews of Watson's book and additional opinions by other
world-renowned biologists and chemists.)
E Sayre, A., Rosalind Franklin and DNA, W.W. Norton, New
York, NY (1978)
(A discussion of the contributions of Rosalind Franklin to the
discovery of the structure of DNA and an analysis of whether her
contributions were acknowledged appropriately in Watson's ver-
sion of the discovery.)
[ Ambrose, S.A., K.L. Dunkle, B.B. Lazarus, I. Nair, and D.A.
Harkus, Journeys of Women in Science and Engineering: No
Universal Constants (Labor and Social Change), Temple
University Press, Philadelphia, PA (1997)
(Challenges faced by women in science and engineering.)
E Djerassi, C., Cantor's Dilemma, Penguin Books, New York,
NY (1989)
(A gripping novel by a world-renowned chemist known for his
discovery of the birth-control pill, about the fierce competition driv-
ing scientific "superstars." A fictionalized version of real ethical
and personal issues faced by scientists every day. This is the first
volume in a tetralogy. You can visit http://www.djerassi.com for
more details on this book and its sequels.)
E Covey, S.R., A.R. Merrill, and R. Merrill, First Things First,
Simon & Schuster, New York, NY (1995)
(One of the most popular time-management books.)
E Seligman, M., Learned Optimism, Pocket Books, New York,
NY (1998)
(The author, a psychologist and clinical researcher, discusses pessi-
mism, optimism, and depression and how they affect quality of life.
The book also discusses the skills needed to change one's attitude
from pessimism to optimism.)


Fall 1999


skills needed to be courteous and generous to others
while making your own points effectively. Do not wait
until you get a job to learn such skills. Your supervisors
generally will not have the time to be your mentors or
advisors. They will merely observe your performance
and will pass you over for promotion or a choice job
assignment if you do not have the necessary skills.
> If English is not your native tongue, speak only English
at work. Ask an English-speaking colleague to proof-
read your papers and listen to your presentations. Take
advantage of technical writing courses and courses on
"English as a second language" offered by the university.

DEVELOP GOOD SOCIAL HABITS
- Mingle with as many peers as possible. Get to know
them. Try to make life-long friendships.
> If you are a foreign student, try to find a roommate who is
not from your own country. Be a cultural ambassador of
your country. If you are a native student, seek out stu-
dents from other countries. Let's make the world a better
place for the next generation.

EXERCISES
1. Write a short essay on your goals in life and in your
professional career. Be honest with yourself. Make a list
of your strengths and weaknesses. Identify what you
can do to eliminate or minimize your weaknesses.
2. Examine and analyze the case studies on professional
practice outlined in On Being a Scientist: Responsible
Conduct in Research (National Academy Press, Wash-
ington, DC 1995; accessed through the web at
www.nap.edu).
3. Write a short research proposal on a topic of your choice
following standard guidelines issued by the university
and ask a friend or your graduate advisor to criticize it.
(You may wish to look through the US National Science
Foundation guidelines on proposals and review criteria;
see www.nsf.gov).

ACKNOWLEDGMENTS
This article is based on a Professional Development Semi-
nar Course developed for the graduate students in the De-
partment of Chemical Engineering at the University of
Florida, and on a couple of seminars I ran recently at the
National University of Singapore. I would like to thank
Jorge Jimenez, Claudia Marin, Anand Jaganathan, and Jonah
Klein, graduate students in the University of Florida Depart-
ment of Chemical Engineering, and my colleague Professor
Mark Orazem, for critically reading a draft of this article and
suggesting improvements. Dr. Paul Huibers, of the Depart-
ment of Chemical Engineering at MIT, read through an
earlier draft and suggested some changes, which I have
incorporated into this version almost verbatim. N
261









Graduate Education


A ChE GRADUATE COURSE IN

MATERIALS DESIGN


BRIAN S. MITCHELL
Tulane University New Orleans, LA 70118


Materials science is perhaps the single largest, multi-
disciplinary, technological subject area, drawing
together experts from such diverse backgrounds
as architecture, physics, biomedical engineering, and even
the arts. Chemical engineers have helped make significant
advances not only in well-established "hard" materials sci-
ence fields such as polymer processing and semiconductors,
but they have also been at the forefront of important emerg-
ing materials science technologies such as tissue engineer-
ing (of the so-called "soft materials"), self-assembling sys-
tems, and nanostructured materials. The irony in these ac-
complishments is that many chemical engineering curricula
neither require a materials science course nor directly pre-
pare undergraduates for careers in these fields, much less
prepare them for advanced study in materials-science-ori-
ented research areas.
The challenge for those of us doing materials-related re-
search in chemical engineering departments, then, is to take
students who may have little or no background in materials
science and prepare them to do state-of-the-art materials
research. Although an undergraduate-level survey course in
materials engineering and science is a good place to start,
what is often needed is a second, "advanced-level survey
course," if there is such a thing, to prepare graduate students
to do research in a wide variety of materials-related areas.

COURSE CONTENT
Most undergraduate materials science textbooks take the
survey approach; that is, a wide variety of topics are pre-


sented in relatively little depth or detail, in order to give the
student at least a passing familiarity with a number of differ-
ent materials-science concepts. A working knowledge of
general chemistry, physics, and calculus is required, but
little or no organic chemistry, physical chemistry, or differ-
ential equations are employed.
Textbooks such as that of Callisteri' are excellent in this
approach, especially since they are frequently updated and
thus expose students to the latest trends in materials science.
They are usually written by materials scientists, metallur-
gists, or ceramists, but rarely by chemical engineers. As a
result, there are a number of concepts that are important to
chemical engineers working in the materials field that must
be taught either one-on-one with the graduate student, dur-
ing group meetings, or in a narrower, graduate-level course.
There are a number of excellent texts for such courses, on
topics ranging from polymer rheology,'21 to ceramics pro-
cessing,m3' to electrical properties of materials.[41 There is
very little in between.
The undergraduate survey text is not appropriate for a
graduate-level course, yet to focus on a specific topic (while
it may be well-taught and of academic importance) may not
provide exposure to a sufficient number of concepts to be
useful to graduate students conducting widely varied materi-
als research. Finally, and perhaps most importantly, these
narrower subject courses do not address or discuss the way
in which a number of important materials have been devel-
oped: through design of materials for a specific application.
The course outline for a graduate-level chemical engineer-
ing course, "Advanced Materials Design," is shown in Table
1. Four features of this course will be highlighted here: one
lecture on the history of materials development; a list of
selected advanced topics; a discussion of the design process;
and examples of materials design projects.


HISTORY OF MATERIALS DESIGN
There are a number of truly fascinating stories related to
the development of certain types and classes of materials.
:hE Division of ASEE 1999


Chemical Engineering Education


Brian S. Mitchell is Associate Professor of
Chemical Engineering at Tulane University.
He received his BS in chemical engineering
from the University of Illinois-Urbana in 1986
and his MS and PhD degrees in chemical
engineering from the University of Wisconsin-
Madison in 1987 and 1991, respectively. His
research interests are in fiber technology and
composites engineering, and in the use of al-
ternative teaching techniques in the classroom.










I Graduate Education


For example, the work of Wallace
Carothers at DuPont on the develop-
ment of neoprene and nylon demon-
strates not only how materials (in this
case polymers) were developed as sub-
stitutes for specific, naturally occurring
materials such as rubber and silk, but
also how their development was spurred
by historical events (World War II, in
this case). This is not very technical
information, of course, but students
should be made aware (or at least re-
minded) that technological advances
occur as a result of a number of differ-
ent driving forces, including chance,
theoretical predictions, and necessity.
There is a particularly good book by
Ivan Amato called Stuff la that provides
a great deal of historical information
and perspective on the development of
materials science as a discipline, and of
specific materials. Although I stop short
of making this a required text for the
Advanced Materials Design course due
to its lack of technical content, it is
nonetheless on the "must read" list for
anyone in the materials area, and it is
worth recommending to all science and
engineering students. It also shows how
some prominent chemical engineers
have played important roles in devel-
oping new materials, and how they em-
ployed design principles to accomplish
their task. An excellent example is the
work of Ilhan Aksay of Princeton Uni-
versity on biomimetic structures.

ADVANCED TOPICS


Although an
undergraduate-level survey
course in materials
engineering and science is a
good place to start, what is
often needed is a second,
"advanced-level survey
course," if there is such a
thing, to prepare graduate
students to do research in a
wide variety of materials-
related areas.



TABLE 1
Course Outline for
Advanced Materials Design
I Selected Advanced Topics in Materials Science
A. The History of Materials Science
B. Crystallography
C. Structure of Glass
D. Structural Imperfections
E. Phase Equilibria
F. Phase Transformations
G. Advanced Characterization Techniques
H. Mechanical Properties
II. Materials Design
A. The Design Process
B. Metals
C. Inorganic Materials
Ceramics (low- and high-tech)
Glasses
Glass-ceramics, ceramers, and cermets
D. Polymers
E. Composites
F. Case Studies, Design Projects


and a semester-long course in crystal-
lography. This topic is of use to those
students who will be conducting re-
search in practically any materials area,
including polymers. In addition to re-
viewing the seven crystal systems, the
reciprocal lattice, Miller-Bravais indi-
ces, symmetry operations, and X-ray
diffraction are discussed. The advanced
content comes from such exercises as
calculation of single-crystal X-ray dif-
fraction patterns from unit cell dimen-
sions, which can be done on a spread-
sheet.161
The lectures on the crystalline state
lead naturally into lectures on the amor-
phous, or glassy, state. Again, discus-
sions of radial distribution functions,
the glass transition, and phase transfor-
mations are equally applicable to inor-
ganic glasses as well as polymers. Struc-
tural defects often receive a great deal
of attention in an undergraduate mate-
rials science course-deservedly so,
since they directly affect many physi-
cal properties. One topic on structural
defects that does not receive a great deal
of attention, except in courses on ceram-
ics, is point defect equilibrium and
Kroger-Vink notation.171 Once Kroger-
Vink notation has been described, the
determination of equilibrium point de-
fect concentrations is particularly relevant
for graduate-level chemical engineers,
since the point defect species are treated
like any other chemical species, and de-
fect reaction equations are like any other
chemical reaction.


A graduate-level chemical engineering course should be
more than a history lesson, of course. One of the primary
purposes of an advanced materials course should be to teach
advanced topics-those that are only introduced at the un-
dergraduate level or that are not covered in sufficient detail.
The difficult question is which topics those should be. At
Tulane University, we have faculty conducting research in
such areas as heterogeneous catalysis, molecular dynamics
simulations of thermophysical properties in polymer single
crystals, nanostructured ceramics, and tissue engineering.
Some of the advanced topics we have selected to address are
shown in Table 1.
Lectures on crystal structure are given at a level some-
where between the undergraduate materials science course


Phase equilibria is also an area that most chemical engi-
neers get a great deal of exposure to at the undergraduate
level. Most of it deals with the liquid and vapor states,
however, and is mostly applied to binary systems. Ternary,
condensed-phase diagrams are described in Advanced Mate-
rials Design. Although this is not mathematically challeng-
ing material, terms and concepts such as conodes, isopleths,
coprecipitational divariant equilibria lines and alkemade lines
take a bit of practice to fully understand. As a final example
of the advanced survey format of this course, a number of
lectures are spent on advanced materials characterization.
Once again, this can be a course in-and-of itself, but there
are a few techniques that are of particular importance to our
department and its researchers. Tulane University has a com-


Fall 1999









Graduate Education

plete thermal analysis laboratory. It contains, among other
things, a differential scanning calorimeter (DSC), differen- TA- 2
tial thermal analyzer (DTA), thermogravimetric analyzer :_
(TGA), dynamic mechanical analyzer (DMA), thermo- .r<,iS.W -rod re
mechanical analyzer (TMA), dielectric analyzer (DEA), and
various combinations of these instruments. A number of
graduate students in the department wish to use the thermal ULmrL f44i
analysis facility, and without turning a graduate-level course
into a technician training session, the students are introduced
to the operation of these analyzers, and the theory behind
selected instruments is discussed.

THE DESIGN PROCESS
It makes sense in a course on "materials design" to discuss Inonla-~-" '
not only the "materials" part, but also the "design" part. The
design aspect of engineering education has certainly not-
been lost on other parts of the chemical engineering curricu- I'
lum, such as process design, and has in fact been emphasized
more recently across the curriculum through emphasis of ct-a companies
design-oriented problems at all levels and in all subject
areas. The design approach has not been taken to any appre-
ciable extent in materials science courses.
In the Advanced Materials Design course, general design -
methodologies such as Cross's methodology,t8t concurrent IT....:_.
engineering,191 and market-driven design10l are discussed. -
More materials-oriented design methodologies are then de-
scribed, in which Ashby's dated, yet still appropriate, text on
mechanical design is used.tI"' Not all materials design prob-
lems, especially newer ones, require a significant mechani-
cal property component, so students are encouraged to use
the more general design strategies to carry out materials a
f-k
selection and development.
An excellent text on materials design that contains a great _..
number of case studies is by Lewis.1'2 This book offers a
wealth of information and emphasizes cost analysis-some-
thing that is often lost in academic environs. The remainder
of the course is spent reviewing the traditional grouping of ii
materials science topics, with an emphasis on physical prop-
erties that can be exploited from a design standpoint.

THE DESIGN PROJECT
As with many chemical engineering courses, the heart of
the materials design course is the design project. The design
project topics for Advanced Materials Design are gleaned
from the recent literature (see Table 2 and references 13-28).
The Materials Research Society Bulletin is a particularly
useful source for these topics, as the articles in this monthly
journal tend to be of intermediate technical difficulty, yet
represent some of the most current, cutting-edge materials
research being conducted. These articles also generally have
excellent bibliographies, thus providing a good starting point -
for the students' literature reviews. The students get to choose --


Chemical Engineering Education










Graduate Education


the topic, with the stipulation that it be outside of their
research area. Some of the topics are very general, such as
nanoceramics; others are more specific, such as discontinu-
ously reinforced metal matrix composites. Some of the top-
ics already have an application associated with them, such as
materials for flat panel displays; others are still in search of
"break-through" applications.
The project topics are selected and assigned early in the
course. For the first homework assignment, the students
must find three additional articles for their topic, preferably
varied in scope; e.g., one review article, one on molecular
mechanisms, and one on processing. They must also write a
brief summary of the potential significance of the topic and
areas where it can be applied. The requirements for the final
report are listed in Table 3.
The goal is to come up with a specific application for their
material-all the way down to drawing a schematic of the
apparatus or article and describing how it works. This may
seem trivial for a topic like "Materials for Flat Panel Dis-
plays," but in this case the student must reverse engineer the
component, determine what the specific materials constitu-
ents are, and more importantly, why they were selected.
In either scenario, the student must come up with a justifi-
cation for the selected materials. In doing so, the student
applies the design criteria, or sees how others applied them,
uses advanced materials science concepts in the analysis of
the application, and thinks practically, yet critically, about
how newly developed materials can be used.

CONCLUSION
Graduate courses need not emphasize the use of elliptical
integrals, nor be as narrow as the instructor's most recent
grant proposal in order to be considered advanced. The three
highest levels of Bloom's taxonomy of Education Objec-
tives-analysis, synthesis, and evaluation[291-are sufficiently
challenging for graduate students, even in a survey-type
course, when the technological content of the system being
analyzed and evaluated is sufficiently complex. Today's
materials applications certainly meet the technological re-
quirement, and a design project for chemical engineering
graduate students on advanced materials applications chal-
lenges the students to use many of the chemical engineering
principles they have learned as undergraduates.

REFERENCES
1. Callister, William D., Materials Science and Engineering:
An Introduction, 4th ed., John Wiley & Sons, New York, NY
(1997)
2. Bird, R.B., B.C. Armstrong, and O. Hassager, Dynamics of
Polymeric Liquids, John Wiley & Sons, New York, NY (1977)
3. Reed, J.S., Principles of Ceramics Processing, John Wiley &
Sons, New York, NY (1995)


4. Solymar, L., and D. Walsh, Lectures on the Electrical Prop-
erties of Materials, 5th ed., Oxford Science Publications,
Oxford, England (1993)
5. Amato, I., Stuff-The Materials the World is Made Of, Basic
Books, New York, NY (1997)
6. Shapiro, F.R., "The Calculation of Crystal Diffraction Pat-
terns Using a Spreadsheet," J. Mater. Educ., 14, 93 (1992)
7. Kingery, W.D., H.K. Bowen, and D.R. Uhlmann, Introduc-
tion to Ceramics, 3rd ed., John Wiley & Sons, New York, NY
(1993)
8. Cross, Nigel, Engineering Design Methods, John Wiley &
Sons, New York, NY (1989)
9. Winner, R.I., J.P. Pennell, H.E. Bertrand, and M.M.G.
Slusarczuk, "The Role of Concurrent Engineering in Weap-
ons System Acquisition," IDA Report R-338 (1988)
10. Pahl, G., and W. Beitz, Engineering Design, translated by
K. Wallace, The Design Council, London and Springer, Ber-
lin, Germany (1984)
11. Ashby, Materials Selection in Mechanical Design,
Butterworth-Heinemann Ltd., Oxford, England (1992)
12. Lewis, G., Selection ofEngineering Materials, Prentice Hall,
New York, NY (1990)
13. Stinson, S., "Delving into Dendrimers," Chem. Eng. News,
p. 28, September 22 (1997)
14. Freemantle, M., "Potential Trigger for Dendrimer Switch,"
Chem. Eng. News, p. 30, May 26 (1997)
15. Service, R.F., "Paving the Information Superhighway with
Plastic," Science, 267, 1921 (1995)
16. Miller, J.S., and A.J. Epstein, "Designer Magnets," Chem.
Eng. News, p. 30, October 2 (1995)
17. Epstein, A.J., "Electrically Conducting Polymers: Science
and Technology," MRS Bull., 22(6), 16 (1997)
18. Rothberg, L.J., and A.J. Lovinger, "Status and Prospects for
Organic Electroluminescence," J. Mater. Res., 11(12), 3174
(1996)
19. Hanna, J., and I. Shimizu, "Materials in Active-Matrix Liq-
uid Crystal Displays," MRS Bull., 21(3), 35 (1996)
20. Agarwal, M., M.R. DeGuire, and A.H. Heuer, "Synthesis of
ZrO2 and Y203-Doped ZrO, Thin Films Using Self-Assembled
Monolayers,"J. Am. Ceram. Soc., 80(12), 2967 (1997)
21. Ritter, S.K., "Boning Up," Chem. Eng. News, p. 27, August
25 (1997)
22. Alivisatos, A.P., "Semiconductor Nanocrystals," MRS Bull.,
20(8), 23 (1995)
23. Mitomo, M., Y-W Kim, and H. Hirotsuru, "Fabrication of
Silicon Carbide Nanoceramics," J. Mater. Res., 11(7), 1601
(1996)
24. Rittner, M.N., and R. Abraham, "The Nanostructured Ma-
terials Industry," Am. Ceram. Soc. Bull., 76(6), 51 (1997)
25. Kevorkijan, V.M., "An Ideal Reinforcement for Structural
Composites," Am. Ceram. Soc. Bull., 76(12), 61 (1997)
26. Newnham, R.E., "Molecular Mechanisms in Smart Materi-
als," MRS Bull., 22(5), 20 (1997)
27. Greer, A.L., "Metallic Glasses," Science, 267, 1947 (1995)
28. Archambault, P., and C. Janot, "Thermal Conductivity of
Quasicrystals and Associated Processes," MRS Bull., 22(11),
48(1997)
29. Bloom, B.S., ed., Taxonomy of Educational Objectives Hand-
book I: Cognitive Domain, David McKay Co., (1956) O


Fall 1999










Graduate Education


A SURVEY COURSE IN


PARTICLE TECHNOLOGY



JENNIFER L. SINCLAIR
Purdue University West Lafayette, IN 47907-1283


n the spring semester of 1998, an overview course in
particle technology was launched in the School of Chemi-
cal Engineering at Purdue University. The student en-
rollment in the initial offering of this course was relatively
high (25 students) for an elective course; hence, the course is
now being offered yearly in Purdue's spring semester. It will
also be taught starting in the spring semester of 2000 via
videoconferencing as a part of Purdue's continuing educa-
tion program for practicing engineers, some of whom are
working part-time towards their Masters of Engineering de-
gree at Purdue.
The objective of the course is to provide a broad overview
of the field, with emphasis on concepts and practical appli-
cations. Specific topics include particle characterization, sedi-
mentation, gas fluidization, pneumatic conveying, gas-solid
separation, particle storage, mixing, size reduction and en-
largement, and dust hazards and explosions. About one week
of coverage is given to each of the above topics; the empha-
sis is clearly toward breadth rather than depth.
At Purdue, as well as at most other universities in the U.S.,
the current educational treatment of particle technology is
limited to a one-semester course. This constraint dictates
that the time available in a single-semester course is best
spent in an overview fashion. Hence, emphasis is on relating
to the students an appreciation for the many aspects of this
complex field and on developing an awareness of the resources
available to them if they find themselves working in industries
involved with the processing of particulate solids.
The overview course in particle technology is offered as a
500-level course available to junior and senior undergradu-
ates as well as to graduate students. Enrollment in the two
offerings of the course to date has been an even mix of
undergraduate and graduate students from a range of disci-
plines that includes chemical engineering, mechanical engi-
neering, food science, agricultural and biological engineer-
ing, civil engineering, and pharmacy. The textbook used in
the course is Introduction to Particle Technology by Martin


Rhodes (Wiley, 1998).
The course includes guest speakers from several industrial
companies such as Dow and DuPont. At least one field trip
to an industrial company involved in solids handling is in-
cluded each semester so that students can see first-hand the
many unit operations discussed in the lectures. The course
schedule for the spring 1999 offering of the course can be
found in Table 1.
Slurry flow is the only subject covered in the course that is
not treated in the Rhodes text. Reading for this material is
given as handouts and is based on the text Bulk Solids
Handling by Woodcock and Mason (Blackie Academic,
1987). Supplementary material for other lectures is taken
from the following texts:
* Principles of Powder Technology, Rhodes; Wiley, 1990
* Processing of Particulate Solids, Seville, Tuzun, and
Clift; Blackie Academic, 1997
Principles of Gas-Solid Flows, Fan and Zhu; Cambridge
University Press, 1997
Particle Size Measurement, Allen; Chapman & Hall,
1997
Fluidization Engineering, Kunii and Levenspiel;
Butterworth-Heinemann, 1991
Pneumatic Conveying of Solids, Marcus, Leung,
Klinzing, and Rizk; Chapman & Hall, 1990

Jennifer L. Sinclair is Associate Professor
of Chemical Engineering at Purdue Univer-
sity. Her research interests are in the areas
of gas-solids flow, fluidization, and particle
mechanics. She is the recipient of several
teaching awards, the NSF-PYI award, and
currently serves on the Executive Committee
of the Particle Technology Forum.


Copyright ChEDivision ofASEE 1999


Chemical Engineering Education










Graduate Education


INTRODUCTORY LECTURE
The aim of this lecture is to con-
vince students of the critical im-
portance of particle technology and
also to clearly show them that the
concepts they learned in a typical
engineering fluids course may not
necessarily translate to the flow and
storage of particles. This lecture
sets the stage and motivation for
the course. If done well with lots
of visuals, it is highly effective in
imparting to students the importance
of knowledge in this technical area.
This same lecture works well as
a recruiting tool to attract students
to the course. At Purdue, chemical
engineering undergraduates must
take a chemical engineering semi-
nar course every semester. During
part of one class period in the semi-
nar course, I present some key con-
cepts from this introductory par-
ticle technology lecture to all of
the chemical engineering students.
Many of the students end up regis-
tering for the particle technology
course because of the material con-
tained in this presentation. I have
also given the lecture to industrial
visitors to our university; they are
usually "sold" on particle technol-
ogy after hearing it.
The basic components of this lec-
ture are a definition of particle tech-
nology, a presentation of the im-
portance of particle technology in
industry, and a presentation of ex-


TABLE 1
Course Schedule


January 12
14
19
21
26
28
February 2
4
9
11
16
18
23
25
March 2
4
9
11
23


Introduction
Particle characterization
Particle characterization
Particle size measurement
Sedimentation
Sedimentation
Packed beds
Fluidization
Fluidization
Exam #1
Pneumatic conveying
Pneumatic conveying
Gas-solid separation
FIELD TRIP: National Starch
FIELD TRIP: Cargill
Slurry flow
Particle mixing
Exam #2
Guest Lecturer:
Rachel Anderson, Dow


Reading in
Rhodes
Chapter 3
Chapter 3
Chapter 3
Chapter 3
Chapter 1
Chapter 2
Chapter 4
Chapter 5
Chapter 5

Chapter 6
Chapter 6
Chapter 7


Notes
Chapter 9


Chapter 8


"Design of Particle Storage Devices"
25 Guest Lecturer
Rachel Anderson, Dow Chapter 8
"Design of Particle Storage Devices"
30 Guest Lecturer:
Mohsen Khalili, DuPont
"Case Studies in Particle Technology"
April 1 Guest Lecturer:
Mohsen Khalili, DuPont
"Case Studies in Particle Technology"
6 Particle size reduction Chapter 10
8 Particle size enlargement Chapter 11
13 Guest Lecturer:
Professor Wassgren, MechE, Purdue
"Simulation of Particle Flow"
15 Dust hazards/explosions Chapter 12
20 Oral presentations Project
22 Exam #3
27 Oral presentations Project
29 Oral presentations Project


amples in which particles behave
in a unique way, often very differ-
ently than fluids. In most of these examples, I give a visual
picture to the audience either by illustrating with a real
particulate material or through the use of a graph, photo-
graph, etc.
An outline of the introductory lecture can be found in
Table 2 (next page).

COURSE PROJECT
One of the key components of the overview course in
particle technology, in addition to the traditional lecture,
homework, and exam format, is the course project. In the


Fall 1999


project, students work in teams to
investigate one specific topic in par-
ticle technology in detail. The team
project comprises one-third of the
course grade, and the last lectures
of the course each semester are de-
voted to presentations of the group
projects. The project brings depth
in one particle technology topic to a
course that emphasizes breadth. The
project also provides additional ex-
perience for the students in the team-
work and communication skills that
are essential on the job.
A course project is very attractive
to the students because they can
work in an open-ended fashion on a
particle technology subject of their
choosing. Most undergraduates en-
joy the team aspect of the course
project since they are accustomed
to working in teams in their senior
engineering design courses and, for
some, in their co-op positions. The
graduate students like the course
project because they are given the
opportunity to probe topics dis-
cussed in lecture in more detail.
Many of the graduate students who
enroll in the course want specific
topics along the lines of their gradu-
ate research developed in greater
detail than the treatment given in
the lectures. Since this is not pos-
sible in the lectures, given the time
constraints, the course project of-
fers another format for meeting these
students' expectations for the course.


In the course project, the students
are engaged in both background re-
search and in making a forward step, that is, moving beyond
what is currently known and putting forth something new.
The "something new" can take the form of a research pro-
posal, new theory, new insight, new calculations, new data
(some students have access to appropriate experimental fa-
cilities in their research group), etc. In the course at Purdue,
the weighting on the background research versus the "some-
thing new" portion of the project is approximately 75/25%.
Students work in teams of three to four people. The teams
and their presentation dates are chosen randomly by picking
numbers out of a hat during the first class meeting. At least


267











Graduate Education


fifteen minutes is allocated during the first lecture period for
the group members to exchange contact information and
class schedules, briefly get to know one another, and to
decide on a group leader. Other opportunities are given
during the semester towards the end of class periods for
group discussions.
The teams are given three weeks to decide on a project
topic. Students are instructed to peruse the titles of articles in
the journals of Powder Technology and Particle Science &
Technology to stimulate ideas for projects. Often when a
graduate student is one of the team members, he or she takes
on the leadership role and guides the course project to a topic
related to his or her graduate research. This pattern of the
graduate student taking charge of the team has not yet cre-
ated any group conflicts; rather, many of the undergraduate


students seem to be relieved when a project direction is
decided on quickly and easily. The only group conflict that
has arisen to date has been when two graduate students were
on the same team and they had areas of graduate research
specialization in particle technology that involved little over-
lap. For that team, coming to an agreement on a project topic
required a lot of compromising among the group members.
Focus areas for project topics have spanned the spectrum
of particle sizes and particle science and technology applica-
tions. Representative topics have included
Use of Electrokinetic Sonic Amplitude in the Characterization
of Colloidal Suspensions
Particle Size Distribution Effects in Pneumatic Conveying
Novel Designs for FCC Reactors
Use of Simulation Techniques to Improve Cyclone Design


Chemical Engineering Education


TABLE 2
Outline of Introductory Lecture

Particle Technology
Particle technology refers to the science and technology related to the handling and processing of particles and powders
Also known as "powder technology" (sometimes when the particle size is less than 100 microns)
Powders or particles also referred to as particulate solids, bulk solids, and granular solids
Particle technology includes solid particles as well as liquid droplets, emulsions, and bubbles
Wet/dry particulate systems-with and without liquid
Importance of Particle Technology
62% of DuPont's 3000 products involve particles (ChE Progress, 1994)
50% of Dow Chemical's products
Rand Corporation Study (ChE Progress, 1985)
37 solids processing plants studied
2/3 operated at less than 80% design capacity
1/4 operated at less than 40% design capacity
(95% is average for the CPI as a whole)
Ignorance of particle technology often results in loss of production, poor product quality, health risks, dust explosions, and storage silo collapse.
Typically, 20-25 deaths occur each year due to failures in particle technology operations.
Particle technology impacts fields of chemical engineering, mechanical engineering, agricultural engineering, food engineering and food science,
electrical engineering, civil engineering, pharmaceuticals, metallurgy, and minerals engineering. In each of these fields I give examples of
processes involving particle technology. I also ask the students for input here because the students in the course come from a diverse set of science
and engineering backgrounds.
Particles Do Not Necessarily Behave Like Fluids
Particles expand in a dry bulk assembly when sheared. Walking on sand at the beach is a good example of particle expansion during shear.
The ability of particles to form a heap. Visual-two different types of particulate material and a discussion of the angle of repose and how particle
cohesivity influences flow behavior.
Differences in pressure drop behavior in pipelines in a single-phase gas versus a gas-particle mixture. Visual-Show and discuss a graph of how it
is possible in dense-phase conveying of particulates to have a reduction in pressure drop with an increase in gas velocity at a constant solids
flowrate. Also discuss how the addition of a small fraction of very fine particles to a turbulent fluid may cause a reduction in the pressure drop.
Particle flow behavior in bends can be very problematic. Visual-An illustration of the roping phenomena; an actual pipe bend ruined by erosion.
Particle storage in hoppers can also be problematic. Visual-Mass flow versus funnel flow-stagnation regions do not occur in fluid storage in a
similar vessel; plugging of the outlet of a hopper.
Particle flowrate out of hopper as the head decreases. Visual-Clear hopper and observation of outlet flowrate as a function of head-contrast
with fluid flow out of a tank as head decreases.
Particle bulk density varies with "tapping." Visual-Tapping of a fine particulate material in a vial and observation of volume occupied by
particulate material-contrast with a single-phase fluid in a vial.
Large particle placed at the bottom of a container of a dry granular material will rise to the surface if the container is vibrated in a vertical plane.
Visual-Shaking of a particulate material in a vial containing one larger particle and observation of the large particle movement.
Fill volume of two types of particles can depend on the order of filling of the container. Visual-Filling ajar with two sizes of nuts and observa-
tion of volume occupied-contrast with combining two fluids and the resulting volume.
Stirring a mixture of two types of particles of different sizes may result in segregation rather than improved mixing quality. Visual-Photographs
of segregation patterns before and after a blending operation-contrast with mixing of two fluids.










Graduate Education


Probing the Mechanisms of Particle Charging
Ultra-High Performance Electrostatic Precipitators
Moisture Content and Caking in Foodstuffs
There are four aspects to be graded in the overall course
project:
1. The first is a written report of at least ten pages prepared by the
group that summarizes the background information on the
topic and the novel aspects of the investigation.
2. The second is an oral presentation of the topic, thirty to forty-
five minutes in length. All of the group members are required
to participate in the oral presentation. Typically, one student
outlines the discussion points in the beginning of the presenta-
tion, and then the team members take turns speaking on each
of the presentation bullets. Often the presentations are
supplemented with visual aids or a short demonstration to
introduce the topic and capture the attention of the audience.
The oral presentation is followed by a questioning period.
During the questioning period, each of the project teams in the
audience is required to ask at least two questions of the
presenting team. This requirement is highly successful in
keeping the class engaged in the presentations; the students
also often generate outstanding questions. This peer question-
ing is one aspect of peer review (see task #3 below) that is
incorporated into the course project to help develop the
communications skills of the students. After the questioning
period is over, the instructor gives the presenting team
immediate feedback, both positive and negative, in front of the
entire class. This helps to improve the quality of the subse-
quent presentations since students get a better understanding of
what is successful, what are some of the pitfalls, and what are
the standards expected for the presentations.
3. Every team performs a peer evaluation of each of the other
teams. The peer evaluation is on both the written and oral
presentations of the course project. In the written report, each
team serves as a reviewer of the other team reports, marking
grammatical and typographical errors directly on the manu-
script. They write a short summary of the manuscript that
includes an overall evaluation, specific positive aspects,
constructive criticisms, and suggestions. For the oral presenta-
tions, a structured evaluation form is used that is provided by
the instructor. Therefore, at the end of the peer evaluation
process, each team has a large amount of anonymous feed-
back-a written and oral report from each of the other teams.
Although these peer evaluations do not influence the grade of
the team being evaluated, they are very instructive; the
students tend to listen and readily accept the comments from
their peers. The peer evaluations prepared by each team are
graded for thoroughness and level of insight by the instructor.
The value of peer review has been documented in the litera-
ture," 5] and its benefits are abundantly evident in the particle
technology course. Perhaps this is due to the fact that the
course is an elective course. Presumably, students already have
some interest in the topic when they enroll in the course and
the peer review merely enhances their involvement in it.
Students take the reviewing task seriously. They do an
excellent job in identifying the strengths and weaknesses in the


work of their fellow students. The peer review also aids the
students in recognizing the strengths and weaknesses of their
own oral and written reports.
4. Finally, each team member submits to the instructor a summary
report of the relative contributions of each of their own group
members, including an assessment of their own contribution to
the team effort. This helps the instructor assign appropriate
individual grades to the group project.

Aside from the technical benefits a particle technology
project brings to the course, there is the additional, more
general benefit of improving team skills. Team skills are a
requirement for a successful workforce; about 80% of U.S.
organizations use teams to accomplish tasks.[J6 In technical
fields, teamwork is particularly crucial as engineers and
scientists become more specialized. Students, through the
course project, gain more experience in how to capitalize on
the unique skills of others, and, in turn, they often learn more
about their own capabilities. In addition, they learn better
how to motivate others, how to organize a group effort, and
how to manage in difficult teams since team members are
not reassigned even if a team is having problems working
together. In fact, student feedback indicates that while being
a member of a "problem team" is certainly not a pleasant
experience, those team members are the ones that make the
strongest comments about their huge learning experiences in
team skills.

SUMMARY
A survey course in particle technology is a highly effec-
tive way to introduce the basics in this field to a diverse
group of students. A "gee-whiz"-type introductory lecture
helps sell the importance of particle technology to different
audiences. Visuals enhance presentation of the unique fea-
tures of particulate systems. Incorporation of a team project
into the course allows for students to focus on one particular
topic in particle technology and adds depth to the breadth of
material covered in this survey course. Also, the course
project brings many positive factors to the learning experi-
ence of the students.

REFERENCES
1. Elbow, P., Writing Without Teachers, Oxford University
Press, New York, NY (1973)
2. Grimm, N., "Improving Students' Responses to Their Peers'
Essays," College Comp. and Comm., 37, 91 (1986)
3. Herrington, A., and D. Cadman, "Peer Review and Revising
in an Anthropology Course," College Comp. and Comm., 42,
184(1991)
4. Holt, M., "The Value of Written Criticism," College Comp.
and Comm., 43 384 (1992)
5. Newell, J., "Using Peer Review in the Undergraduate Labo-
ratory," Chem. Eng. Ed., 32, 194 (1998)
6. Robbins, S., Organizational Behavior, 8th ed., Prentice-Hall,
Upper Saddle River, NJ, 284 (1998) 0


Fall 1999









Graduate Education
' -------------------------------- __________


EXPERIENCES WITH AN

EXPERIMENTAL PROJECT

IN A GRADUATE CONTROL COURSE



EDWARD P. GATZKE, RAJANIKANTH VADIGEPALLI, EDWARD S. MEADOWS, FRANCIS J. DOYLE, III
University of Delaware Newark, DE 19716


A graduate-level class on process control tradition-
ally employs a standard lecture-style course, possi-
bly coupled with an independent course project car-
ried out in a simulation environment. If one steps back to
critique this approach, it is important to first address the
skills required by a practicing process-systems engineer. As
a guide to the requisite abilities required of a process-
systems engineer, one may consult the list of control design
steps provided by Skogestad and Postlethwaite'" shown in
Table 1. Is the typical engineering graduate well prepared to
accomplish these tasks? There have been no comprehensive
studies to answer this question, but Kheir, et al.,121 reported
the results of an informal survey of industrial employers of
control engineers. The highest rated aspects of the current
methods of control education were control-system knowl-
edge, job preparation, and curriculum. The analytical skills
of the students were considered strong. Such responses seem
to indicate some success for items 7 through 9 of Skogestad's
list of control-design steps, areas that correspond to skills
Ed Gatzke received his BSChE from the Georgia Institute of Technology in
1995. After two years of graduate study at Purdue University, he moved to
the University of Delaware for completion of his PhD. He has held intern-
ships with Teledyne Brown Engineering, Mead Paper, and Honeywell. His
interests include process control, optimization, and artificial intelligence.
Raj Vadigepalli received his BTech from the Indian Institute of Technol-
ogy, Madras, in 1996, and began his PhD research in chemical engineer-
ing at Purdue University in the fall of 1996. He moved to the University of
Delaware in 1997 to complete his doctoral degree with Professor Francis
J. Doyle. His research focus includes modeling and analysis of control
mechanisms in biological systems and distributed hierarchical methods for
control of large-scale process systems.
Edward S. Meadows is a postdoctoral fellow at the University of Dela-
ware, working in the areas of modeling and control of polymerization
reactors as part of a broader research program in optimization and control
of chemical processes. He received his PhD degree from the University of
Texas in 1994.
Frank Doyle received his BSE from Princeton in 1985, his CPGS from
Cambridge in 1986, and his PhD from Caltech in 1991, all in chemical
engineering. He was an Assistant Professor at Purdue University before
coming to the University of Delaware as an Associate Professor in the fall
of 1997, and his research interests are in the areas of process and
biosystems analysis and control.


typically emphasized by a theoretical, textbook-and-lec-
ture control course.
Unfortunately, existing approaches to control engineering
education are not necessarily producing engineers who are
as knowledgeable in other areas. The Kheir survey respon-
dents reported that control engineers received lower ratings
in the areas of laboratories, hands-on experience, and inter-
personal skills. The course described in this paper uses both
a standard lecture class and an experimental group project
related to the course material. This provides an opportunity
to address the deficiencies identified by Kheir and colleagues,
while reinforcing the positive aspects of traditional control
engineering education methods.

COURSE DESCRIPTION
In the latest (fall, 1998) offering of this course, Advanced
Process Control, there were seven students enrolled for a
grade and five students auditing the class. Of the seven
students taking the class for a grade, five were University of
Delaware graduate students and two were industrial profes-
sionals enrolled for continuing education credit.
As a main reference, the course used the text by Skogestad
and Postlethwaite,"1 and the major topics covered in the
course included
Classical multivariable control
Analysis of performance limitations
Uncertainty characterization
Robust controller synthesis
Control structure selection and plant-wide control
One of the key strengths of the Skogestad and Postlethwaite
text is the treatment of performance limitations, and this
topic was covered in depth in the lecture and reinforced via
the experimental project. The course project was assigned in


Copyright ChE Division of ASEE 1999


Chemical Engineering Education









Graduate Education


the middle of the semester, and the students were given the choice of a
theoretical independent course project (related to their thesis research)
or the opportunity to work on the experimental system as a group
project. Of the five on-site students, four elected to carry out their
project using the experimental four-tank system.

EXPERIMENTAL SYSTEM
An interacting four-tank process is currently used in both the elective
multidisciplinary undergraduate control laboratory and the advanced
graduate control course. The design is inspired by the benchtop appara-
tus described in Johansson and Nunes.131 A simple schematic is shown in
Figure 1. Two voltage-controlled pumps are used to pump water from a
basin into four overhead tanks. The two upper tanks drain freely into the
two lower tanks, and the two bottom tanks drain freely into the reservoir
basin. The liquid levels in the bottom two tanks are directly measured
with pressure transducers, and the top tanks have high-level alarm
signals generated by electro-optical sensors. As can be seen from the
schematic, the piping system is configured such that each pump affects
the liquid levels of both measured tanks. A portion of the flow from one
pump flows directly into one of the lower-level tanks where the level is
monitored. The rest of the flow from a single pump is diverted into
an overhead tank, which drains into the other monitored tank. By
adjusting the bypass valves on the system, the amount of interaction
between the two pump flowrates (inputs) and the two lower tank
level heights (outputs) can be varied. For this work, it is assumed
that an external unmeasured disturbance flow may also be present
that drains or fills the top tanks.
The original work of Johansson and Nunes131 employed tanks with a
volume of 0.5L. The present work uses 19L (5 gallon) tanks, attempting
to create a visual impression of practical reality for the students. The
scale of the apparatus is indicated in Figure 2. In the lower right-hand



TABLE 1
Steps in Control System Design

1. Study the system (plant) to be controlled and obtain initial information about the
control objectives.
2. Model the system and simplify the model, if necessary.
3. Analyze the resulting model; determine its properties.
4. Decide which variables are to be controlled (controlled outputs).
5. Select the control configuration.
6. Decide on the type of controller to be used.
7. Decide on performance specifications, based on the overall control objectives.
8. Design a controller.
9. Analyze the resulting controlled system to see if the specifications are satisfied; and if
they are not satisfied, modify the specifications or the type of controller.
10. Simulate the resulting controlled system, either on a computer or pilot plant.
11. Repeat from step 2, if necessary.
12. Choose hardware and software, and implement the controller.
13. Test and validate the control system, and tune the controller on-line, if necessary.


corner of the photograph, one can see the display of
a computer control system used as an interface to
the experiment. A Bailey Freelance Distributed Con-
trol System (DCS) was employed to introduce the
students to actual operating software employed
in industry. Furthermore, the PC-based architec-
ture made the system cost-effective for a univer-
sity application and facilitates hardware and soft-
ware upgrade paths.
The experimental package consists of three sepa-


Pumpl T Pump 2



Figure 1. Schematic of the four-tank
system.


figure Z. Laoorarory apparatus.


Fall 1999









Graduate Education


rate components, as shown in Figure 3:
1. Experimental Station: tanks, level sensors, level
alarms, valves, and pumps
2. Process Station: hardware that carries out the control
input-output and communicates between the Experi-
mental Station and the Operator Station
3. Operator Station: PC-based system were Process
Station information is monitored and modified
The Process Station communicates with the Operator Sta-
tion over a private TCP/IP network. The Freelance applica-
tion package DigiTool was used to create a process database
that is loaded onto the Process Station. The DigiVis applica-
tion allows operator interaction with the Process Station and
process database. Operator displays were created that al-
lowed the students to operate the four-tank system (see Fig-
ure 4) as well as to track the trends of key operating variables
(see Figure 5).
For the graduate control class, it is necessary to use more
complex control algorithms than can be easily implemented
using the Freelance packages. Matlab/Simulink can be used
to calculate the control moves needed for the experimental
system. A Dynamic Data Exchange (DDE) interface is used
to link Matlab/Simulink with Freelance. The Simulink dis-
play (Figure 6) emulates a standard simulation flowsheet.
By default, the Bailey DCS controls the process using manual
or PID control. Once the student has toggledd" control (to
Matlab from Bailey), however, the Simulink "simulation"
drives the inputs to the Bailey system as the simulation
proceeds. This creates a very flexible environment for imple-
menting complex control algorithms on a moderately com-
plex experimental system.

MATHEMATICAL DESCRIPTION
OF THE PROCESS
Both a nonlinear model and a linearized model are given
in Johansson and Nunest3' for the four-tank system. The
models used for this work include the disturbance effects of
flows in or out of tanks 3 and 4. The nonlinear differential
equations governing the heights in this four-tank system are
given in Table 2, and the linearized version is seen in Table
3. The liquid levels in tanks one and two, h, and h2, are
considered measured variables. The speed of the pumps, v,
and v2, are considered as manipulated inputs. The pump
speeds are manipulated as a percentage of the maximum
pump speed. The disturbances dl and d2 model the unmeasured
disturbance effects of flows in or out of tanks three and four.
This model is a simple mass balance, assuming Bernoulli's
law for flow out of the orifice. The gamma values, yi,
correspond to the portion of the flow going into an upper
tank from pump i. In Johansson and Nunes,l31 it is shown that
inverse response in the modeled outputs will occur when


Matlab DigiTool -----. Process Station *" Process Measurments
DigiVis 0----- Database "'-- Process Inputs
SDigiDDE -*"

Figure 3. Schematic of the control system.


Figure 4. Screenshot of Freelance four-tank schematic.


Figure 5. Screenshot of Freelance tank-level trends.


Chemical Engineering Education


Process Station Experimental Station


Operator Station










Graduate Education


TABLE 2
Nonlinear Model Equations
dh1 a- a2 --)2h ylkl
-- -- 2g + -gh + Vi
dt A, A A
dh2 a2 2g2 24 + yk
di A2 A, A1
dh3 a3 (1-y2)k2 kdldl


dh4 a4 2 (1-yl)kl kd,d2
dt A4 A4 A4
A- -- -- A A
TABLE 3
Linearized Model Equations


0 0


0 -- 0
1
0 0
T3
0 0 0


y1iki
A,
0

0

(1-y1)kl
A4


0

Y2k2
A,
(l- 2)k2
A3
0


A, 92h(0)
a, y g


Y7 + Y2 < 1. A modification introduced by the students in the class was the
presence of a disturbance introduced by a submersible pump in the upper
tanks. These disturbances' effects are modeled as a constant leak into or
out of the upper tanks.

PROJECT SUMMARIES
To illustrate the use of the four-tank system in the graduate control
course, the following projects are briefly described. It should be noted
that each of the four elements (modeling, analysis, synthesis, and imple-
mentation) was performed by each student group. A more detailed theo-
retical treatment of the results can be found
in Vadigepalli, et al.141

PROCESS IDENTIFICATION
s


Although the fundamental model de-
scribed earlier is a reasonably accurate de-
scription of the system dynamics, many of
the parameters are not available a priori,
which required estimation of several model
parameters. The tank areas A, can be mea-
sured directly from the apparatus. Using
tank drainage data, the cross-sectional out-
let areas ai can also be determined. The
steady-state operating points of v, = 60%
and v, = 60% were used for subsequent
results. The system valves were
ELUS set such that the operating point
S exhibits inverse response
.. (y, + 2 < 1). Time constants, Ti,
for the linear system model were
on the order of 40 seconds.


The students designed a suit-
able test input sequence to gen-
erate data for the estimation of
the remaining parameters. In this
case, they elected to identify the
parameters of the original non-
linear model, requiring the solu-
tion of a nonlinear optimization
problem. The problem was for-
mulated to minimize the 2-norm
of the difference between the
nonlinear model and actual mea-
surements, searching over four
parameters. Using dynamic data
from the experiments, the optimi-
zation routine found the optimal
pump gains k, and gamma values
yi as depicted in Table 4. A simi-
lar routine was employed to model
the characteristics of the distur-
bance introduced by the submers-
ible pumps, kd, and kd2.


Fall 1999


Figure 6. Screenshot of the Matlab interface.
Figure 6. Screenshot of the Matlab interface.


I
~,~yrp~_~:~~i~b~L~'~I~4*IIPI6E~a~-~~e~


1 0
Ti
1










Graduate Education


A critical step in any identifica-
tion procedure is validation of the
model against novel data. The stu-
dents were successful in validating
the model that resulted from the pre-
vious optimization problem. They
were able to capture the known in-
verse response in the system, and
they also were able to compare the
nonlinear model response to a lin-
ear approximation, which was sub-
sequently used for analysis.

ACCEPTABLE
CONTROL ANALYSIS
As mentioned earlier, one of the


key insights derived from this course is the limitation to
achievable closed-loop performance due to intrinsic system
properties. Once the students had obtained the physical mod-
els of the system, they computed a linearized approximation
at a steady-state operating point and analyzed the controlla-
bility properties of the resulting linear system. The inputs
and outputs of the system were appropriately scaled before
the controllability analysis was carried out.
The first metric considered was the relative gain array
(RGA) as a function of frequency. For the system configura-
tion employed in this study, the students found that the
diagonal RGA elements were very near to 1 at low fre-
quency, suggesting an easily decoupled system. But as
the frequency increased to the bandwidth region, the
students discovered that the diagonal RGA values de-
creased significantly, indicating the importance of multi-
variable interactions in the bandwidth of interest. Such
an insight is particularly valuable at the graduate control
level to highlight the limited interpretation of the steady-
state RGA value.
Additional insight is derived from an analysis of the singu-
lar values of the system. More specifically, their ratio (the
condition number) gives an indication of the sensitivity of
the plant to uncertainty. The condition number at low fre-
quencies was small, between 1 and 3. But it decreases with
frequency, implying that the plant is more sensitive to uncer-
tainty at steady state than at higher frequencies. In addition,
the low frequency minimum singular value is above 1. This
means that adequate control action should be possible;
the input moves will be able to move the outputs a
sufficient amount to track setpoints. The minimum
singular value of the plant is greater than 1 up to the
frequency of o=0.007 rad/sec. This indicates a poten-
tial constraint on the controller bandwidth because of
high frequency input saturation.
Another quantity of interest in control systems in general,


and the four-tank system in particular,
is the location and direction of multi-
variable process zeros. For the operat-
ing conditions in this study, the multi-
variable zeros are found to be at -0.0791
and 0.0285 rad/sec. The input zero di-
rection corresponding to the right-half-
plane (RHP) zero is [-0.715, 0.699]T,
and the output direction is [0.718,
0.696]T. From these directions, one can
see that forcing one pump up while the
other is forced down causes the sys-
tem to display inverse response. The
presence of the RHP-zero could also
be seen in a plot of the RGA, in that the
elements of the RGA change sign from


frequency o)=0 to frequency o = _. The lesson that the stu-
dents will take away from this analysis is that the RHP-zero
also limits the controller bandwidth.

UNCERTAINTY CHARACTERIZATION
For completeness in the overall project description, the
topic of uncertainty characterization is briefly mentioned.
The technical details can be found in Vadigepalli, et al.141
The emphasis was on bounding the uncertainty between the
approximate linear model that was used for controller syn-
thesis and the actual physical system with parametric uncer-
tainty. A multiplicative input uncertainty structure was de-
termined by the students to adequately represent the actual
non-ideal behavior of the system. After subjecting the linear
model to parametric variations (10% in yi and k,), approxi-
mate bounds were determined from the corresponding fre-
quency plots of the multiplicative uncertainty. This uncer-
tainty characterization is central to the robust controller de-
sign task that is described below.

ROBUST CONTROLLER
DESIGN AND IMPLEMENTATION
The students employed robust control theory to initially
design an H, controller following the procedures detailed
in Balas, et al.J5 Using a D-K iteration procedure, a robust
12l-order controller with a structured singular value, g, less
than 1 was obtained. The controller was implemented in the
real system. As one might expect with a physical system, the
simulations did not precisely match reality. The nonidealities
of the pumps, level sensors, and head losses in the piping all
contributed to these discrepancies. Other unmodeled phe-
nomena witnessed by the students include the formation of
vortices in the upper water tanks above the drainage holes
and spontaneous triggering of the level alarms due to con-
densation. Despite the lack of perfect agreement between
theory and practice, the students were able to generate con-


Chemical Engineering Education


TABLE 4
Model Parameters


a, a2 2.3 cm k, 5.51 cm-/s
a,, a4 2.3 cm2 k2 6.58 cm3/s
A A,, A3, A4 730 cm2 g 981 cm/s2
v (0) 60% 7l 0.333
v2(0) 60% Y2 0.307
T, 53.8 sec h,(0) 14.1 cm
T, 48.0 sec h,(0) 11.2 cm
T, 38.5 sec h3(0) 7.2 cm
T4 31.1 sec h,(0) 4.7 cm










Graduate Education


trollers with robust performance guarantees.
Representative results demonstrating the disturbance rejection capa-
bility and setpoint tracking performance of one controller design are
shown in Figures 7 and 8, respectively. This controller was designed
for disturbance rejection, which results in excessive input moves for
setpoint moves. A robustly performing setpoint tracking controller was
also implemented. This design requires an additional setpoint filter in
order to satisfy the constraints on the input moves.
The students clearly mastered a moderately complex control problem.


Time (seconds)
Figure 7. Disturbance rejection using robust controller.


Fall 1999


SUMMARY
We have described the use of an elegant experi-
ment for reinforcing the theoretical content of a
typical graduate control course. Although the over-
all physics of the process are not very sophisti-
cated, we have shown that the system exhibits rich
behavior that can be used to exercise principles in
modeling, analysis, and advanced control design.
The use of a PC-based DCS coupled with
MATLAB/Simulink was particularly effective in
the implementation of the laboratory control pro-
cess. The PC-based system was more flexible than
traditional DCS systems, and the DDE interface
facilitated a range of complex control designs that
are appropriate for the graduate level.
Our ongoing efforts with this experiment in-
clude the use of the four-tank system in a
multidisciplinary control engineering laboratory.
The course was first offered in the spring of 1999
as a senior-level elective and drew students from
chemical, electrical, and mechanical engineering.
We plan to report our experiences with this imple-
mentation in a future publication.

ACKNOWLEDGMENTS
We would like to acknowledge the support of
our former Dean, Stuart Cooper, who first encour-
aged us to create such a lab and provided the initial
funding. The continuing support of our department
Chair, Eric Kaler, and Dean, Andras Szeri, is greatly
appreciated. None of this work would have been
possible without the expert craftsmanship of George
Whitmyre, who constructed the four-tank system.
We would also like to acknowledge the additional
graduate students who worked on the four-tank sys-
tem-Luis J. Puig and Radhakrishnan Mahadevan.

REFERENCES
1. Skogestad, S., and I. Postlethwaite, Multivariable
Feedback Control, John Wiley & Sons, New York,
NY (1996)
2. Kheir, N.A., K.A. Astrom, D. Auslander, IKC. Cheok,
G.F. Franklin, M.M. Masten, and M. Rabins, "Con-
trol Systems Engineering Education," Automatica,
51(8), 147 (1995)
3. Johansson, K.H., and J.L.R. Nunes, "A Multivari-
able Laboratory Process with an Adjustable Zero,"
in Proc. American Control Conf. (1998)
4. Vadigepalli, R., E.P. Gatzke, and F.J. Doyle III,
"Robust H, Control of a Multivariable Experi-
mental 4-Tank System," in preparation (1999)
5. Balas, G.J., J.C. Doyle, K. Glover, A. Packard, and
R. Smith, p -Analysis and Synthesis Toolbox User's
Guide, The Mathworks, Natick, MA (1995) J

275


S0.5
a-


0 __


0 500 1000 1500


Time (seconds)

Figure 8. Reference tracking using robust controller.


1 I


, ,


2000 2500 3000


--











Random Thoughts...





FAQS. II

Active Learning vs. Covering the Syllabus

and Dealing with Large Classes


RICHARD M. FIELDER, REBECCA BRENT
North Carolina State University Raleigh, NC 27695


In an earlier column,111 we listed the top ten questions we
get at teaching workshops and responded to the first one
("Is there any hard evidence that the instructional meth-
ods we recommend actually work?") In this column we
consider two more questions.
Early in our workshops-usually within the first 15 min-
utes-we suggest that instructors include brief active exer-
cises in their lectures. Some participants invariably express
concern that they have to present a lot of material in their
courses, and one of them poses Question #2: How can I take
the time for those exercises and still cover the syllabus?
Another follows up by observing that he or she teaches a
lecture class to 175 students and raises Question #3: Can you
use these methods in large classes?


Can you use active learning and
still cover the syllabus ?

A huge volume of material can be "covered" in a short
period of time. If you put all of your lecture notes in
PowerPoint or on transparencies and flash through them in
class, you can get through several hundred pages of text in a
month. The question is, what is your objective? If it is
simply to present all of the prescribed course material, re-
gardless of how much or little of it the students actually
absorb, then you should not use active learning exercises-
they do indeed slow things down. On the other hand, if the
objective relates to what the students learn as opposed to
what you present, then the goal should not be to cover the
syllabus but to uncover the most important parts of it.
People acquire knowledge and develop skills only through
repeated practice and feedback, not by watching and listen-
ing to someone else showing and telling them what to do.* In
" For theoretical and empirical support of this claim, see any text
on cognitive psychology written in the last twenty years, e.g.,
Pressley and McCormick.2'


lecture classes, most students are neither practicing nor re-
ceiving feedback on anything. They are just sitting there-
sometimes watching and listening to the lecture, sometimes
thinking of other things, sometimes daydreaming or sleep-
ing. Most of them would learn just as much if the classes
were cancelled and they were simply given the lecture notes
and homework assignments and perhaps review sessions
before the tests.
It's a much different story if lectures are punctuated with
brief active exercises that call on students-working indi-
vidually or in small teams-to answer questions, begin prob-
lem solutions, fill in missing steps in derivations, brain-
storm, formulate questions about material just presented,
summarize, or do anything else that they may subsequently
be asked to do in homework and on tests.13? The exercises
energize the students (sometimes literally waking them up),
direct their focus to the most important points in the lecture,
and increase their subsequent concentration when the lecture
continues. They give the students practice in the methods
and skills the course is intended to teach them and immedi-
ate feedback on their efforts, thus meeting the criteria for
learning to occur. Even if some material were dropped from
the course syllabus to make way for the exercises, the in-
creased learning would more than compensate for the loss.
But there is no need to shorten the syllabus. Suppose that
instead of saying every word and writing every statement
and drawing every diagram and deriving every equation in
class, you were to put a lot of the material in class handouts
that include gaps-skipped steps in derivations, axes with
no curves showing-and exercises with spaces left for re-
sponses. "Estimate the solution of this problem." "If you
increase the temperature, how would you expect the product
yield to vary? Why?" "Draw the free-body diagram" "Fill
in the missing steps between Eqs. (4) and (5)." Further,
suppose you announce that you will not go over most of the
Copyright ChE Division of ASEE 1999


Chemical Engineering Education











details in the handouts in class, but any of it-especially the
gaps and questions-could show up on the test. Most of the
students will then actually read the handouts-at least after
the first test, when they discover that you meant it.
This strategy accomplishes several things. By eliminating
the need to say and write and draw everything in class, you
buy yourself many classroom hours that can be devoted to
the things that make learning happen-spending more time
on conceptually difficult material, giving more examples,
asking and answering questions, and implementing active
learning. You can fill in some of the gaps in the handouts in
class; get the students to fill in others in active learning
exercises; and leave some for them to work out for them-
selves before the test. The students learn more (we learn by
doing, not by watching and listening), the classes are more
lively, daily attendance increases, and the syllabus is safe.


Do active learning methods work in large classes?

The larger a class, the more essential it is to use active
learning.4 7] In a traditional lecture class with 15 students, it
is not too difficult to get almost everyone actively involved
in asking and answering questions and participating in dis-
cussions of course material. In a class with 40 students it is
extremely difficult to do so, and in a class of 75 or more it is
virtually impossible. Few students have the self-confidence
to risk looking foolish by asking or answering questions in
front of a large number of classmates, and the traditional pep
talks proclaiming that there are no dumb questions and that
wrong answers are also valuable generally have little effect.
On the other hand, when a class is periodically given some-
thing to do in groups of two or three, the risk of embarrassment
is minimal-the only real difference between a class of 20 and
a class of 200 is that the latter class is noisier during activities.
A key to making active learning work in large classes is to
stop the activity after the prescribed time interval and call on
individual students or teams to state their results." If you
only call for volunteers to provide responses after a group
exercise, many students will not participate in the activity,
knowing that sooner or later another student or the instructor
will supply the answer. If they know that any of them could
be called on, the same fear of embarrassment that keeps
them from volunteering responses in the whole class will
prompt most of them to work with the small group so they
will be ready with something if they are picked.
Instructors who have never used active learning in a large

When we do this, we tend to overload on the back of the class-
room, where many students go to avoid the instructor's attention.
In our classes the students quickly learn that they can run but they
can't hide.


class usually envision two problems. They worry that some
students will refuse to participate under any circumstances
and that the noise level during the activity will make it
difficult to regain control of the class.
In our experience, more than 90% of the students in a class
routinely participate in active learning exercises after the
first few (when they feel awkward and unsure about what
they are supposed to do), and the usual involvement is closer
to 100%. Nevertheless, it disturbs instructors to see even one
student sitting with arms crossed, pointedly refusing to par-
ticipate, and the instructors often take such observations as
evidence that the method is failing.
That's the wrong way to look at it. Suppose a full 10% of
your students sit on their hands during an active learning
exercise. This means that 90% of your students are engaged
in thinking about what you want them to think about and
trying to apply the concepts you have been teaching, so that
the odds are 9 to 1 in your favor. In a typical traditional
lecture, the percentage of the class actively engaged in think-
ing about the lecture content at any given time, let alone
trying to apply it, is generally very low. Even if it is as high as
10%, which is unlikely, the odds are 9 to 1 against you. No
instructional method-lecturing, active learning, multimedia
tutorials, or anything else-is guaranteed to reach every stu-
dent. As an instructor, the best you can do is go with the odds.
It is true that in a large class the noise level can make it
more difficult to bring the students' attention back to you,
which makes it important to establish a signal (e.g., a buzzer,
whistle, or handclap) for them to finish their sentence and
stop the discussion. After the first few exercises, we have
never had to wait for more than 10 seconds for the room to
quiet down, even with 400 people there. Besides, if you are
teaching a class in which the students are so involved in
answering your questions or working out your problems that
you have trouble getting them to stop, there are far worse
problems you could have.

REFERENCES
1. Felder, R.M., and R. Brent, "FAQs," Chem. Eng. Ed., 33(1), 32 (1999)
2. Pressley, M., and C.B. McCormick, Cognition, Teaching and Assess-
ment. HarperCollins, New York, NY (1995)
3. Felder, R.M., (i) "Any Questions?" Chem. Eng. Ed., 28(3), 174 (1994);
(ii) "How About a Quick One?" Chem. Eng. Ed., 26(1), 18 (1992)
4. McKeachie, W.J., Teaching Tips: Strategies, Research, and Theory for
College and University Teachers, 10h ed., Houghton Mifflin Co., Bos-
ton, MA (1999)
5. Felder, R.M., "Beating the Numbers Game: Effective Teaching in
Large Classes<' Proc. 1997 Annual ASEE Conf., American Society for
Engineering Education (1997) users/f/felder/public/Papers/Largeclasses.htm>
6. "On Teaching Large Classes," occasional_papers/large_classes.htm>
7. "Teaching Large Class Sections," The Penn State Teacher. II. Learning
to Teach; Teaching to Learn U


Fall 1999


All of the Random Thoughts columns are now available on the World Wide Web at
http://www2.ncsu.edu/effectiveteaching/ and at http://che.ufl.edu/-cee/











class and home problems


The object of this column is to enhance our readers' collections of interesting and novel
problems in chemical engineering. Problems of the type that can be used to motivate the student
by presenting a particular principle in class, or in a new light, or that can be assigned as a novel
home problem, are requested, as well as those that are more traditional in nature and that
elucidate difficult concepts. Manuscripts should not exceed ten double-spaced pages if possible
and should be accompanied by the originals of any figures or photographs. Please submit them to
Professor James O. Wilkes (e-mail: wilkes@engin.umich.edu), Chemical Engineering Depart-
ment, University of Michigan, Ann Arbor, MI 48109-2136.




BEWARE OF

BOGUS ROOTS WITH

CUBIC EQUATIONS OF STATE

RONALD M. PRATT
National University of Malaysia Bangi, Selangor, Malaysia 43600


he Peng-Robinson equation of state and its close kin,
the Soave-Redlich-Kwong equation, are simple yet
very effective tools for solving phase equilibria prob-
lems involving hydrocarbons and other nonpolar and slightly
polar species. Being cubic equations, when solved for the
compressibility factor, Z, they will either yield three real
roots or a single real root and a complex pair. It would be
most convenient and is sometimes believed that one single
root implies a single phase while three real roots imply
liquid and vapor phases are in equilibrium. Sadly, such is
not the case. Care must always be taken to extract the
correct root. Major blunders can be made, as we will show
in the following problem.

(PROBLEM STATEMENT)

Pure n-butane at 430K and 60 bars is throttled to a final
pressure of 10 bar, as shown in Figure 1. What is the tem-

Ronald M. Pratt is a lecturer in the engineering department at the
National University of Malaysia. He obtained his BS in mathematics and
in chemical engineering at the Colorado School of Mines, his MS in
mathematics at the Fuxin Mining Institute in Liaoning Province, China,
and his PhD in chemical engineering at the Colorado School of Mines.
Research interests involve molecular dynamics and fractal modeling,
and his teaching responsibilities have included undergraduate, gradu-
ate, and statistical thermodynamics courses and molecular simulation.

Copyright ChE Division of ASEE 1999


T1 = 430K T2 = ?
PI = 60 bar P2 = 10 bar

---M--
n-butane
Figure 1. Throttling of n-butane to known final pressure.

perature of the stream as it exits the valve? Use the Peng-
Robinson equation of state to model the PVT behavior of n-
butane.

SOLUTION

The Peng-Robinson equation is written as
RT a
P= (1)
v-b v(v+b)+b(v-b)
where
R universal gas constant
T absolute temperature
v molar volume

a ac [l+m(l- Ti/2 T
a. 0.45723553 R'T'2P


Chemical Engineering Education












m 0.37464 + 1.54226 co-0.26992 (02
b 0.077796074 RT/P
T critical temperature = 425.1K for n-butane1'
P critical pressure = 37.96 bar for n-butane111
o pitzer acentric factor = 0.200 for n-butane1'I

It is common to rewrite the Peng-Robinson equation as a
cubic polynomial,

f(Z)= Z3 + cZ2 + Z + = 0 (2)

where
a B-l

P A-2B-3B2
y B + B' AB
and
A aP/(RT)2
B = bP/RT
Since an energy balance written across the valve (assum-
ing residence time of the fluid in the valve is so short that
heat loss through the valve casing is negligible) states that
AH = 0, we therefore need to find the exit temperature, T2,
that satisfies this condition. This requires that we be able to
calculate the enthalpy change across the valve, AH. We will
consider AH to be the sum of two parts, an ideal gas contri-
bution and a residual correction for non-ideal behavior,

AH= AHID + AR (3)

The ideal gas contribution is determined from ideal gas
(low pressure) heat capacity data:
T,
AHID CCdT (4)
T,

Heat capacities for gases in the ideal gas state are func-
tions of temperature only and are usually given by correla-
tions. A common correlation'" is

CP =R(A+BT+CT2+DT2) (5)

Table 1 shows the coefficients for n-butane in the ideal gas
state.
The residual contribution is calculated using standard equa-
tions12'31 derived from the Peng-Robinson equation of state,

AHR = HR H (6)

where


Ta'-a Z+B(+ )
HR T8 -nZ -) + RT(Z 1)
bVs Z+B(l-V2)


TABLE 1
Ideal Gas State Heat
Capacity Coefficients
for n-butane

n-butane
A 1.935
B 36.915 x 10-3
C -11.402x 106
D 0


TABLE 2
Enthalpy Changes

T2,K) AH(J/mole)


400
375


1810.13
5508.98


350 2394.94
325 -683.42
330.531 0.00


Sda -ma
dl [l+m(l T-/T,)]TT


HR and H2 are evaluated from Eq. (7) using the compress-
ibility factors corresponding to the initial and final states,
respectively.
A temperature for the stream leaving the valve may be
guessed and AH calculated as indicated above. Proceeding
by trial and error (the secant method]41 could be used to
impose self-consistency and avoid a trial-and-error solu-
tion), we obtain Table 2. We see that a value of T2 = 330.531K
gives a AH equal to zero (within two decimal places accu-
racy).
The "solution" is that the exit stream is n-butane vapor at
330.531K. All done, right? Not quite. Everything seems well
until one looks at a phase diagram for n-butane or notices
that the temperature is well below its boiling point at 10 bar
pressure (T'"'=352.475K), and therefore at these exit condi-
tions (10 bar, 330.531K) n-butane is a subcooled liquid. This
is shown in Figure 2. The actual state of n-butane at 10 bar


0 200 400 600
kJ Ikg


800 1000 1200


Figure 2. Pressure-enthalpy diagram for n-butane.


Fall 1999











and 330.531K is shown by the m in Figure 2, obviously far
from the correct solution (Point 2 in Figure 2), which indi-
cates that the exit stream is a mixture of vapor and liquid.
The calculation has been deceiving us with bogus quasi-
vapor roots. Vapor roots can only be used for temperatures
above the boiling point. Below this temperature, liquid roots
must be used. Therefore, to proceed with the solution to this
problem, we should first determine the boiling point, Tsat, for
n-butane at 10 bar. Since at the boiling point, liquid and
vapor phases must be in equilibrium, we must find the tem-
perature at which the chemical potentials of both phases are
equal. For a pure component, this is equivalent to saying that
the Gibbs free energies must be equal for the two phases.
Since the ideal gas contribution to the Gibbs free energy is
the same for each phase, we only need concern ourselves
with the residual contribution. At the boiling point we re-
quire that

G = (8)
The residual Gibbs free energies are calculated from the
Peng-Robinson equation of state using the standard derived
formula12.3'


-0.5 0 0.5 1 1.5
v, m^3/kmnl


GR b = n -(- RT(Z B)+RT(Z 1) (9)
b;8 Z + B(l-V2) I

The vapor GR in Eq. (8) is computed from Eq. (9) using the
largest compressibility factor root. Similarly, the liquid GR
should be calculated using the smallest root. Different tem-
perature values may be selected on a trial-and-error basis
until the equivalence of Eq. (8) is satisfied to within some
tolerance. (Again the secant method can be used to facilitate
coding of this algorithm.) Proceeding in this manner, we
find that at 352.475K, GR = GL = -540.28 J/mole, and there-
fore Tsa = 352.475K.
For this problem, one will find that AH is positive when
using the vapor roots at T'"", and AH is large and negative
when using the liquid root at Tsat. Therefore, the exit stream
is a mixture of liquid and vapor in just the right combination
to make AH = 0. Equation (6) must be modified to include
both a vapor and liquid contribution to the enthalpy of the
exit stream,

AHR = xHRv + (1 x)HR HR (10)


2 25 =23438
2 2.5 3


Figure 3. Magnified pressure-volume diagram in the region
P=10 bar for n-butane


Chemical Engineering Education


TABLE 3
Computed Compressibility Factors

T ZL Zmiddle Zv vL(m3/kinol) Vmiddl(m3/kmol) v (m3/kmole)
280 0.03982 none none 0.09270 none none
293 0.03907 0.44221 0.48898 0.09617 1.07724 1.19116
352.475 0.03880 0.13666 0.79982 0.11370 0.40048 2.34383
396 0.05482 0.05694 0.86624 0.18048 0.18746 2.85197
600 none none 0.96897 none none 4.83360

I











where x is the quality or percent vapor in the two-phase exit
stream. When the calculation is made using Eq. (7), the exit
stream is found to have a quality of 0.8434. Therefore, the
correct solution to the problem is that the exit stream is at its
saturation temperature of 352.475K and consists of 84.34%
vapor and 15.66% liquid (as shown in Figure 2).

DISCUSSION
To illustrate more clearly what has happened here, we will
look at solutions of the Peng-Robinson equation for Z (and
v) at 10 bar at various temperatures. Obviously, at 10 bar, n-
butane exists as a superheated vapor above Ta"" and as a
subcooled liquid below T"s'. At various temperatures at P=10
bar, we obtain Table 3 from Eq. (2).


Which roots are valid?
Certainly we can rule out
all of the intermediate or
middle values. (These in-
termediate roots that lie
within the saturation en-
velope are of use in sta-
bility analysis,151 some-
thing we are not con-
cerned with here.) Also,
any liquid roots above the
boiling point must be
ruled out, and any vapor
roots below the boiling
point must be eliminated.
Only the values in bold
print hold any physical
significance for us. (The
Peng-Robinson equation
is not recommended for
calculating subcooled liq-
uid values, but values are


0.02
2
0.02 293K
0.00

Da
;-).02

-0.04

352.475
-0.06 -


-0.08 .
0 0.1 0.2 0.3 0.4 0.5
Z


treated in Figure 4, which shows the cubic polynomial in Z
(Eq. 2) as a function of Z. This area is marked "Danger!" in
Figure 4. The polynomial crosses the zero horizontal axis
three times within the danger region 293K fore, in our example above, at 330.531K, the Peng-Robinson
equation cheerfully provided an erroneous vapor root that
gave us a nonsense solution to the problem.
A similar situation exists at temperatures above the boiling
point. Between the boiling point and temperatures as high as
396K (a 43K spread), bogus liquid roots are calculated. This
dangerous region is also marked on Figure 4. At tempera-
tures over 396K, only a single (vapor) root is calculated, and
there is no danger of bogus roots.


The key point is that before we can decide which roots are
valid and which are bo-
gus, we must already
know the boiling point.
0K An equivalent procedure
would be to select the
value of Z that corre-
sponds to the lowest re-
nger sidual Gibbs free energy
or fugacity161 since the
liquid and vapor free en-
ergy curves cross at the
boiling point. Without
K=BoilingPo taking these steps, it is
Danger! rK easy to end up in big
K 600K trouble.
0.6 0.7 0.8 0.9 1 CONCLUSION

In conclusion, it is not


Figure 4. The Peng-Robinson polynomial
f(Z) = Z3 + oZ2 + PZ + y
as a function of Z for n-butane at 10 bar for various temperatures.


physically significant
even if they are of low accuracy.)
Figure 3 is a magnified PV diagram in the region of 10 bar
and shows the bogus liquid root at 396K (0.18048 m3/kmol)
and the bogus vapor root at 293K (1.19116 m3/kmol). Their
respective valid superheated vapor and subcooled liquid vol-
ume roots are also shown. The saturated molar volumes are
also indicated in Figure 3. Note that the bogus roots lie
within the phase envelope.
The danger is that we obtain what appear to be liquid and
vapor roots in regions quite far from the boiling point. A
value of 293K is the minimum temperature (rounded to a
whole number) that will still yield a bogus vapor root. At
temperatures lower than this, the Peng-Robinson equation
will provide just one real (liquid) root, and there is no dan-
ger. In this region between the boiling point and 293K (about
a 60K spread), bogus vapor roots will appear. This is illus-


possible to assume sim-
ply that large roots of Eq.
(2) are vapor values and
that small roots are for


the liquid. There is a large margin on both sides of the
boiling point where bogus liquid or vapor roots are calcu-
lated. Selection of the correct root requires additional infor-
mation, and considerable care must be taken.

REFERENCES
1. Smith, J.M., H.C. Van Ness, and M.M. Abbott, Introduction
to Chemical Engineering Thermodynamics, 5th ed., McGraw-
Hill, New York, NY (1996)
2. Sandler, S.I., Chemical and Engineering Thermodynamics,
John Wiley & Sons, New York, NY (1999)
3. Kyle, B.G., Chemical and Process Thermodynamics, Prentice
Hall, Englewood Cliffs, New Jersey (1992)
4. Carnahan, B., H.A. Luther, and J.O. Wilkes, Applied Nu-
merical Methods, John Wiley & Sons, New York, NY (1969)
5. Walas, S.M., Phase Equilibria in Chemical Engineering,
Butterworth-Heinemann, Boston, MA (1985)
6. Savage, P.E., "Spreadsheets for Thermodynamics Instruc-
tion," Chem. Eng. Ed., 29, 262 (1995) U


Fall 1999











, W curriculum


PARTICLE TECHNOLOGY

ON CD


MARTIN J. RHODES
Monash University Clayton, Victoria, Australia 3168


he importance of particle technology to the practic-
ing chemical engineer has been highlighted by ar-
ticles such as those by Ennis, et al.,I'" which drew
attention to "the legacy of neglect in the U.S.," and Nelson,
et al.,121 which invited us to "teach 'em particle technology."
These articles and the excellent series of articles on particle
science and technology in the spring 1998 issue of CEE have
done much to raise awareness in industry and academia of
the importance of particle technology to the process indus-
tries, of the initiatives that have been set in place to address
the problem, and the need to teach it in chemical engineering
courses.
Several of the CEE articles drew attention to the shortage
of educational resources for particle technology. Davis and
Fan'31 highlighted the lack of suitable teaching materials and
recommended that booklets of homework problems, soft-
ware, CD-ROMs, laboratory demonstrations, experiments,
and textbooks were required. Nelson and Davies141 announced
the establishment of a web site for gathering multimedia
educational modules prepared by experienced people in the
particles field for dissemination to educators in chemical
engineering. Chase and Jacob151 reported on their successful
introduction of a solids processing course, team-taught by
academia and industry to senior undergraduates at the Uni-
versity of Akron.
These authors highlighted the need to use a range of pri-
mary references and reported on students' strongly voiced
opinion that better textbooks are needed on the subject.
Donnelly and Rajagopalan161 reported on the development of
a series of instructional modules on particle technology top-
ics at the Engineering Research Center for Particle Science
and Technology. The objective of the module series pro-
gram is to permit particle technology topics to be squeezed,
in small doses, into the already overcrowded chemical engi-
neering curriculum.
This article will focus on educational resources for teach-
ing particle technology and, in particular, on laboratory and


classroom demonstrations, which highlight important phe-
nomena and the ways in which the behavior of particulate
solids is surprising and often counter-intuitive when intu-
ition is based on our experience with fluids.
Personal experience gained from teaching particle tech-
nology over a period of fifteen years, at two institutions,
taught me that in order to get students' attention it was often
necessary to do some demonstrations to show how powders
behave differently from liquids and gases. A dust explosion,
for instance, is impressive and never fails to grab attention.
A good-sized fluidized bed, preferably with a floating plas-
tic duck, is another good one for audiences of all ages and
backgrounds. A large steel ball that rises to the top of a
beaker of sand upon shaking, is a favorite, and since it is the
only one that is readily portable, I tended to rely on it more
and more as I grew older and lazier.
I realized at an early stage that demonstrations of the many
interesting phenomena in particle technology are time con-
suming to set up in the lecture theater or the laboratory.
Therefore, I made short videos of the more interesting phe-
nomena and those that are the most difficult to explain
through the spoken and written word, diagrams, or photo-
graphs. I also borrowed video clips from others who are
more talented at setting up the demonstrations (Professor
Derek Geldart of Bradford University on fluidization and
NEU Engineering on pneumatic transport).

Martin Rhodes is Reader in the Department
of Chemical Engineering at Monash Univer-
sity in Australia. With a keen interest in par-
ticle technology education, he has directed
continuing education courses in the area and
is author of the undergraduate textbook In-
troduction to Particle Technology. His re-
search interests include fluidization, gas-par-
ticle flows, interparticle forces, and particle
mixing.


Copyright ChE Division of ASEE 1999


Chemical Engineering Education


282











The CD-ROM medium al-
lowed me to combine video clips
and explanatory text in a form
that is easy to use by both the
educator in the classroom and
the student at home. The result-
ing CD-ROM of "Laboratory
Demonstrations in Particle Tech-
nology" was compiled with the
assistance of one of my research
students, Alfi Zakhari, over a
period of several months.

CD-ROM OF
LABORATORY
DEMONSTRATIONS IN
PARTICLE TECHNOLOGY
The topics covered in the labo- Figure 1. Core flow of
ratory demonstrations featured 250-micron sand wi
on the CD-ROM include flow to ac
patterns in hoppers, fluidization
phenomena, hindered settling, gas cy-
clones, dust explosions, pneumatic trans-
port, size and density segregation, and
stresses developed in particulate solids.
The user can easily navigate the topics
on the CD by using mouse-activated but-
tons. An explanation of what is featured
under each topic is given below.

Mass Flow and Core Flow
in Storage Hoppers

Mass Flow In perfect mass flow,
all the powder in a storage hopper is in
motion whenever any of it is drawn from
the outlet. Mass-flow hoppers are smooth
and steep. A video sequence shows sand
of mean particle size 250 p.m in mass
flow. The use of alternate layers of col-
ored powder in this sequence clearly Figure 2. A Gel
shows the key features of the flow pat- fluidized
terns: the powder surface remains level
until it reaches the sloping section; the flowing channel
coincides with the walls of the silo; all the powder is in
motion; particle velocity profiles are flat in the parallel-
walled section of the hopper.
Core Flow This occurs when the powder flows toward
the outlet of a silo in a channel formed within the powder
itself. The second video sequence shows the same sand (250
pgm) discharging from a hopper where the sloping walls are
less steep. Core flow results (see Figure 1). Alternate layers
of colored powder highlight the important features of core
flow: the surface of the powder forms an inverted cone;


solid
ith s
tas


dart
in a


during discharge, powder flows
along this surface; the only sol-
ids in motion are those flowing
along these surfaces and down
the central channel or core; the
regions of powder lower down
in the hopper are stagnant until
the hopper is almost empty.
Whether we get mass flow
or core flow depends not only
on the slope of the hopper wall,
but also on the properties of
the powder and the interaction
of the powder with the hopper
wall's material of construction.
This fact is demonstrated in a
third video sequence in which
Is in a hopper. Solids are a different sand (mean size of
ome particles colored 100 gpm) gives core flow in the
tracers. steep-angled hopper.

Fluidization
Geldart Classification of Powders *
Geldartt18 classified powders into four
groups (A, B, C, D) according to their
fluidization properties at ambient con-
ditions. The Geldart Classification of
Powders is now used widely in many
fields of particle technology.
El Group A: Powders that, when flu-
idized by air at ambient conditions,
give a region of non-bubbling fluidi-
zation, beginning at the minimum flu-
idization velocity Um,, followed by bub-
bling fluidization as fluidizing veloc-
ity increases, are classified as Group
A. A video clip shows cracking cata-
lyst, a typical group-A powder, exhib-
iting a region of non-bubbling fluidi-
Group-A powder zation as gas velocity is increased from
"2-D" bed. zero through Umf and on to the mini-
mum bubbling velocity Umb. Expan-
sion of the non-bubbling bed as the gas velocity is increased
is clearly seen.
A second video sequence shows that when the air supply is
interrupted, the bed level initially drops abruptly as the
bubbles escape and then more slowly as the gas escapes
from the expanded emulsion phase-another characteristic
of Group-A powders.
A third video shows a Group-A powder in a backlit two-
dimensional fluidized bed, showing splitting and coales-
cence and maximum stable bubble size (see Figure 2).
L1 Group B: The first video shows beach sand, a typical


Fall 1999











Group-B powder, fluidized by air. The video demonstrates that with
Group-B powders, bubbles appear as soon as the powder fluidizes,
ie., at Um. A second video clip shows Group-B powder in a two-
dimensional fluidized bed, and demonstrates that, in Group-B pow-
ders, bubbles continue to grow as they rise and as gas velocity is
increased, never achieving a maximum size (see Figure 3).
El Group C: These are very fine powders that, because of the domi-
nance of interparticle forces, are incapable of fluidization in the strict
sense. Bubbles do not occur. The gas flow forms channels through the
powder. Cracks form, and sometimes discrete plugs of solids are
lifted by the gas flow. The video shows the formation of cracks,
channels, and rising plugs as an attempt is made to fluidize a Group-C
powder (see Figure 4).
LE Group D: These are powders made up of large particles, which like
Group-B powders give only bubbling fluidization when fluidized by
air at ambient conditions, but are distinguished by their ability to
produce deep spouted beds. The video clip shows a deep spouted bed
of rice grains, a typical Group-D material (see Figure 5).

Slugging When the size of the bubbles is greater than about one-
third of the diameter of the fluid bed vessel, the bubble rise velocity is
controlled by the vessel itself. The bubbles become slugs of gas, and
the bed becomes a slugging fluidized bed. A slugging fluidized bed is
shown in the video sequence.

Pneumatic Transport of
Powders
The pneumatic transport
of particulate solids is
broadly classified into two
flow regimes: dilute (or
lean) phase flow and
dense-phase flow.
El Dilute-phase transport:
Under these dilute-phase
flow conditions the solid
particles behave as indi-
viduals, fully suspended in
the gas, and fluid-particle
forces dominate. This is
simulated in the first video
sequence.
El Dense-phase transport:
At the opposite end of the
scale is dense-phase flow,
characterized by low gas
velocities (1-5 m/s) and *
high solids concentrations
(greater than 30% by vol-
ume). In dense-phase
transport, particles are not .
ra r, s a n Figure 4. Attempting to fluidize a
fully suspended and there Geldart Group-C powder
is much interaction be- (wheat flour).


Figure 3. A Geldart Group-B powder fluidized in
a "2-D" bed.


figure 5. A spoutea jiulazea dea oJ rice,
demonstrating typical Geldart
Group-D behavior.


Chemical Engineering Education











tween the particles. Examples of horizontal and vertical
dense-phase transport are shown in video sequences.
Size and Density Segregation
[ Pouring Powder into a Heap: The video sequence dem-
onstrates the segregation that occurs when a mixture of two
different sizes or particles is poured into a heap. Fine par-
ticles are colored differently from larger particles. The
mixture is poured into a narrow Plexiglas box. The char-
acteristic "Christmas Tree" segregation pattern, with the
fines occupying the center of the heap, is clearly ob-
served (see Figure 6). The dominant segregation mecha-
nism in this case is percolation.
[J Segregation in a Rotating Drum: The video sequence
shows a mixture of different-sized particles rotated in a
Plexiglas drum at around 60 rpm. Bands of finer particles
(dark colored) develop over a period of a minute or two (see
Figure 7). The dominant segregation mechanism is again
probably percolation, although other mechanisms are
likely to be involved.
[E Segregation by Vibration: A steel ball bearing, about 25
mm in diameter, is placed at the bottom of a beaker and the
beaker is filled with sand (about 250 pm, but size is not too
critical). The beaker and contents are shaken vertically by



-I


Figure 6. Segregation pattern formed by pouring a free-
flowing mixture of two sizes of particles into a heap
(the fine particles are the darker ones).


Figure 7. Segregation pattern formed by rotating a free-
flowing mixture of two sizes of particles in a horizontal
drum (fine particles are darker).


Fall 1999


hand. After a few shakes, the steel ball has risen to the top of
the sand. Smaller and less-dense balls may be used to dem-
onstrate that the speed of segregation in this case increases
with size and density of the ball. Several mechanisms have
been proposed to explain this effect, e.g, (a) the steel ball is
driven by convection currents set up in the sand; (b) sand
flows into voids created beneath the ball, causing it to rise;
(c) the large momentum of the ball compared to that of the
sand particles drives the ball upwards during the upward
motion of the beaker. A further video sequence shows a two-
dimensional version of the steel ball experiment described
here. A steel disc is shown rising through a bed of glass
beads in a narrow Plexiglas box that is vibrated vertically.
Colored tracer particles show the motion of the glass ballotini
as the steel disc rises. A strobe effect on the video camera
allows the motion of the box to be eliminated.

Fire and Explosion Hazards of Fine Powders
Finely divided combustible solids, or dusts, dispersed in
air can give rise to explosions in much the same way as
flammable gases. Dust explosions have been known to give
rise to serious property damage and loss of life. Most people
are probably aware that dust explosions have occurred in
grain silos and flourmills, and in the processing of coal. But
explosions of dispersions of fine particles of metals (e.g.,
aluminum), plastics, agricultural products, sugar, and phar-
maceutical products can be particularly potent. Processing
steps where fine powders are in dilute suspensions, or are
heated, have a strong association with dust explosions; ex-
amples include dilute pneumatic conveying and spray dry-
ing, which involves heat and a dilute suspension.
In the video sequence, the explosive potential of a few
grams of brown coal is demonstrated in the vertical tube
apparatus. Corn flour, wheat flour, and ground sugar may
also be used. This apparatus is used to classify the powder as
explosible or non-explosible and to determine the minimum
dust concentration for explosion, minimum energy for
ignition, and in a modified form for minimum oxygen for
combustion. Such information is required for the design
of safe plant and equipment for handling and processing
combustible fine powders.
Gas Cyclone Separators
The reverse-flow gas cyclone is a commonly used device
for separating fine solids from suspension in a gas. Inlet gas
is brought tangentially into the cylindrical section and a
strong vortex is thus created inside the cyclone body. Par-
ticles in the gas are subjected to centrifugal forces that move
them radially outwards, against the inward flow of gas and
towards the inside surface of the cyclone on which the solids
separate. The direction of flow of the vortex reverses near
the bottom of the cylindrical section and the gas leaves the
cyclone via the outlet in the top (the solids outlet is sealed to
gas flow). The solids at the wall of the cyclone are pushed
285











downwards by the outer vortex and out of the solids exit.
The video sequence shows a Plexiglas cyclone separating
cracking catalyst from suspension in air. The sequence shows
the flow of the suspension into the cyclone and its transport
in the vortex to the solids exit.

Batch (Hindered) Settling of a Suspension
The simple batch-settling test can supply all the informa-
tion for the design of a thickener for separation of particles
from a liquid. In this test, a suspension of particles of known
concentration is prepared in a measuring cylinder. The cyl-
inder is shaken to thoroughly mix the suspension and then is
placed upright to allow the suspension to settle. The posi-
tions of the interfaces that form are monitored in time. The
video sequence shows the type of settling in which three
zones of constant concentration are formed-a top zone of
clear liquid, a middle zone of concentration equal to the
initial suspension concentration, and the lower zone of final
sediment concentration.

Stress Developed in a Powder
The variation in stress with depth of powder, in the case
where no force acts on the free surface of the powder, is
shown in the video sequence. A force is applied to the lower
surface of the bed of particles via a piston and a spring. The
degree of compression of the spring gives an indication of
the force required to move the bed of particles. Stress is
developed within the bed of particles. The magnitude of the
wall friction opposing motion of the bed is proportional to
the stress developed within the bed and increases with bed
depth. The video sequence shows that, beyond a certain
depth, the wall friction is so great that the bed of particles
cannot be moved. Most of the applied force is transmitted to
the tube walls. In the case of powders stored in a bin, the
walls of the bin support most of the weight of the powder.

USE OF THE CD-ROM
The CD-ROM is intended for use by students on their own
time, although it can equally well be used by the educator in
a classroom equipped with a video projector linked to a
computer with a CD drive. It is intended to be complemen-
tary to the textbook Introduction to Particle Technology.'71
The primary objective of this textbook is to introduce the
subject of particle technology to students studying chemical
engineering. The approach taken is to take a number of key
topics in particle technology, giving the fundamental science
involved, and linking this, wherever possible, to industrial
practice. The coverage of each topic is intended to be exem-
plary rather than exhaustive.
The topics give coverage of broad areas within particle
technology: characterization (size analysis), processing (flu-
idized beds, granulation), particle formation granulationn,
size reduction), fluid-particle separation (filtration, settling,
gas cyclones), safety (dust explosions), transport (pneumatic


transport and standpipes). The topics included demonstrate
how the behavior of powders is often quite different from the
behavior of liquids and gases. The book includes 37 worked
examples and 76 homework exercises with answers. A
solution manual giving fully worked solutions to all the
homework exercises is now available from the Depart-
ment of Chemical Engineering at Monash University (http:/
/www.eng.monash.edu.au/chemeng/).

COMPUTER REQUIREMENTS
Hardware: 486 CPU; 66 MHz; 4 MB RAM; VGA moni-
tor
Operating Systems: CD is self-launching on Microsoft
Windows 95 or NT.

ACQUIRING THE CD
The purpose of putting the demonstrations on CD-ROM
was to be able to make them readily accessible and available
to educators and students. The CD-ROM is available from
the Department of Chemical Engineering at Monash Univer-
sity. Multiple copies are available for distribution to stu-
dents. Those interested should contact the author at
e-mail: martin.rhodes @ eng.monash.edu.au
fax: Int+61-3-9905-5686

ACKNOWLEDGMENTS
The author is grateful to Alfi Zakhari for putting together
the CD-ROM under the author's guidance, and to research-
ers John Sanderson, Igor Sidorenko, and Mao Qi-Ming for
setting up demonstrations and making videos. The author
would also like to thank Professor Derek Geldart of the
University of Bradford, England, for permission to use his
video clips on fluidization, and to NEU Engineering, Woking,
Surrey, England, for permission to use their video clips on
pneumatic transport.

REFERENCES
1. Ennis, B.J., J. Green, and R. Davies, "Key Challenges in
Particle Technology: The Legacy of Neglect in the U.S.,"
Chem. Eng. Prog., 32, April (1994)
2. Nelson, R.D., R. Davies, and K. Jacob, "Teach 'em Particle
Technology," Chem. Eng. Ed., 29, 12 (1995)
3. Davies, R.H., and L-S. Fan, "Teaching Fluid-Particle Pro-
cesses," Chem. Eng. Ed., 31(2), 94 (1998)
4. Nelson, R.D., and R. Davies, "Industrial Perspective on
Teaching Particle Technology," Chem. Eng. Ed., 31(2), 98
(1998)
5. Chase, G.G., and K.V. Jacob, "Undergraduate Teaching in
Solids Processing and Particle Technology: An Academic/
Industrial Approach," Chem. Eng. Ed., 31(2), 118 (1998)
6. Donnelly, A., and R.J. Rajagopalan, "Particle Science and
Technology Education Initiatives at the University of
Florida," Chem. Eng. Ed., 31(2), 122 (1998)
7. Rhodes, M.J., Introduction to Particle Technology, John Wiley
and Sons, Chichester, England (1998)
8. Geldart, D., "Types of Fluidization," Powder Tech., 7, 285
(1973) U


Chemical Engineering Education















Ray W. Fahien Award


Ray W. Fahien Award


Presented to
Robert P. Hesketh
Rowan University


This award was established in 1996 to honor the memory of Ray Fahien, editor of Chemical Engineering
Educationfrom 1967 until his death in 1995. He was effectively the founding father of the journal,
establishing it as a premier publication vehicle in the field of chemical engineering education. He
selflessly gave his time and talents to advance pedagogical scholarship, particularly in the careers of
young educators, through his dedication to the journal and to the profession.

Given annually to an educator who has demonstrated a scholarly approach to teaching and learning and
who has shown evidence of vision and contribution to chemical engineering education. Educators who
have been faculty members for not more than ten years as of July 1st in the year of the award will be
eligible. Nominees are evaluated based on 1) outstanding teaching effectiveness and 2) educational
scholarship. The award recipient should have made significant contributions to chemical engineering
education that go beyond his or her own institution.

Prior Winners: Kirk H. Schulz (1997); Douglas E. Hirt (1998)


William H. Corcoran Union Carbide Lectureship Joseph J. Martin Award
Award Award presented to
presented to presented to Robert P. Hesketh
John M. Prausnitz Liang-Shi Fan and C. Stewart Slater
U. of California-Berkeley Ohio State University Rowan University


ASEE Fellow Member Honorees
R. Neal House Purdue University U John W. Prados, University of Tennessee

Donald E. Marlowe Award James E. Stice, University of Texas
Chester F. Carlson Award C. Stewart Slater, Rowan University
General Electric Senior Research Award Arthur W. Westerberg, Carnegie-Mellon University


ASEE Section Awards
Dow Outstanding New Faculty Award
Rocky Mountain Section Kristi S. Anseth, University of Colorado
St. Lawrence Section Paschalis Alexandridis, State University of New York-Buffalo
Southeast Section Kimberly E. Forsten, Virginia Polytechnic Institute and State University
Outstanding Teaching Award
Middle Atlantic Section Andrew L. Zydney
Midwest Section Frank Manning, University of Tulsa
North Midwest Section Kirk H. Schulz, Michigan Technological University
Pacific Northwest Section Willie (Skip) Rochefort, Oregon State University
Outstanding Campus Representative Award
Middle Atlantic Section Deran Hanesian, New Jersey Institute of Technology
Effective Teaching Award-Engineering
Francis Manning, Tulsa University
Thomas C. Evans Instructional Unit Award
Douglas E. Hirt, Clemson University


Fall 1999 28











] essay


UNIVERSITIES. WHY?



J.M. HAILE
Clemson University Clemson, SC 29634


As the twentieth century draws to a close, the situa-
tion in many institutions of higher education might
be characterized as one of general frustration .
frustration not only among faculty and students but also
among administrators and the society that supports those
institutions. Students seek to reduce frustration by refusing
to take responsibility for their learning, by ignoring the
advantages offered by the university, or, in short, by relegat-
ing education to the periphery of their lives. Faculties seek to
reduce frustration by shifting their focus from "teaching" to
"research" and by narrowing the definition of education;
now, its meaning is largely confined to the transmission of
knowledge sufficient for students to enter a profession. Ad-
ministrators and state legislatures seek to reduce their frus-
tration by imposing regulations and accountability on uni-
versities in the form of management models transferred from
business. In previous generations, faculty were largely un-
hindered because, in the public's view, universities made
only marginal contributions to society. But today, even the
routine activities of faculty are presumed to be too important
to remain unfettered.
The thesis of this essay is that the problems and frustra-
tions now besetting institutions of higher education stem
largely from a misunderstanding of what such institutions
are supposed to be and misdirection relative to what they are
able to accomplish. Such misunderstanding and misdirec-
tion promote short-term demoralization of students, fac-
ulty, and administrators and lead to long-term degen-
eracy of the entire enterprise."1 So, what are universities
supposed to be about?

HISTORICAL SKETCH
In Western cultures, formal schooling first appeared in the
ancient civilizations that thrived along the Tigris, Euphrates,
and Nile Rivers of mid-east Asia. Those schools trained a
class of scribes, some of whom would later become religious
leaders and advisors to the ruling class. The instruction


centered on reading, writing, the arithmetic needed for ac-
counting, and simple reasoning skills that applied to rules for
conducting religious ceremonies and civil actions. In other
words, from the beginning, a formal procedure was deemed
necessary to help students learn to recognize and interpret
abstract symbols and to develop the thought patterns re-
quired to manipulate those symbols. But ancient societies
needed only a few symbol manipulators: the large bulk of
humanity had no use for training in abstractions, for their
needs were fixed on the concrete problem of sustaining life.
Such needs could be met by informal instruction provided
by family and by apprenticeship to craftsmen for learning
specialized skills.
By the Age of Pericles in ancient Greece (ca. 430 BC),
education had spread from the clerics to the youth of a
leisured class. Naturally, this change brought with it a shift
in focus; leisured youth has little patience with the intrica-
cies of either clerical accounting or religious dogma. In-
stead, those ancient youths, like ours today, sought to
understand their relations with the physical world and
their relations with others. The first forms the basis for
scientific inquiry; the second pertains to the proper struc-
ture and function of society.
The ancient Greeks had a genius for reducing matters to
their essentials, and they used education as a vehicle for
seeking such simplifications. Thus, they found that abstract
reasoning simplifies when abstractions are placed in context.
Context simplifies because it shifts our point of view from
an inward one, in which the abstraction is a central issue, to
an outward one, in which an abstraction is seen as part of a
larger whole. In her book, The Greek Way, Edith Hamilton
explained this by the following metaphor.[21

J.M. Haile, Professor of Chemical Engineering at Clemson University, is
the author of Molecular Dynamics Simulation, published by John Wiley &
Sons in 1992 and is the 1998 recipient of the Corcoran Award from the
Chemical Engineering Division of ASEE.


Copyright ChE Division of ASEE 1999


Chemical Engineering Education










In medieval and Renaissance Europe, many communities
undertook wondrous feats of architecture and engineering
that culminated in great cathedrals-complex, vast, and in-
tricate structures of wood, stone, iron, masonry, and glass
woven into arcs, columns, domes, naves, towers, ribs, vaults,
and flying buttresses. By the 14th century,
the elaboration had extended to decoration of
the interiors, including reliefs on walls, stained The the
glass, richly detailed mouldings, surface pat-
terning, networked vaultings, and highly or- essay i
namented interior columns. What remains in- probl
congruous about these impressive structures frustra
is that they were not placed within the con-
text either of their physical surroundings or bes
of the socioeconomic conditions of their so- institf
cities. They did not blend into the environ- higher
ment, but rather dwarfed it-arising from the
earth to intimidate their modest neighbors stem
and the surrounding landscape. A cathe- fir
dral can be beautiful, yet terrifying-inter- misundt
nally consistent, yet elusive-but it always of Wi
draws attention to itself, to its own logic
and grandeur, and away from the world in institU
which it sits. suppol
In contrast, with the temples of the ancient and mih
Greeks we have beauty of a very different relative
kind-a beauty based on simple and restrained
proportion. (The ancient Greeks did not even they ai
have the arch; rather, they had to rely on the accoJ
post and lintel.) Those proportions extend be-
yond the geometry of the building to include
the context into which the temple was placed. The Parthenon
was beautiful not merely because of the precise proportions
and optical illusions that were built into its structure, but also
because it was designed to occupy the Acropolis-the high-
est point in ancient Athens. The Greek temple had no need of
elaborate ostentation, for its beauty was reinforced by its
environment. These same qualities-simplicity, proportion,
and context-characterize sound engineering practice; thus,
Petroski has observed thatl3

Good engineering blends into the environment,
becomes a part of society and culture so naturally
that a special effort is required to notice it.
But the development of minds that can recognize simplic-
ity, proportion, and context, as well as manipulate the ab-
stractions that pertain to them, is no small task; a process of
formal education is required, as the ancient Greeks realized.
How can this be done? Perhaps etymology can offer a hint.
Although the fundamental ideas about education are Greek,
our word education comes from Latin: the sources are the
Latin verbs educare, meaning to raise or bring up, and
educere, meaning to lead or draw out. Thus, an appealing


isis
s th


lion
etti
,tio
edu
lar,


erst
lat.
tioz
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sdir
e to
e a
mpJ


Fall 1999


metaphor is to liken education to drawing water from a well
(students might prefer to liken it to extracting a tooth).
Such an interpretation serves as the basis for the Socratic
method of teaching, exemplified by any of Plato's dialogs,
but most explicitly in the Meno.[4] Thus, edu-
cation is more than transmitting information
to students; rather, to educate means to draw
of this students out so their minds surround knowl-
at the edge, embrace it, and make it a part of them-
selves. For the instructor, this means that sim-
and ply telling ideas to students is not enough;s51
is now for students, it means that merely adding to
their store of knowledge is not nearly enough.
ng To paraphrase Alfred North Whitehead, the
nS Of merely well-informed person is the most use-
cation less bore on earth.161
gely From ancient times and languages, let us
a now shift to the mid-nineteenth century. In
anding 1852, the Church established the Catholic
University in Dublin so that Catholic youth
such might have access to the same advantages of
iS are education as their Protestant neighbors. But
to be although the University was new, the educa-
tional challenges it faced were neither new
ecUton nor parochial. Indeed, certain of those chal-
what lenges are with us still. On the occasion of
ble to assuming the position as the first Rector of
the University, John Henry (Cardinal)
lish. Newman observed, with dismay, that171

All things now are to be learned at once,
not first one thing, then another,
not one well, but many badly.
Learning is to be without exertion,
without attention, without toil;
without grounding, without advance, without finishing.
There is to be nothing individual in it;
and this, forsooth, is the wonder of the age.
"Nothing individual in it"-fearsome words that are indica-
tive of our age.
By the mid-twentieth century, the scenes and the players
had changed again, but the challenges remained. In address-
ing the deplorable state of Spanish society between the World
Wars, Jos6 Ortega y Gasset asserted that a principal purpose
of the university is to teach the vital ideas of the society.1'
Vital ideas include those of science and engineering, which
interpret the physical world; those of politics and law, which
formulate how society is regulated; those of economics and
business, which try to explain the trade for goods and ser-
vices; those of the humanities, which try to help us under-
stand ourselves and our relations to one another; and those of
the arts, which foster self-expression. Note that this purpose
is concerned solely with ideas, for the mind can grapple only











with ideas, and it is only the mind that can be the recipi-
ent of the teaching. (For a readable introduction to the
connections among objective facts, concepts, and soci-
ety, see Bronowski.81)
The sum total of the vital ideas of a society comprises that
society's culture, so even more important than training pro-
fessionals, universities are to transmit the culture of a society
to succeeding generations. This has become an exceedingly
difficult task, for many reasons. One is the sophisticated
abstract thought that is required to describe and understand
modem societies. E. O. Wilson has pointed out that cultures
evolve in tandem with advances in scientific understanding
and with increased facility at manipulating abstract symbols
that represent those understandings.19' This means that, rela-
tive to earlier generations, we have more to do to bring
students to an appreciation of the culture in which they live.
More here refers not only to the number of abstractions, but
also to the complexities inherent in the network of those
many abstractions by which we represent and manipulate
our environment. Thus, in 1999 a committee of the National
Research Council asserted that U.S. students have a poor
understanding of basic scientific principles and their relation
to everyday life;101 further, that

Institutions of higher education should provide diverse
opportunities for all undergraduates to study science,
mathematics, engineering, and technology.

Note this plea applies to all undergraduates.

CHALLENGE TO ENGINEERING EDUCATION
We now want to extend the general comments from the
previous section to the education of engineers. To prevent
the discussion from becoming too abstract, we present it
within the context of a hierarchical cognitive model for
learning. In recent years, several such models have been
proposed; at least three are similar and closely related, al-
though they were proposed independently and are based on
different kinds of evidence. Thus, the cognitive hierarchy
proposed by Egan1"1 is based on studies in educational psy-
chology; the hierarchy proposed by Donald1121 is based on
studies of cultural evolution, and that by Haile'13'15] is based
on studies of brain function. These hierarchical models are
all integrative; that is, the progression to a higher level
requires the individual to master skills and to reorganize
knowledge gained at lower levels.

THE PHILOSOPHIC LEVEL OF UNDERSTANDING
Egan's version of the cognitive hierarchy contains five
levels:1'" somatic, mythic, romantic, philosophic, and ironic.
Each level corresponds to a specific mode for getting thoughts
out of the mind and into forms by which they can be dis-
sected, analyzed, and reassembled. Thus, to oversimplify


considerably, the somatic level includes tactile learning,[161
mythic corresponds to oral learning, romantic involves graph-
ics and written learning, philosophic refers to learning by
formal reasoning, and the ironic level encompasses excep-
tions, limitations, and learning by modeling.
In this hierarchical model, it is the philosophic level that
contains the basic skills required of engineers. At the philo-
sophic level, knowledge and skills mastered at lower levels
may promote development of higher-order thinking skills:
inductive and deductive logic, inferential reasoning, math-
ematical reasoning, analysis and synthesis, critical thinking,
creation of theoretical constructs, and generalizations. These
operations relate, simplify, and extend knowledge gained at
lower levels. To maintain control over the material, we seek
simplifications via patterns, theories, and schema that orga-
nize knowledge into useful structures; that is, in the words of
Mach,'171 we seek economy of thought. The reorganization of
knowledge into abstract and economical structures is the
characteristic activity of learning at the philosophic level.
Note that philosophic understandings may develop, but
they do not necessarily do so. Of the numerous human
cultures that have appeared throughout history, only one-
the ancient Greek-developed to the level of philosophic
understanding. Over the years there has been endless specu-
lation as to why this is so: What was unique to Greek
society? Donald offers the persuasive answer that the break-
through came when the Greeks combined writing with for-
mal logic.1121 Making logic visible through writing clarifies
analysis and communication, and it stimulates further men-
tal growth to levels that, apparently, cannot be reached in
any other way.
The consequences of these observations are profound:
individuals cannot complete the transition to the philosophic
level by themselves. To do so, people must live in a commu-
nity of philosophic and ironic thinkers and learn from them.'"
This is the sine qua non of the university.

IMPLICATIONS FOR ENGINEERING EDUCATION
The traditional view has been that engineers are problem
solvers; hence, engineering was traditionally taught by hav-
ing students solve many, many problems. In recent years,
this view has broadened to encompass a variety of reasoning
skills that are captured under the general rubric of "critical
thinking." But, based on their experience, many engineering
educators have come to believe that today's students are
generally weak problem solvers and poor critical thinkers.
To cite just one example, Wankatl8"' has noted that

My personal observation is that the average engineering
student of 20 years ago was a better problem solver but not as
skilled at calculating as the average engineering student now.

This observation has provoked educators to subject students


Chemical Engineering Education











to more problem solving and more thinking exercises. Thus,
we find recitation sections, student workshops, and spe-
cialized courses devoted explicitly to problem solving,
and we find problem-based learning, discovery-based
learning, and web-based learning intended to develop
and exercise critical thinking.
It is my contention that "more of the same" will not prove
to be the most effective way to overcome these educational
difficulties. Instead, before we can expect students to func-
tion properly at the philosophic level, we must address their
deficiencies at the somatic, mythic, and romantic levels. For
example, the use of equations in derivations, proofs, and
problem solving are logical exercises and, hence, are philo-
sophic activities; however, equations themselves are collec-
tions of abstract written symbols and, hence, are romantic
devices. Further, individual terms and symbols in an equa-
tion are usually interpreted at cognitive levels other than the
philosophic; thus, the interpretation might be in relation to
equipment (somatic), or in terms of a narrative that describes
a process or procedure (mythic), or it might invoke sche-
matic diagrams and plots (romantic). If we ignore these
lower levels of understanding or if we tacitly assume that
students can invoke these levels on their own initiative, then
their success in such philosophic exercises as performing
derivations and solving problems will be fragmentary.
Similarly, manipulations of data-the inferences and de-
ductions that attach meaning to data-are logical exercises
and, hence, invoke philosophic understanding. However, the
steps used to acquire and organize data combine lower levels
in the cognitive hierarchy. Collecting the data involves so-
matic activities using instruments attached to an apparatus or
processing equipment; narrative descriptions of the process
and the experimental protocol are mythic activities; organiz-
ing the data into tabular and graphic forms is a romantic
activity. Many sophomores and juniors fail to find meaning
in data because they cannot organize the data into tables or
plots that reveal patterns or trends.
With the activity we call problem solving, success re-
quires a much more complex array of cognitive skills than is
usually required to manipulate equations and analyze data.
Problem solving is obviously philosophic: we use abstract
symbols to represent quantities and processes, and we ma-
nipulate those symbols according to logical rules to extract
unknowns from knowns. But to find an algorithm for solving
a problem, we appeal to more cognitive levels than just the
philosophic. Thus, WankatI181 notes

The expert problem solver writes things down, draws sketches,
constructs a variety of different representations of the problem
... expects the problem to eventually make sense and is
looking for this sense ...

The expert expects that finding a sensible interpretation of a
problem will also indicate a direction toward a solution; in


pursuing that search, the expert appeals to many levels in the
cognitive hierarchy. For example, sketches, schematics, and
plots are romantic devices; connecting the problem to hard-
ware and equipment appeals to somatic understandings; nar-
rative descriptions of processes and responses to changes in
variables are mythic activities; models introduced to achieve
appropriate simplifications are ironic devices. In contrast to
the expert, many sophomores flounder at solving problems
because they fail to sketch the situation, or to articulate a
story about the situation, or to connect the situation to hard-
ware, or to recognize what equations might apply-their
low-level cognitive skills are insufficient for the task.
These examples suggest that success at the philosophic
level requires facility with understandings at other levels. If
we accept that the fundamental purpose of the university is
to develop and exercise philosophic understandings, then
our responsibility to today's students seem clear: we must
pay more attention to developing lower-level cognitive
skills rather than simply intensifying our emphasis at the
philosophic level.

CONCLUSION
The purposes of a university are to develop in students the
ability to interpret and manipulate abstract symbols that
pertain to the vital ideas of modem society. The manipula-
tion of such symbols involves a suite of high-level, critical
thinking skills; however, critical thinking apparently devel-
ops only when the student lives among, and learns from,
those who not only have mastered critical thinking but who
also can shift effortlessly among cognitive levels; these are
attributes of ironic thinkers. Thus, a university faculty is a
community of ironic thinkers intent on elevating students to
high cognitive levels. To become adept at such high-level
skills, students must develop a foundation of low-level cog-
nitive skills; but compared to previous generations, today's
students need more help from university instructors in devel-
oping that necessary foundation.
From Plato to Bacon to Jefferson to Ortega y Gasset to the
present, informed thinkers in Western cultures have argued
that the life of the mind is not merely worth living, but that it
is indispensable for society to flourish: every society needs
philosophic and ironic thinkers who understand how the
world works, how society functions, and how abstract rea-
soning can be deployed to improve society. Today, universi-
ties are the only institutions that can possibly develop the
necessary understandings: church, government, and industry
have all abandoned attempts to develop human potential in
favor of feel-good policies, special interests, and the bottom
line. Universities are under attack to do the same. But if we
succumb to these pressures, if we teach skills that expand
pocketbooks but not minds, if we are satisfied to help stu-
dents feel good rather than challenge them intellectually,
Continued on page 299.


Fall 1999











[e, -classroom


A PHENOMENA-ORIENTED

ENVIRONMENT FOR TEACHING

PROCESS MODELING

Novel Modeling Software and Its Use in Problem Solving



ALAN S. Foss, KEVIN R. GEURTS, PETER J. GOODEVE, KEVIN D. DAHM
University of California Berkeley, CA 94720
GEORGE STEPHANOPOULOS, JERRY BIESZCZAD, ALEXANDROS KOULOURIS
Massachusetts Institute of Technology Cambridge, MA 02139


New avenues to teaching process modeling are sorely
needed in our discipline. The methods we have
been practicing seem to have been ineffective; they
have not been active and concerted. We have instead de-
pended too much on students individually inventing some
sort of approach as they struggle to find their way through
the modeling maze in homework assignment after home-
work assignment. Missing has been an articulation of a
natural and intuitive hierarchy and its use in declaring the
character of a process representation, a hierarchy comprising
such matters as conservation principles, thermodynamic con-
straints, phase conditions, phase equilibria, reaction phe-
nomena, and transport phenomena. Missing also is an aware-
ness of many in academia that process models are presently
at the heart of industrial control systems and optimization
methods for process operations, and that our graduates ought
to be prepared to contribute to that technology.
In an attempt to address this shortcoming, we propose a
new avenue for teaching modeling and have brought into
being new software embodying a model-building hierarchy
that can guide students in using their engineering science
background in crafting models for problem solving. Our
approach is unconventional, and the opportunity extraordi-
nary for breaking through this instructional omission and
breaking through hurdles that students see in their path.
Our motivation further derives from having observed that
many students are at a loss in identifying the physics and
phenomena operative in a process and how to use their
background in engineering science to make an integrated
representation of the process. Moreover, many sense their


weakness or lack of confidence in writing the equations to
represent the physics. A disciplined focus on stating the
physics and a release from incessant equation writing is
the major contribution that this software brings to stu-
dent learning. Through a selection of examples, we illus-
trate how the teaching of modeling can be enhanced with
features of the software.
"ModelLA" is the name we have given to this program. Be
prepared for something different.
The program offers students a phenomena-oriented envi-
ronment expressed in the fundamental concepts and lan-
guage of chemical engineering, such as mass and energy

Alan Foss has conducted beginning- and senior-level courses in
chemical engineering at Berkeley for three decades, experience that
has motivated this new approach to teaching modeling and this new
modeling software.
Kevin Geurts earned his PhD degree at the University of Washing-
ton in the mathematical modeling of polymer flows and is now a
process systems analyst and modeler at the Exxon Corporation in
Houston, Texas.
Peter Goodeve earned degrees in psychology and human factors
engineering and is a freelance software developer and programmer.
George Stephanopoulos is the A.D. Little Professor of Chemical
Engineering at MIT. He has been teaching and researching various
aspects of process systems engineering for 25 years at the Univer-
sity of Minnesota, National Technical University at Athens, and MIT.
Jerry Bieszczad is a PhD candidate in chemical engineering at MIT
working on the logic of mathematical modeling. He is the principal
designer of ModelLA.
Alex Koulouris earned his PhD at MIT, where he is a Research
Associate. He has been working on the development of ModelLA,
multi-scale systems for estimation and control, and the development
of modeling languages for process systems engineering.
Copyright ChE Division of ASEE 1999


Chemical Engineering Education











balancing, phase equilibria, reaction stoichiometry and rate,
modes of heat and species transport. Through a freely ac-
cessed hierarchy of declarations of such elements of engi-
neering science, the user is assisted in recognizing, for ex-
ample, that energy balances must be declared, that chemical
equilibrium constrains species behavior, and that a zero en-
tropy increase must be imposed to attain minimum compres-
sion work. All levels of the hierarchy are accessible at any
time by user request. Unlike the rigid lists of earlier model-
ing software, elements of the hierarchy are not "pre-wired."
It is just the physics that has to be declared-no equations;
the software writes the equations. That is what is unconven-
tional. And, by simply requesting a solution, the equations
are solved numerically in a few seconds without user inter-
vention in the numerical method. The results are displayed
graphically for rapid assessment of the characteristics of the
model. The feedback about misinformed declarations of the
physics is instantaneous-certainly a major improvement
over the one-week turn-around time of homework sets.
Such modeling capability can complement instruction in
modeling throughout the curriculum. Modeling, in our opin-
ion, should be a part of all instruction in engineering, and it
should be done in the context of resolving an engineering
problem. By teaching modeling in a problem-solving con-
text, one can better demonstrate how the nature of models is
influenced by the context, how models serve problem solv-
ing, and how the structure of efficient problem solving is
shaped by the use of models. The program can be especially
helpful in the process-design course as a complement to the
use of process simulators such as Aspen and Chemcad,
providing students, through model building, a means for
understanding the nature of the relations hidden in the simu-
lator modules. ModelLA is different, having modeling rather
than simulation objectives; its modeling capability is what
complements.


Figure 1. Double-effect evaporator modeling project illustrating the
spectrum of phenomena for incorporation in a model.


HELPING STUDENTS IDENTIFY THE PHYSICS AND
THE PHENOMENA
Knowing where to start is not easy for beginning and
inexperienced students. Take, for example, the double-effect
evaporator process in Figure 1. There is a lot going on here.
In the first place, the instructor will have introduced this
project as one of trading off energy and equipment costs in
synthesizing an economical process for the desalination of
sea water. To build a model for decision making about a
process design, students will need to recognize the presence
of the phenomena identified in the ellipsoidal bubbles. We
emphasize that the evaporators have to be modeled. Unlike
the process units displayed on the screens of process-simula-
tion programs, the pictorial icons here are empty shells; there
is no model associated with them. The model has to be built.
Through interactive Q-and-A with the instructor and concur-
rent use of ModelLA to declare the physics in the bubbles,
students can build a model suitable for investigating, for ex-
ample, the influence of the temperature drop across the train,
the degree of concentration of the brine, and other decisions.
A perennial difficulty in assigning such a project is the
lack of physical feel of many students for the qualitative
cause-effect relations of the process variables to one an-
other. With the availability of the software, those students
can explore an instructor-built model and acquire insight
into the effect of changes in operating conditions before
attempting to craft his or her own model. Figure 2 shows one
such set of explorations: the effect of condenser coolant flow
rate on pressures and vapor flow rates in the various units.


Pressures
Generator
101.5i
kPa

!J97.6 1
Evaporator 1 r
31 -
kPa

27
Evaporator 2 1
9.9 1
kPa -


8.5 Condenser 0
kPa' n


S 5.7
1000 mol/min 2000 mol/min


Vapor Flow Rates
Generator
,11.* 44


.3
3/min
Evaporator 1
1.3


.0 -
3/min
Evaporator 2
-0.144


.096
13/min
1000 mol/min 2000 mol/min


Figure 2. Students can gain familiarity with
the evaporation process by interrogating
an instructor-built model for the effect of
coolant rate on pressures and vapor rates.


Fall 1999










All this is calculated in a few seconds with a single request
for such an analysis. The results reveal, perhaps for the first
time for some students, that pressure in the condenser de-
creases with increasing coolant flow, that the pressure de-
crease propagates upstream to the steam generator, that there
is a pressure gradient from one unit to the next, and that
vapor rates in the units differ. Then the question for the
students is, "Why does all this happen?" With such knowl-
edge, students should be able to make intelligent declara-
tions of the physics far better than had they not explored
the behavior.

PUTTING THOSE INSIGHTS TO WORK
IN MODELING THE EVAPORATOR
Exploration of the instructor-built model alerts students
that there are two component parts of the evaporator, that
they are linked by heat exchange, and that they are differ-
ent-one a boiling liquid mixture and the other a condensing
pure vapor. Such recognition suggests that declarations about
the internal structure and the character of the evaporator
parts need to be made in crafting a model. This is accom-
plished in ModelLA by disaggregation of a process unit into
its internal parts. Figure 3 shows how a modeler would use
the disaggregation window (Level 2) to state his or her view
of the evaporator internals through placement of a mixture
unit, a tubes unit, and linkages of convective flows to those
of the parent (Level 1) located on the edges of the disaggre-
gation window. A heat flux between the tubes and mixture is
declared as an essential linkage for effecting evaporation.
One can see that all of this is done in a visual, graphical
manner, a feature quickly grasped by the user.


At this level, declarations can
also be made about the phases
present in each subunit, the species
in them, equations of state, the equi-
librium relations between the
phases, and the "mechanisms" for
heat transport and vapor flow. Such
declarations are made through a hi-
erarchy of dialogs. As these decla-
rations of species and phase equi-
librium are made, a linkage is es-
tablished to a physical-properties
data base for the estimation of
quantities such as vapor pressures,
activity coefficients, densities, and
enthalpy of phase change that are
eventually needed in the numerical
solution of the model equations.
We have operated with a relational
database containing data for over
2000 chemical compounds. The
user may also supply any special


data particular to the process being modeled.
It is at this level where the engineering science concepts
and facts are introduced into the model. To accomplish this
in an organized manner, students need disciplined guidance
in an environment familiar to chemical engineers. They get
it through the hierarchy of declarations of structure and
phenomena shown in the right side of Figure 3. That set of
hierarchical elements applies to just the declarations needed
for this part of the model. The full set available in ModelLA
is much more extensive. The Modeling Assistant shown at
the bottom in Figure 3 guides the user in branching to the
major elements of the hierarchy.
Learning about the physics of the process takes place very
rapidly here because the guidance given by the program at
each juncture is centered on the logical consistency of the
declarations made and because the feedback about inconsis-
tency is essentially instantaneous. One of our student evalu-
ators remarked that ModelLA guards the user from accumu-
lating mistakes. A good amount of self-learning takes place
about the modeling process without instructor prompting.

PROCESS SYNTHESIS-
EXECUTING A TOP-DOWN APPROACH
The top-down synthesis of a process system can be shown
to students as an orderly and rational way to evolve the
structure of a process'] and provides a good example of the
use of the hierarchical structure of the software. Unlike the
bottom-up approach usually employed with process-simula-
tion programs, the top-down approach affords the user a
view of the direction of subsequent development and the
type of model needed to support that development. Some


Add New -e..Unl J Add N. Fj l I Spo Spew and RllI| Ed Roeo Un i. Edl Fkux. Ed CornolLoops. Modd Smul.o
IBlackbo Unit Unl wth Vapo. Lqud Equdibnum 9 Spati ly llnDI ed U
SUrntwthVap.oPhae I UwithLud LqudEquibnum UrnfromTempateL ay
SUn MlWhLLq.dPha.s *IStagedUnim Help


Figure 3. The subunits of the evaporator are identified in a disaggregation
window, fluxes stated, and material properties declared.


Chemical Engineering Education











describe it as a target-directed approach. In a top-down approach, the
progression of one's thoughts about creating process structure is intuitively
organized as a hierarchy, proceeding from overall (top level) objectives and
successively broken down into levels of finer detail. That hierarchy matches
exactly ModelLA's hierarchy of declarations of process structure and con-
tent. As an example of how a top-down synthesis can evolve with the use of
ModelLA, we show three levels of the synthesis of a process for the
hydrodealkylation of toluene to benzene, the HDA process.'
The synthesis starts at Level 1 in Figure 4 with simple declarations of the
products to be produced from candidate raw materials, the chemical species
present in the process, the expected chemical reactions, the expected by-
products and waste products, and energy fluxes between the process and
environment. ModelLA's hierarchical elements accessed for such declara-
tions are shown to the right of the Level 1 depiction in Figure 4. Next, with
an appreciation that a reaction section and a separation section would be
needed, a modeler would place such elements in Level 2, a disaggregation
of Level 1, as shown in Figure 4. Such a step is a top-down step in the
synthesis, the educational benefit being an opportunity for the student to


Hydrodealkylation HDA
Level 1
Toluene Purge Benzene
HDA Plant

Hydrogen Byproducts
eat and Wor k

Level 2 purge
Recycle P
Toluene I Benzene
Mix Reaction Separation
Section Section
Hydrogen S Byproducts
Heat and Work


Figure 4. Process synthesis pursued through successive sublevels
corresponding to the multilevel hierarchy of ModelLA.


express his or her perception of the big pic-
ture. Such declarations are made by access-
ing the hierarchical elements shown to the
right of Level 2 in Figure 4.
The big picture now has to be fleshed out
with some definite proposals for accomplish-
ing the reactions and the separations. A flesh-
ing out of the reaction section is illustrated by
the disaggregation of Level 2 in Figure 5. In
Level 3 of this example, the modeler must
function in a bottom-up mode, placing and
connecting process units whose functional-
ity the modeler must eventually describe,
stating substructure, species, phases, reac-
tions, and fluxes. This is the level where
process inventions are made.
The educational value here is the direction of
attention on a well-defined segment of the en-
tire process so that decisions about process
structure and the modeling of the set of units in
that segment can be made and tested without
interference from other segments. For example,
the type of reactor model, ways to prevent
catalyst coking, and conditions to enhance re-
action selectivity can be scouted. There is plenty
of opportunity here for the instructor to point
out the place and need for a model in problem
solving and synthesis. The opportunity is also
there to point out the structure of problem
solving. The top-down strategy comes to
meet the bottom-up inventions of the sub
levels as the process is further and further
disaggregated into elementary operations and
basic phenomena.
One can also see here an opportunity for
collaboration among team members in a net-
worked environment, say, in the design course,
where one member would develop the reactor
section and another the separation section.
As the user's invention of model structure
proceeds, the software assembles information
about the hierarchy of model units and their
connections and displays it as the hierarchical
tree of model units shown in Figure 5 for the
purpose of keeping the user up-to-date on the
model so far constructed. Such a display is
especially useful when moving back and forth
between several levels of the model.
Completion of the models of the units placed
in Level 3 of Figure 5 is accomplished through
the hierarchical modeling elements shown at
the right. A particularly essential element is


Fall 1999


Hierarchical Elements Accessed
*Global species declared
*Global reactions defined
*Placing flows
*Convective
*Heat
*Shaft work
Hierarchical Elements Accessed
*Internal Structure
*Placing Subunits
*Placing Flows
*Convective
*Heat
*Shaft Work


Figure 5. Successive disaggregations bring one to the point at which
process subunits can be fully defined and modeled.


295









the species consistency check. It scans the model units of
each level to determine whether the distribution of spe-
cies declared by the user makes physical sense. If it does
not, guidance is then given to assist the modeler in recti-
fying the omissions.

SATISFYING THE DEGREES OF FREEDOM
A very considerable amount of insight and knowledge
about the qualitative cause-effect relationships in a process
system is needed to identify quantities that
fully specify the operating conditions of the
process. It is in this aspect of modeling that "MJ d
the students' engineering ability is thoroughly
taxed, and in the taxing, further developed.
This is also where the instructor can help de- V,-, O"
velop that insight through questions and an- :-.-~
swers in interactive sessions with the students. -:_ p ri
Complex processes often bring to the fore per- -
plexing conflicts in satisfying the degrees of
freedom, particularly when energy and mass -
fluxes interact. This is certainly the case in a
process as complex as the HDA process. O ffe s.
Even models of modest size can have a dozen --.
or more degrees of freedom. Without some _.-
assistance, satisfying these with statements of --ani
operating conditions and physical parameters
would be a daunting and likely an unavailing .I-mp .
task. It is neither of these with the ModelLA J d
program. Candidate quantities are identified COeCej
for user consideration, unit by unit, flux by -?.I-
flux, phase by phase, variable by variable, h
species by species. A running count of the
degrees of freedom yet to be satisfied is dis- :-
played as the user makes selections. This DOF
analytical engine also identifies conflicts in the user's selec-
tions and offers a list of alternative quantities that can be
swapped with the current selection.
In the case of dynamic models, the DOF analytical engine
simultaneously also makes an analysis of the index of the set
of differential algebraic equations and informs the modeler
when the index exceeds 1. Such an analysis is necessary
because selection of a certain combination of quantities to
satisfy the degrees of freedom can sometimes result in a
large index. Current numerical integration algorithms cannot
integrate a differential algebraic equation set with an index
greater than 1. Information regarding the source of the high
index is reported so that the modeler may reconsider the set
of design variables.

CALCULATIONS AND THEIR USE
When it is confirmed that the index is 1 or less and all
degrees of freedom have been satisfied, the user may launch
a calculation of the model equations. Calculations are made


ii


'a
Bti~
enL





pt




a


Chemical Engineering Education


without user intervention by a state-of-the-art numerical en-
gine, gPROMS,[2,3 and for the double-effect evaporator, are
completed in 4 or 5 seconds.
Students and instructors like to see trends of process vari-
ables over ranges of operating and design conditions like
those shown in Figure 2 because insight about the process is
more easily grasped. Trends can be calculated and displayed
for all variables very quickly. The numerical data of such
calculations can be used in deciding on operating conditions
_or examining the trade-offs among design de-
cisions. The engineering problem can be ad-
I" is the dressed in this way.
ohave BUT THE EQUATIONS!
D t-I WHAT ABOUT THE EQUATIONS?
,: By all means, have the students write the
Md4OF equations-but only after they have gained an
ling. understanding of the physics and an apprecia-
nIt tion of the qualitative cause-effect relation-
ships among the variables.
Ldets a One might think that an assignment in writ-
ing the model equations after having crafted a
model with ModelLA and after having re-
ed solved an engineering problem would be un-
L8fnt necessary and anticlimactic. It is neither. First,
f i 5i e it is necessary because there has to be a clo-
ental sure to the project that is satisfying to the
S..lnd students. We found that students in our trial
group wanted to write equations and to con-
8o f firm that their model and calculations matched
.30 those of ModelLA. Second, one will find that
S,.... even after having articulated the physics, not
everyone is sure-footed in identifying a model
envelope and subunit envelopes. That is,
some run off in wrong directions. Further, one will find a
significant fraction confused about representing such
things as the rate of accumulation of internal energy in a
mass of material in terms of the process variables and the
flux of energy in and out of the process. Instruction is
assuredly needed to straighten out those basic matters.
That instruction is one of the activities that sustains an
interest in writing equations and saves it from being anticli-
mactic. We recommend that the instructor work through the
equation writing with the students in an interactive work-
shop environment because many will still need help with
matters such as those just mentioned and because there is not
much incentive to have students struggle alone through the
equation maze at this stage. Focused and concentrated in-
struction in formulating model equations reinforces an
instructor's continuing admonition for physical thinking at
all stages of modeling and that the equations are just a
symbolic statement of the physics. That will be a revela-
tion to students who have the impression that equation











writing is all mathematics.
An alternative approach, which we think ineffective, is to
have the software display the equations to the student piece
by piece as he or she makes declarations of the process
attributes, that is, the materials, phases, fluxes, and reac-
tions. Such displays are unguided and physically uninterpreted
and are not an effective pedagogical method.
In the workshops there is the further opportunity for the
instructor to point out the character of the set of equations,
how a choice of variables can transform a nonlinear model
into a linear model, how natural divisions in the process
structure result in separate blocks of equations, and how one
can order the terms of the equations to form an easily
computable structure, as for example, the structure of a
linear set. Students left alone in a sea of equations sel-
dom are aware of the equation structure. They can ben-
efit from the instructor's insight here.
A full set of notes for the instructor T_Tub
about writing the equations for every
model is given in a set of course mod-
ules described in a later section. The
equations are laid out following the
logic and cause-effect relations articu-
lated in an earlier section of the module
640
and thus should appeal to the physical
understanding developed there. Two 635
methods of solving the equations are
developed in the course modules for s 3
every model. A paper-and-pencil ,
method follows directly, step-by-step, 825
the articulation of the physics, the iden- 620
tification of the unknowns, and the na-
ture of the relations needed to complete 615
the model. Solution by use of general- Radial
purpose numerical solvers such as
Matlab, Mathcad, and Polymath is also Figure 6. Two-di
presented. In the case of linear dynamic profile in a phth
models of a single state variable, a calculated bj
closed-form analytic solution is derived.
Numerical calculations of the derived
equations are presented for all models
and compared with the ModelLA cal- C
culations. Thus, the instructor has ma- 4-- _out
trial to close the loop for the students.

CURRICULUM-WIDE
MODELING CAPABILITIES
Modeling of spatially distributed and
dynamic processes is a frequently en-
countered challenge for students
throughout the curriculum. ModelLA Figure 7. Cascade
has the capability for both. Further, stu- is constructed after
dents can investigate control of pro- can be measu


men,
alic
SaM


cont
r ide.
red a


cesses by placing control systems around dynamic process
models.
Spatially Distributed Processes Tubular reactors, ab-
sorption columns, cooling towers, adsorption beds, and tu-
bular heat exchangers all need at least a one-dimensional
spatial representation of species behavior and energy flows.
ModelLA has 3-D spatial modeling capability, offering rect-
angular, cylindrical, and spherical coordinates. As an ex-
ample of that capability, the temperature distribution in a 2-
D model of a phthalic anhydride reactor produced by
ModelLA is shown in Figure 6.
Dynamic Processes Instruction in modeling the dy-
namic behavior of processes can be introduced profitably in
the first course in material and energy balancing. We simply
remark that early experience in dynamic system modeling
gives students an early understanding of interactions in pro-
cess systems and potentially an ap-
ctorrzmatl(r,z) preciation for the evolution of the
steady-state condition. Declaration
of the attributes of a dynamic pro-
cess model proceeds in the same
way as that of a steady-state model
with additional attention needed to
specify the initial conditions. Spa-
tially distributed dynamic pro-
cesses can be modeled.
Multiloop Control Systems Con-
trol loops can be placed on the pro-
A cess flow diagram as shown in Fig-
ure 7, for example, by the cascade
system on a CSTR. The user can
S Fow select a PID controller algorithm or
craft a custom controller action in-
volving, for example, logic elements
and actions triggered by a time se-
sional temperature quence. The salient educational merit
anhydride reactor of ModelLA's use in configuring
'odelLA model. control systems is the challenge to
identify which variables should be
B_ measured, which should be manipu-
lated, and how to link them. Other
1 types of process models in other
c ..n types of software by necessity re-
cw zX veal the measurement transducers
r2 and control valves, thus surrender-
STC2 ing the educational benefit of this
intellectual challenge.
TC2 SP
TCT1 SP COURSE MODULES
1 ~ FOR ASSISTANCE IN

rol system for a CSTR MODELING INSTRUCTION
ntifying variables that To assist instructors in using the
nd manipulated. software for instruction in model-


Fall 1999


ereai











ing, we have developed several course modules that can be
used in concert with two of the most popular texts on mate-
rial and energy balancing, namely those written by Felder
and Rousseau[41 and Himmelblau.151 Several modules on
more advanced topics have also been developed. The
modules treat the modeling of process systems presented
in those texts, some being simple "warm-up" exercises of
the single-answer variety, and others involving analyses
of trade-off in operating costs with product value in a
search for optimum operating conditions.
One of the important components of each module is an
articulation of the physics and the qualitative cause-effect
relationships of the process, thus giving the instructor back-
ground about the project. Because students can benefit from
such an analysis as well, students are asked in a preliminary
homework assignment to identify the process variables, what
affects them, how they might be determined, and to name the
relations that fully define a model. Students can benefit from
a Q-and-A session with the instructor following such an
assignment and before embarking on building a model.
The modules also lay out a completed ModelLA model,
showing all subunits, fluxes between them, phases, reac-
tions, and transport relations. The full set of design variables
and initial conditions is given and the full set of ModelLA
declarations is provided on a disk file so that a numerical
simulation is ready for execution. For each ModelLA model,
tips and reminders are given to the instructor concerning
certain declarations that may not be obvious or that might be
overlooked. These can be passed on to the students as they
develop the model. Some models may be crafted in more
than one way. In those instances, we have included a discus-
sion of the philosophy of the approaches and have given the
rationale for the approach selected.
Results of the numerical simulation of all models are
given in graphical or tabular form and are discussed in
relation to the physics and cause-effect characteristics treated
in the preliminary homework assignment and also in relation
to questions asked in other assignments. Projects involving
design or operating trade-offs show the behavior of an ob-
jective function as a function of split fractions and fraction
conversions, for example.
As a means of getting students "up to speed" in use of the
program, we have prepared an on-screen tutorial that guides
the learner through the several types of declarations in the
hierarchy interactively with a "live" ModelLA program run-
ning concurrently. Our experience is that students pick up
the general structure and features of the program in about a
2-hour session with the tutorial and the finer details with
subsequent use in modeling projects.

SUMMARIZING THE EDUCATIONAL INITIATIVES
This phenomena-oriented and hierarchically structured soft-
ware propels students quickly into model building and prob-


lem solving. The model can be built expeditiously because
the focus is on the phenomena and because students need not
struggle with equation writing. The hierarchical structure of
the software embodies the same hierarchy used by engineers
in declaration of model characteristics and thus promotes a
natural and intuitive flow of model development.
The release from equation writing permits the students to
push ahead with model development and problem solving
and helps them build a "can-do" confidence in completing
an engineering project. Writing equations is deferred to the
end of the project. Students at that point are much better
informed about process character and more receptive to in-
struction about formulating model equations. Further, the
instructor has the opportunity to describe the structure of the
model, a matter rarely treated, but one of value when consis-
tently brought into view across the curriculum. Thus, we
favor the inversion of the usual order of equation writing and
problem resolution.
The ability to build a model quickly and efficiently with
ModelLA is a major contribution to student learning. Stu-
dents are steadily engaged with the physics and are given
instant feedback about inconsistencies or just plain impos-
sible constructions. Waiting for instructor approval is thus
unnecessary. Efficiency is very important also in satisfying
the degrees of freedom through identification of design and
operating variables. There is a good amount of qualitative
cause-effect analysis needed on the part of the student in
this, and ModelLA helps one to move through selection of
design variables rapidly in an orderly sequence.
This new avenue to teaching modeling can speed student
grasp of using engineering science concepts in any course
environment. Inasmuch as our current method of instruction
rests heavily on quantitative models of fundamental phe-
nomena and on models of process systems, there is consider-
able incentive to improve the efficiency and effectiveness of
that instruction. There is a marked commonality of modeling
needs across the curriculum that can benefit from this hierar-
chical modeling environment.

AVAILABILITY OF THE PROGRAM
ModelLA and several course modules will be available in
the near future to faculty members interested in helping
us evaluate its effectiveness in teaching modeling. Re-
quests should be made on departmental letterhead to Pro-
fessor George Stephanopoulos at MIT. The program will
be available to all interested persons following the evalu-
ation period.

ACKNOWLEDGMENT OF OUR HELPERS
Miklos Gerzson assisted in scouting some early ideas for
familiarizing students with process behavior. Michael
Lasinski assisted with coding of some of the graphical dis-
plays. Berkeley junior-year students Adam Cate, Valerie


Chemical Engineering Education











Grill, James Comb, and Ryan Overstreet assisted with evalu-
ation of the software and with the development of process
models. Professor Terje Hetzberg of the Norwegian Institute
of Technology, Trondheim, in a sabbatical year at Berkeley
assisted the Berkeley team with modeling techniques and
evaluation of the software.

THANKS TO COLLEAGUES ABROAD
We benefited significantly from the help of Professor Costas
Pantelides and his associates at Imperial College, London,
whose state-of-the-art numerical solver (a component of
gPROMS) added importantly to this project. Software for
the analysis of the index of differential-algebraic equations,
generously provided by Professor Wolfgang Marquardt of
the Lehrstuhl Fuer Prozesstechik, RWTH, Aachen, Germany,
was a key element in assessing the numerical solvability of
the equations. Professor Rafiqul Gani of the Chemical En-
gineering Department, Lynby, Denmark, helped us with es-
timating phase conditions in our early scouting work.

SUPPORT BY THE
NATIONAL SCIENCE FOUNDATION
We are appreciative of the support of the Directorate
for Education and Human Resources of the National Sci-
ence Foundation for the development of this software
and course modules.

REFERENCES
1. Douglas, James M., Conceptual Design of Chemical Pro-
cesses, McGraw-Hill, New York, NY (1988)
2. Barton, P.I., and C.C. Pantelides, "Modeling of Combined
Discrete/Continuous Processes," AIChE J., 40, 966 (1994)
3. Oh, M., and C.C. Pantelides, "A Modeling and Simulation
Language for Combined Lumped and Distributed Param-
eter Systems," Comput. Chem. Eng., 20, 611 (1996)
4. Felder, Richard M., and Ronald W. Rousseau, Elementary
Principles of Chemical Engineering, 2nd ed., John Wiley &
Sons, New York, NY (1986)
5. Himmelblau, David M., Basic Principles and Calculations
in Chemical Engineering," 6th ed., Prentice Hall (1996) U




Universities Why?
Continued from page 291.

then not only do we hinder student growth, but we also
undermine the university and, ultimately, corrupt society.
If this seems farfetched, consider the catastrophic conse-
quences of the Soviet experiment in which a society at-
tempted to provide economic security while suppressing
intellectual growth and development. Consider further the
grave difficulties now being faced by countries of the
former Soviet Union-difficulties engendered because
too many of their people fail to understand how modern


societies function.

In our society, the difficulties of educating are exacerbated
by an astonishing degree of self-satisfaction. It is possible to
operate cars, computers, and microwave ovens without know-
ing anything about how they work; possible to vote and pay
taxes without understanding the rudiments of government;
possible to work at a job without comprehending the larger
workings of the economy; possible to be courteous and well-
meaning while ignoring the deeper implications of human
psychology. In other words, it is possible for many to live
only at the surface of the culture and to be unconcerned
about the underpinnings by which the society functions.
The operative question is this: For a society to survive and
its culture to continue to evolve, what is the smallest fraction
of the population that must comprehend how the society
functions? In modern societies, it is the unique responsibility
of universities to keep that fraction above the minimum.

REFERENCES
1. Ortega y Gasset, Jose, Mission of the University, Princeton
University Press, Princeton, NJ (1944)
2. Hamilton, E., The Greek Way, Norton, New York, NY (1930)
3. Petroski, H., The Pencil, A.A. Knopf, New York, NY (1990)
4. Hamilton, E., and H. Cairns, eds, The Collected Dialogues of
Plato, Princeton University Press, Princeton, NJ (1961)
5. Wilson, F.R., The Hand, Pantheon, New York, NY (1998)
6. Whitehead, Alfred North, "The Aims of Education," presi-
dential address to the Mathematical Association of England,
1916; reprinted in Alfred North Whitehead, An Anthology,
edited by F.S.C. Northrop and M.W. Gross, Macmillan, New
York, NY (1953)
7. Newman, John Henry, The Scope and Nature of University
Education, 2nd ed., Longman, Green, Longman, and Rob-
erts, London (1859)
8. Bronowski, J., Science and Human Values, Harper & Row,
New York, NY, Ch. 2 (1956)
9. Wilson, E.O., Consilience, A.A. Knopf, New York, NY (1998)
10. Committee on Undergraduate Science Education, Trans-
forming Undergraduate Education in Science, Mathemat-
ics, Engineering, and Technology, National Research Coun-
cil, National Academy Press, Washington, DC (1999)
11. Egan, K., The Educated Mind, University of Chicago Press,
Chicago, IL (1997)
12. Donald, M., Origins of the Modern Mind, Harvard Univer-
sity Press, Cambridge, MA (1991)
13. Haile, J.M., "Toward Technical Understanding. I. Brain
Structure and Function," Chem. Eng. Ed., 31, 152 (1997)
14. Haile, J.M., "Toward Technical Understanding. II. Elemen-
tary Levels," Chem. Eng. Ed., 31, 214 (1997)
15. Haile, J.M., "Toward Technical Understanding. III. Advanced
Levels," Chem. Eng. Ed., 32, 30 (1998)
16. Petroski, H., "Work and Play," Am. Sci., 87, 208 (1999)
17. Mach, E., The Science of Mechanics, 6th ed., Open Court
Publishing, LaSalle, IL (1960)
18. Wankat, P.C., "Reflective Analysis of Student Learning in a
Sophomore Engineering Course," J. Eng. Ed., 88, 195 (1999)
0


Fall 1999


299











, Oclassroom


COMPUTER SIMULATION OF


TRACER INPUT EXPERIMENTS


J.A. CONESA, J. GONZALEZ-GARCIA, J. INIESTA,
P. BONETE, M. INGLES, E. EXP6SITO, V. GARCIA-GARCIA, V. MONTIEL
Universidad de Alicante Alicante, Spain


incorporating a personal computer in the classroom has
brought a new quality to the study of chemical engineer-
ing that was unthinkable just a few years ago. Due to its
mathematical calculation powers, the computer allows us to
study complicated experimental systems that are unapproach-
able from an analytical point of view, and its rapid results
are especially beneficial in chemical engineering. Experi-
mental results of several systems can be simulated by using
the theoretical equations that govern the process. This meth-
odology permits us to quickly analyze the influence of differ-
ent variables that affect the system behavior without the long
and hard experimental testing that can distract a student.
This paper proposes a practical class for undergraduates in
their first year of chemical engineering where the character-
ization of a reactor is achieved through recording the resi-
dence time distribution (experimental response obtained from
a typical test stimulus-response for the hydrodynamic char-
acterization). The distributions are simulated with a theoreti-
cal model allowing the quantification of the parameters char-
acterizing the reactor behavior as a function of the operating
conditions (flow rate).
Specifically, this paper provides the particulars for a prac-
tical session using a versatile computer program that simu-
lates the tracer input experiments. It is necessary, however,
that the students have prior knowledge of reactor design
theory. This background material should have included the
ideal reactor models and the solutions to problems where
several curves were analyzed using the momentum method
or through simple iteration.'11
The practical lesson described here has been designed for
two students working together for a period of approximately
four hours. The students should have some knowledge of
how to program in the BASIC language, but it is not abso-
lutely necessary. The experimental work is short and repeti-
tive, so the students can center their attention more com-


pletely on the simulation. This obliges the students to
make decisions concerning the design and plan of the
lesson in the following ways:
They must elect the number offlow rates to study.
1 They must perform small modifications in the BASIC
program in order to extend its application (with
instructor supervision).
Finally, a student must hand in a report detailing the ex-
perimental procedure, its results, the conclusions gained,
and the important and useful modifications that were made
to the BASIC program. Once the reports have been pre-
sented and the program modifications detailed, the instructor
can propose extending the program to the study of even
Juan A. Conesa is Professor of Chemical Engineering at the University
of Alicante, where he received his Chemistry Science degree in 1992 and
his PhD in Chemical Engineering in 1996. He conducts research on
combustion and pyrolysis of different materials and also focuses on
characterization of chemical reactors and activated carbon production.
Jose Gonzalez-Garcia received his degree in Chemistry in 1990 and his
PhD in 1998 from the University of Alicante, where he is currently a
member of the academic staff. His research interests are in electrochemi-
cal engineering and applied electrochemistry.
Jesus Iniesta is a doctoral student at the University of Alicante, where he
obtained his Master's degree in Electrochemistry. His interest is in elec-
trochemical treatment of hazardous organic compounds.
Pedro Bonete received his degree in Chemistry in 1990 and his PhD in
1995 from the University of Alicante, where he is currently a member of
the academic staff. His academic research involves organic and
electroorganic synthesis.
Marina Ingles received his bachelor degree in 1996 and his Master's in
1998 from Alicante University. His academic research involves organic
electrosynthesis.
Eduardo Expdsito received his Master's degree in 1994 from C6rdoba
University and his PhD from the University of Alicante. His academic
research involves wastewater treatment and organic electrosynthesis.
Vincente Garcia-Garcia received his PhD in chemistry in 1991. His
research interest is applied electrochemistry. He has worked with labora-
tory and pilot-plant experiments.
Vincente Montiel Leguey is Associate Professor in the Department of
Physical Chemistry at the University of Alicante. His research interests
are in electroorganic synthesis and wastewater treatment by electro-
chemical methods.
Copyright ChEDivision of ASEE 1999


Chemical Engineering Education


)


i


)











more complicated systems.
The main objective is to demonstrate how the personal
computer can help in the quantitative characterization, de-
sign, and scale of a reactor-a matter of some difficulty
when other techniques are used. From the technical point of
view, it is interesting to identify the flow pattern, to analyze
the reactor behavior when the flow rate is varied, and to
classify the reactor when the objective is to optimize the
chemical process inside the reactor.

BACKGROUND AND THEORY
There are two standard models for the ideal behavior of a
continuous chemical reactor: the piston plug flow and the
backmixed reactor (widely studied in specialized litera-
ture[2"31). Nevertheless, real reactors show deviations from
this ideal behavior for a wide number of situations. A vari-
ety of theoretical approaches have developed in the litera-
ture for this non-ideality.
The dispersion model for a tubular reactor is presented by
Levenspiell2] in considering a hydrodynamical behavior with
plug flow and axial dispersion:
aC a2C C
a= ax v (1)
at 8z az
where
C concentration of property measured
t time
z length in the flow direction
v linear flow rate
Dax axial dispersion coefficient

Equation (1) is usually expressed in dimensionless form as
aC _a 1 (2C
--+ (2)
ae aZ Pe aZ2
using the Peclet number, Pe=vL/Dax, where L is the total
length of the reactor in the flow direction. The dimensionless
time, 0, is defined as

e= t (3)


TABLE 1
Different Models for Non-Ide


12 l (1 )2
Open/Open C(0)= exp e
2/CloseCPe Nu 4y c Peq


Closed/Closed Numeric integration. Boundary condition equations:


High Dispersion Degree


tr, the mean residence time, is
L


Z is the dimensionless length (=z/L), and C is the normalized
concentration of the measured property (C is the conductiv-
ity in this paper).
The solution of Eq. (2) depends on the boundary condi-
tions for the input and the output.[41 Some of these solutions
are analytical. For the resolution of Eq. (2) it is interesting to
consider whether or not the dispersion degree is high. On the
other hand, the boundary conditions must be kept in mind,
i.e., if the system can be considered open or closed. Table 1
shows a scheme of the different cases that can be presented.
This dispersion model defines with great exactness several
practical situations, especially when the shape of the experi-
mental curves is Gaussian with a high symmetry (if the
dispersion degree is low) or with a tail (if the dispersion
degree is high).151
The model presented in this paper considers a more global
non-ideal situation: coexistence of a dead volume inside the
reactor and two flow paths, each modeled with an axially
dispersed plug-flow model. Thus, Eq. (2) is the differential
equation defining the dispersion model for each flow. In this
paper, we considered the most common situation: open-open
flow (inlet and outlet do not change the flow pattern) and a
high axial dispersion degree. Equation (2) has, in this case,
an analytical solution. The solution for the residence time
distribution is, for each flow,

1 Pe Pei
C(0)=I _Pi exp -ei(1-,) (5)
2 It i 46 0i

Other models are available in the literature as the simple
tanks in series model151 with just one parameter, or more
complex multi-parameter differential models.'61 The former
is not attractive from the didactic point of view, since it is
less intuitive. The latter allows a better explanation of the
mass transport phenomena, but it must be used only when
there is evidence of
such phenomena, or
alFlow when the simpler
*al Flow
models are not able to
Low Dispersion Degree reproduce the experi-
mental data.


1 ( (1-6)2
C(e) = P exp 4/Pe
2Vi/Pe I 4/ Pe


1 dC
Z =0 then 8(0)=C dC
Pe dZ


EXPERIMENTAL
DESIGN AND
RESULTS
In the proposed simu-
lation model (see Fig-
ure 1), there are two
flows and a dead vol-


Fall 1999










ume, with five fitting parameters to optimize. The five pa-
rameters are: two mean residence times, two Peclet num-
bers, and the ratio between the dead volume and the total
volume (Vd/V). From these parameters the ratio between the
volume used by flow 1 (flow rate = Q,) and the total volume
(V,/V) can be calculated by using

V=Vi +V2 +Vd (6)
Q = Q1 +Q2 (7)
Vi
ti = (8)
Qi

The optimization method used is the Flexible Simplex
method171 and the objective function (O.F.) is the sum of the
square of the differences between experimental and calcu-
lated values of the residence-time distribution E(t)

O.F.= [Ecac(t)- Eexp(t)]2 (9)

The computer program estimates the best parameters to fit
the experimental data, provides them, calculates the E(t)
curve, and uses the value of the objective function.

DESCRIPTION OF THE EXPERIMENTAL SYSTEM
Figure 2 shows a schematic diagram of the experimental
system used to measure and analyze the stimulus-response
curve. The procedure is based on the instantaneous modifi-
cation of a property of the fluid in the reactor inlet and
recording the variation of this property with time at the
outlet of the reactor. In this case, the electric conductivity of
the fluid is modified by the injection of a small volume of
saturated solution of the tracer. This response will be the
data file for beginning the parameter-estimate calculation.
Of course, the data acquisition could be computerized and
the data analyzed on the same computer.
Any kind of reactor could undergo this analysis. The sole
condition for the reactor is to know the total volume. In the
practical example that follows, a built-in-house filter-press
electrochemical reactor (UA200.08) is used. The compartment
for the fluid is a drum of dimensions 18x12x0.8 cm. A more
detailed description of this reactor can be found elsewhere.'S'
The design of the hydraulic part of the system is a typical
configuration: a deposit for the fluid (water), pumps, and
flow-rate measurement units controlled by valves permitting
flow-rate adjustment in each experiment. More details can
be found in the literature.[91

EXPERIMENTAL DEVELOPMENT
Previous to the Experiment Before experimental record-
ing of the curves, it is important to calibrate the measure-
ment apparatus. The conductivity probe and the flow-mea-
surement units must be calibrated for the fluid and tempera-
ture of the experiment. An erroneous measurement of the


flow rate would lead to an overflow situation. In this particu-
lar case the students must calibrate the probe, so the flow
rate calibration is given to them. It is important to keep the
solution temperature constant during the experiment because
conductivity depends on the temperature. This is attained
with a thermostat heat exchanger in the reservoir.
Curve Response Measurement Once the flow rate, the
temperature, and the other conditions are stabilized, the pulse
of tracer can be rapidly injected, collecting the conductivity-
time data shown in Figure 2. The injection of the tracer must
be done as close as possible to the reactor inlet. In this case,
the tracer was 2 mL of a saturated KCl solution (4.3 M). A
conductivity probe (Ingold) measures the conductivity of
the outflow stream reactor. This probe is connected to a
conductivity meter with an analog output of 0 to 10 V (error


Figure 1. Sketch of the model for flow characterization.


2
3


I~


Figure 2. Diagram of the experimental set up:
1. reservoir; 2. thermometer; 3. heat exchanger; 4. pump;
5. valve; 6. flowmeter; 7. injection of tracer; 8. reactor; 9.
conductivity probe; 10. conductimeter; 11. computer.


Chemical Engineering Education


Axially dispersed
plug flow
Volume =V,


Axially dispersed
plug flow
Volumen=Vi ,


302











less than 1%). The conductivity meter, through a data acqui-
sition card (12 bits, monopolar channel, input free tension 0-
10V), permits saving the data in an ASCII file in the com-
puter (PC-compatible system, at least 80386 processor, 2
MB RAM memory). Recording the response must be
done until the value of the conductivity signal reaches
the initial value. This simple procedure is repeated for
every flow rate studied.
Analysis of the Response The computer program pro-
posed in this paper needs the data collected in an ASCII file
with names RV**.GEX, where the flow rate must be in-
cluded. If the experimental system is similar to the one in
this paper (with the data acquisition card), the conductivity-
time curve will be recorded automatically by the computer.
The experiments can also be done by simply recording the
analog X-t curve and digitizing it.
The computer program is written in BASIC; a copy of it
can be requested by e-mailing JA.CONESA@UA.ES. The
program needs the reactor dimensions, the name of the data
file, the flow rate, and the initial value of the parameters to
be fitted (in part II of the program).

r 1


0 5 10 15 20 25
t/s

Figure 3. Superposition of experimental and calculated
curves. Volumetric flow 105 L/h.


TABLE 2
Estimating Model Parameters for Different Volumetric
Flow Rates

Q/L h' / s Pe, T2 /S Pe2 Vi/V V/V O.F.
66 3.84 15.46 12.72 2.76 0.33 0.42 1.5 103
105 3.38 20.11 8.74 3.58 0.43 0.21 5.0 10-3
155 2.41 22.38 6.65 3.39 0.43 0.10 3.3 10-


Fall 1999


The solution is not strongly dependent on the initial values
of the parameters. Thus the initial values for the mean resi-
dence time could be selected as the ratio between the total
volume and the flow rate (the same value for both ways).
On the other hand, typical values of the Peclet number
are between 1 and 50, and the initial value of Vd/V could
be selected as 0.5.
When these initial parameters, experimental conditions,
and response curve values are entered, the program can be
run. Using the initial values of the parameters, the suc-
cessive iterations will diminish the value of the objective
function. After each iteration, the program shows the
new value of the parameters, the current value of the
objective function, and the minimum value O.F. achieved
until this iteration.
The simulation ends when the value of the O.F. minimum
reached is repeated and the variations of the parameter val-
ues do not change. The program generates an output data file
(with ASCII format and name RV**.CAU) with five col-
umns of data: time, experimental residence time distribu-
tion, calculated residence time distribution, calculated resi-
dence time distribution for flow through path 1, and calcu-
lated residence time distribution for flow through path 2. In
addition, the optimized parameters are also saved at the end
of the output file (Pe and average residence time for each
path, and V,/V), and with the value of the dead volume (V,/
V) and minimum O.F. reached.

ANALYSIS OF RESULTS
The experiments were carried out with three different flow
rates (66, 105, and 155 1/h). Figure 3 shows the experimental
and calculated E(t) curves, E,(t), and E2(t), respectively, for
the flow rate 105 1/h. The optimized parameters for the three
experiments are shown in Table 2. In the Table, "Q" is the
flow rate, Ti is the average residence time of the path "i",
and V,/V and O.F. were defined previously.
Analyzing the results, we can conclude:
El An increase in the flow rate produces a decrease of the
residence time in both flow paths, favoring path 1 (of
minor residence time and a higher Pe, i.e., greater
plug flow behavior) versus path 2, with low Pe. This
conclusion is obtained from the value of the parameter
V,/V. The flow circulating through path 1 can be
calculated using the relationship between the average
residence time and the flow rate (Eq. 8).
[ The flow rate also affects the percentage of dead
volume, decreasing as the flow rate increases. This is
a very important conclusion.

DISCUSSION
The practical lesson proposed in this paper allows the
Continued on page 309.

303


105 Uh
RTDexptal
- RTD calc
- El
. E2











S ethics


HOW TO LIE

WITH ENGINEERING GRAPHICS



P. AARNE VESILIND*
Duke University Durham, NC 27708-0287


he essence of engineering is truthfulness. If we are
truthful in all of our conduct, then we are most likely
acting ethically. While this may seem like an over-
simplification, the idea of truthfulness certainly addresses
the central issue of engineering communication. The nega-
tive side of truthfulness is a bit more ethically complicated.
What does it mean to not tell the truth? Are all non-truths
lies? Are all lies unethical?
In engineering communication, as in all communication,
there are two basic types of non-truths: lies and deceptions.
In both cases the intent is to have the recipient of the infor-
mation draw a false conclusion from the available informa-
tion. While both methods of eliciting false conclusions may
be morally wrong, there is a well-defined operational differ-
ence between a lie and a deception.
A "lie" is a categorical statement known by the teller to be
untrue. An engineer who tells a client that the client's report
has been mailed, for example, while knowing full well that it
is still being prepared, is telling a lie. Most lies are verbal,
but lies may also be told by body language, such as nodding
the head, or by graphics when, say, some data points are
intentionally omitted to "make the graph look better."
Lying requires only that incorrect information is inten-
tionally transmitted. If I say "I am ten feet tall," that is a
lie, regardless of who I tell it to.
In contrast to a lie, a deception is an action that begins with
a statement (verbal or graphical) that may be true, but the
intention is for the listener or reader to draw a false conclu-
sion. If an anxious client asks an engineer for the status of a
report, the engineer can say that "it is essentially finished."
The client might interpet this as meaning that it will be
collated in time to be picked by by FedEx that afternoon, but
the fact might be that not all of it has yet been written. If, by
using such a phrase as "essentially finished," the engineer

* Department of Civil and Environmental Engineering


knows that he or she is creating a false impression (without
overtly lying), he or she is guilty of intentional deception,
and deception with an intent to mislead or obfuscate is not
honorable behavior. If the client is savvy enough to ask what
the engineer means by "essentially finished," the engineer
has a chance to tell the truth or to lie.
Deception in the hands of a professional such as an engi-
neer can have serious repercussions. For example, suppose
an engineer writes a technical article about an explosion at a
chemical plant and intentionally uses incomplete informa-
tion that has the result of deceiving the journal readership.
The engineer is not actually lying, but rather is using partial
data without reporting that other data have been omitted. To
publish such misleading information is unethical behavior.
Other engineers can draw unwarranted conclusions from
such an incomplete report and the result could be additional
industrial accidents.
Just as words can be used to mislead a reader, unscrupu-
lous or incompetent illustrators can distort engineering illus-
trations with both lies and deceit. Thus, we must judge
engineering illustrations not only on the value of their infor-
mation and on their appearance, but also on their integrity.
In most cases, graphics have a certain sacred value to
engineers, and illustrations are seldom blatant lies. Few en-
gineers and scientists will intentionally misplace a data point

Aarne Vesilind received his PhD in environ-
mental engineering from the University of North
Carolina in 1968. Following a post-doctoral year
with the Norwegian Institute for Water Research
and another as a research engineer with Bird
Machine Company, he joined the faculty at
Duke University. He is presently involved in
research on waste management, including pro-
cesses for dewatering wastewater residues,
Management of municipal solid waste, treat-
ment of industrial wastes, and environmental
ethics in engineering.
Copyright ChE Division of ASEE 1999


Chemical Engineering Education










on a graph or add points without having the data. For this
reason, most engineering readers place a great deal of weight
and credibility on data points.
Sometimes, however, some researchers or practitioners
fail to include all the relevant data points or will move data
points to "improve" the graph. Occasionally, data points are
so far off the line that the researcher is tempted to either
discard them as "something went wrong here" or note them
as "rogue points." There even exists a statistical test that can
be used for removing (with full statistical justification) the


data point from the graph. This is
the one "rogue point" may in
fact have been an indicator
of something very important
and totally unexpected.
Fortunately, instances where
engineers and scientists have
used graphs for transmitting in-
correct information (lies) seem
to be rare, and in cases where
there have been fabrications of
data, the scientific community
has properly condemned the
actions. A much more insidi-
ous (and more common) mis-
communication of graphical
information is the use of illus-
trations for purposes of decep-
tion. Graphs don't have to ac-
tually lie to express incorrect
information since it is the per-
ceived information that matters.
Most misleading illustrations
are deceptions rather than lies.
Such deception can be achieved
by several unethical techniques,
including optical illusion, in-
appropriate cause and effect,
unwarranted visual embellish-
ment, and misuse of data.

OPTICAL ILLUSIONS
Optical illusions in engineer-
ing drawing create misper-
ceptions that can cause mis-
takes. Engineering drawings
must not only be accurate, but
they must also be perceived ac-
curately by others. Our eyes
can play tricks on us, and it is
the responsibility of the com-
municator to minimize the po-
tential for misperception.


a risky business since






/ \
A

< >


Psychologists have identified at least five different visual
illusions:0]
1. Illusions of extent-the size or length is misjudged
2. Illusions of direction-the orientation of a line or
figure is misjudged
3. Illusions of shape
4. Illusions of brightness
5. Illusions of motion


Figure 1 shows some


examples of the first illusion-
illusion of extent. In Figure
1A, the length of the straight
line between the arrows is
equal, but the optical illu-
sion is that the lower one is
longer. This same trick can
be applied to space, shown
in Figure IB. Figure IC
shows that the outer circle
of a concentric pair is un-
derestimated while the in-
ner circle is overestimated.
Figure ID shows that for
two equal figures between
converging lines, the one
nearest the "vanishing
point" is perceived as larger.
Illusions of extent can be
used to draw graphics that
misrepresent the facts. Fig-
ure 2 is an example of such
a misrepresentation. Draw-
ing the bar graph inside di-
verging lines suggests a de-
crease that in fact is not true.
Figure 3 shows several
examples of the illusion of
direction in which the ori-
entation of a line or figure is
misjudged. Figure 3A shows
that although the two line
segments intersecting the
parallel line are actually on
the same straight line, they
do not appear that way to
the eye. Figure 3B shows
how the sequence of white
and black squares can make
the lines between them ap-
pear to bend. Figure 3C
shows two parallel lines that
certainly do not appear to
be parallel.


Fall 1999


O0


I I


Figure 1. Illusions of extent.












1 2 3 4 5
Figure 2. Using illusion of extent to deceive the reader











A B C
Figure 3. Illusions of direction


O5










The illusion of direction can be used in a graphic as
shown in Figure 4. Even though the two lines are parallel,
the illusion is that the lines are diverging and the casual
observer is left with the impression that the number of
people smoking cigarettes has grown at a faster rate than
the number of people not smoking.
Illusions of shape are illustrated in Figure 5. The straight
lines on top of the pointed arch in Figure 5A appear to
bend to make a sharp point. Figure 5B shows three arcs of
equal sized circles. The more of the arc that is shown, the
more the arc appears to curve. All arcs have, however, the
same radius. Figure 5C is an amazing figure showing how
the circle can appear to be distorted.
The illusion of shape can be shown by the embellished
bar graph in Figure 6. Not only is the last bar fancied up,
but the chevrons also give an optical illusion of fatness on
top, suggesting growth that isn't there in reality.
Illusions of brightness can be illustrated by the block
diagram in Figure 7A. If you look at the figure for a while,
you will see darker spots in the white spaces at the corners
of the black squares.
Illusions of motion are often used to trick the eye. Air-
plane pilots have long been aware of the apparent motion
of spots of light during a dark night, called autokinesis. In
one interesting experiment, the subjects were placed in a
very dark room and asked to focus on a tiny spot of light
on the far wall. They were told that the light would be
moved to spell words and the test (they thought) was for
them to try to read the words. All subjects read what they
wanted to read, while in fact the light never moved!
Figure 7B shows an example of autokinesis. If you stare
at the figure for a while, you will see swirling motion.
Motion is optically created while the figure is obviously
not moving.

IMPLIED CAUSATION
Another way graphics can deceive is by implying causa-
tion where none is warranted. Figure 8 shows the correla-
tion between the rate of typhoid fever deaths and the
fraction of the population with public water supplies. Such
graphs have been repeatedly published by environmental
engineers who want to convince the world that they have
performed magnificently and should receive due credit for
their efforts. There is no doubt that the construction of
clean public water supplies helped reduce the typhoid
death rate, but this graph does not prove it. An excellent
correlation also results from plotting the reduction in the
typhoid death rate and the decrease in the manufacture
of buggy whips. The conclusion, if causation is mis-
taken for correlation, is that either buggy whips cause
typhoid or the reduction in typhoid deaths resulted in
the decrease in buggy whips.


number of people
smoking and not
smoking cigarettes


96 97 98 99
Figure 4. Using illusion of direction to deceive the reader.








A B C

Figure 5. Illusions of shape.


4


3
Price ($) "

n-
2





1 2 3 4
Year
Figure 6. Using illusion of shape to deceive the reader.













A B

Figure 7, Illusion of brightness and illusion of motion.


Chemical Engineering Education


not smoking












50 75

40 80
Typhoid \ typhoid Population
Fer 30 Served
es 30 85by Public
Deaths Water
(number Wate
per \Supplies
100,00020 90(%)
population)
10 95
water supplies _-
0 100
1890 1900 1910 1920 1930 1940
Year
Figure 8. Correlation between population with public
water supplies and the typhoid fever death rate in the
United States. (After Whipple and Horwood, from Fair,
G.M., J.C. Geyer, and D.A. Okun, Water and Wastewater
Engineering, John Wiley & Sons, New York, NY 1966).


4.5 Ib/cap/day


1960 1990

Figure 9. Deceptive use of two-dimensional pictures to
represent one-dimensional data.



30

25-
Number of
Nobel 20
Prizes
Awarded to
Americansl 5 -

10-

5

0 1901- 1911- 1921- 1931- 1941- 1951- 1961- 1971-
1910 1920 1930 1940 1950 1960 1970 1974
Figure 10. Misleading line graph due to uneven scale.
(National Science Foundation, Science Indicators, 1974,
Washington, DC, 1976)


VISUAL EMBELLISHMENTS
A third common source of misperceived (and thus un-
ethical) graphics is the use of visual embellishments. One
oft-used visual embellishment technique is the two-dimen-
sional bar graph. A bar in a bar graph is one-dimensional,
showing the quantity as its height. But the bar can also be
shown as a two-dimensional picture. Figure 9 shows how
trash cans represent the bars, but these are actually two-
dimensional pictures. From this figure we see that even
though 4.5 is only 50% larger than 3.0, the appearance is
much greater since the reader sees the area of the trash
cans, not just the height.

MISREPRESENTATION OF DATA

Some graphs are clearly intended to mislead. For ex-
ample, Figure 10 shows a notorious graph that appeared in
a government document arguing that the United States was
losing its edge in science and technology since our share of
the Nobel prizes seemed to have dropped precipitously.
The truth is that the last data point (1971-1974) is the total
number of Nobel prizes for only afive-year interval, whereas
all the remaining points represent Nobel prizes received
during ten-year intervals.
Some graphs deceive because the data are plotted cumu-
latively, and the reader is not sufficiently warned to inter-
pret the graph in such a fashion. Figure 11 shows the use of
various forms of power for electricity production. A
quick glance suggests that nuclear power is the most
important energy source and continues to provide the
greatest share of electricity. The data in this graph are,
however, plotted cumulatively so that the energy pro-
duction from various sources is the difference between
the adjacent lines.


Figure 11. An example of a deceptive graph where
the data are summed.


Fall 1999


3 Ib/cap/day


Annual
Energy
Use
(Joules
x 1016)


1980 2000


1900 1920 1940 1960
Year












Broken scales can also convey misleading information. Broken scales
occur either when an axis does not start at zero or when the scale is
temporarily discontinued. Note how Figure 12A creates a mistaken im-
pression by not starting at zero and thus conveys a very different impres-
sion from the more honest Figure 12B. Good practice requires that all
broken scales be clearly indicated.
Sometimes it is possible to conceal data points in such a way as to make
the rest of the data appear much more impressive, and thereby mislead the
reader. Like Figure 13A, Figure 13B shows accurate points, but with the
abscissa moved so that the points are concealed.
Sometimes the authors of a graph read more into the data than a reason-
able person might. Figure 14A shows data used as the foundation for a



4.8
5-
Solid 4.6 5
Waste 4 -- O,-- '
Production
(b/cap/day) 4- 3
2
4.2 1

4.0 0 I I
1960 1970 1980 1990 2000 1960 1970 1980 1990 2000
Year Year
A B

Figure 12. Data as presented by the authors (A) and a more honest
presentation without the broken scale (B).


8a

Y 0 00
4 o
00 o
V0
2 2 -2

101 id2 id4 10' idl 10 0 d2 ld4 1'd id
x x

A B

Figure 13. Data obtained in a research experiment (A) and the plot
presented by the authors (B).


8 8

0 C- 0
O oO O
o o
4 004 0

2 2

o I 01 o I 1 00
0 6 12 18 20 24 0 6 12 18 20 24
X X

A B

Figure 14. Data obtained in a research experiment (A) and the line as
drawn by the authors (B).


complex theoretical model. Figure 14B shows
the same data with the line as drawn by the
authors. There is no reason to draw such a line-
except that the model developed by the authors
predicted that this would occur. The most that
can be said in such cases is that the data cer-
tainly did not disprove the model. Claiming that
the data offer proof of the model is, however,
unwarranted.
Statistics can be used to suggest causation
where none exists. The famous British prime
minister Benjamin Disraeli is supposed to have
said that there are three kinds of lies-lies, damn
lies, and statistics. Disraeli notwithstanding, as
long as statistics are calculated accurately, the
result cannot represent lies. On the other hand,
statistics opens up a tremendous opportunity
to deceive. There is no doubt that the inter-
pretation of statistics can be manipulated to
serve the desired end.
One of the most used (and abused) statistical
techniques is the least-squares fit of data. The
theory is that the best fit is obtained when the
sum of the squares of the vertical distances be-
tween the experimental values of Y and the
line representing the relationship between X
and Y is minimized. If the sum of the square
of these distances approaches zero, then the
fit is perfect.
The statistic used to measure this goodness of
fit is known as R2. If the calculated R2 = 1.0,
then the data fit perfectly. That is, we get a
perfect straight line and all of the data points


15 15

10 10
Y
5. *
5 5
2 = 0.67 = 0.67
0 0
0 5 10 15 0 5 10 15


15

10
Y
5 R R= 0.67
0 0 5 10 15
X


15

10

5 R= 0.67
0
0 5 10 15
X


Figure 15. Four plots with data showing
identical R2 values. (After Anscombe, F.J.,
"Graphs in Statistical Analysis," Am.
Statistician, 27, 17, 1973).


Chemical Engineering Education












fall exactly on the line. If R2 = 0, then there is no fit whatso-
ever; there is no correlation between X and Y.
Shady ethics enter when R2 is used to determine the good-
ness of fit without also including the plotted data, or without
using common sense. Figure 15 shows how statistical corre-
lation can be subverted.121 The four data sets can be plotted to
yield exactly the same R2 = 0.67. Each data set has the same
mean and is described by the same least-squares equation.
And yet the data, when plotted and viewed on the plots,
represent four totally different populations. Only by plotting
the data would the reader understand the actual relationship
between the two variables.

CONCLUSION
Depicting the truth by avoiding both lies and decep-
tions in engineering graphics is invariably the safest course
of action for engineers. Or, as Mark Twain suggested,
"Always tell the truth. That way you don't have to re-
member what you said."

REFERENCES
1. The psychology of optical illusion has been studied for over
200 years. Many of the examples used can be found in two
excellent books: J.O. Robinson, The Psychology of Visual
Illusion, Dover Publications, Mineola, NY (1992), and M.
Luckiesh, Visual Illusions, Dover Publications, Mineola, NY
(1965)
2. Anscombe, F.J., "Graphs in Statistical Analysis," Am. Stat-
istician, 27, 17 (1973); as described in Betthouex, P.M., and
L.C. Brown, Statistics for Environmental Engineers, Lewis
Publishers, Boca Raton, FL (1994) N



Tracer Input Experiments
Continued from page 303.
student to understand and complete the theoretical lessons
concerning chemical reactor design. The versatility and ra-
pidity that comes with using a personal computer has excel-
lent pedagogical aspects. It must be remembered, however,
that it is necessary to refer constantly to the suitability of
using more simple models (lower number of parameters),
making some of the variables in the program constant. In
this way, we avoid the problem of using models with more
parameters than degrees of freedom of the system.
The time necessary for recording the responses and simu-
lation of one curve of residence time distribution, once the
preliminary steps are finished, is estimated to be between 10
and 15 minutes for a reactor of dimensions similar to the one
described in this paper. This allows the student to perform a
series of eight different flow rates in two hours, using the
first hour to prepare and calibrate the system as well as to
prepare the tracer solution. The last hour can be used to
discuss different aspects with the teacher, proposal of pro-
gram modifications, and other applications.


CONCLUSIONS
This class was designed for students to familiarize them
with the concepts of reactor design and characterization. The
reasonably good agreement between experimental and cal-
culated values of the RTD makes them feel confident about
applying engineering concepts.
The students find the experimental procedure relatively
uncomplicated and possible to complete within the labora-
tory period. Using personal computers to study an electro-
chemical reactor rather than simply studying the theoretical
concepts provides better comprehension of the reactor flow
pattern and the model development.
It is important that the theoretical concepts be explained in
class before the students attempt the laboratory exercises.
Operational problems also become clear while the students
are performing the experiments. For example, the impor-
tance of rapid injection of the tracer was discovered by
several students who found that the response was "abnor-
mal" in the sense that many peaks were found when non-
instantaneous modification of the conductivity was
achieved in the input.
Another important concept involved in this practice is the
optimization method and its structure in the BASIC pro-
gram. Students appreciate when someone explains how
to run an optimization method such as the Simplex used
in this lab session.
Students find the session interesting and enjoyable, and
they relate well to the engineering principles involved. The
lesson allows them to perform and validate what they have
learned in class.

REFERENCES
1. Davis, R.A., J.H. Doyle, and O.C. Sandall, "Liquid-Phase
Axial Dispersion in a Packed Gas Absorption Column," Chem.
Eng. Ed., 27, 20 (1993)
2. Levenspiel, O., The Chemical Reactor Omnibook, OSU Book
Store, Corvallis, OR (1979)
3. Nauman, E.B., Chemical Reactor Design, John Wiley &
Sons, New York, NY (1987)
4. Westerterp, K.R., W.P.M. Swaaij, and A.A.C.M. Beenackers,
Chemical Reactor Design and Operations, John Wiley &
Sons, Amsterdam (1984)
5. Levenspiel, O., Chemical Reaction Engineering, John Wiley
& Sons, New York, NY, p. 253 (1972)
6. King, C.J., Separation Processes, McGraw-Hill, New York,
NY, 570 (1980)
7. Himmelblau, D.M., Process Analysis Statistical Methods,
John Wiley & Sons, New York, NY (1968)
8. Gonzdlez-Garcia, J., V. Montiel, A. Aldaz, J.A. Conesa, J.R.
Perez, and G. Codina, "Hydrodynamic Behaviour of a Filter-
Press Electrochemical Reactor with Carbon Felt as a Three-
Dimensional Electrode," Ind. Eng. Chem. Res., 37, 4501
(1998)
9. Ingl6s, M., P. Bonete, E. Exp6sito, V. Garcia-Garcia, J.
Gonzalez-Garcia, J. Iniesta, and V. Montiel, "Electrochemi-
cal Regeneration of a Spent Oxidizing Solution: An Ex-
ample of a Clean Chemical Process," J.Chem. Ed., (in press)
0


Fall 1999


309











e Stclassroom


INTRODUCING

PROCESS CONTROL CONCEPTS

TO SENIOR STUDENTS

Using Numerical Simulation


MOBOLAJI E. ALUKO, KENNETH N. EKECHUKWU
Howard University Washington, DC 20059


Among all the courses in the chemical engineering
curriculum, students generally find process control
the most challenging. Perhaps one reason is that it is
one of the final courses of their undergraduate curriculum.
Our observation, confirmed by another source,111 was that
students oftentimes characterize the course as an abstract
study with extensive mathematical derivations that bear little
or no relevance to the practice of chemical engineering. This
has prompted a re-examination of process control instruc-
tion at Howard University, with interest focused on how
knowledgeable the graduating students are with respect to
being able to apply their process-control knowledge when
they leave for industry.
Although this re-examination is still proceeding, we want
to share some of our experiences with a learning module that
was introduced for the purpose of helping students rethink
their views about process control. Understanding how the
subject of process control was viewed, we felt there was a
need to stimulate interest in the course by adapting the
course materials in a manner that makes learning exciting.
We have done this through an assignment involving model-
ing and simulation using the Mathcad software package.
The typical tasks covered in the assignment range from
routine material, component, and energy balances to numeri-
cal simulation of uncontrolled and controlled systems. The
assignment thus formulated substantially covers most of the
major topics in the undergraduate process control curricu-
lum. The only set of new material that is needed to comple-
ment the students' knowledge in order for them to be able to
do the assignment is the control law, under which a brief
explanation of the effects of proportional, integral, and de-
rivative control modes are explained. As for modeling and
simulation, the knowledge the students have gained from
prior courses in chemical engineering calculations,1[2 kinet-
ics,131 heat transfer,[41 and advanced calculus are more than


enough to get them through the assignment. The instructors'
responsibility lies solely in guiding the students so that they
will be able to synthesize ideas based on what they have
already learned in these prior courses. With proper guidance,
a successful modeling and simulation of the system was
found to be beneficial to the students in introducing various
aspects of process control, such as the concept of a closed
feedback control loop.151

PROBLEM STATEMENT
The simulation assignment was taken from established
sources[6'71 with slight modification. Given was a CSTR
equipped with a cooling jacket in which a first-order exo-
thermic reaction of decomposition of hydrogen peroxide
into water and oxygen occurred in the presence of excess
sodium hydroxide, which acted as a catalyst.

H202 + (NaOH) -- H20+ 02 + (NaOH)
2
Mobolaji E. Aluko is Professor and Chair of
the Department of Chemical Engineering at
Howard University. He received his BSc from
the University of Ife, Nigeria, his MSc, DIC,
from the Imperial College, London, and his
PhD from the University of California, Santa
Barbara. His research interests are in the math-
ematical modeling of chemical reactors, mate-
rials processing, and coal-related technolo-
gies.

Kenneth N. Ekechukwu is a lecturer and se-
nior research fellow at Howard University. He
earned his MSc and PhD from Warsaw Uni-
versity of Technology, Poland. He joined
Howard's Department of Chemical Engineer-
ing in 1992, where he has been pursuing re-
search activities in coal-based technologies,
materials science engineering, and develop-
ment of new products via environmentally be-
nign processes.
Copyright ChEDivision of ASEE 1999


Chemical Engineering Education











The reacting mixture flowed in through a linear valve
while the product was discharged through a square root
valve. We wanted to investigate the uncontrolled and
the controlled dynamic behavior of the concentration
of HO22 and the temperature of the reactor from time
t = 0 to some time after first filling (starting with an
empty reactor), following which control was initiated.
The need to formulate the relevant mass, component,
and energy balances in a manner that was fairly general
and capable of accepting different parameter values
such as inlet concentration, temperature, reactor vol-
ume, and others was emphasized. The parameters of
the system are presented in Table 1. The mean tem-
perature difference between the reacting mixture and
the coolant was expressed as a function of difference in
temperature of the reacting mixture and the inlet tem-
perature of the coolant as


T TCin
T T = F
1+
Fc


2QcCp
where Fc = 2Q
UAc


The students were asked to show all steps of the
formulation, including the system diagram (Figure 1),
and to state all assumptions clearly. We pointed out
that the units of the data provided were all mixed up,
which meant that conversion to a uniform system of
unit was required before simulation. The problem as-
signment was to culminate in showing the reactor's
liquid height, concentration, and temperature profiles
as a function of time with a short comment on the
stability of the system.


CLASS ORGANIZATION
The class was organized into teams averaging four to five stu-
dents for the assignment and met three times a week (usually
before noon on Monday, Wednesday, and Friday) for one-hour
lectures, which was in addition to a 3-hour laboratory period per
week, scheduled on Monday afternoon.
A substantial portion of this open-ended assignment was treated
within the framework of the laboratory. The importance of team-
work was stressed, with an emphasis on including the workload
distribution in the final report as a requirement. The team members
were also asked to exclude the names of any inactive participant in
the report (the student in question would receive a failing grade).
One of the items in the list of topics to be discussed each week was
how well the team members interacted and whether there was a
need to either exclude or split any team into small number of
students. Usually, the students refrained from creating conditions
that would precipitate splitting their team since it would amount to
a heavier workload per student left on the team. Perhaps as a result
of these prior arrangements, no team was split.

THE MODELING
The model of the CSTR system was expressed in dimensionless
state-space form, in terms of liquid height (equivalent to liquid
volume for the reactor vessels that were not uniform in cross-
sectional area), concentration, and temperature. Equations (1) and
(2) (see Table 2, next page), respectively, designated the dimen-
sionless state space of the system under uncontrolled and con-
trolled conditions, with applicable initial conditions and Jacobian
defined by Eqs. (3) and (4), respectively. These systems character-
ize the time variations of the state space, which belong to a class of
nonlinear autonomous equations in which there was no time vari-
able involved in the definition.
Large nonlinear systems occur in many important applications
such as the simulation and control of chemically reacting systems


Controller


Final Control Element


STemperature
Setpoint

SThermocouple


F=kv h; T, CA,C, p


Coolant Out
QC, TC

Figure 1. A closed feedback control loop of the modeled CSTR showing the
essential components and parameters.


Coolantln
Qc, Tcin


TABLE 1
Values of Parameters Used in Simula-
tion*

V 16.2 liters
k 5.04 x 10't 1/sec
E 18.620 cal/mol
Cp 0.865 cal/g C
C, 62.5 BTU/(hr ft2oF)/(lb/min)"3
U CIQQ"/3
T 220C
T 10C
To 14C
CAO 11.5 mol/liter
F 0.5 liter/min
p 1.1081 g/cm3
AH -22.6 kcal/mol
Qc 900-3600 lb/min
Kv 0.9 cm25/min
Kp 3 liter/min K
D 25.2 cm
A. 3.18 ft2
*Symbol names are stated in the nomenclature


Fall 1999


F, Ti,CAi,Cp,pi ,Pi











whose solutions sometimes precipitate what is known as
"still problems." The still problems usually arise from mix-
ing of terms of fast and slow dynamics with the consequence
that the use of Runge-Kutta's fixed-step technique will yield
unsatisfactory results. Students were therefore reminded that
stiff problems are more competently resolved by employing
varying-step methods such as the modified-adaptive step,
Brulisch-Stoer or Rosenbrock techniques, all of which are


built into the Mathcad software package (see Table 3).
Most students were already familiar with Mathcad and
the decision to use it for the problem assignment enabled a
focused attention on the problem solution rather than be-
ing worried with writing a correct high-level program-
ming language. Additionally, it enabled a different under-
standing of other process control simulation modules, such
as the use of Process Identification and Control Loop


Chemical Engineering Education


312











Explorer system, PICLES,'8" and MATLAB/SIMULINK,'[9"1
which were introduced later for different process-control
problem assignments. Advanced control system"21 is a simi-
lar software package that is also available.

CASE STUDIES
The tasks of the problem assignment en-
compassed simple case studies aimed at
determining the dynamics of the
Method
Uncontrolled system duringfill-up
Varying Step Te
Uncontrolled system at constant
liquid height Rosenbrock Tec
liquid height
Fixed StepTechr
P-only controlled system at constant
liquid height Burlisch-Stoer T
P-only controlled system right from
start-up
Effects of multiple-fold increase in cooling rate

Typical simulation conditions associated with each case
study are explained in Table 4, with representative graphi-
cal results shown in Figures 2 through 4. Prior to simula-
tion, it was instructional for the students to make the
equations dimensionless and to prepare a table of vari-
ables detailing the input values assigned to each param-
eter under each case study, as shown in Table 5.


OBSERVATIONS AND CONCLUSIONS
Our observations can be summarized in two categories:
the pedagogical value of the approach and the usefulness of
simulation as a powerful tool in learning various concepts in
process control. From the standpoint of pedagogy, it was


TABLE 3
Various Built-In Solution Tools of Mathcad
Inputs Outputs
chnique Z=Rkadapt(X, 6 6f, points, D( 6 ,X)) Z=F( 6,X,X2,X,)
hnique Z=stiffr(X, 0 O, points, D( 6,X),J) Z=F( 6,X,X,,X,)
lique Z=rkfixed(X, 0 O, points, D( ,X)) Z=F( ,X,,X,,X3)
technique Z=stiffb(X, 6,, points, D( 6,X),J) Z=F( ,X,,X,,X3)



TABLE 4
Various Simulation Case Studies Investigated

Case Studies Conditions
I Uncontrolled dynamics during fill-up (1) X,=0; X2=l; X3=l
II Uncontrolled dynamics at constant height (2) F ,=Fo; X,=l; X,=l; X,=l
III P-only controlled system at constant height (3) F,=K,(X3-X ) and (2)
IV P-only controlled system at startup (4) Fo=Kc(X3-Xe) and (1)
V Effects of multiple-fold increase in cooling rate (5) n=l,2..N; Qc=nQcn and (2)


Fall 1999












observed that the problem assignment formulated in this
5 manner gave the students a lot of confidence by focusing
their attention on the subject of the problem, which was to
model and simulate the system. There was an opportunity to
4 investigate as many case studies as possible, the result of
which advanced general understanding of the concepts that
are vital to learning of the course materials.
Toward the end of the assignment, the preconceived no-
3 --- tion of the course being a means of learning mathematics
was suddenly changed to the use of mathematics as a tool in
learning process control. Consequently, there was a general
feeling of "I can do it on my own" among many students.
S2 This was the kind of confidence we wanted them to develop,
I / CFeed Height and our feeling was overwhelming when we saw it work.
SConcentration
Temperature Secondly, breaking up the assignment into various case
..studies enabled the students to answer simple "what-if" ques-
tions associated with them. For example, Case Study I dealt
with investigating the dynamics of the uncontrolled system
during fill-up, with the outlet valve closed (see Figure 2). It
0o 1. was learned that so long as the valve remained closed, the
0 1 2 3 4 5
Dimensionless Time liquid level in the reactor would continue to rise, the effect of
which would possibly lead to overflow. The evidence of the
Figure 2. Case Study I: The dynamic response of the system attaining stability in concentration and temperature,
uncontrolled system during startup, with no effluent i.e., X2 and X3 eventually settling at certain bounded levels
output. The tank fills at dimensionless time=l.. .
Sas time approached infinity even as the liquid level increased,


1.4 1.6




1. 12
Q
0 0






0.84 1 096 ----

I oo P-Only Controlled Temp., Kp=3 Liter/minK
(cona troled)To temperature n cocIE Concentration at coolant rate, Qc=900 Ib/min
K\-x- Concentration Without System Control 0 Concentration at coolant rate, 2*Qc
Concentration at coolant rate, 4*Qc
_t' Concentration With System Control o o Temperature at coolantrate, Qc
a r l o o o Temperature at coolant rate, Qc
S0.56 1 064 00 Temperature at coolant rate, 2*Qc
Temperature at coolant rate, 4*Qc



0.28 032




0 0
0 1 2 3 4 5 0 1 2 3 4 5
Dimensionless Time Dimensionless Time


Figure 3. Comparison of Case Studies I (uncontrolled) and III Figure 4. Case Study V: The effects of multiple-fold increase in
(controlled) for temperature and concentration dynamics. Appli- flowrate of the coolant is marked by decreased frequency in oscil-
cation of proportional control effectively removed the oscillations latory behavior of temperature and concentration, which eventu-
in both variables, ally led to the disappearance of oscillation completely.

314 Chemical Engineering Education












was seen. When a proportional control was applied for con-
trol of temperature using the inlet flowrate of the feed as the
manipulated variable (see Figure 3), the oscillatory behavior
in both concentration (X2) and temperature (X3) was re-
moved. The controlled system experienced gradual decay
rather than oscillatory changes that marked the behavior of
the uncontrolled system.
In Case Study V where the flowrate of the coolant was
increased in multiple-fold of up to four, the system experi-
enced pronounced oscillation in temperature and concentra-
tion despite the fact that control was applied. But the charac-
ter of the oscillatory behavior was marked by a decrease in
frequency, which eventually disappeared with increase in
coolant flowrate (Figure 4). This was an indication that
flowrate of the coolant could alternatively be used as a
manipulated variable to control the system temperature. The
students learned at this point that there was more than one
way of achieving control of the system, having discovered
the two candidates for manipulated variables, i.e., the feed
inlet stream and the flowrate of the coolant.

The assignment also gave the students the opportunity to
revisit past courses such as kinetics, heat transfer, and calcu-
lus, and gave them the chance to apply the knowledge they
have previously learned to this assignment. Since this as-
signment was given in the first two weeks of the course, many
students recognized the need to review some of the earlier
course materials they had taken prior to process control.
Overall, this problem assignment received positive com-
mendations from over two-thirds of the class, with many of
them stating that it helped them integrate ideas and to use
them to study typical problems that occur in many chemical
industries. From our point of view, the project was worth-
while, considering the foundation work it laid for better
understanding of various topics taught in other courses in the
past. Most important in our estimation, however, was its
value in fostering understanding of the subject of process
control as a course.

ACKNOWLEDGMENTS
Grateful acknowledgments are hereby made to all students who
took the course in chemical engineering process control. Our spe-
cial thanks go to Masiane Kabelo, Olive Sikem, and Bashir Elabor
for providing in-depth responses about the course.

NOMENCLATURE
A cross sectional area of the tank, cm2
A surface area for heat transfer, cm2
a coefficient (see Eq. 5)
b coefficient (see Eq. 5)
CA concentration of component A in tank (H,0), mole/liter
CA, inlet concentration of component A (H,O,), mol/liter
Cp specific heat capacity, J/g K
C, parameter associated with heat removal rate, BTU/(hr ft2oF)(lb/
min)"3
c coefficient (see Eq. 5)


D diameter of the reactor, cm
D( 0,X) vector valued function of the state-space variables
d coefficient (see Eq. 5)
E energy of activation, J/mol
F. system parameter associated with cooling, dimensionless
Fo dimensionless flowrate
F, inlet flow rate, liter/min
h height of the liquid in the tank, cm
J Jacobian matrix
ko pre-exponential factor, I/sec
Kc controller gain, liter/min*K
K proportional gain
K valve constant, cm25/sec
P, coefficient (see Eq. 5)
P, coefficient (see Eq. 5)
R universal gas constant, J/mol K
Q coolant volumetric flowrate, liter/min
T temperature of the reacting mixture in the tank, C
Tc temperature of the coolant in the jacket, C
T inlet temperature of the reacting mixture in the tank, C
Te setpoint temperature of the reacting mixture in the tank, C
U overall heat transfer coefficient, J/cm2 K
V volume of the reacting mixture, liters
X, dimensionless height
X, dimensionless concentration
X3 dimensionless temperature
X," dimensionless inlet concentration
X," dimensionless inlet temperature
Xc, dimensionless inlet temperature of the coolant
X_, dimensionless temperature setpoint
y Arrhenius number, dimensionless
AH enthalpy of reaction, J/mol
p density of the reacting mixture in the tank, g/cm3
0 residence time, min

REFERENCES
1. Lant, P., and B. Newell, "Problem-Centered Teaching of Process
Control and Dynamics," Chem. Eng. Ed., 30(3), 228 (1996)
2. Himmelblau, D.M., Basic Principles and Calculations in Chemical
Engineering, 6th ed., Prentice Hall (1996)
3. Fogler, H.S., Elements of Chemical Reaction Engineering, 3rd ed.,
Prentice Hall, Chapter 9 (1999)
4. Russell, T.W.F., and M.M. Denn, Introduction to Chemical Engi-
neering Analysis, John Wiley & Sons, New York, NY, Chapters 12,
13(1972)
5. Stephanopoulous, G., Chemical Process Control: An Introduction
to Theory and Practice, Prentice Hall, Chapter 14 (1984)
6. Ramirez, W.F., Process Simulation, Heath Company, p. 81 (1976)
7. Ramirez, W.F., and B.A. Turner, "The Dynamic Modeling, Stabil-
ity, and Control of a Continuously Stirred Tank Chemical Reactor,"
AIChE J., 15(6), 853 (1969)
8. Cooper, D.J., "PICLES: A Simulator for 'Virtual World' Education
and Training in Process Dynamics and Control," Comp. Applica-
tions in Eng. Ed., 4(3), 207 (1996)
9. Doyle III, F.J., E.P. Gatzke, and R.S. Parker, "Practical Case Stud-
ies for Undergraduate Process Dynamics and Control Using the
Process Control Modules (PCM)," Comp. Applications in Eng. Ed.,
(in press, 1999)
10. Bequette, B.W., K.D. Schott, V. Prasad, V. Natarajan, and R.R.
Rao, "Case Study in an Undergraduate Process Control Course,"
Chem. Eng. Ed., 32(3), 214 (1998)
11. Bequette, B.W., "Case Study Projects in an Undergraduate Process
Control Course," Proceedings of Control-97, Sydney, p. 212 (1997)
12. Koppel, L.B., and G.R. Sullivan, "Use of IBM's Advanced Control
System in Undergraduate Process Control Education," Chem. Eng.
Ed., 20, 70 (1986) U


Fall 1999












a classroom


USING A COGENERATION FACILITY

To Illustrate Engineering Practice to Lower-Level Students



ROBERT P. HESKETH, C. STEWART SLATER
Rowan University Glassboro, NJ 08028-1701


Almost every university has a power plant facility
that is an excellent resource for students of engi-
neering processes and equipment. These physical
plants contain many unit operations, such as heat exchang-
ers, combustors, turbines, and boiler water-treatment sys-
tems that may include membrane devices! The systems are
equipped with pumps, compressors, fans, pipes, atomizers,
tanks, finned boiler tubes, inner-wall transfer surfaces, valves,
etc. In addition, a modern facility includes a data-acquisition
system to obtain data to control the plant consisting of ori-
fice plates, pressure transducers, thermocouples, level gauges,
and vibration meters. Concentration measurements are made
using NDIR gas analyzers for CO, CO2 and total hydrocar-
bons. And oxygen is measured using paramagnetic analyz-
ers and NOx using chemiluminescence. Concentration mea-
surements are also made of impurities in the boiler water.
These plants are a rich source of engineering examples that
are readily accessible to engineering students.
At Rowan University, we use our cogeneration facility in
our freshman and sophomore chemical engineering courses.
In the freshman year we introduce our students to measure-
ment devices, process flow diagrams, and process simula-
tion. This is accomplished in the freshman engineering course
in a three-week module on process measurements.

ROWAN ENGINEERING CLINICS
The Rowan engineering faculty are taking a leadership
role by using innovative methods of teaching and learning,
as recommended by ASEE,"11 to better prepare students for
entry into a rapidly changing and highly competitive market-
place. Key program features include
Inter- and multidisciplinary education created through
collaborative laboratory and course work
Stressing teamwork as the necessary framework for
solving complex problems


- Incorporation of state-of-the-art technologies through-
out the curricula
Creation of continuous opportunities for technical com-
munication.
To best meet these objectives, the four engineering pro-
grams of chemical, civil, electrical, and mechanical have a
common engineering clinic throughout their program of study.
In addition to the engineering clinic, they share a common
first year of courses. Our first three classes of entering fresh-
men are between 101 and 115 students with an average SAT
score of 1252 and who graduated in the top 14% of their
high school class.
The primary goal of Rowan University's freshman engi-
neering course is to immerse students in multidisciplinary
projects that teach engineering principles using the theme of
engineering measurements in both laboratory and real-world
settings. Many freshman programs focus on either a design


Robert Hesketh is Associate Professor of
Chemical Engineering at Rowan University.
He received his BS in 1982 from the University
of Illinois and his PhD from the University of
Delaware in 1987. After his PhD he conducted
research at the University of Cambridge, En-
gland. His teaching and research interests are
in reaction engineering, freshman engineer-
ing, and mass transfer.


C. Stewart Slater is Professor and Chair of
Chemical Engineering at Rowan University. He
received his BS, MS, and PhD from Rutgers
University. His teaching and research interests
are in separation and purification technology,
laboratory development, and investigating novel
processes for interdisciplinary fields such as
biotechnology and environmental engineering.
S He has written over 70 papers and several book
chapters.


Copyright ChE Division of ASEE 1999


Chemical Engineering Education










project or a series of discipline-specific experiments that may not be cohesively inte-
grated. Some institutions have used traditional discipline-specific laboratory experi-
ments at the freshman level,121 while others engage students in discipline-specific
freshman engineering design projects.J31 One of the NSF coalitions, ECSEL, has major
efforts in freshman design that have been widely reported.4'51 At Rowan, freshman
engineers are introduced to industrial problems through a series of four modules and
interactive lectures on problem solving, safety, and ethics. In this paper, we will
discuss a portion of the process engineering module that uses the vehicle of a
cogeneration plant.
Freshmen can be overwhelmed when introduced to real engineering processes, and it
is important to have well-defined objectives. They need to understand that they are only
being introduced to the problems and are not expected to know all of the engineering
principles of the processes. Our overall objectives for the fall-semester freshman engi-
neering clinic are
[ Engineering Measurements Students will understand and apply the concepts of
accuracy, precision, resolution, and linearity; calibrate devices; have a knowledge
of the basics of data acquisition; analyze a problem and select appropriate
measurement devices for actual engineering processes.
E[ Engineering Communication Students will produce plots using Excel to
illustrate engineering principles; use PowerPoint for presentations; use word
processing for reports of actual engineering problems. Students will develop the
ability to work in multidisciplinary teams, have effective meetings, and use a
problem-solving strategy on real engineering problems.
El Engineering Fundamentals Students will convert units, examine equations for
dimensional homogeneity; use engineering equations, apply basic concepts (e.g.,
hydrostatic pressure, Hooke's law, Ohm's law) applied to actual engineering
problems.
Four measurement modules are employed in this freshman engineering clinic: manu-
facturing, structural, process, and electrical engineering. Spatial measurements and
measurement fundamentals are introduced to freshman engineering students as they
fabricate a MAG-type flashlight from an aluminum rod. Several structural measure-
ments are shown to the students using a bridge module. Students first survey a bridge
site, conduct strain measurements on a model bridge, and simulate the bridge.
The university cogeneration plant is used to show the use of temperature, pressure,
flow, and concentration measurements. The students tour the cogeneration plant and
record data of temperature, pressure, and flowrate of the water in the cogeneration unit.
They then return to the computer laboratory and simulate two heat exchangers, using
their readings, and perform hand calculations for homework. This is followed by
two weeks of experiments using temperature, pressure, and flowrate devices seen
in the cogeneration plant.
The final module has the students construct a temperature alarm circuit and investi-
gate the use of C++ programming in measurements. Thus, the clinic focuses on mea-
surements in the field and also in traditional laboratory settings. Field trips tend to excite
students by breaking down the monotony of being indoors and helping them prepare for
realistic engineering measurements.

PROCESS MEASUREMENTS MODULE
The process measurements module presents a "day in the life of an engineer" to
freshman engineering students. A problem is posed to students requiring them to visit
the university cogeneration facility. At this site both traditional (gauges and thermom-
eters) and data acquisition measurement systems are employed to monitor the steam and
electricity generation process. This laboratory and homework session is followed by


These
[cogeneration]
plants contain
many unit
operations,
such as heat
exchangers,
combustors,
turbines,
and boiler
water-treatment
systems that
may include
membrane
devices! The
systems are
equipped with
pumps,
compressors, fans,
pipes, atomizers,
tanks, finned
boiler tubes,
inner-wall
transfer surfaces,
valves, etc.
In addition, a
modern facility
includes a
data-acquisition
system to obtain
data to control
the plant
consisting of
orifice plates,
pressure
transducers,
thermocouples,
level gauges, and
vibration meters.


Fall 1999


317











two more laboratory sessions in which students make pro-
cess measurements using similar equipment to that seen in
the cogeneration plant. The module lasts three weeks, with
each week having a 1-hour and a 3-hour session.
Preceding the cogeneration site visit, students are given
lecture and problem sessions on teamwork, safety, system of
units and unit conversions, dimensional homogeneity, and
significant figures. On the week of the site visit, the students
are given a brief introduction to the cogeneration process
and are shown photographs of equipment that they are re-
quired to identify on the site visit.
At the completion of this module on the cogeneration
facility, freshman students should be able to
Convert units of simple dimensions.
Convert units of a variable, such as flowrate.
Calculate the temperature of saturated steam when given a
gauge pressure and an appropriate equation.
Examine an equation for dimensional homogeneity.
Obtain measurements of temperature, pressure, and mass
flowrate and perform an energy balance on the heat
exchangers in the cogeneration system.
Create a simple heat exchanger network using the chemical
process simulator HYSYS.
Identify from a photograph the following: orifice plate,
pressure transducer, thermometer, and pressure gauge.
Describe the process of cogeneration to a high school
student.


Condensate Return to Plant
(Steam condensed to water)

Figure 1. Overall schematic of Rowan University Steam &
Electricity Generation


Figure 2. Rowan cogeneration plant fabricated by Energy Recovery International.


Chemical Engineering Education


Fuel & Air

























Figure 3. Cogeneration process waterflow diagram.


TABLE 1
Plant-Trip Readings

Reading
Reading Value Units
Feed-water flowrate to cogeneration facility 25.1 1000 lbm/h
Steam flowrate from cogeneration facility 21.6 1000 Ibm/fl
Feed-water temperature 216 F
Feed-water pressure 250 psig
Boiler-inlet water temperature 330 "F
Steam pressure from cogeneration system 150 psig


COGENERATION PLANT INTRODUCTION
Rowan University uses steam for both heating and cooling
of its buildings. An additional benefit to the process is the
generation of electricity. We explain to the students that the
process of electricity and steam generation is called cogen-
eration. It is obvious to most students how a building is
heated with steam using radiators, but it is not obvious how
to cool a building with steam! Professors are probably aware
that steam is used with absorption refrigeration[6-81 and
we are very pleased to see that one of the best treatises
on this subject is in Perry's handbook![91
The overall flow diagram for the use of steam at j4
Rowan University is shown in Figure 1. In the Steam
Plant, steam is produced by three conventional boilers
and a cogeneration unit. Steam flows through under-
ground pipelines to each of the university buildings,
through radiator units or the refrigeration absorption
units (air cooling), and then is returned as condensate
to the steam plant. In our new engineering building,
these units are located on the fourth floor, and we are
attempting to modify this laboratory to use this floor
for future engineering classes.
An advantage of using this steam plant is that both
traditional (gauges and thermometers) and data-acqui-
sition measurement systems are employed. Most of the
traditional gauges are for measuring temperature, pres-
sure, and liquid height. At the other end of the spec-


trum is the advanced data-acquisition sys-
tem, which records 65 channels of informa-
.. tion including vibrations, power, voltage,
amperage, temperature, pressure, gas, and
SGP T g, "' flowrates. Students are able to see the advan-
I tages of using both mechanical gauges and
steam..Fow.te pressure transducers. Also given throughout
.R.F this module is the cost of various types of
am Pressure measurement equipment.

SITE VISIT
Students are given the process flow dia-
gram shown in Figure 2 to illustrate the com-
plexity of a relatively small portion of the
steam plant pertaining to the cogeneration. Figure 3 is also
given to the students and shows only the steam production
side of the cogeneration unit. Using this relatively simple
figure, students relate their knowledge of boiling water to
produce steam to that of steam production in a cogeneration
unit. The students obtain readings (shown in Table 1) from
every device marked in Figure 3. Obtaining readings in the
plant turns the plant trip into an active learning experience.
They need to obtain information from this trip that they will
use immediately in the simulation and homework. In addi-
tion, a quiz is given showing photographs of some of the
common measurement equipment. A map of the cogenera-
tion facility is also given to the students to show placement
of the equipment and measurement devices in the building.
Using these figures, students are guided by professors and
upper-division chemical engineering students through the
combustion process and the production of steam and elec-
tricity.
These readings are used as input to a chemical process
simulation package, HYSYS, and as input to a set of hand


Figure 4. HYSYS-generated process flow diagram with
summary tables.


Fall 1999











calculations for a homework assignment. In both
the HYSYS simulation and homework assign-
ment, the students determine the heat duties of
two heat exchangers.
Upon completion of this short site visit, stu-
dents have seen actual process equipment and
obtained readings from a real process. The stu-
dents now have motivation to perform engineer-
ing unit conversions and calculations described in
the next two sections.

PROCESS SIMULATION
At the end of the site visit, students return im-
mediately to the computer room and are led
through a simulation program of the two heat
exchangers. The students follow a self-paced tu-
torial on using HYSYS to simulate their process.
They start the computer program and select the
ASME steam tables as the thermodynamic prop-
erty package. Next they simulate the two heat
exchangers as heaters. After installing each heater,
they enter the readings obtained in the plant.
From this simulation, they obtain the tempera-
ture of saturated steam and the values of the
heat duties of both heaters. A process flow
diagram, generated by HYSYS, of these two
heaters is shown in Figure 4.
After completing this laboratory, students have
experienced two of the activities in the "day in the
life of an engineer." They have visited an actual
plant and then have returned to the computer to
simulate a portion of this process.

HOMEWORK
For homework, students must calculate by hand
the heat duties on both heat exchangers and the
temperature of the saturated steam. In this assign-
ment, they must show all unit conversions and
calculations, and all equations must be dimen-
sionally homogeneous. To aid the students in these
calculations, the answers to most of their calcula-
tions are obtained from the HYSYS simulation
printouts. These printouts contain the plant read-
ings in both the English and SI system of units.
So the student will obtain agreement between
the heat duty on the economizer, but will not
get an exact agreement with the simulated boiler
heat duty.
It is very important to give all the necessary
equations to the freshmen with a clear explana-
tion of the variables. We have also found that the
description or name of each measurement must
be identical to both the HYSYS variable names


and the equation variable names. Finally, the variable names must be
explicitly given in each equation. For example, instead of T in heat
capacity, heat capacity expressions must be given for all of the tempera-
tures (Tw, T,,,,,, TB,).
The heat capacities of the water vapor and liquid were obtained from
empirical correlations based on the ASME steam tables, which are valid
in the range 373 < T < 470 K. In each of these equations, the units for
each constant are explicitly shown. This allows the freshman to deter-
mine if each equation is dimensionally homogeneous.

CF= 4788.26 3.4297 g TFw + 4.885 x 10-3 3 (TW) (1)
P kgK kgK kgK

Hpw = CF(TFw -273.16K) (2)
The temperature of saturated steam is calculated as

= -2.075 x 10-4 1en M steam + 2.683 x 10-3 (3)
Tsteam K 1.01325 x 0Pa) K
An enthalpy balance on each heat exchanger is calculated from

HpWriFW + Qeconomizer = HsBIrFW (4)
Using the results of these energy balances, an estimate of the energy
recovered using the economizer was conducted.
This exercise shows the students the equations that the computer
simulation has used to perform engineering calculations. This removes
the magic of the computer and shows students the equations that the
computer is using in the simulation. After completing this session, the
students have the advantage of seeing a process familiar to them (boiling
water), performing an advanced computer simulation and then conduct-
ing hand calculations of the process.

SECOND AND THIRD WEEK LABORATORY EXPERIMENTS
In the next two laboratory sessions, four experiments are conducted in
which the students use equipment similar to that observed in the cogen-
eration plant. The experiments performed are
Flowrate measurement: rotameter operation and calibration
Temperature measurement: immersion heaters
Pressure measurement: tank efflux and implosion of a 2-L soda
bottle
The rotameter operation and tank efflux experiments are classic chemi-
cal engineering experiments that have been adapted from Perna.21 The
tank efflux experiment is modified by adding 3 pressure-measurement
devices; a sight gauge, a pressure transducer, and a low-pressure dia-
phragm gauge. The implosion experiment employs a vacuum pressure
gauge, water aspirator, and a 2-L soda bottle to graphically show stu-
dents the effect of vacuum. The immersion water heater experiment is
unique in that domestic electric kettles are employed and the students
determine that dT/dt = Qin/mCp,' for most of the heating process.

SECOND-YEAR EXPERIMENTS
USING THE COGENERATION FACILITY
The use of the cogeneration facility continues into the mass and


Chemical Engineering Education











energy balance course typically taken by students in their
second year. Once again, students and professors have an
excellent example of real-world mass and energy balances.
They learn the approximate compositions of natural gas
(fuel oil has a much higher complexity!). Students use their
knowledge of oxidation stoichiometry to determine percent
excess air and predict outlet concentrations. The students
check their answers by comparing them to gas analyzer
measurements of oxygen, carbon dioxide, and carbon mon-
oxide. Water produced is usually not measured, but if de-
sired, a gas stream sample can be obtained and either the
water condensed or a hygrometer can be used to determine
water concentrations. Additionally, mass balances can also
be performed on water-treatment systems, including con-
ventional systems and novel membrane systems.
Since these balances are based on actual measurements,
students find they are not able to obtain an exact balance on
mass and energy. They learn that measurement devices have
a limited accuracy and may need to be recalibrated. This was
the case the first time we tried to complete a mass balance on
the cogeneration fuel stream. Our industrial sponsors are
very excited to hear that students conduct balances on actual
systems, because many of the problems in a real plant are
related to a faulty or out-of-calibration measurement device.
The energy balances on the system were started in the
freshman year to see that heat flows from the hot gas to the
water. Steam tables are introduced and students use their
knowledge of heat capacity and enthalpy gained from chem-
istry and this course to perform energy balances. In this
sophomore course, they now understand the equations that
were employed in the freshman engineering module. In the
sophomore course students calculate the source of energy
production from the combustion reactions. They use stan-
dard heats of combustion, fluid flowrates, and chemical com-
positions to determine outlet gas temperatures. Using mea-
sured values, students determine the magnitude of the en-
ergy losses in a cogeneration system. They can now under-
stand in more detail why an economizer was added to re-
cover additional energy from the exiting gases. In addition,
they can conduct simulations to examine the effect of in-
creasing the surface area of the two heat exchangers on the
energy recovered. This brings engineering economics into
their coursework!

SAFETY AND ENVIRONMENTAL CONCERNS
The cogeneration plant is also an excellent vehicle to
introduce safety, health, and environmental concerns. All
freshmen are required to wear safety glasses, hard hats,
closed-toe shoes, ear plugs (near turbines), and clothing that
covers all limbs. Safety features are shown to students dur-
ing the introductory lecture and tour, such as guards for
rotating equipment and pressure-relief valves. The required
EPA monitoring system is shown in which both a continu-


Fall 1999


ous paper printout and electronic data are produced. The
stack emissions sampling point is readily identified from the
catwalk around the stack. Starting freshmen to think about
safety and environmental issues in a plant is an excellent
reinforcement to their use of laboratory safety.

CONCLUSIONS
The university cogeneration or physical plant is a rich and
diverse resource that should be used in many chemical engi-
neering classes. The plant is on campus and is easily acces-
sible. In addition to the time savings in not having to travel
to an off-campus site, students can be used as tour guides to
minimize group size. Using small groups to tour a facility
allows students to hear the tour guide as well as to ask
questions about the process. By using real-world examples
of engineering, the student's level of understanding and
motivation to learn new material increases dramatically. The
use of a cogeneration facility in chemical engineering courses
is designed to immerse students into multidisciplinary, real-
world, laboratory projects that teach engineering principles.
Students are excited and challenged by working in real-
world settings and are motivated to learn the underlying
engineering principles.

ACKNOWLEDGMENTS
Special thanks are given to the physical plant staff headed
by Glenn Brewer for help in preparing the cogeneration
module, Mark Showers, chemical engineering students, and
faculty for giving tours of the facility. Funding for this work
was made possible through a grant from the DuPont Educa-
tional Aid Foundation.

REFERENCES
1. ASEE, "Engineering Education for a Changing World," Joint
project report by the Engineering Deans Council and Corpo-
rate Roundtable of the American Society for Engineering
Education, Washington, DC (1994)
2. Perna, A., and D. Hanesian, "A Discipline Oriented Fresh-
man Engineering Measurement Laboratory," 1996 ASEE
Annual Conference 2326a, Washington, DC., June (1996)
3. McConica, C., "Freshman Design Course for Chemical Engi-
neers," Chem. Eng. Ed., 30(1), 76 (1996)
4. Dally, J.W., and G.M. Zhang, "A Freshman Engineering
Design Course," J. Eng. Ed., 82(2), 83 (1993)
5. Regan, T.M., and P.A. Minderman, Jr., "Introduction to
Engineering Design: A Major Engineering Education Pro-
cess Improvement," Proc. 4th World Conf. on Eng. Ed., 3,
243, St. Paul, MN (1995)
6. McQuiston, F.C., and J.D. Parker, Heating, Ventilating,
and Air Conditioning: Analysis and Design, 4th ed., Wiley,
New York, NY, 659 (1994)
7. Moran, M., and H.N. Shapiro, Fundamentals of Engineer-
ing Thermodynamics, 3rd ed., Wiley, New York, NY, 659
(1996)
8. Smith, J.M., H.C. Van Ness, M.M. Abbott, Introduction to
Chemical Engineering Thermodynamics, 5th ed., McGraw-
Hill, New York, NY, 305 (1996)
9. Perry, R.H., and D. Green, Perry's Chemical Engineers' Hand-
book, 7th ed., 11 (1996) E

321











M.4 1 curriculum


DESIGNING A

PETROLEUM DESIGN COURSE

IN A PETROLEUM TOWN


H.W. YARRANTON, W.Y. SVRCEK
University of Calgary Calgary, Alberta, Canada T2N 1N4


Until recently, the Department of Chemical and Pe-
troleum Engineering at the University of Calgary
offered undergraduate degrees only in Chemical
Engineering and Chemical Engineering with a Petroleum
Minor. As a result of a joint university and industry initia-
tive, however, a new degree in Oil and Gas Engineering was
added to the program in 1998.
The curriculum of the new Oil and Gas Engineering De-
gree was largely based on the advice of an industry advisory
committee consisting of representatives from several major
companies in Calgary's oil and gas sector. The committee
identified the fourth-year Petroleum Design course as a
key component of the new curriculum. This provided an
opportunity for creating a course that draws on the high
concentration of oil and gas companies and petroleum
professionals in Calgary.
Now it was up to us to design the design course. First, we
considered why design is taught at universities.

WHY TEACH DESIGN?
Perhaps the best way to answer the question is to examine
the difference between undergraduates without design train-
ing and practicing engineers. "Academic" undergraduates
will have taken a number of courses, each dealing with a
specific topic area such as heat transfer, thermodynamics, or
reservoir engineering. They should be familiar with funda-
mental principles of engineering science and are well versed
in solving narrowly defined problems based on those prin-
ciples. For example, they can find the pressure drop of a
specified single-phase fluid in a given pipeline at given
conditions. They will also have received some training in
writing reports and making presentations.
Academic undergraduates are probably not fully aware of
the interrelation of many topics covered in the undergradu-
ate program. They have been trained to tackle problems


individually and, at least in technical courses, they are rarely
called upon to present their results in any format other than
written assignments, short reports, or examinations. They
have little or no experience with managing partial or contra-
dictory data, conducting economic evaluations, and solving
"design" problems. Here, a "design" problem is a problem
that requires "the devising of an artifact, system, or process
to best meet a stated objective.""' For instance, "design a
process to produce styrene for the Alberta market that meets
the corporate economic hurdles." Note that design problems
are open-ended; that is, the number of options and amount of
detail that can be considered is limitless.
Practicing engineers deal primarily with design problems.
They are usually selecting processes or choosing between
competing technologies. Most of the methods and theories
they learned in college are embedded in simulation software.
Their hard-earned university knowledge is used primarily to
check the simulation results for implausible results. But they
must be aware of the interaction of all facets of their under-
graduate knowledge. For example, is there heat loss from
the pipeline and does the flowing fluid enter the two-
Harvey W. Yarranton is Assistant Professor of
Chemical and Petroleum Engineering at the Uni-
versity of Calgary. He received his BSc (1985)
and his PhD (1997) degrees in Chemical Engi-
neering from the University of Alberta. His re-
search interests are in the thermodynamics and
transport of hydrocarbons and the treatment of
water in oil emulsions.




William Y. Svrcek is Professor of Chemical
and Petroleum Engineering at the University of
Calgary. He received his BSc (1962) and his
PhD (1967) degrees in Chemical Engineering
from the University of Alberta. His teaching
and research interests center on process con-
trol and design.


Copyright ChE Division of ASEE 1999


Chemical Engineering Education










phase region? Is erosion or corrosion possible at the
operating conditions?
The university experience has been designed to give prac-
ticing engineers the tools to analyze problems and to adapt to
new circumstances, for they will face new circumstances.
Practicing engineers will often work on projects and tech-
nologies that were barely mentioned in college.
They will usually be part of a team and will be
expected to have good interpersonal and com- The
munication skills. They will often evaluate eco-
nomics and will frequently present the results had
orally and in written form. suffic
Until design was introduced into the engineer- to re
ing curricula, there was a glaring difference be- work
tween the training undergraduate engineers re-
ceived and the work they did as practicing engi- of St
neers. In fact, universities are still criticized for tWO ft
training potential graduate students rather than term
potential industrial engineers.12] Universities have
responded in several ways. Some have intro-
duced design case studies that are introduced in OVerW
the first year and worked on in more detail COmt
throughout the program.31 Many, including
Calgary, have added a co-op or internship pro-
gram where students work in industry jobs for inex]
terms of four to twelve months. Now, all accred- engine
ited North American universities are required to impOf
offer design courses. W
The final-year design course provides the best
opportunity to teach design principles and bridge studeJ
the gap between the university and industry. By with
this time, the students have learned many of the wit
scientific principles they need to solve engineer- o
ing problems. Many have completed an intern-
ship work term and are at least familiar with the and (
industrial environment. The design course al-
lows them to integrate the material from other
courses and to work on a "open-ended" design problem. For
this reason, it is sometimes referred to as the "capstone"
course of an undergraduate program.141

ESSENTIAL ELEMENTS
OF DESIGN COURSE PROJECTS
The comparison of an "academic" undergraduate with a
practicing engineer highlighted the elements we wished to
include in the design course. They are
An open-ended design problem
Real data
Experience relevant to industry
Application and integration of all undergraduate
material
Teamwork
Economic evaluations


Use of commercial software
Written reports
Oral presentations
We then selected projects and structured the course to in-
clude all the above elements.

PROJECTS


projects
to be of
ient scope
quire the
of a team
dents for
Our-month
s and yet
not
rhelmingly
ilex for a
oup of
erienced
eers. Most
fantly, we
nted the
nts to deal
real data
& all its
addictionss
,missions.


The elements listed above apply equally well
to any design course. The next step was to
develop projects from the petroleum area that
met the requirements of the course. What is
involved in petroleum engineering? It encom-
passes a broad range of activities just as chemi-
cal engineering does. Petroleum engineers may
be called upon to estimate the size of a reser-
voir and to predict production from a well or
the reservoir. They may design waterfloods,
miscible floods, steam floods, or even
firefloods (underground combustion) to dis-
place oil from the reservoir. They may drill,
complete, or stimulate wells. They may de-
sign pipelines or separators, or work in a gas
plant. Economic evaluations, land sale evalu-
ations, and negotiation with joint-interest own-
ers are also part of the job. Petroleum engi-
neering even extends to offshore produc-
tion and oil sands processing. What projects
should we draw on from the broad range of
activities?
To apply all the undergraduate material and
gain a perspective of the industry, we desired
projects that included downhole (reservoir) as-
pects as well as facilities (oil batteries, gas
plants, etc.) and the wellbore (drilling and
completions). The projects had to be of suffi-
cient scope to require the work of a team of
students for two four-month terms and yet not


overwhelmingly complex for a group of inexperienced engi-
neers. Most importantly, we wanted the students to deal with
real data with all its contradictions and omissions.
We decided to concentrate on projects involving relatively
straightforward reservoirs, such as a sandstone reservoir or a
homogeneous carbonate reservoir. But the projects them-
selves are broad and open-ended. We ask the students to
examine an existing reservoir and evaluate its reserves and
existing production scenario. The students then have a
choice-they can recommend strategies to increase the value
of the reservoir in its present state, or they can re-engineer
the development of the reservoir. In other words, they could
take all the knowledge of today and develop the reservoir as
if it had just been discovered. The advantage of the second
option is that depleted reservoirs with little remaining poten-
tial can still be used as projects.


Fall 1999











In either case, the students are asked to design appropriate
facilities, construct a drilling and completion program, and
generate production forecasts as well as capital and operat-
ing cost estimates. They then compare the economics of
several strategies and recommend the optimum development


strategy for their reservoir. As in real life, the design
problem statements are deceptively simple
(see Table 1). Note that the progression from
design statement to problem definition to
evaluation of alternatives resembles typical T
chemical engineering design processes,151 al-
though the details differ. Design Pr
With the help of several Calgary companies,'61 E Design
we assembled data sets that included the same for the I
information that practicing engineers deal with retrogra
reservoi
to assess reservoirs; that is, well logs, conven-
E Design
tional and special core data, pressure data (in- Countes
cluding build-up test data), and PVT data. The reservoir
students were able to access any other required E Optimiz
data, such as well locations, completion data, the Blac
and production rates, from a commercial data- sandstorm
base available at the department or from the E Evaluate
the Spar
AEUB (Alberta Energy and Utilities Board), a sandstorm
provincial regulatory agency.
It is these data sets that make our design
course unique. In petroleum engineering, a ma- T
jor issue is describing the reservoir, its size, Required
thickness, porosity, and permeability distribu- Oil and
tions, etc. This description and the associated
reservoir maps are constructed from well logs Year
and other available data. These data represent a Numeri
tiny fraction of the reservoir and are often con- Engin
tradictory or incomplete. Hence, judgment and Heat an
interpretation are critical. A considerable part Chemic
Them
of the first term of the design course is spent Partial
characterizing the reservoir. This evaluation Equat
draws on many of the petroleum engineering Separat
courses in our program, listed in Table 2. Drilling


PROGRAM STRUCTURE
The Department of Chemical and Petroleum
Engineering at the University of Calgary has a
four-year undergraduate program (not includ-
ing time spent on internship work terms). The
program includes a three-part series of single-
semester design courses starting in the second
half of the third year and concluding at the end
of the fourth year.
Both chemical and oil and gas engineering
undergraduates are enrolled in the same third-
year design course. Equipment sizing, cost esti-
mation, and profitability analysis are introduced
in this course, and the textbook used is Plant


ABL
Exam
'oblen

a gas-c
Brazeau
de con
r.
a water
sYYY
r.
e the w
k Butti
ie resei
a stea
ky Ah
ie reser



AtBL
3rd at
jas E
Cours


cal Me
eering
d Mas'
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nodyna
Differ
ions
ion Pro
and C


Design and Economics for Chemical Engineers. 71 The stu-
dents are assigned group projects worth 25% of the course
grade. A chemical engineering project involves optimizing a
given process and a HYSYSI81 simulation of the process is
provided. An oil and gas engineering project involves as-
sessing various strategies for developing a given reservoir.
In this case, an EXODUS'91 simulation of the
reservoir is provided. The projects give the
students an opportunity to practice engi-
LE 1 neering design principles and engineering
pie economics on a problem of limited scope.
iStatements The projects also serve to introduce the

cycling scheme simulation software used in the fourth-year
ycling scheme
iNisku D design courses.
densate In the fourth year, the chemical engineer-

flood for the ing and the oil and gas engineering students
flood for the
sandstone enter different design classes: Process Design
I and Petroleum Design II, respectively. The
'aterflood on students taking a petroleum minor can choose
Stratified between the two design courses. While the
rvoir. design courses are run separately, we mod-
m flood for eled the structure of the petroleum design
eavy-oil
rvoir. course on the long-standing and very suc-
cessful chemical engineering process de-
sign course.[101
E 2 In both cases, the Design I course is in-
nd 4th Year tended to be a first-pass design where the
engineering students can evaluate "their" process or reser-
es voir and perform preliminary design, costing,
and economics. The level of detail is similar
thods in to a budget cost estimate; that is, shortcut
methods are employed and costs are accurate
STransfer to approximately 25%. In the second fourth-
ineering year course, Design II, the students work on
mics
ential the same project but to a greater level of
detail, similar to an AFE (authorization for
cesses I expenditure) cost estimate. In this case, de-
ompletions tailed design methods are employed and
engineering
3r Year manufacturer's quotes are obtained on major
equipment, and costs are expected to be accu-
eservoir rate to 10%.

duction
action STRUCTURE OF PETROLEUM

DESIGN COURSES
s Media Petroleum Design I The students are
creating given one week to form a group (3-4 students

and per group) and choose their top three projects
valuation from a list provided in the first class. The key
Well Testing here is that the students are free to make up
ign I their own groups. We do not force students
ign II
[ineering into groups, thus avoiding personality con-
flicts during the term. The projects are allo-
cated as much as possible on a first-come-


Chemical Engineering Education


nII anda as Ec
Economics (
Design)
Oil and Gas R
Engineering
Petroleum Pro
Engineering
4" Year
Flow in Porou
Oil and Gas T
Processes
Well Logging
Formation E
Introduction to
Petroleum Des
Petroleum Des
Petroleum Eng
Laboratory











first-served basis. As a result, the better-organized students
tend to get the projects of their choice. One disadvantage of
this approach is that the poorer students tend to get concen-
trated into groups that will struggle with the course. On the
other hand, these same students cannot coast through the
course hidden in a group of otherwise good performers.
Once the projects are chosen, the students review their
data sets, analyze what they can, and search for missing
information from a petroleum database, AccuMap,"" in the
literature, at the AEUB, or through industry contacts. They
use well logs and core data to construct cross-sections, struc-
ture maps, and appropriate pay maps of their reservoir. They
determine volumetric reserves, and using pressure and pro-
duction history, they perform a material balance to obtain a
second reserves estimate. They usually reach this point at the
midterm of the course. After the midterm, they use analyti-
cal techniques (such as decline analysis, solution gas mod-
els, and Buckley-Leverett-Welge waterflood predictions) to
assess various development scenarios."12 141 They also size
and cost surface facilities (such as oil batteries, gathering
systems, water plants, and gas plants), estimate drilling and
completion costs, and evaluate project economics using the
techniques learned in the Design I course.
The students are required to meet once a week with their
project supervisor, a faculty member. Typically, each fac-
ulty member involved with the course manages two to four
projects. The students, individually or as a group, are free to
visit the supervisor more frequently. These visits tend to
increase exponentially as the midterm approaches. The mid-
term consists of a six-page report and a five-minute oral
presentation given to four supervisors or faculty members.
One representative of each group presents a GANTT chart
of their work schedule, discusses findings to date, and indi-


cates what each member of the group
supervisors can then ask any group
member a question on any part of the
project. The group members are ex-
pected to be familiar with all aspects
of their project, although leeway is
given for detailed questions.
The midterm has a number of posi-
tive aspects. It informs the supervi-
sors of the progress of each group. It
is a milestone that forces the group to
have achieved some results; other-
wise, the students (being human)
might leave it to the end. Finally, the
midterm allows the course coordina-
tor to identify any personality prob-
lems within the groups. The students
also make individual in-class presen-
tations on their part of the project.
The presentations allow the course


is working on. The


coordinator to identify "coasters," students who did not con-
tribute to the project, and they give each student practice in
making individual presentations.
The final phase of the Petroleum Design I is a preliminary
design report. This brief, typed report summarizes the reser-
voir evaluation, development strategy selection, forecasting,
facilities design and costing, and preliminary economic indi-
cators. The students are also expected to produce cross-
sections, reservoir maps, and facility schematics.
Petroleum Design I By the end of Petroleum Design I,
the students are expected to have a good understanding of
their reservoir description and history and to have come up
with some promising development strategies. In Petroleum
Design II, they correct errors from Design I, simulate the
reservoir, usually on EXODUS, and simulate their facilities
on HYSYS. With the reservoir simulator, they are expected
to obtain a history match of the pool production to date and
to generate forecasts for several development strategies. They
are asked to create a PFD of the facilities, a P&ID drawing
of one piece of equipment such as a heater-treater, and to
obtain quotes for major pieces of equipment. They are also
asked to prepare a simple drilling and completion program
and estimate capital and operating costs for the project. They
then evaluate the project economics and perform some risk
and sensitivity analysis. The Design II course is intended to
duplicate as closely as possible the steps an engineer em-
ployed by an oil and gas producing company goes through to
evaluate capital projects.
The Design II course includes weekly meetings with the
supervisor, a midterm, individual presentation, and a final
report. A final oral group presentation is also required after
the winter term exams are finished. It consists of a half-hour
formal presentation followed by a fifteen-minute question
period. We describe it as a "formal" presentation because


not only are supervisors and stu-
dents present, but also other fac-
ulty members and practicing engi-
neers from industry. In fact, as
many as 300 letters go out to major
companies, inviting them to send
interested engineers to these final-
project presentations; typically, 20
to 30 practicing engineers attend.
The atmosphere is one of thesis
defense. The students all partici-
pate in the presentation and then
collectively face questions, first
from other students and guests
(industrial participants and other
faculty), and finally from the
project supervisors. Students are
graded for the final presentation
as well as the midterms and


Fall 1999


TABLE 3
Grading Scheme for Petroleum Design II

% of Final Grade
A. Design Project Report
Project Organization 5%
Process Flow Diagram (PFD) and P&ID 5%
Reservoir Maps 5%
Technical Content 25%
Calculations, diligence, and accuracy; design
methods and approach;figures and graphs;
clarity of approximations and design factors
Economics 5%
Summary, conclusions, recommendations 5%
Total Report 50%

B. Weekly Meetings 5%
C. Midterm Examination 15%
D. Classroom Presentation 10%
E. Final Oral Presentation and Project Defense 20%
Total 100%












project reports. An example of the grading
system is shown in Table 3.

OTHER CONSIDERATIONS

Use of Software A significant issue in
undergraduate education is the use of commer-
cial software, especially process and reservoir
simulation packages. Most practicing engineers
use commercial software rather than writing
their own programs or solving lengthy calcula-
tions by hand, yet it is vital to understand
enough of the underlying theory to recognize
when the simulation results are misleading and
to identify appropriate optimization strategies
to test on the simulator. As educators, we want
to avoid promoting the blind acceptance of the
results obtained from commercial software.

We avoid this potential trap by emphasizing
hand calculations in the Design I course. Ap-
plying hand calculations to a reservoir prob-
lem, for example, forces the students to think



TABLE 4
Commercial Software Used in Petroleum
Design II course


AccuMapt"]
EXODUS[91
IMEX. STARS, and GEM1"5
HYSYSI'8
FAST""'
WELLFLO"7'
PIPER" and PIPEFLO"7
PEEP"8'


well information data base
reservoir simulation
reservoir simulation
process simulation
well test analysis
wellbore hydrodynamics
pipeline hydrodynamics
petroleum economics


TABLE 5
Lecture Topics

Design II


Project Management
Geology/Geophysics
Core Analysis
Log Interpretation
Mapping and Volumetrics
PVT and Material Balance
Primary Production Forecasting
Waterflood Design
Reservoir Simulation
Block Diagrams and PFDs
Gas Treating
Process Design Calculations
Petroleum Economics


Digitizing
Coning
Drilling
Completions
Artificial Lift
PFDs and P&IDs
Separators
Compressors
Pumps
Risk and Economics


about the principles of fluid flow, thermodynamics, and material balances.
With hand calculations, it is often easier to recognize a result that violates
common sense, such as an unrealistically high injection rate for a given
permeability-pay. The hand calculations also provide a check on the simula-
tion results of the Design II course. For example, if a 30% recovery factor is
predicted by hand and a 50% recovery is predicted in a simulation, can the
simulation output be believed?

With appropriate hand calculations and common-sense checks, the stu-
dents can use the commercial software listed in Table 4. Training is provided
for AccuMap, EXODUS, and PEEP. The students usually have been ex-
posed to FAST, WELLFLO, and HYSYS in other courses. The software
training is given outside normal class time.

Since simply learning to use commercial software can be time consuming
(especially reservoir simulators), it is critical to have teaching assistants who
are well versed in the use of the software. Our teaching assistants are
graduate students currently enrolled in petroleum engineering. One challenge
facing the program is securing a stream of graduate students with suitable
backgrounds to act as design-course teaching assistants. We are attempting to
attract part-time Masters of Engineering students who work in local industry.

Use of Lectures The students entering the petroleum design course have
quite varied backgrounds. Some are in the oil and gas program, while others
are taking the petroleum minor. Some have internship or other industry
experience, while others have none. As a result, there are different gaps in
the knowledge and experience of each student. In Design I, we use the
lectures to fill these gaps, with a strong emphasis on applied engineering.
For instance, we spend several lectures on waterflood design leading to the
programming of a waterflood forecast on a spreadsheet. The program is
based on the Buckley-Leverett-Welge method.[121 Voidage replacement,
injectivity calculations, sweep efficiency estimation, and waterflood pat-
tern selection are also covered. There are also several lectures devoted
to process design. Since the necessary material is already covered in the
process design course, these lectures are held in common. A list of
lecture subjects is given in Table 5.

In Design II, the lectures are even more applied, such as artificial lift
design. Most lectures in the second term are given by industry or service


MiOierm Reporr ue NOV. Z
Midterm Oral Exam Nov. 5


Final Report Due
Dec. 8


Figure 1. GANTT chart for a Petroleum Design I project.


Chemical Engineering Education


Design I


SID PTASKNAE SSber 2October November December
ID TASKNAME 3 3 1 4 2 t3 1 4 1 2
1 Log Interpretation
Core Analysis
2 Mapping

Assign Pool Boundaries
4 Test Interpretation uAP
5 Production Plots J
6 Pool History C ,
7 Base Case i
8 Strategies Cavu.
s Reserves
10 Production Forecast
11 Facilities g
12 Economics )P ,


I












company representatives. Hence, the students can learn from
experts in a given field and develop contacts for work on the
project or in the future.
Project Management Another issue in a design course is
how much time to devote to project management. Is it appro-
priate for the students to prepare detailed schedules, critical
path analysis, etc., for their project? In our opinion, the stu-
dents have too little experience to prepare a meaningful sched-
ule at the beginning of the project. Instead, we ask them to
prepare a simple GANTT chart outlining the major tasks and
assigning duties and target dates to each group member. An
example chart is given in Figure 1. We have found that this
simple chart is sufficient to identify potential bottlenecks and
ensure a fair allocation of tasks. It also demonstrates that
unless certain tasks, such as log interpretation, are completed
early in the project, it will be nearly impossible to complete
the project on time.

SUMMARY AND FEEDBACK
The major advantages and disadvantages of the approach to
design taken at the University of Calgary are summarized in
Table 6. In general, the feedback from the students has been
very positive. Examples of anonymous student comments are
An excellent course that provides an overview of industry
tasks required for oilfield development.... Course generally
covered at a high pace.
Challenging but very interesting and makes students look
for other resources of information
Course provides opportunity to learn a lot about general
engineering practices (petroleum). Incorporates all aspects
of reservoir engineering to production engineering.
Good course to get experience of what working as a
reservoir engineer is like.
Very usefulfor "hands on" experience that will be used in
industry. Maybe a little too much work.


TABLE 6
Advantages and Disadvantages of the Petroleum Design Coua


Pros
Use of industry data
realistic design problems
students faced with real data
Team teaching
topics taught by industry experts
students interact with practicing engineers
Use offaculty supervisor
allows close supervision of each group
grading by consensus
Use of analytical methods
encourages understanding of underlying
physics
encourages "common-sense" checks
Use of software
broad application
training for work in industry


* time consuming to prepare data sets
* dependent on industry cooperation


* difficult to maintain continuity in lectures
* lectures not always delivered at optimum time

* increases teaching load of faculty


*limited application to complex situations
typically faced by design engineers


*encourages button-pushing solutions
* learning software is time intensive
* an experienced TA is essential


These comments are representative of the students' responses
to the request to "please provide general comments about the
course." Negative responses have not been withheld. In all,
13 students out of 20 responded to the request, and half of
the responses referred only to other issues, such as teaching.
The course was rated as 6.1 out of 7, compared with a
faculty average of 5.5 out of 7. The comments and ratings
indicate that students believe they have gained broad and
relevant experience.

ACKNOWLEDGMENTS
We thank Richard Baker, Steve Gordon, Linda van Gastel,
and Dave Douceur for providing data sets for design projects.
We are indebted to Michael Aikman, the first teaching assis-
tant for the design course.

REFERENCES


1. Biegler, L.T., I.E. Grossman, and A.W. Westerberg, Systematic Meth-
ods of Chemical Process Design, Prentice-Hall, New Jersey (1997)
2. Horwitz, B.A., and L.G. Nault, "Rethinking Academia; Relate to the
Real World," Chem. Eng. Progress, p. 84, October (1996)
3. Hirt, D.E., "Integrating Design Throughout the ChE Curriculum,"
Chem. Eng. Ed., 32(4), 290 (1998)
4. Rockstraw, D.A., J. Eakman, N. Nabours, and S. Bellner, "An Inte-
grated Course and Design Project in Chemical Process Design,"
Chem. Eng. Ed., 31(2), 94(1998)
5. Brennan, D.J., "Chemical Engineering Design and Undergraduate
Education," Chemica 1995, Proceedings of the 23rd Australian Chemi-
cal Engineering Conference, Adelaide, September 24-27, 2, p. 187
(1995)
6. Personal communication with Petro-Canada Oil and Gas, PanCanadian
Petroleum Ltd., Altana Exploration Co., and Epic Consulting Ser-
vices Ltd.
7. Peters, M.S., and K.D. Timmerhaus, Plant Design and Economics
for Chemical Engineers, 4th ed., McGraw-Hill, New York, NY (1990)
8. HYSYS"', Reference Manual, AEA Engineering Technology Soft-
ware, Calgary, Alberta, Canada T2E 2R2 (1999)
9. EXODUS"', Reference Manual, T.T. & Associates
Inc., CanTek Group, Calgary, Alberta, Canada T2P
3N3 (1999)
10. Svrcek, W.Y., M.F. Mohtadi, P.R. Bishnoi, and L.A.
Behie, "Undergraduate Process Design: An Open-
rses Ended Approach," ASEE Conference, Atlanta, Geor-
gia, June 16-20(1985)
11. AccuMap"', Reference Manual, EnerData Corp.,
Calgary, Alberta, Canada T2N 1X7 (1999)
12. Dake, L.P. Fundamentals of Reservoir Engineering,
Elsevier, Amsterdam (1978)


13. Bradley, H.B., ed., Petroleum Engineering Handbook,
Society of Petroleum Engineers, Richardson, TX (1992)
14. Craig, F.F., Jr., "The Reservoir Aspects of Water-
flooding," SPE Monograph 9, Henry Doherty Series,
New York, NY (1971)
15. IMEX"', STARS"', GEM"', Reference Manuals, Com-
puter Modeling Group, Calgary, Alberta, Canada T2L
2A6 (1999)
16. FAST'', PIPER"', Reference Manuals, Fekete Asso-
ciates Inc., Calgary Alberta, Canada, T2G 0M2 (1999)
17. WELLFLO'", PIPEFLO"', Reference Manuals,
Neotechnology Consultants Ltd., Calgary, Alberta,
Canada T2E 8A4 (1999)
18. PEEP"', Reference Manual, Merak Projects Ltd.,
Calgary, Alberta, Canada T2P 3R7 (1999) U


Fall 1999











laboratory


LOW-COST EXPERIMENTS IN MASS TRANSFER

Part 5. Desorption of Ammonia from a Liquid Jet


M.H.I. BAIRD, I. NIRDOSH*
McMaster University Hamilton, Ontario, Canada


he rate of gas-liquid mass transfer, absorption or
desorption, is controlled by diffusional (film) resis-
tances in the gas and liquid phases. The overall resis-
tance is the sum of the two film resistances. If one film
resistance is much larger than the other, the mass transfer
rate is controlled mainly by the larger resistance. As dis-
cussed in the standard texts, such as Geankoplis,111 the con-
trolling resistance depends on the solubility of the transfer-
ring gas in the liquid phase. For some typical solute gases
transferring between air and water at ambient conditions,
controlling resistances are

Controlling resistance Solute gases
Liquid diffusion Oxygen, carbon dioxide (sparingly soluble)
Liquid and gas diffusion Sulfur dioxide (moderately soluble)
Gas diffusion Ammonia, hydrochloric acid gas (highly
soluble)

Previous papers in this series1231 have described some simple
undergraduate-level experiments with liquid-phase control,
using oxygen or CO2 as the transferring gas.
It is also desirable to study cases in which mass transfer is
controlled by the gas phase, but as the above table indicates,
the highly water-soluble gases are hazardous substances.
Some years ago, students at McMaster University operated a
packed-absorption tower in which an ammonia/air mixture
was scrubbed with water. Much care was needed in the
control of the ammonia stream to make up the gas mixture,
and there was sometimes trouble with leaking valves on the
ammonia gas cylinder. Eventually the experiment was dis-
continued for safety reasons.
This paper describes a replacement experiment that was
recently developed in which ammonia is desorbed from an
aqueous solution into a stream of air. This is inherently safer
since the ammonia levels in the gas phase are limited by the
ammonia concentration in the aqueous feed solution. The
experiment does not require pure ammonia gas. The objec-

* Address: Lakehead University, Thunder Bay, Ontario, Canada


tive of the experiment is to measure mass transfer coeffi-
cients for the desorption of ammonia from a liquid jet, at
different liquid flow rates and for different jet lengths.
Recommended time for the experiment is two laboratory
periods of three hours.

EXPERIMENT DESCRIPTION
The schematic flow diagram is shown in Figure 1. The
main items of equipment are mounted on a vertical wooden
panel about four to six feet from floor level. The feed solu-
tion is a 1.5 mol/L standardized solution of ammonia in
water that can be made up by the laboratory technician prior
to the experiment. This concentration was chosen as a com-
promise to balance the needs for rapid rates of mass transfer
(favored by higher concentration) and safety (favored by
lower concentration). At ambient temperatures, the equilib-
rium mol fraction ammonia in the gas phase above this solu-
tion is between 2% and 3%. Accurate values are available from
the literature141 for the temperature of the experiment.
The ammonia solution is fed from an overhead reservoir
through a stainless steel needle valve and rotameter to a
desorption cell. Typically, the feed liquid flow is in the range

Malcolm Baird received his PhD in chemical
engineering from Cambridge University in 1960.
After some industrial experience and a post-
doctoral fellowship at the University of
Edinburgh, he joined the McMaster University
faculty in 1967. His research interests are liq-
uid-liquid extraction, oscillatory fluid flows, and
hydrodynamic modeling of metallurgical pro-
cn.sses. "


SInder Nlrdosh received his BSc and MSc in
chemical engineering from Panjab University
(India) and his PhD from Birmingham Univer-
sity (United Kingdom). He joined Lakehead Uni-
versity in 1981, and his research interests are
in the fields of mineral processing and electro-
chemical engineering.
Copyright ChE Division of ASEE 1999


Chemical Engineering Education











of 50 to 300 mL/min. The desorption cell consists of a
vertical 15-cm section of 5-cm internal diameter glass tub-
ing, closed at each end by rubber stoppers. The feed solution
enters the top of the cell through a glass nozzle of internal
diameter 1.4 mm, which can be made easily by a glass-
blower from standard glass tubing. The free jet of solution
falls from this nozzle to a collector tube (see Figure 1)
located at a measured distance
(L) below the nozzle. The col-
lector tube should be slightly NV(air)
larger in diameter than the jet; Air +
an internal diameter of about
2.5 mm is recommended. At
steady state, the liquid level By-pass\ 2-oy
in the collector tube should
come right up to the open end,
and there should not be any
gas entrainment. This control
can be quite easily achieved /,
by means of a manually ad-
Water Trap Acid
justable overflow leg, as ter fap bubbler
shown in Figure 1. Some lat-
eral adjustment of the posi-
tions of the jet and the collec-
tor can be made by hand, since Figure 1. Schen
the tubes are held by a rubber
stopper that has some flexibility. The variation of jet length
can be achieved by extending or retracting the jet nozzle
between experiments.
It is inevitable that some drops of solution will occasion-
ally spill over the collector tube, and for this reason a few
mL of kerosene are placed at the base of the cell to provide a
mass-transfer barrier. There is also provision to occasionally
drain off any large amount of spilled ammonia from the base
of the cell, as shown. The main liquid flow leaving the cell
still contains most of the ammonia feed, and it is collected in
a receiver for reuse. It is important to avoid the use of copper
or brass in any of the valves or lines handling ammonia
solution since these metals are slowly attacked by aqueous
ammonia; this is apparent from a blue coloration of the
solution with cuprous ammonium salts.
A continuous flow of atmospheric air is drawn through the
cell, entering from the bottom. The exit air, containing des-
orbed ammonia gas, leaves the cell from the top. During the
preliminary adjustment of the system it flows through a
bypass line to a trap, and then to a rotameter, needle valve,
and water aspirator (ejector). The air flow is adjusted to a
fixed value (typically between 1 and 5 L/min) by means of
the needle valve and rotameter. The system should be run for
three to four minutes at the adjusted liquid and gas flows, to
reach a steady state before gas analysis is begun.
The air leaving the cell contains a small amount of ammo-
nia, typically no more than 1 mol%. Analysis is carried out


natic


by a semi-continuous chemical method, by scrubbing with
dilute hydrochloric acid. Before the experiment, a standard
fritted-glass bubbling tube is filled with a known volume
(typically 100 mL) of 0.01 mol/L dilute hydrochloric acid,
with a few drops of methyl red indicator, and is connected to
the system, as shown in Figure 1. The gas analysis is begun
by turning a 2-way cock to divert the exit gas through the
bubbling tube. As the cock is
turned, a stopwatch must be
started. Because of the large
1.5 mol/L gas-liquid interfacial area pro-
NH3 soln duced at the bubbler, the ab-
sorption of the ammonia from
Solution flw the gas phase is extremely ef-
ficient and it reacts stoichio-
Adjstobe metrically with the acid. After

S Vent sufficient time has elapsed, all
I NV the acid will be consumed and
Kerosene (liq)
Serene the pH of the liquid in the bub-
bler will rise sharply, accom-
panied by a change in the me-
to solution thyl red color from pink (acid)
ir in to yellow (alkaline). The color
change occurs over a period
flow diagram. of 1-2 s, which is much smaller
than the neutralization time of
100 s. At the above endpoint, the stopwatch is stopped and
read, and the gas flow is then diverted to the bypass.
The rate of mass transfer is calculated from the moles of
acid neutralized in the bubbler, and the neutralization time
m'= VACA /tN (1)
The molar concentration of ammonia in the exit gas from the
desorption cell can be obtained from the mass transfer rate
and the gas flow rate

c2 = m' /QG (2)
At the end of each experiment, the liquid and gas flows are
shut off and the bubbler is removed for rinsing with distilled
water.

EXPERIMENTAL PLAN
A typical plan for two 3-hour laboratory periods calls for
measurement of the mass transfer coefficient at three differ-
ent jet lengths (for example, 3, 5, and 7 cm) and three or four
different flow rates within the operating range. In addition,
at least some of the experiments should be replicated with
different concentrations of acid in the bubbler. Changes in cA
would affect tN but would not be expected to affect the value
of kg obtained at the same liquid flowrate and jet length.
Because of time constraints, the jet diameter and the air
flowrate are the same in all experiments.
An average time of 15 to 20 minutes is spent on each


Fall 1999










experiment, with students working in groups of two. Al-
though the mass-transfer measurement itself takes only one
to three minutes, additional time is needed for adjustment of
the operating conditions and for achieving steady state. Also,
from time to time the ammonia-feed reservoir has to be
refilled. Goggles and gloves should be worn by the students
when they are handling the ammonia and acid solutions,
e.g., when they are recharging the bubbler. The ammonia
levels in the ambient air are low, but minor discomfort may
be experienced if there is not adequate ventilation in the
laboratory.

CALCULATION OF
MASS-TRANSFER COEFFICIENTS FROM DATA
The mass-transfer rate, m', is the product of the mass-
transfer coefficient, the interfacial area, and the concentra-
tion driving force
m'= kgA(c -c2) (3)
The terms m' and c2 have already been obtained through
Eqs. (1) and (2). The interfacial area A can be calculated
from the jet length, L, and the orifice diameter, d. For precise
work, allowance should be made for the acceleration of the
jet due to gravity. But for short jets and high velocities
(keeping in mind that this is only an undergraduate-level
experiment), the acceleration effect can be ignored. There-
fore, we use
A = tdL (4)
The equilibrium concentration of ammonia in the gas phase,
c*, can be obtained from standard sources.141 For 1.5 mol/L
ammonia in the solution, the values of c* at 200C and 25C
are, respectively, 0.837 and 1.076 mol/m3; these values are
less than 0.1% of the liquid phase concentration, illustrating
the very high solubility of ammonia. The back-concentration
term is taken as c2 (calculated from Eq. 2), based on the
assumption that the gas space within the cell is "well mixed."
This was found to give consistent results, and it is reasonable
to expect that the combined effects of gas and liquid flow
would result in a well-mixed gas phase in the cell.
Rearranging Eq. (3), the mass transfer coefficient can be
obtained from known data as

kg = m'/[A(c*-c2)] (5)

EQUATIONS FOR PREDICTION OF
MASS-TRANSFER COEFFICIENT
The conditions of the experiment do not correspond ex-
actly to any of the commonly available predictive equations
because little is known about the hydrodynamic conditions
in the gas space in the cell. It is thought that the gas is
circulating due to the action of the liquid jet and the
throughflowing stream of gas, and the flow is likely to be
weakly turbulent. There are two simple equations that can at


least provide an approximate comparison with the data.

HIGBIE PENETRATION MODEL[15
This well-known equation is based on the simple concept
of unsteady diffusion into the gas phase during the "contact
time," t, for which the liquid is exposed to the gas. In using
this equation, it is assumed that the gas film adjacent to the
liquid jet is moving down with it at the same velocity,
namely
U= Q /(7d2/4) (6)
The contact time between liquid and gas is L/U, or

T -=d2L/(4QL) (7)
According to the penetration model,

kg = 2(Dg / )0. (8)

where Dg is the molecular diffusivity of ammonia in air,
which can be estimated from the method of Fuller, et al., as
cited in Perry's Handbook.'61 Values of Dg at 200C and 25C
are, respectively, 2.36 x 10-5 and 2.43 x 10-5 m2/s. Equation
(8) can also be expressed in dimensionless form as

ShL =1.128(ReL Sc)o05 (9)
where the Sherwood and Reynolds numbers are based on jet
length. Equations (8) and (9) can only be regarded as ap-
proximate for the present case, since they assume that the
gas is moving down at the same velocity as the liquid jet; no
allowance is made for a developing boundary layer or the
effects of turbulence in the bulk gas flow.

BOUNDARY-LAYER MODELm
As an alternative to the penetration model, it could be
assumed that the air is dragged down in a developing lami-
nar boundary layer adjacent to the interface, with ammonia
diffusing through the boundary layer. For this case

ShL = 0.664 Re.5 Sc1/3 (10)
In this work, Re, is always well below the critical value of
500,000 at which there is a transition to turbulent flow in the
boundary layer. But the use of Eq. (10) is also open to
criticism since it was developed for a flat plate, whereas the
interface in this case is cylindrical. Moreover, the bulk gas
may be turbulent, which could affect the boundary layer.

RESULTS AND DISCUSSION
Figure 2 shows 12 directly measured mass-transfer coeffi-
cients from a typical student project,"8 plotted against jet
velocity on a linear scale. It can be seen that kg always
increases with the velocity and in general it decreases with
increasing jet length.
The results can be expressed in dimensionless form by


Chemical Engineering Education


330











conversion to Sherwood number,
which can then be compared with
the model Eqs. (9) and (10). The
Schmidt number is essentially con-
stant (=0.65) except for minor ef-
fects of temperature between differ-
ent experiments.

Therefore, a plot of Sherwood
number versus Reynolds number al-
lows the data to be compared with
the two model equations, as shown
in Figure 3. Both models predict that
ShL oc ReoL5, so they appear on the
log-log scale as two parallel straight
lines, which are shown dashed. The
data points fall between the two pre-
dictions; lower than the penetration
theory but higher than the boundary
layer prediction.
When students are confronted with
a case like this in which the results
do not agree very well with the "theo-
retical predictions," they are apt to
find fault with the experiment and
the accuracy of their data. But when
an analysis of measurement errors is
done, the measurement accuracy for
kg is found to be better than +10%.
Then a question for the students is:
why are there deviations of 30% or
more between the results and the
models?


1.0 1.5 2.0 2.5
Jet velocity, U, m/s

Figure 2. Effect of jet velocity and jet
length on mass transfer coefficients.


I.
80 -
a

40- 0 o




i f I
C 0

f 20-

I I


1000 2000 5000
Reynolds number, ReL


The students are encouraged to dis- Figure 3. Dimens
showing comparison
cuss ways in which their actual ex- Symbols are the s
periment departs from the sets of
idealizing assumptions built into the
two simple theoretical models. The curvature of the jet sur-
face and the complex and probably turbulent gas-flow pat-
terns in the cell have already been mentioned. If the theoreti-
cal treatment could be "fine tuned" to account for these
effects, better agreement could be expected, but that would
take us into the realm of graduate research.

This low-cost experiment can be set up with normal labo-
ratory glassware and fittings. It provides students with a
reasonably accurate method of measuring gas-film controlled
mass-transfer coefficients that can then be compared with
simple (though approximate) theoretical predictions.

ACKNOWLEDGMENTS

The apparatus was built with financial support from the
Department of Chemical Engineering at McMaster Univer-
sity. The authors are grateful to Ms. J. Derkach and Mr. Paul


lopoo


ionless plot of data
with Eqs. (9) and (10).
ame as in Figure 2.


REFERENCES
1. Geankoplis, C.J., Transport Processes and Unit Operations,
3rd ed., Prentice Hall, Englewood Cliffs, NJ, p. 600 (1993)
2. Nirdosh, I., and M.H.I. Baird, "Low-Cost Experiments in
Mass Transfer. Part 1.," Chem. Eng. Ed., 30, 50 (1996)
3. Nirdosh, I., L.J. Garred, and M.H.I Baird, "Low-Cost Experi-
ments in Mass Transfer, Part 3. Mass Transfer in a Bubble
Column," Chem. Eng. Ed., 32, 138 (1998)
4. Perry, R.H. and D. Green, eds., Perry's Chemical Engineers'
Handbook, 6th edn., McGraw-Hill, New York, NY, pp. 3-101
(1984)
5. Geankoplis, C.J., Transport Processes and Unit Operations,
3rd ed., Prentice Hall, Englewood Cliffs, NJ, p. 478 (1993)
6. Perry, R.H., and D. Green, eds., Perry's Chemical Engineers'
Handbook, 6th edn., McGraw-Hill, New York, NY, pp. 3-285
(1984)
7. Geankoplis, C.J., Transport Processes and Unit Operations,
3rd ed., Prentice Hall, Englewood Cliffs, NJ, p. 477 (1993)
8. Rajkovic, A., "Ammonia Desorption from a Jet," McMaster
University Chemical Engineering Report, March 19, (1998)
N


Fall 1999


Gatt, who assembled the apparatus and
mounted it on a panel. In addition, the
authors are grateful to the Natural Sci-
ences and Engineering Research Coun-
cil of Canada for providing financial
resources for the preparation of this pa-
per.

NOMENCLATURE
A interfacial area, m2
cA initial concentration of acid in
bubbler, mol/m3
c, concentration of ammonia in exit
gas, mol/m3
c* equilibrium concentration of
ammonia in gas, mol/m3
D molecular diffusion coefficient of
g
ammonia in air, m2/s
d jet diameter, m
k mass transfer coefficient, m/s
g
L jet length, m
m' mass transfer rate, mol/s
QG air flow rate, m3/s
QL water flow rate, m'/s
ReL Reynolds number, pUL / .t
Sc Schmidt number, t /(pDg)
ShL Sherwood number, k L/D
t, time to neutralize acid in bubbler, s
U jet velocity, m/s
VA volume of acid in bubbler, m3
Greek Symbols
gl viscosity of air, Pa.s
p density of air, kg/m3
t contact time, s











classroom


Activities to Enhance

UNDERSTANDING OF THE MOLE

AND ITS USE IN ChE



DUNCAN M. FRASER, JENNIFER M. CASE
University of Cape Town Rondebosch, 7701 South Africa


Moles are a fundamental unit of measure in chemi-
cal engineering. Our students learn about moles
(in the form of gmol) in chemistry, both at school
and during their first year at university. In chemical engi-
neering, we introduce them to the new units of kmol and
Ibmol, and the problems that arise highlight a general lack of
understanding of the mole concept.
We have been aware for some time that our students have
difficulty with moles, and this led us to tackle student under-
standing of moles as a research project in which we first
quantified the nature and extent of the misunderstanding and
then set out to design and implement a set of activities to
promote conceptual change in this area. The intervention
also dealt with a number of other concepts related to the
mole. Following implementation of the intervention, stu-
dents were again tested to measure the extent of improve-
ment in their understanding.

Duncan Fraser holds degrees of BSc and
PhD, both from the University of Cape Town,
where he has been lecturing since 1979. He
has taught a wide range of courses, from first
year to fourth year, including mass and en-
ergy balances, thermodynamics, transport
phenomena, solid-fluid operations, optimiza-
tion, process control, and design. His pri-
mary research interests are in engineering
education and process synthesis.


Jennifer Case obtained her BSc (Hons) de-
gree in Chemistry from the University of
Stellenbosch, after which she taught for a few
years in a high school She became interested
in the field of educational research after doing
an MEd degree in Science Education at the
University of Leeds, and she currently serves
as the Educational Development Officer in the
Department of Chemical Engineering at the
University of Cape Town.


All of this took place in the context of a new course for
freshman chemical engineering students in which they are
introduced to the basic concepts in chemical engineering as
well as helped in developing certain key skills for the subse-
quent study of chemical engineering.'l One of the skills
developed is unit conversion, and the different mole units
are introduced here. A central element of the course is intro-
ducing students to unfamiliar concepts through the use of
familiar objects.
The full details of this research project are reported else-
where.121 The main objective of this paper is to present an
overview of the test (used to determine understanding) and
the intervention activities, together with evidence for their
effectiveness in dealing with the misconceptions, with the
hope that other chemical engineering educators would be
encouraged to try them out or to use them in a modified
form.

TESTING FOR UNDERSTANDING
Group interviews were used to explore possible miscon-
ceptions that students might hold about moles. Analysis of
these transcripts identified three common misconceptions:
1. The amounts kmol, lbmol, and gmol are seen as masses.
2. The amounts kmol, Ibmol, and gmol are all the same,
because they are all moles.
3. The volume of a gas is not seen as proportional to its amount.
In order to be able to measure the extent to which these
misconceptions were held in the class, a conceptual test was
developed, based on the above research findings. For ex-
ample, Question 1.2 tested misconception #1:

1.2 60 lbmol of N2 weighs 60 lb. True / False?


Copyright ChE Division of ASEE 1999


Chemical Engineering Education











The main objective of this paper is to present an overview of the test (used to determine understanding)
and the intervention activities, together with evidence for their effectiveness in dealing with the
misconceptions, with the hope that other chemical engineering educators would be
encouraged to try them out or to use them in a modified form.


Question 2.1 (in multiple choice format) is typical of a
number of questions that probed misconception #2:


2.1 Consider the following
P Q R
1 kmol of CO, 1 Ibmol of CO, 1 gmol of CO2

Which one of the following statements is true?
a) P, Q, and R all have the same number of molecules.
b) P and R have the same number of molecules.
c) P and Q have the same number of molecules.
d) They all have different numbers of molecules.
e) None of the above statements are true.


Question 3.1 tested misconception #3:


3.1 Consider the following 50 m3 vessels, each contain-
ing gas with the given composition:
Vessel A B
Volume 50 m3 50 m3
Composition 25% CO, 100% CO,
(by volume) 25% CH4
50% H2
A and B are at the same temperature and pressure.
Which one of the following statements is true?
a) A contains more molecules than B.
b) B contains more molecules than A.
c) A and B contain the same number of molecules.
d) None of the above statements is true.

This test was specifically designed so that no numerical
calculations were required in answering the questions (as
can be seen in the sample questions above). Despite this, it
was interesting to observe during the administration of the
test that many of the students tried to use numerical calcula-
tions to find the answers. Even though calculators were not
permitted, many students covered their question papers with
calculations.
The results of the test confirmed that misconceptions were
widespread in the class: 38% of the students showed evi-
dence of misconception #1 (tested by one question); 28%
showed misconception #2 (this was averaged over five ques-


Fall 1999


tions); and 27% showed misconception #3 (averaged over
two questions).'21 When the same test was administered again
after the intervention activities (described in the next sec-
tion), it revealed a significant increase in understanding.

INTERVENTION ACTIVITIES
We designed a series of intervention activities to address
the misconceptions that had been identified during the inter-
views and the conceptual test. At the same time, we took the
opportunity to deal with other related questions, albeit in a
less focused manner.
The major objective in designing these activities was to
give students a concrete visual or experiential point of refer-
ence for their understanding. This approach was based on
recommendations in the literature concerning the general
use of tangible objects in helping learners develop appropri-
ate mental representations of chemical systems[3-51 as well as
more specific recommendations regarding their use in devel-
oping the mole concept.6'71 Where it was not possible to use
concrete objects, we used thought experiments instead.
The activities were designed to follow one another. Stu-
dents performed them in groups of three and were encour-
aged to discuss their findings with one another and with the
tutors. Multiple sets of apparatus were available so that five
groups could perform them simultaneously. A class of ninety
students could then be handled in six batches over the course
of one afternoon. The activities presented here are a refine-
ment of the original set of five activities described by Case
and Fraser.121
Activity #1
The purpose of this activity is to help students see the
difference between the different kinds of moles they will
need to work with as chemical engineers (gmol, lbmol, and
kmol). They measure out 1 gmol, 1 lbmol, and 1 kmol of
water, using a scale, and then are asked a series of questions
to help consolidate what they have observed. The activity
ends with an inspection of a display of bottles, each contain-
ing 1 gmol of a different substance, to provoke thinking
about moles, molar mass, density, form, etc.
Activity #2
This activity is aimed at helping students make sense of
gas volumes and mixtures of gases. The first task involves a
box containing a mixture of squash balls and ping-pong
balls, which have approximately the same diameter but sig-
nificantly different masses. This provides an analogy for a
mixture of different gases, such as oxygen and hydrogen,

333











that occupy the same volume but have different masses.
The second task helps them visualize the volume occupied
by 1 gmol of any gas at STP using a 22.4-litre Perspex box.
They are also asked to calculate the masses of two different
gases that would fill this box at STP. This is followed by a
third task in which they calculate the mass of air occupying
the room where they are working and then are asked what
would happen to the mass of air in the room if its composi-
tion were different.

Activity #3
This activity is a thought experiment in which the students
are asked, first, to calculate the kinetic energy of 1 kmol of
each of three different gases, using their molar masses and
average velocities. This leads to a discussion of why dif-
ferent gases all occupy the same volume at STP, using
the assumption that this is related to their having the
same kinetic energy.
The second task here involves determining the volume
occupied by the actual molecules (from their molecular di-
ameter) and hence the fractions of both water vapor and
liquid water that are empty space. This is to help clarify the
difference between liquids and gases.

Activity #4
The final activity simulates chemical reactions using nuts
and bolts. The concept of moles is further reinforced by
getting students to weigh out a large number of each of the
reactantss" on the basis of an average mass per nut or bolt (in
the same way that coins are "counted" by weight at a bank).
One bolt is "reacted" first with one nut, and then with two
nuts. The difference between
reacting numbers of each "re-
actant" and masses of each


"reactant" is emphasized by
the last two tasks in which
they weigh out equal masses
of nuts and bolts and then
"react" them.


EFFECT OF
INTERVENTION
When the students were
tested again to gauge if their
understanding had improved,
there was a significant in-
crease in their level of under-
standing. Figure 1 compares
the pre- and post-test scores
of all the students. It shows
that those who could improve
the most had done so, and
that the average improvement
is half the maximum possible.


This figure also shows that there was no difference between
the students who were interviewed and those who were not,
which indicates that it was the intervention rather than being
sensitized to the issues, that made the difference.
Table 1 gives a complete question-by-question analysis of
the pre- and post-test results, arranged according to whether
the questions covered the misconceptions being directly tack-
led or not. The shift of students from wrong to right answers,


Course tutor, holding the "mole" box.


Figure 1.


Chemical Engineering Education


20 ------- --------------
18
16
14
012
S+ Interviewed
S10 A A Not Interviewed
8 "- .. -- -- MaximumChange
S...... Average Change
6 '' .
4
2
0
a a I
-2
5 10 15 20 25
Pre-test Score












as well as from right to wrong, is also shown. The shift from
right to wrong is taken as a measure of the randomness of
answering; this was consistent across the different groups of
questions and averaged 6.4% over all the questions.
Table 1 shows clearly that the intervention had a much
greater impact on the three misconceptions directly tackled
(net shift from wrong to right of 17.1) than on the other
issues tackled (net shift of 5.8). This is to be expected, given
the clearer focus on them in the design of the intervention.
When the data in Table 1 is analyzed according to the


TABLE 1
Question-by-Question Analysis of Results
("W" to "R" means Wrong to Right: "R" to "W" means Right to Wrong)


Pre- Post-
Test Test Shift
Misc. %cor. %cor. W to R R to W Net


Misconceptions Tackled in Intervention

1.2 Ibmol 1 64% 76% 19 9 10
1.5 kmol/gmol 2 76% 88% 16 7 9
1.9 Avogadro's number 2 51% 90% 34 3 31
1.10 kmol/gmol gas 2 69% 80% 16 7 9
2.1 moles and molecules (same) 2 65% 91% 22 1 21
2.6 Avogadro's number 2 44% 85% 36 3 33
2.8 moles and gas volume 2 56% 83% 26 5 21
3.1 diff. gases at same conditions 3 63% 71% 15 8 7
3.6 gas mixture composition 3 59% 75% 20 7 13
Average 61% 82% 22.7 5.6 17.1
Other Issues Tackled in Intervention

1.1 kmol 61% 98% 31 2 29
1.3 m mass -kmol 68% 53% 10 22 -12
1.8 molecule and components 68% 75% 10 4 6
2.2 moles and mass (same) 89% 93% 8 5 3
2.3 moles and molecules (diff) 76% 84% 9 3 6
2.4 moles and mass (diff) 83% 85% 12 10 2
2.5 does P affect Ibmol 63% 73% 16 8 8
2.7 kmol of diff. substances 66% 68% 12 11 1
2.9 reaction stoichiometry 93% 91% 5 6 -1
3.2 mass of gas mixture/pure gas 61% 78% 15 2 13
3.3 gas mixture composition 70% 61% 5 12 -7
3.4 gas mixture composition 56% 75% 20 5 15
3.5 pure gas cf mixture 74% 90% 18 5 13
Average 71% 79% 13.2 7.3 5.8
Not tackled in Intervention
1.6 unit conv 98% 93% 1 5 -4
1.7 unit conv 75% 83% 10 4 6
Average 86% 88% 5.5 4.5 1.0
OverallAverage 69% 81% 16.1 6.4 9.7


Error in Pre-Test
1.4 m mass lb mol


46% 98% 42


etI m Topic


three misconceptions (see Case and Fraser'21 for details of
this), misconception #1 dropped from 38% to 22%, miscon-
ception #2 from 28% to 9%, and misconception #3 from
27% to 22%. The first two changes (16% and 19%) are
significant compared to the randomness of answering (6%),
whereas the third one is not (5%). This means that mis-
conceptions #1 and #2 showed significant increases in
understanding, whereas misconception #3 did not. This
points to the effectiveness of activity #1 in addressing
misconceptions #1 and #2.
Perhaps even more important than this analysis was feed-
back over the past three years from those who teach the
subsequent mass and energy balance course. They have noted
a significant decrease in problems concerning moles.

CONCLUSIONS
What surprised and encouraged us was how enthusiasti-
cally all the students engaged in the activities-even the
more advanced students, who we thought might find them
trivial or boring. It appeared that none of the students had
encountered similar activities at school, indicating that their
previous experience in learning chemistry had been quite
deficient in the use of tangible objects.
Why not try out the mole test on your students? You might
be interested in the results. You may also find something in
the mole activities that would be useful to try in your class,
or use them as a springboard for developing other activities
(we found developing them to be an exciting and creative
challenge). Full copies of both the conceptual test and the
intervention activities may be obtained by contacting the
first author at
dmf@chemeng.uct.ac.za

REFERENCES
1. Fraser, D.M., "Introducing Students to Basic ChE Con-
cepts: Four Simple Experiments," Chem. Eng. Ed., 33(3),
190 (1999)
2. Case, J.M., and D.M. Fraser, "An Investigation into Chemi-
cal Engineering Students' Understanding of Moles and the
Use of Concrete Activities to Promote Conceptual Change,"
International Journal of Science Education, in press
3. Lythcott, J., "Problem Solving and Requisite Knowledge of
Chemistry," J. of Chem. Ed., 67(3), 248 (1990)
4. Raghavan, K., and R. Glaser, "Model-Based Analysis and
Reasoning in Science: The MARS Curriculum," Sci. Ed.,
79(1), 37 (1995)
5. Garnett, P., P. Garnett, and M. Hackling, "Students' Alter-
native Conceptions in Chemistry: A Review of Research and
Implications for Teaching and Learning," Studies in Sci.
Ed., 25, 69 (1995)
6. Spargo, P., "Teaching the Mole Concept," Higher Education
Diploma course notes, School of Education, University of
Cape Town (1987)
7. Staver, J.R., and A.T. Lumpe, "Two Investigations of Stu-
dents' Understanding of the Mole Concept and Its Use in
Problem Solving," J. of Res. in Sci. Teaching, 32(2), 177
(1995) U


Fall 1999


"""' '"""













SI* N *D *E X


Graduate Education Advertisements


Akron, University of.............................................. 338
Alabama, University of ......................................... 339
Alabama, Huntsville, University of........................ 340
Alberta, University of ........................ 341
Arizona, University of ............................................. 342
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Auburn University ................................................ 344
Brigham Young University ................................... 441
British Columbia, University of ............................ 441
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Engineering Research Center for Particle Science.. 444
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Louisville Speed Scientific School, University of .. 447
Maine, University of............................................... 385


Chemical Engineering Education













Manhattan College.................................................. 386
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Queensland, University of ..................................... 415
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Rhode Island, University of..................................... 450
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Singapore, The National University of.................. 420
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Widener University ................................................. 455
Wisconsin, University of ........................................ 437
Worcester Polytechnic Institute............................. 438
Wyoming, University of ........................................ 439
Yale University ..................................................... 440


Fall 1999












Graduate Education in Chemical Engineering

Teaching and research assistantships as well as
industrially sponsored fellowships available
up to $17,000.

In addition to stipends,
tuition and fees are waived.

PhD students may get
some incentive scholarships.

The deadline for assistantship applications is March 15th.


G. G. CHASE
Multiphase Processes, Fluid Flow, Interfacial
Phenomena, Filtration, Coalescence





H. M. CHEUNG
Nanocomposite Materials, Sonochemical
Processing, Polymerization in Nanostructured
Fluids, Supercritical Fluid Processing





S. C. CHUANG
Catalysis, Reaction Engineering, Environmen-
tally Benign Synthesis


J. R. ELLIOTT
Molecular Simulation, Phase Behavior,
Physical Properties, Process Modeling


E. A. EVANS
Materials Processing and CVD Modeling







L. K. JU
Biochemical Engineering, Environmental







S. T. LOPINA
BioMaterial Engineering and Polymer
Engineering


H. C. QAMMAR
Nonlinear Control, Chaotic Processes


For Additional Information, Write
Chairman, Graduate Committee
Department of Chemical Engineering The University of Akron Akron, OH 44325-3906
Phone (330) 972-7250 Fax (330) 972-5856 www.ecgf.uakron.edu/~chem


Chemical Engineering Education









Chemical Engineering

at the


University



of


Alabama



A dedicated faculty with state-of-the-art facilities
offer research programs leading to Master of
Science and Doctor of Philosophy degrees.


Research Interests:


Biomass Conversion, Catalysis and Reactor
Design, Controlled Release, Energy Conversion
Processes, Environmental Studies, Fuel Cells,
Hydrodynamic Stability, Magnetic Storage Media,
Mass Transfer, Metal Casting, Microelectronic
Materials, Microencapsulation, Polymer Rheology,
Process Dynamics and Control, Reservoir
Modeling, Suspension and Slurry Rheology,
Thermodynamics, Transport Process Modeling


For Information Contact:
Director of Graduate Studies
Department of Chemical Engineering
The University of Alabama
Box 870203
Tuscaloosa, AL 35487-0203 An
Phone: (205) 348-6450


equal employment/equal educational
opportunity institution.


Fall 1999


Faculty
G.C. April, Ph.D. (Louisiana State)
D. W. Arnold, Ph.D. (Purdue)
C. S. Brazel, Ph.D. (Purdue)
E. S. Carlson, Ph.D. (Wyoming)
P. E. Clark, Ph.D. (Oklahoma State)
W. C. Clements, Jr., Ph.D. (Vanderbilt)
W. S. Epling, Ph.D. (Florida)
R. A. Griffin, Ph.D. (Utah State)
D. T. Johnson, Ph.D. (Florida)
P. W. Johnson, Ph.D. (New Mexico Tech.)
T. M. Klein, Ph.D. (NC State)
A. M. Lane, Ph.D. (Massachusetts)
M. D. McKinley, Ph.D. (Florida)
R. G. Reddy, Ph.D. (Utah)
L. Y. Sadler III, Ph.D. (Alabama)
al V. N. Schrodt, Ph.D. (Penn. State)
J. M. Wiest, Ph.D. (Wisconsin)
339







CHEMICAL &


MATERIALS ENGINEERING


The Department of Chemical and
Materials Engineering at The University of
Alabama in Huntsville offers you the
opportunity for a solid and rewarding
graduate career that will lead to further
success at the forefront of academia and
industry.
We will provide graduate programs
that educate and train students in
advanced areas of chemical engineering,
materials science and engineering, and
biotechnology. Options for an M.S. and
Ph.D. degree in Engineering or Materials
Science are available.
Our faculty are dedicated to interna-
tional leadership in research. Projects are
ongoing in Mass Transfer, Fluid
Mechanics, Combustion, Bioseparations,
Biomaterials, Microgravity Materials
Processing, and Adhesion. Collaborations
have been established with nearby
NASA/Marshall Space Flight Center as
well as leading edge biotechnology and
engineering companies.
We are also dedicated to innovation in
teaching. Our classes incorporate
advances in computational methods and
multi-media presentations.



Department of Chemical Engineering
The University of Alabama in Huntsville
130 Engineering Building
Huntsville, AL 35899


FACULTY R: RESEARCH AREAS

Ram6n L. Cerro Ph.D. (UC-Davis)
Professor and Chair
Capillary hydrodynamics, multiphase flows, enhanced heat
transfer surfaces.
(256) 890-7313, rlc@che.uah.edu

Chien P. Chen Ph.D. (Michigan State)
Professor
Multiphase flows, spray combustion, turbulence modeling, numerical
methods in fluids and heat transfer.
(256) 890-6194, cchen@che.uah.edu

Krishnan K. Chittur Ph.D. (Rice)
Professor
Protein Adsorption to Biomaterials, FTR/ATR at solid-liquid interfaces,
biosensing.
(256) 890-6850, kchittur@che.uah.edu

Douglas G. Hayes Ph.D. (Michigan)
Assistant Professor
Enzyme reactions in nonaqueous media, separations involving
biomolecules, lipids and surfactants, surfactant-based collidal aggregates.
(256) 890-6874, dhayes@che.uah.edu

James E. Smith Jr. Ph.D. (South Carolina)
Professor
Kinetics and catalysis, powdered materials processing, combustion
diagnostics and fluids visualization using optical methods.
(256) 890-6439, jesmith@che.uah.edu

Jeffrey J. Weimer Ph.D. (MIT)
Associate Professor, Joint Appointment in Chemistry
Adhesion, biomaterials surface properties, thin film growth, surface
spectroscopies, scanning probe microscopies.
(256) 890-6954, jjweimer@matsci.uah.edu







UAH.
The University of Alabama In Huntsville
An Affirmative Action/Equal Opportunity Institution
Web page: http://chemeng.uah.edu
Ph: 256.890.6810 FAX: 256.890.6839


h~rlmlsli~PllON










































The University of Alberta is well
known for its commitment to excel-
lence in teaching and research. The
Department of Chemical and Materi-
als Engineering has 34 professors and
over 100 graduate students. Degrees
are offered at the M.Sc. and Ph.D.
levels in Chemical Engineering, Ma-
terials Engineering, and Process
Control. All full-time graduate stu-
dents in the research programs re-
ceive a stipend to cover living ex-
penses and tuition.



For further information, contact
Graduate Program Officer WCM
Department of Chemical and Materials Engineering
University ofAlberta
Edmonton, Alberta, Canada T6G 2G6

PHONE (780) 492-5805 FAX (780) 492-2881
e-mail: chemical.engineering@ualberta.ca
web: www.ualberta.ca/chemeng


CHEMICAL ENGINEERING FACULTY

P. CHOI, Ph.D. (University of Waterloo)
Statistical Mechanics of Polymers Polymer Solutions and Blends
K. T. CHUANG, Ph.D. (University of Alberta)
Mass Transfer Catalysis Separation Processes Pollution Control
I. G. DALLA LANA, Ph.D. (Univ. of Minnesota) EMERITUS
Chemical Reaction Engineering Heterogeneous Catalysis
J.A.W. ELLIOTT, Ph.D. (University of Toronto)
Thermodynamics Statistical Thermodynamics Interfacial Phenomena
D. G. FISHER, Ph.D. (University of Michigan) EMERITUS
Process Dynamics and Control Real-Time Computer Applications
J.F. FORBES, Ph.D. (McMaster University)
Real-Time Optimization Control of Sheet Forming Processes
M. R. GRAY, Ph.D. (California Inst. of Tech.) DEAN OF GRADUATE STUDIES
Bioreactors Chemical Kinetics Bitumen Processing
R. E. HAYES, Ph.D. (University of Bath)
Numerical Analysis Reactor Modeling Computational Fluid Dynamics
B. HUANG, Ph.D. (University of Alberta)
Controller Performance Assessment Multivariable Control Statistics
S. M. KRESTA, Ph.D. (McMaster University)
Turbulent & Transitional Flows Multiphase Flows CFD
S. LIU, Ph.D. (University of Alberta)
Fluid-Particle Dynamics Transport Phenomena Mass Transfer
D. T. LYNCH, Ph.D. (University of Alberta) DEAN OF ENGINEERING
Catalysis Kinetic Modeling Numerical Methods Polymerization
J. H. MASLIYAH, Ph.D. (University of British Columbia)
Transport Phenomena Colloids Particle-Fluid Dynamics Oil Sands
A. E. MATHER, Ph.D. (University of Michigan)
Phase Equilibria Fluid Properties at High Pressures Thennodynamics
W. C. MCCAFFREY, Ph.D. (McGill University)
Reaction Kinetics Heavy Oil Upgrading Polymer Recycling Biotechnology
P. A. J. MEES, Ph.D. (University of Alberta)
Computational Fluid Dynamics Transport Phenomena Pulp and Paper
K. NANDAKUMAR, Ph.D. (Princeton University)
Transport Phenomena Distillation Computational Fluid Dynamics
F. D. OTTO, Ph.D. (University of Michigan) EMERITIS
Mass Transfer Gas-Liquid Reactions Separation Processes
M. RAO, Ph.D. (Rutgers University)
Al Intelligent Control Process Control
S. L. SHAH, Ph.D. (University of Alberta)
Computer Process Control System Identification Adaptive Control
S. E. WANKE, Ph.D. (University of California, Davis) CHAIR
Heterogeneous Catalysis Kinetics Polymerization
M. C. WILLIAMS, Ph.D. (University of Wisconsin)
Rheology Polymer Characterization Polymer Processing
Z. XU, Ph.D. (Virginia Polytechnic Institute and State University)
Surface Science & Engineering Mineral Processing Waste Management


Fall 1999











FACULTY/ RESEARCH INTERESTS I


ROBERT ARNOLD, Professor (Caltech)
Microbiological Hazardous Waste Treatment, Metals Speciation and Toxicity
PAUL BLOWERS, Assistant Professor (Illinois, Urbana-Champaign)
Chemical Kinetics, Catalysis, Surface Phenomena
JAMES BAYGENTS, Associate Professor (Princeton)
Fluid Mechanics, Transport and Colloidal Phenomena, Bioseparations,
Electrokinetics


WENDELL ELA, Assistant Professor (Stanford)
Particle-Particle Interactions, Environmental Chemistry
JAMES FARRELL, Assistant Professor (Stanford)
Sorption/desorption of Organics in Soils
ROBERTO GUZMAN, Associate Professor (North Carolina State)
Protein Separation, Affinity Methods
ANTHONY MUSCAT, Assistant Professor (Stanford)
Kinetics, Surface Chemistry, Surface Engineering, Semiconductor Processih
Microcontamination
KIMBERLY OGDEN, Associate Professor (Colorado)
Bioreactors, Bioremediation, Organics Removal from Soils
THOMAS W. PETERSON, Professor and Dean (CalTech)
Aerosols, Hazardous Waste Incineration, Microcontamination
ARA PHILIPOSSIAN, Adjunct Associate Professor (Tufts)
Chemical/Mechanical Polishing, Semiconductor Processing
JERKER PORATH, Research Professor (Uppsala)
Separation Science
EDUARDO SAEZ, Associate Professor (UC, Davis)
Rheology, Polymer Flows, Multiphase Reactors
FARHANG SHADMAN, Professor (Berkeley)
Reaction Engineering, Kinetics, Catalysis, Reactive Membranes,
Microcontamination
RAYMOND A. SIERKA, Professor Emeritus (Oklahoma)
Adsorption, Oxidation, Membranes, Solar Catalyzed Detox Reactions
JOST 0. L. WENDT, Professor and Head (Johns Hopkins)
Combustion-Generated Air Pollution, Incineration, Waste
Management
DON H. WHITE, Professor Emeritus (Iowa State) 45(
Polymers, Microbial and Enzymatic Processes
DAVID WOLF, Visiting Professor (Technion)
Fermentation, Mixing, Energy, Biomass Conversion

For further information, write to

Chairman,
Graduate Study Committee
Department of Chemical and
Environmental Engineering
University of Arizona
Tucson, Arizona 85721
The University of Arizona is an equal
opportunity educational institution/equal
opportunity employer.
Women and minorities are encouraged
to apply.


CHEMICAL AND


ENVIRONMENTAL


ENGINEERING


at


THE


UNIVERSE


OF

ARIZONA


The Chemical and Environmental Engineering Department
at the University of Arizona offers a wide range of research
opportunities in all major areas of chemical engineering and
environmental engineering, and graduate courses are offered in
most of the research areas listed here. The department offers a fully
accredited undergraduate degree as well as MS and PhD graduate
degrees. Strong interdisciplinary programs exist in bioprocessing
and bioseparations, microcontamination in electronics manu-
facture, and environmental process modification.
Financial support is available through fellowships, government
and industrial grants and contracts, teaching and
research assistantships.
Tucson has an excellent climate and many
recreational opportunities. It is a growing modern city of
,000 that retains much of the old Southwestern atmosphere.


Chemical Engineering Education











CHEMICAL, BIO, AND MATERIALS ENGINEERING AT


ARIZONA


STATE


UNIVERSITY


3 0 '
Beaudoin, Stephen P., Ph.D., North Carolina State
University Transport Phenomena and Surface Science 0
concerning Pollution Prevention, Waste Minimization, and ',
Pollution Remediation *
Beckman, James R., Ph.D., University of Arizona -Crystalli- *
zation and Solar Cooling
Berman, Neil S., Ph.D., University of Texas, Austin Fluid
Dynamics and Air Pollution
Burrows, Veronica A., Ph.D., Princeton University Surface
Science, Semiconductor Processing
Garcia, Antonio A., Ph.D., U.C., Berkeley Acid-Base Interac-
tions, Biochemical Separation, Colloid Chemistry
Raupp, Gregory B., Ph.D., University of Wisconsin Semiconductor
Materials Processing, Surface Science, Catalysis
Razatos, Anna, Ph.D., University of Texas, Austin Biotechnology
Rivera, Daniel, Ph.D., Cal Tech Process Control and Design
Sater, Vernon E., Ph.D., Illinois Institute of Tech
Torrest, Robert S., Ph.D., University of Minnesota Multiphase Flow, Filtration, Flow
in Porous Media, Pollution Control


0 0 0 0
0 ,o C4IMICAL #I,4" 0

0 ", 0 0


81:o si*e' 0


1 40 co0 r 0


CR 06
~aapu


NARY

40

I


u +
o o


4.


S* ,
-b 0

0 0 4
*qo O .

4"



Graduate

Research in a

High Technology

Environment


Guilbeau, Eric J., Ph.D., Louisiana Tech University Biosensors, Physiological Systems, Biomaterials
He, Jiping, Ph.D., University of Maryland Biomechanics, Robotics, Computational Neuroscience, Optimal Control, System Dynamics and Control
Kipke, Daryl R., Ph.D., University of Michigan Computation Neuroscience Machine Vision, Speech Recognition, Robotics Neural Networks
Massia, Stephen, Ph.D., University of Texas Bio materials Molecular and Cellular Engineering
Panitch, Alyssa, Ph.D., University of Massachusetts Tissue Engineering
Pizziconi, Vincent B., Ph.D. Arizona State University- Artificial Organs, Biomaterials, Bioseparations
Sweeney, James D., Ph.D., Case-Western Reserve University- Rehab Engineering, Applied Neural Control
Towe, Bruce C., Ph.D., Pennsylvania State University- Bioelectric Phenomena, Biosensors, Biomedical Imaging
Yamaguchi, Gary T., Ph.D., Stanford University Biomechanics, Rehab Engineering, Computer-Aided Surgery




Adams, James, Ph.D., University of Wisconsin, Madison Atomistic Simulation of Metallic Surfaces Grain Boundaries Automobile Catalysts *
Polymer-Metal Adhesion
Alford, Terry L., Ph.D., Cornell University Electronic Materials Physical Metallurgy Electronic Thin Films Surface/Thin Film
Dey, Sandwip K., Ph.D., NYSC of Ceramics, Alfred University Ceramics, Sol-Gel Processing
Krause, Stephen L., Ph.D., University of Michigan Ordered Polymers, Electronic Materials, Electron X-ray Diffraction, Electron Microscopy
Mahajan, Subhash, Ph.D., University of Michigan Semiconductor Defects. Structural Materials Deformation
Mayer, James, Ph.D., Purdue University -Thin Film Processing Ion Bean Modification of Materials







Fall 1999 343




























Faculty
Robert P. Chambers University of California, Berkeley
Harry T. Cullinan Carnegie Mellon University
Christine W. Curtis Florida State University
Steve R. Duke University of Illinois
Mahmoud El-Halwagi University of California, Los Angeles
James A. Guin University of Texas, Austin
Ram B. Gupta University of Texas, Austin
Gopal A. Krishnagopalan University of Maine
Jay H. Lee California Institute of Technology
Y. Y. Lee Iowa State University
Glennon Maples Oklahoma State University
Ronald D. Neuman The Institute of Paper Chemistry
Stephen A. Perusich University of Illinois
Timothy D. Placek University of Kentucky
Christopher B. Roberts University of Notre Dame
.. R. Tarrer Pildat I', nr\
Bruce J. Talarchuk in ,uitr' r t \,t i\rll'',i


Research Areas

* Biochemical Engineering Biotechnology
Pulp and Paper Process Control
Catalysis and Reaction Engineering
Computer Aided Process Synthesis,
Optimization and Design
Environmental Chemical Engineering
Pollution Prevention Recycling
Materials Polymers Surface Science
Colloid and Interfacial Phenomena
Thermodynamics Supercritical Fluids
* Separation Electrochemical Engineering
* Fluid Dynamics and Transport Phenomena
Fuels and Energy


Deparnment o. iaal Egineeng
Auir -Unt ve rsiy, A L'36849-
mo- i (334):f4-47
S--Fax 334)-44-2063
.4- E.


Financial as,'slance is available to qualified applicants.


Auburn Uniaverity is an Equal 'Opportnity Edrational-lHnslumon


?












DEPARTMENT OF CHEMICAL

AND PETROLEUM ENGINEERING


FACULTY

R. G. Moore, Head (Alberta)
J. Azaiez (Stanford)
H. Baheri (Saskatchewan)
L. A. Behie (Western Ontario)
C. Bellehumeur (McMaster)
P. R. Bishnoi (Alberta)
R. A. Heidemann (Washington U.)
C. Hyndman (Ecole Polytechnique)
A. A. Jeje (MIT)
A. Kantzas (Waterloo)
B. B. Maini (Univ. Washington)
A. K. Mehrotra (Calgary)
S. A. Mehta (Calgary)
B. J. Milne (Calgary)
M. Pooladi-Darvish (Alberta)
W. Y. Svrcek (Alberta)
M. A. Trebble (Calgary)
H. W. Yarranton (Alberta)
B. Young (Canterbury, NZ)
L. Zanzotto (Slovak Tech. Univ., Czechoslovakia


The Department offers graduate programs leading to the M.Sc. and Ph.D.
degrees in Chemical Engineering (full-time) and the M.Eng. degree in Chemical
Engineering, Petroleum Reservoir Engineering or Engineering for the
Environment (part-time) in the following areas:
Biochemical Engineering & Biotechnology
Biomedical Engineering
Environmental Engineering
Modeling, Simulation & Control
Petroleum Recovery & Reservoir Engineering
Polymer Processing & Rheology
Process Development
Reaction Engineering/Kinetics
Thermodynamics
Transport Phenomena
Fellowships and Research Assistantships are available to all qualified applicants.


SFor Additional Information Write *
Dr. A. K. Mehrotra Chair, Graduate Studies Committee
Department of Chemical and Petroleum Engineering
University of Calgary Calgary, Alberta, Canada T2N 1N4
E-mail: gradstud@ench.ucalgary.ca


The University is located in the City of Calgary, the Oil capital of Canada, the home of the world famous Calgary Stampede and the
1988 Winter Olympics. The City combines the traditions of the Old West with the sophistication of a modern urban center. Beautiful
Banff National Park is 110 km west of the City and the ski resorts of Banff, Lake Louise,and Kananaskis areas are readily accessible. In
the above photo the University Campus is shown with the Olympic Oval and the student residences in the foreground. The Engineering
complex is on the left of the picture.
M$W UNIVERSITY OF

8 CALGARY


wCA0 R
'-^. l


Fall 1999


I


)










The


UNIVERSITY


OF


CALIFORNIA


at


BERKELEY


. offers graduate programs leading to the
Master of Science and Doctor of Philosophy.
Both programs involve joint faculty-student
research as well as courses and seminars within
and outside the department. Students have the
opportunity to take part in the many cultural
offerings of the San Francisco Bay Area and
the recreational activities of California's north-
ern coast and mountains.


RESEARCH INTERESTS
Biochemical Engineering
Electrochemical Engineering
Electronic Materials Processing
Energy Utilization
Fluid Mechanics
Kinetics and Catalysis
Polymer Science and Technology
Process Design and Development
Separation Processes
Surface and Colloid Science
Thermodynamics


FACULTY


ALEXIS T. BELL

HARVEY W. BLANCH (Chair)

ELTON J. CAIRNS

ARUP K. CHAKRABORTY

DOUGLAS S. CLARK

SIMON L. GOREN

DAVID B. GRAVES

ENRIQUE IGLESIA

ALEXANDER KATZ


JAY D. KEASLING

C. JUDSON KING

ROYA MABOUDIAN

SUSAN J. MULLER

JOHN S. NEWMAN

JOHN M. PRAUSNITZ

CLAYTON J. RADKE

JEFFREY A. REIMER

DAVID V. SCHAFFER


PLEASE WRITE:
DEPARTMENT OF CHEMICAL ENGINEERING UNIVERSITY OF CALIFORNIA
BERKELEY, CALIFORNIA 94720-1462

346 Chemical Engineering Education














University of California, Davis


Department of Chemical Engineering & Materials Science
Offering M.S. and Ph.D. degree programs in both Chemical Engineering and Materials Science and Engineering


Faculty


David E. Block. Assistant Professor Ph.D.. University of Minnesota. 1992* Industrialfennentation, biochemical processes in phannaceutical
industry-
Roger B, Boulton, Professor Ph.D., University of Melbourne, 1976 Fermentation and reaction kinetics, crystallization
Stephanie R. Dungan, Associate Professor Ph.D.. Massachusetts Institute of Technology. 1992 Micelle transport, colloid and interfacial
science in food processing
Bruce C. Gates, Professor Ph.D.. University of Washington. Seattle. 1966 Catalysis, solid superacid catalysis, zeolite catalysts, bimetallic
catalysts, catalysis by metal clusters
Jeffery C. Gibeling, Professor Ph.D.. Stanford University. 1979 Defonnation fracture and fatigue of metals, layered composites and bone
Joanna R. Groza, Professor Ph.D., Polytechnic Institute. Bucharest, 1972 Plasma activated sintering and processing of nanostructured
materials
Brian G. Higgins, Professor Ph.D.. University of Minnesota. 1980 Fluid mechanics and interfacialphenomena, sol gelprocessing, coatingflows
David G. Howitt, Professor Ph.D., University of California, Berkeley, 1976 Forensic and failure analysis, electron microscopy, ignition and
combustion processes in materials
Alan P. Jackman, Professor Ph.D.. University of Minnesota. 1968 Protein production in plant cell cultures, bioremediation
Marjorie L. Longo, Assistant Professor Ph.D.. University of California. Santa Barbara, 1993 Hydrophobic protein design for active control,
surfactant microstructure, and interaction of proteins and DNA with biological membranes
Benjamin J. McCoy, Professor* Ph.D.. University of Minnesota, 1967 Supercritical extraction, pollutant transport
Karen A. McDonald, Professor Ph.D., University of Maryland, College Park, 1985 Plant cell culture bioprocessing algal cell cultures
Amiya K. Mukherjee, Professor D.Phil.. University of Oxford. 1962 Superplasticity of intennetallic alloys and ceramics, high temperature
creep defonnation
Zuhair A. Munir, Professor Ph.D., University of California. Berkeley. 1963 Combustion synthesis, nmultilayer combustion systems, functionally
gradient materials
Alexandra Navrotsky, Professor Ph.D.. University of Chicago. 1967 Thernodynamics and solid state chemistry: high temperature calorimetry
Ahmet N. Palazoglu, Professor Ph.D., Rensselaer Polytechnic Institute, 1984 Process control and process design of environmentally benign
processes
Ronald J. Phillips, Associate Professor Ph.D.. Massachusetts Institute of Technology. 1989 Transport processes in bioseparations. Newtonian
and non-Newtonian suspension mechanics
Robert L. Powell, Professor Ph.D.. Johns Hopkins University. 1978 Rheology, suspension mechanics, magnetic resonance imaging of
suspensions
Subhash H. Risbud, Professor and Chair Ph.D.. University of California. Berkeley. 1976 Semiconductor quantum dots, high T superconducting
ceramics, polymer composites for optics
Dewey D.Y. Ryu, Professor Ph.D.. Massachusetts Institute of Technology. 1967 Biomolecular process engineering and recombinant bioprocess
technology
James F. Shackelford, Professor Ph.D., University of California, Berkeley, 1971* Structure of materials, biomaterials, nondestructive testing of
engineering materials
J.M. Smith, Professor Emeritus Sc.D.. Massachusetts Institute of Technology. 1943 Chemical kinetics and reactor design
Pieter Stroeve, Professor Sc.D.. Massachusetts Institute of Technology. 1973 Membrane separations, Langimir ,:. I~ ,. colloid and
surface science
Stephen Whitaker, Professor Ph.D.. University of Delaware. 1959 Multiphase transport phenomena


The multifaceted graduate study experience in the Department
of Chemical Engineering and Materials Science allows students to
choose research projects and thesis advisers from any of our faculty
with expertise in chemical engineering and/or materials science and
engineering.
Our goal is to provide the financial and academic support for
students to complete a substantive research project within 2 years
for the M.S. and 4 years for the Ph.D.


SAN /
FRANCISCO


LOCATION:
Sacamento. 17 miles
San Francisco. 72 miles
Lake Tahoe: 90 miles

Davis is a small, bike-friendly university town
located 17 miles west of Sacramento and 72 miles
northeast of San Francisco, within driving dis-
tance of a multitude of recreational activities in
Yosemite, Lake Tahoe, Monterey. and San Fran-
cisco Bay Area.

For information about our program, look up our web
site at http://wwwi.chmts.ucdavis.edu.
or contact us via e-mail at
chmsgradasst@engr.ucdavis.edu
On-line applications may be submitted via
https://secureweb.ucdavis.edu:2443

Graduate Admission Chair
Professor Jeffery C Gibehng
Department of Chenical Engineering & Materials Science
University of California, Davis
Davis, CA 95616-5294, USA
Phone (530) 752-7952 Fax (530) 752-1031


Fall 1999











UNIVERSITY OF



CALIFORNIA

Graduate Studies in IRVINE
Chemical and Biochemical Engineering
and
Materials Science and Engineering
for Chemical Engineering, Engineering, and Science Majors

Offering degrees at the M.S. and Ph.D. levels. Research in frontier areas
in chemical engineering, biochemical engineering, biotechnology and materials
science and engineering. Strong physical and life science and engineering groups on campus.
FACULTY
Ying Chih Chang (Stanford University)
Nancy A. Da Silva (California Institute of Technology)
James C. Earthman (Stanford University)
Steven C. George (University of Washington)
Stanley B. Grant (California Institute of Technology)
Juan Hong (Purdue University)
Enrique J. Lavernia (Massachusetts Institute of Technology)
Henry C. Lim (Northwestern University)
Martha L. Mecartney (Stanford University)
Farghalli A. Mohamed (University of California, Berkeley)
Frank G. Shi (California Institute of Technology)
Vasan Venugopalan (Massachusetts Institute of Technology)

Joint Appointments:
G. Wesley Hatfield (Purdue University)
Roger H. Rangel (University of California, Berkeley)
William A. Sirignano (Princeton University)

The 1,510-acre UC Irvine campus is in Orange County, five miles from the Pacific Ocean and
40 miles south of Los Angeles. Irvine is one of the nation's fastest growing residential,
industrial, and business areas. Nearby beaches, mountain and desert area recreational
activities, and local cultural activities make Irvine a pleasant city in which to live and study.

For further information and application forms, please visit
http://www.eng.uci.edu/cbe/
or contact
Department of Chemical and Biochemical Engineering and Materials Science
School of Engineering University of California
Irvine, CA 92697-2575


Biomedical
Engineering
Bioreactor
Engineering
Bioremediation
Ceramics
Combustion
Composite
Materials
Control and
Optimization
Environmental
Engineering
Interfacial
Engineering
Materials
Processing
Mechanical
Properties
Metabolic
Engineering
Microelectronics
Processing and
Modeling
Microstructure
of Materials
Nanocrystalline
Materials
Nucleation,
Chrystallization
and Glass
Transition
Process
Polymers
Recombinant
-Cei Technol-
ogy
Separation
Processes
Sol-Gel Process-
ing
STwo-Phase
Flow -
*Water Pollution
Control
.____ ,____


348


Chemical Engineering Education









CHEMICAL ENGINEERING AT


UCLA


RESEARCH

AREAS

* Molecular Simulations
* Thermodynamics and
Cryogenics -l
* Process Design, Dynamics, and '
Control
* Polymer Processing and Transport-
Phenomena
* Kinetics, Combustion, and
Catalysis
* Surface and Interface Engineering
* Electrochemistry and Corrosion
* Biochemical Engineering
* Aerosol Science and
Technology
* Air Pollution Control and Environ-
mental Engineering



PROGRAMS
UCLA's Chemical Engineering Department offers a
program of teaching and research linking fundamental
engineering science and industrial practice. Our Depart-
ment has strong graduate research programs in Bioengi-
neering, Energy and Environment, Semiconductor Manu-
facturing, Molecular Engineering of Materials, and Pro-
cess Systems Engineering.
Fellowships are available for outstanding applicants in


FACULTY
J. P. Chang
P. D. Christofides
Y. Cohen
M. W. Deem
T. H. K. Frederking
(Prof. Emeritus)
S. K. Friedlander
R. F. Hicks
E. L. Knuth
(Prof. Emeritus)
J. C. Liao
V. Manousiouthakis
H. G. Monbouquette
K. Nobe
L. B. Robinson
(Prof. Emeritus)
S. M. Senkan
W. D. Van Vorst
(Prof. Emeritus)
V. L. Vilker
(Prof Emeritus)
A. R. Wazzan


CONTACT



.Fall 1999 349 Ag

Fall 1999 349


both M.S. and Ph.D. degree programs. A fellowship
includes a waiver of tuition and fees plus a stipend.
Located five miles from the Pacific Coast,
UCLA's attractive 417-acre campus extends from
Bel Air to Westwood Village. Students have access
to the highly regarded science programs and to a
variety of experiences in theatre, music, art, and
sports on campus.










University of California, Riverside
Department of Chemical and Environmental Engineering




The Graduate Program in Chemical and Environ- arlan and Rosemary Bourns College of
mental Engineering offers training leading to the
degrees of Master of Science and Doctor of Phi- engineering
losophy. All applicants are required to submit
scores from the general aptitude Graduate Record
Examination (GRE).

For more information
and application materials, write:
Graduate Advisor
Department of Chemical and
Environmental Engineering
University of California
Riverside CA 92521

Visit us at our website:
http://www.engr.ucr.edu/chemical



Faculty
Wilfred Chen (Cal Tech) Environmental Biotechnology, Microbial Engineering, Biocatalysis

Marc Deshusses (ETH, Zurich) Environmental Biotechnology, Bioremediation, Modeling

Mark R. Matsumoto, Chair (UC Davis) Water and Wastewater Treatment, Soil Remediation

Ashok Mulchandani (McGill) Biosensors, Environmental Biotechnology

Joseph M. Norbeck (Nebraska) Advanced Vehicle Technology, Air Pollution, Renewable Fuels

Akula Venkatram (Purdue) Micrometeorology, Air Pollution Modeling

Anders O. Wistrom (UC Davis) Particulate and Colloidal Systems, Wastewater Treatment

Yushan Yan (CalTech) Advanced Materials, Zeolite Thin Films, Catalysis



The 1,200-acre Riverside campus of the University of California is conveniently located
50 miles east of Los Angeles within driving distance to most of the major cultural
and recreational offerings in Southern California. In addition, it is virtually
equidistant from the desert, the mountains, and the ocean.


Chemical Engineering Education














UNIVERSITY OF CALIFORNIA


SANTA BARBARA


ERAY S. AYDIL Ph.D. (University of Houston) Microelectronics and Plasma Processing.
SANJOY BANERJEE Ph.D. (Waterloo) Environmental Fluid Dynamics, Multiphase Flows, Turbulence, Computational Fluid Dynamics.
BRADLEY F. CHMELKA Ph.D. (U.C. Berkeley) Inorganic-Organic Hybrid Materials, Zeolites and Molecular Sieves, Polymeric Solids, Liquid
Crystals, Solid-State NMR.
GLENN H. FREDRICKSON Ph.D. (Stanford) (Chair) Statistical Mechanics, Glasses, Polymers, Composites, Alloys.
JACOB ISRAELACHVILI Ph.D. (Cambridge) (Vice-Chair) Surface and Interfacial Phenomena, Adhesion, Colloidal Systems, Surface
Forces, Biomolecular Interactions, Friction.
EDWARD J. KRAMER Ph.D. (Carnegie-Mellon) Microscopic Fundamentals of Fracture of Polymers, Diffusion in Polymers, Polymer
Surfaces and Interfaces.
FRED F. LANGE Ph.D. (Penn State) Powder Processing of Composite Ceramics, Liquid Precursors for Ceramics, Superconducting Oxides.
L. GARY LEAL Ph.D. (Stanford) Fluid Mechanics, Physics and Rheology of Complex Fluids, including Polymers, Suspensions, and Emulsions.
GLENN E. LUCAS Ph.D. (M.I. T.) Mechanics of Materials, Structural Reliability.
DIMITRIOS MAROUDAS Ph.D. (M.I.T.) Theoretical and Computational Materials Science, Microstructure Evolution in Electronic and
Structural Materials.
ERIC McFARLAND Ph.D. (M.I. T.) M.D. (Harvard) Biomedical Engineering, NMR and Neutron Imaging, Transport Phenomena in Complex
Liquids, Radiation Interactions.
DUNCAN A. MELLICHAMP Ph.D. (Purdue) Computer Control, Process Dynamics, Real-Time Computing.
SAMIR MITRAGOTRI Ph.D. (M.I.T.) Drug Delivery and Biomaterials
DAVID J. PINE Ph.D. (Cornell) Polymer, Surfactant, and Colloidal Physics, Multiple Light Scattering, Photonic Crystals, Macroporous
Materials.
ORVILLE C. SANDALL Ph.D. (U.C. Berkeley) Transport Phenomena, Separation Processes.
DALE E. SEBORG Ph.D. (Princeton) Process Control, Monitoring and Identification.
MATTHEW V. TIRRELL Ph.D. (U. Massachusetts) Polymers, Surfaces, Adhesion Biomaterials.
T. G. THEOFANOUS Ph.D. (Minnesota) Multiphase Flow, Risk Assessment and Management
W. HENRY WEINBERG Ph.D. (U.C. Berkeley) Surface Chemistry, Heterogeneous Catalysis, Electronic Materials, Materials Discovery
using Combinatorial Chemistry
JOSEPH A. ZASADZINSKI Ph.D. (Minnesota) Surface and Interfacial Phenomena, Biomaterials.
PROGRAMS
AND FINANCIAL SUPPORT
The Department offers M.S. and
Ph.D. degree programs Finan-
cial aid, including fellowships,
teaching assistantships, and re-
search assistantships, is avail-
able.
THE UNIVERSITY
One of the world's few seashore
campuses, UCSB is located on
the Pacific Coast 100 miles
northwest of Los Angeles. The
student enrollment is over
18,000. The metropolitan Santa
Barbara area has over 150,000
residents and is famous for its
mild, even climate.

For additional information
and applications, write to
Chair Graduate Admissions Committee Department of Chemical Engineering University of California Santa Barbara, CA 93106

Fall 1999 351








Chemical Engineering at the


7 CALIFORNIA


INSTITUTE


OF


TECHNOLOGY

"At the Leading Edge"


Frances H. Arnold
John F. Brady
Mark E. Davis
Richard C. Flagan


cl


George R. Gavalas
Konstantinos P. Giapis
Julia A. Kornfield
John H. Seinfeld


David A. Tirrell
Nicholas W. Tschoegl
(Emeritus)
Zhen-Gang Wang


Aerosol Science
Applied Mathematics
Atmospheric Chemistry and Physics
Biocatalysis and Bioreactor Engineering
Biomaterials
Bioseparations
Catalysis
Chemical Vapor Deposition
Combustion


Colloid Physics
Fluid Mechanics
Materials Processing
Microelectronics Processing
Microstructured Fluids
Polymer Science
Protein Engineering
Statistical Mechanics


For further information, write
Director of Graduate Studies
Chemical Engineering 210-41 California Institute of Technology Pasadena, California 91125
Also, visit us on the World Wide Web for an on-line brochure: http://www.che.caltech.edu
Chemical Engineering Education






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CASE WESTERN RESERVE UNIVERSITY
M.S. and Ph.D. Programs in Chemical Engineering


FACULTY

Stuart Adler
John Angus
Colman Brosilow
Robert Edwards
Donald Feke
Nelson Gardner
Howard Greene
Uziel Landau
Chung-Chiun Liu
J. Adin Mann
Philip Morrison
Syed Qutubuddin
Robert Savinell


Research Opportunities


* Low Pressure Growth of Diamonds
* Process Control
* Colloidal Phenomena and Microemulsions
* Electrochemical Engineering
* Biomedical Sensors
* Synthesis of Electronic Material
* Polymers and Interfacial Phenomena
* Fuel Cells
* Catalysis and Reactor Design
* Separation Processes
* Interfacial Transport and Liquid Crystals
* In Situ Diagnostics


CWRU
CWRU


Chemical Engineering Education


Students in the Department of Chemical Engineering are involved in state-of-the-art re-
search. Here, two students make adjustments to a component of a prototype fuel cell


For more information on
Graduate Research,
Admission, and Financial Aid,
contact:

Graduate Coordinator
Department of
Chemical Engineering
Case Western Reserve University
10900 Euclid Avenue
Cleveland, Ohio 44106-7217

or see our home page at

http://cheme.cwru.edu




Full Text

PAGE 1

:: C ... .... 1:::1 I,) ::i l;i.l b.o :: ... I.. :: ... b.o :: I.. b ... t.) C ('-l :: 1:::1 t.) ... I.. "' I.. I: :: ... ::~ b.o C :: ... l;i.l "' ... .... ;. 1:::1 ... I,) ... b.o I: :: ... .:: I.. I,,,) :: ... b.o .... :: ::i .... .. .... .... 1:::1 "' :: t.) .... ... I: :: 1:::1 .:: I,) I,,,) .. I.. I: chemical engineering education VOLUME33 NUMBER4 FALL 1999 GRADUATE EDUCATION ISSUE Feature Articles .. _____________________ Getting the Most Out of Graduate School (pg. 258), Raja go palan A ChE Graduate Course in Materials Design (pg. 262), Mitchell A Survey Course in Particle Technology (pg. 266), Sinclair Experiences With an Experimental Project in a Graduate Control Course (pg. 270) Gatzke, Vadigepalli, Meadows, Do yle Essay: Universities ... Why? ( pg 288) Haile Particle Technology on CD (pg. 282) Rh odes How to Lie With Engineering Graphics ( pg. 304) Vesilind Computer Simulation of Tracer Input Experiments ( pg. 300) Conesa, et al. Designing a Petroleum Design Course in a Petroleum Town (pg. 322) Yarranton, Svrcek Activities to Enhance Understanding of the Mole and Its Use in ChE ( pg 332) Fraser, Case A Phenomena-Oriented Environment for Teaching Process Modeling (pg. 292) Foss, Geurts, Goodeve, Dahm, Stephanoloulos, Bieszczad, Koulouris Active Learning vs Covering the Syllabus and Dealing With Large Classes (pg. 276) Felder Br e nt Class and Home Problems: Beware of Bogus Roots With Cubic Equations of State ( pg 278) Pratt Introducing Process Control Concepts to Senior Students Using Numerical Simulation (pg. 310) Aluko, Ekechukwu Using a Cogeneration Facility to Illustrate Engineering Practice to Lower-Level Students (pg. 316) Hesketh, Slater Low-Cost Experiments in Mass Transfer: Part 5. Desorption of Ammonia from a Liquid Jet (pg. 328) Baird, Nirdosh -----1999 Awards: ASEE ChE Division (pg. 287) ----

PAGE 2

Index to Graduate Education Advertisements can be found on pages 336-337

PAGE 3

EDITORIAL AND BUSINESS ADDRESS: Chemical Engineering Education Department of C h e mic al Engineering University of Florida Gainesville, FL 32611 PHONE and FAX: 352-392-0861 e -mail : cee@che ujl.edu Web Page: http :// www .c he.ujl.edu/cee/ EDITOR T. J. Anderson ASSOCIATE EDITOR Phillip C. Wankat MANAGING EDITOR Carole Yocum PROBLEM EDITORS James 0. Wilkes University of Michigan LEARNING IN INDUSTRY EDITOR William J. Koros Fall 1999 University of T exas, Austill PUBLICATIONS BOARD CHAIRMAN E. Dendy Sloan, Jr. Colorado School of Mines PAST CHAIRMEN Gary Poehlein Georgia Institut e of T ec hn ology Klaus Timmerhaus University of Colorado MEMBERS Dianne Dorland University of Minnesota Duluth Thomas F. Edgar University of Texa s at Austin Richard M. Felder North Caroli11a State University Bruce A. Finlayson University of Washington H Scott Fogler University of Michigan David F. Ollis North Caroli11a Stat e Univ e rsity Angelo J Perna New J ersey Institut e of Te c hnolog y Ronald W. Rousseau Georgia Institute ofTec/1110/ogy Stanley I. Sandler University of Delaware Richard C. Seagrave Iowa State University M. Sami Selim Colorado School of Mines Jam es E. Stice University of T ex a s at Au s tin Donald R. Woods M c Master U11iversity Chemical Engineering Education Volume 33 Number 4 Fall 1999 GRADUATE EDUCATION 258 Getting the Most Out of Graduate School Raj Raja gopalan 262 A ChE Graduate Course in Materials De sign, Brian S. Mitchell 266 A Survey Course in Particle Technology J ennife r L. Sinclair 270 Experiences With an Experimental Project in a Graduate Control Course, Edward P Gat zke, Rajanikanth Vadigepalli Edward S. Meadows, Francis J. Do y le, Ill RANDOM THOUGHTS 276 FAQS. II: Active Leaming vs Covering the Syllabus and Dealing With Large Classes Ri c hard M. Felder, R ebecca Brent CLASS AND HOME PROBLEMS 278 Beware of Bogus Roots With Cubic Equations of State, Ronald M. Pratt CURRICULUM 282 Particle Technology on CD Martin J. Rhodes 322 Designing a Petroleum Design Course in a Petroleum Town H. W. Yarranton W. Y Svrcek ESSAY 288 Universities ... Why ?, J M. Hail e CLASS ROO M 292 A Phenomena-Oriented Environment for Teaching Proces s Modeling : Novel Modeling Software and Its Use in Problem Solving Alan S. Foss Kevin R. Geurts Peter J. G_oodeve K ev in D Dahm, George Stephanoloulos J e rry Bie szczad, Alexandros K o u/ouri s 300 Computer Simulation of Tracer Input Experiments J .A. Conesa J Gon z tilez-Garcfa J Ini esta, P Bonete M. Ingles, E. Exp6sito, V. Garcfa-Garcfa, V. Montiel 310 Introducing Proces s Control Concept s to Senior Students Using Numerical Simulation, Mobolaji E. Aluko, K e nn eth N. Ekechukwu 316 Using a Cogeneration Facility to Ulustrate Engineering Practice to Lower-Level Students Rob er t P. Hesketh C. Stewart Slater 332 Activities to Enhance Understanding of the Mole and Its Use in ChE Dun can M. Fraser Jennifer M Case ETHICS 304 How to Lie With Engineering Graphics P. Aarn e Vesilind LABORATORY 328 Low-Cost Experiments in Mass Transfer : Part 5. Desorption of Ammonia from a Liquid Jet M.H.J Baird I Nirdosh 287 199 9 Awards : ASEE ChE Division 336 Index of Graduate Education Advertisements CHEMICAL ENGINEERING EDUCATION ( ISSN 0009-2479 ) is published quarterly by the Chemical E n gineering Division American Society for Engineering Education, and is edited at tire University of Florida. Cor r espondence regarding editorial maJter circulation, and changes of address s hould be sent to CEE, Chemical Engineering DepartmetJt University of Florida Gainesville, FL 326JJ-6005. Copyright ~ 1999 by the Chemical Engineering Division American Society for Engineering Education. The statements and opinions expressed in this pen odical are those of the wri te rs and not necessarily those of th e ChE Division ASE which body assumes no r es ponsibility for them Defective copies replaced if notified within 120 days of publication Write for information 011 subscription cos ts and for back copy cos t s and availability POSTMASTER: Send address changes to CE Chemica l ,, gineering Department. University of Florida Gainesville, FL 32611-6005 Periodicals Postage Paid at Gainesville, Florida 257

PAGE 4

[ Graduate Edu c ation GETTING THE MOST OUT OF GRADUATE SCHOOL RAJ RAJAGOPALAN University of Florida Gainesville, FL 32611-6005 Ra j Ra j agopala n is Professor of Chemical Engineering at the University of Florida where he has been since 1996. His research activi ties focus on colloid physics and complex flu ids. In addition, he maintains an active interest 258 in teaching at both undergraduate and graduate levels His educational activi ties include the co author-ship of a textbook on colloids and the develop ment of other in structional materi als. Copyrigh t ChE Divi sion of ASEE 1999 W hat you learn in graduate sc hool can be the foundation for a life-long learning experience and a successful career, but it takes more than a good undergraduate preparation and a desire to get an advanced de gree to get the most out of graduate school. The following are some bits of advice and recommendations based on my own experience-as a student and as a faculty member-and on what I have learned from my students. Although my comments are addressed largely to graduate students in science and engineering, many of the observations should be of u se to all graduate students regardless of the discipline. Some of the book s in the li s t of annotated references at the end of this article have detailed guidelines on specific issues you may face during your studies and beyond. One of the books by Carl Djerassi a renowned chentist, is a fictionalized account of the competition and personal professional, and ethical issues faced by graduate students and faculty involved in day-to-day research Another, by James Watson of the DNA fame, is a real-life story that reads almost like fiction. I have included these two books so that you have more than a list of dry se lf-help books. These two book s may possibly teach you more than all the other books put together. ATTITUDE MAKES A DIFFERENCE The first and foremost factor i s the attitude one brings to one's life. A major part of how successful we are in what we set out to do in life often depends on our attitude. Someone who feels like a "winner" is more likely to be a winner; one who feels like a victim is likely to end up being one Most people I have talked with recall their student years as among the best years of their lives but how much you get out of school, profes s ionally and otherwise, depend s to a large extent on what expectations, comntitment and di sci pline you have and how much you demand from yourself. Here are so me points to ponder : First, know what to expect from graduate school and what commitments and responsibilities are expected of you. Do not postpone learning essential professional skills and basic life skills" until you get a job or leave graduate school. For example, I have known many students who have, either consciously or subconsciously, postponed learning good communication skills, social sk ills needed for teamwork and building a network of peers--only to regret it later. As a research student you are a junior research colleague of the faculty. This is a privilege, but one that comes with certain responsibilities and account ability. Be aware of them. LEARN GOOD WORK HABITS Discipline Matte r s Graduate research is about generating or implementing new concepts. It is not a nine-to-five job. Most successful s tudents I know put in at least seventy hours a week. Expect to work hard and expect to s pend long hours. Keep good laboratory notebook s. Divide them into sec tion s, e.g one for research papers you read one for your own work, etc. When you read a research article, write down the full reference in your research notebook, cut and paste a xerox copy of the abstract into the notebook, summarize the salient Ch e mi c al Engineering Education

PAGE 5

points and major result s, cut and paste key figures and tables (alo ng with your own annotations), s ummarize major que s tion s of inter est to you and make a li s t of important cross-references. (Yo u may also want to write down the date s to make the research notebook a "jo ur nal" of your thoughts and progre ss.) You'll appreciate the value of this habit when you are ready to write up your results for publication or when you write your the sis. If you are copying something verbatim from a publi cation, make a note that it i s a verbatim record to avoid later using it inadvertently in your own work without giving proper credit to the original source. (See my com ment l ater on plagiarism .) Spend at least one day a week in the library It is you r responsibility to keep up with the literature. (It is your research and your thesis .) Do not expect your research advisor to do it for you. Take ownership of your project. Attend seminars and learn from the experts. Observe what techniques the speakers use to make their pre se nta tions engaging and under s tandable. Also observe what mistakes they make and avoid them in your own pre se tations. Attend the seminars even if the talks are not on your research topic-you never know what connections yo u can make to your own work or how what you learn from the talks can help you later in yo ur career. Stay focused on your re searc h but learn about areas other than your own The market is fluid and a typical emp lo yer often wants someone who ha s a broader back gro und than the one defined by your s pecific work. Do not expect to work on the sa me problem you studied for yo ur MA, MS or PhD when you go into the workforce. Rem ember that graduate sc hool is about learning to learn on one's own. If your stipend comes from a research grant to your advisor learn about the expectations and deadlines the funding agency place s on your advisor. Understand what pressure s your advisor faces in keeping the funds flowing. Form Networks: Learn from Others Take the initiative and form a "jo urnal club or research colloquium club with other graduate s tudents who have similar interests Conduct regular dis c ussion meetings to learn from each other (and to develop presentation skills) Use the journal club and si milar activities to form a collegial network of your peer s You never know when you might need the help of one of your sc hoolmates Get to know the fac ult y on your thesi s committee and others from whom yo u have taken cla sses. In general, get to know as many faculty members as possible from within and outside yo ur department. Make it a point to meet with them periodically to seek their advice and to learn from their experiences Not only do you broaden Fall 1999 Graduate Education ] your experience by doing thi s, but yo u also create a pool of faculty member s who know you well enough to write meanin g ful letter s when you need one. Form a "g lobal n e twork ." If you have questions abo ut a paper yo u are reading, write to the authors. Most authors are plea se d to respond Do not however, be discouraged if you do not hear from them-the world is not perfect. Attend a few national or international professional meet ing s in your di sc ipline even if you have to pay for the expenses. It i s an investment in your future and money well s pent. Use your attendance to meet and to get to know experts from outside your institution. Seek balance in what yo u do. If you are doing theoretical work, learn the relevant experimental issues. If you are an experimentalist, try to get a perspective on the theo retical i ss ues. Remember that theory does not neces sarily mean dealing with equations." Mathematics is a language and a medium to achieve an end. Seek e ducation be yo nd the classroom or your research work. Learn to observe and listen. If you have the right attitude yo u can learn from everyone and from every experience, po si tive as well as negative College life offers you an opportunity unmatched by any to broaden your horizon. Break the barriers. Attend talk s or se minar s in di sc ipline s very different from yours. For example, if you are in the hard sc iences attend some se minar s in cultural anthropology, art criticism, linguis tics or the like Learn how sc holar s in the "s oft" sciences approach their research. Deal with Difficulties Head On; Strive to Stay Positive Research is a solitary activity Do not always expect others to get excited about what you find exciting. You can minimize the i so lation if you build a network of interested indi v idual s as I suggested earlier. Re searc h i s full of up s and down s ( more downs than ups, normally ), and the key to success is to learn to bear with or overcome the down s. Try hard to s tay motivated. If you are feeling down, take a break do something you enjoy, and then return to your work. If yo u think you need so meone to cheer you up or urge you on talk to one of your friends or see your research advisor and ask for advice or help Divide your work into manageable portion s, and make s ure that yo u make progres s in at le ast one of them on a regular ba s i s. Even incremen tal progre ss is better than none at all and will keep you motiv a ted Take a course on time management. Most people can u se one. If you feel that you are constantly under s tre ss and hav e 259

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'--G-~_'ll_d_u_a_t_e_E_d_u_c_a_ti_o_n _______ ___________ _________ _________ ~] diffi cu lt y copi n g, d ea l w ith it h ead on Talk with a sy path e tic frie nd or with your re searc h advi so r or a faculty memb er. Take a course on stress management. There are man y se lf-h e lp book s available on both timeand stress mana ge ment a nd the y can be u se ful. Most universitie s provide profe ss ional counseling for students with prob lem s a nd run se minar s on time-management (among other thing s, s uch as public pre se ntation interper so nal skills and conflict resolution) unable to communicate your achievements to others. I have known many individual s who have advanced rapidly in their job s largely due to their communication skills. Do not underestimate the importance of writing effec tively and elegantly Reading only technical articles or articles in your own profession tends to decrease your verbal skills and vocabulary Make it a habit to read on a regular ba s i s, the works of authors known for their command of the language. If you usuall y free of charge. Take advantage of the se It i s not unusual to have differ ences of opinion with your ad visor You may even "dislike" your advisor so metimes. It is n a tural. It i s only human But you'll find that in the end the overall po s itive experience will overcome difficultie s yo u face along the way. It is how you re s pond to set b acks that deter mine s yo ur s ucce ss and th e qualit y of yo ur life. Pay Attention to Ethics Re searc h is a hum a n endeavor and i s not always an objective searc h for the truth, but do not let that di sco urage you or make you b e nd the rule s Strive for the highest s tandard s Pay attention to professional ethics Make sure you are aware of the rule s of author ship of public a tions Acknowl edge in your publication s those who h ave provided assistance in your work ( be generous, but get their permi ss ion ) TABLE 1 References and Web Sites on Technical Writing Books Alley, M. Th e Craft of Scientifi c Writin g, 3rd ed., Springer Ver l ag New York NY (1996) B oo th W.C. G.G. Co l omb and J M. Willi a m s, Th e Craft of R ese arch University of Chicago Pr ess, Chicago IL (1995) Bru saw, C.T. G.J. Alred a nd W.E. Oliu Handb ook of T ec hni ca l Writin g, 4th ed St. Martin 's Pr ess, New Yo r k, NY ( 19 93) Da y, R.A ., H ow t o Writ e a nd Publish a Sci en t ific Pa per 4 th ed Oryx Pre ss (1994 ) Dodd J.W ., ed., Th e ACS Styl e Guid e : A Manualf o r Authors and Editors 2nd ed American Chemical So c iety Washington DC (1997) Matthews J R. J M Bowen and R.W Matthew s, Suc ce ssful Scientifi c Writing, Cambridge University Press Cam brid ge UK ( 1996 ) Strunk Jr. W and E. B White Th e El e m e nts of Sty l e, 3rd e d ., Allyn and Bacon Boston MA ( 1979 ) Tech11ical Writi11r llltemet Li11ks Online Writing Lab Purdue Univer s it y, We s t Lafayette IN http: //ow l.english.purdue .e du/ Grammar Hotline Directory http: //w ww.re.cc. va.u s writcent/gh/index htm Strunk & White 's El e m e nts of Styl e http ://ww w.columbia .e du/a c i s/ba rtl e by/ s trunk WWWebster Dictionary http :// www.m-w com/ n et dict.htm WWWebster The sa uru s http ://www.m -w. com/t h esa uru s. htm Technical Writing: Book s and R e f e renc e Sources http //www. interlo g.com/~kso lty s/ twritres.html are in the sciences or engineering read well-written popular science articles in magazines (e g. Disco ver, Th e N ew Scientist, S c ientifi c Ameri ca n e t c ) to learn how professional writers avoid jargon and communi cate complicated concepts in an en gaging style. Identify also some w e ll-known authors of non-techni cal material and read their works periodically so that you keep your verbal s kills honed Good writing requires clear think ing. Practice writing short summa ries of long articles or scholarly es says at a level accessible to a novice Table 1 contains a list of books and internet sites on effective writing Try to be gender -neutral in your writing. It is not a matter of being fashionable or being politically cor rect. It is a matter of recognizing respecting, and encouraging the par ticipation of both sexes in our pro fession Learn to make oral presentation s effectively This includes knowing how to organize your thoughts logi cally a nd how to prepare effective If you use idea s or re s ult s of others, do not forget to cite the relevant ( primary) reference s. If you use someone else 's writing verbatim, follow the copyright require ments Do not forget to give proper credit. When you are writing your the s i s or paper s, it i s easy to transfer sen tence s yo u m ay have copied into your notebook from other so urce s without attribution In our profession there i s no grea ter s in than plagiarism i.e ., trying to get, even unintentionally credit for so meone else's ideas viewgraphs and knowing the proper body language. If you need help join a public presenta tion group such as the Toastmasters Club (see http:// www.toastmasters.org) Make periodic presentations to your re se arch group and ask your friends and advisor to criticize your presentation (co nstructivel y). In your pre se ntations focus on your work but pre se nt your re s ult s in the context of the broader scope of your research group and those of others elsewhere. Doing so is much more impressive to for example, a prospective employer, for it s how s that you understand the broader context of your work and that you have the initiative to learn the broader context of whatever you are assigned. MASTER COMMUNICATION SKILLS Our profe ss ion i s about generating ideas and communicat ing them to others You fail if you are poor in eit h er; that is you can fail even when you are good at what you do, but are 260 Learn to be effective in a group setting. Learn the social Chemica l Engin ee rin g Edu cat ion

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SOME USEFUL REFERENCES [J Careers in Science and Engineering: A Student Planning Guide to Grad School and Be y ond National Academ y Press Washington DC ( 1996 ) (A planning guide fo r students conside r ing entering graduate school o r in graduate school Gives r eal-life examples of career paths of scientists and engineers. Contains short case studies of different caree r paths and lists of "action points. You can read this book in the electronic r eading room at www.nap.edu .) [J On Being a Scientist: Responsible Conduct in Research, National Academy Press, Washington DC (1995 ) ( Advice on pr ofessional, pe r sonal, and ethical issues that a gradu ate student or a beginning r esearcher faces P resents a number of h y p ot h etica l open-ended scenarios designed to draw attention to ethical isues one may face in r esea r ch. You can read this book in the electronic reading r oom at www.nap. e du .) [J Feibelman, P.J. A PhD Is Not Enough: A Guid e to Sur v i v al in Science, Addison-Wesley New York, NY (1994 ) ( A concise and easy-tor ead volum e on what it takes to be success ful especially in an academic career .) [J Me d awar P.B., Advice to a Young Scientist Basic Books New York, NY (1981 ) ( Advice from a Nobelist to graduate students and scientists in the early stages of their ca r eers .) [J Watson, J.D., Double Helix: A Personal Account of the Dis covery of the Structure of DNA, G.S. Stent, ed., W.W. Norton, New York NY (1980 ) ( An engaging record of the autho r 's pe r spective of th e competition t h e excitement, and the human side of science in action writt e n a lm ost like a racy nov e l. This special Norton edition, edited by Stent, a well-known mo l ecula r b iologist h imse l f, h as a number of c r itical reviews of Watson's book and additional opinions by other worldr enowned biologists and chemists. ) [J Sayre, A Rosalind Franklin and DNA, W W Norton, New York NY (1978 ) ( A discussion of the contributions of Rosalind Franklin to the discovery of the structure of D NA and an anal ysis of whether h e r contributions were acknowledged appropriately in Watson 's ve sion of the discovery .) [J Ambrose, S.A., K.L. Dunkle, B.B. Lazarus I. Nair, and D.A. Harkus, Journeys of Women in Science and Engineering : No Universal Constants ( Labor and Social Change), Temple University Press, Philadelphia, PA (1997) (C h a ll e n ges faced b y women in science and engineering.) [J Djerassi, C. Cantor's Dil emma, Penguin Books, New York NY (1 989 ) (A g r i pp ing novel b y a wor l d -r enowned c h emist known fo r his discovery of t h e b irt h -cont r ol pi ll a b out the fie r ce competition d r iv ing scientific "supersta r s. A fictionalized version of real ethical a n d pe r sonal issues faced by scientists every day. This is the first vo lum e in a tet ra logy Yo u can visit h ttp : I I www.djerassi.com fo r mo r e de t a il s o n t h is b ook and its se q uels .) [J Covey, S.R., A.R. Merrill, and R. Merrill First Things First, Simo n & Schuster, New York, NY (1995) ( On e o f t h e most p o p ular time -m anagement b ooks .) [J Seligman, M., Learned Optimism, Pocket Books New York, NY (1 998 ) ( The author a psychologist and clinical resea r cher discusses pessi mism, optimism and dep r ession and how they affect quality of life. Th e book also discusses the skills needed to change one's attitude from pessimism to o p timism ) Fall / 999 Graduate Education J ski ll s n ee d e d t o b e co urt eo u s a nd ge n ero u s t o o th e r s w hil e m a kin g yo ur ow n p o int s effec ti ve l y. D o n o t w a it until yo u ge t a j o b t o l e arn s u c h s kill s. Yo ur s up erv i s or s ge n e r al l y w ill n o t h ave th e tim e t o b e yo ur m e ntor s or a d v i so r s. Th ey wi ll m ere l y o b se r ve yo ur p erfo rman ce a nd w ill p ass yo u ove r fo r p ro m o ti o n or a c h o i ce j o b assig nm e nt i f yo u d o not h ave th e n ecessary s kill s. If En g li s h i s n o t yo ur n a ti ve t o n g u e, s p eak o nl y E n g li s h a t wo rk. As k a n E n g li s h -s p eaki n g co ll eag u e t o proof r ea d y our p a p e r s and li s t e n t o y our pr ese nt a ti o n s Tak e a d v ant age o f t ec hni c al w ritin g co ur ses and co ur ses on En g li s h as a seco nd lan g u age" offe r e d b y th e uni ve r s i ty. DEVELOP GOOD SOCIAL HABITS Ming l e wi th as ma n y p ee r s as p ossi bl e G e t t o kn ow th e m T r y t o m ake lifel o n g fr i e nd s h i p s. If yo \J are a fore i g n s tud e nt tr y t o fi nd a roo mm a t e w ho i s n o t fro m yo ur ow n co untr y. B e a c ultu ra l a mb assa d o r of yo u r co untr y If yo u are a n a ti ve s tud e nt see k o ut s tu d e nt s fro m o th e r c ountri es. L e t 's mak e th e w o rld a bett e r pl ace fo r t h e n ext ge n e rati o n EXERCISES 1. Writ e a s h o rt essay o n yo ur goa l s in life a nd in your p rofess i o n a l caree r. B e h o n est wi th yo ur se l f. M ake a li s t of yo ur s tr e n g th s a nd weaknesses. Id e nti fy w h a t y ou c an d o t o e limin a t e o r minimi ze yo ur w e akn esses 2. E x amin e a nd an a l yze th e case s tudi es o n pro fess ion a l p rac ti ce o utlin e d in On B e in g a Scientist: R esponsi bl e C o n d u ct in R esea r c h ( N a ti o n a l A ca d e m y Pr ess, Wa s h i n g t o n DC 1 9 9 5 ; accesse d throu g h th e we b a t www. n a p. e du ) 3. Writ e a s h o rt r esearc h p ro p osa l o n a to pi c of yo u r c h o i ce fo ll ow in g s t an d ar d g u i d e lin es i ss u e d b y th e uni ve r s it y a nd ask a frie nd o r yo ur gra du a t e a d v i so r t o c riti c i ze i t. ( Y o u m ay w i s h t o l oo k thr o u g h th e US Na ti o n a l S c i e n ce F o und a tion g uidelin es on prop osa l s a nd r ev i e w c riteria ; see www. n sf.gov) ACKNOWLEDGMENTS Th is ar ti c l e i s b ase d o n a Pro fess ion a l D e v e lopm e nt Semi n ar C o u rse d eve l o p e d fo r th e g raduat e st ud e nt s in th e D e p a rtm e nt of Ch e mi ca l E n g in ee rin g a t th e Univ e r s ity of F l o rid a, and o n a co upl e of se minar s I ran r e centl y a t the N a tional Uni v er s it y of Sin g ap o r e I w o uld like to thank Jor ge Jim e n ez, Cl a udi a Marin An a nd Ja ga n a than a nd Jonah Kl ei n g raduat e s tud e nt s in th e Uni v er s it y o f Florid a D e part m e nt o f Ch e mi c al En g in e erin g, a nd m y c oll ea gu e Profe ss or M ark O raze m fo r c riti cal l y r ea din g a d raf t of thi s a rticl e a nd s u gges tin g imp rove m e nt s. Dr. P a ul Huib e r s, o f th e D e part m e nt of Ch e mic a l E n g ine e rin g a t MIT r ea d th ro u g h an ear li er dr af t and s u gges t e d so m e c h a n ges, w hi c h I ha ve in c orporated into thi s ve r s ion alm os t v erb a tim 26 /

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[ Graduate Education ] ~-----------------~ A ChE GRADUATE COURSE IN MATERIALS DESIGN BRIANS. MITCHELL Tulane University New Orleans LA 70118 M aterials sc ience i s perhaps the s i~gle large s t mu_Iti di sci plinary technological s ubJect area, drawin g together experts from s uch diver se background s as architecture, phy s ic s, biomedical engineering, and eve n the art s. Chemic a l engineers have helped make significant advances not only in w e llesta blished hard material s sc ence fields s uch as polymer processing and se miconductor s, but they h ave also been at the forefront of important emerg ing materi a l s sc ience technologies s uch as ti ss ue engineer ing (of the so-ca lled "sof t material s"), se lf-a sse mbling sys tems, and nanostructured materials. The irony in the se ac comp li shments i s that many chemical engineering curricula neither require a material s scie nce course nor directly pre pare under gra duates for careers in the se field s, much le ss prepare them for advanced s tudy in materialssc ience-ori ented re sea rch areas. The c hallen ge for tho se of u s doing materi a l s -related re se arch in c hemi cal engineering department s, then is to take st udent s w ho ma y have littl e or no back gro und in material s sc ience and prepare them to do s tate-of-thea rt material s research Although an under gra duate level s urvey course in material s engineering and scie nce i s a good place to s tart what is often needed is a seco nd advanced-level s urvey co urse ," i f there is s uch a thing to prepare graduate s tudent s to do re searc h in a wide variety of material s -related areas. COURSE CONTENT Most undergraduate materials science textbooks take th e s urvey approach; that i s, a wide variety of topics are preBrian S. Mitchell is Associate Professor of Chemical Engineering at Tulane University He received his BS in chemical engineering from the University of Illinois-Urbana in 1986 and his MS and PhD degrees in chemical engineering from the University of Wisconsin Madison in 1987 and 1991 respectively His research interests are in fiber technology and composites engineering and in the use of al ternative teaching techniques in the classroom sented in relatively little depth or detail in order to give the s tudent at l eas t a pa ss in g familiarity with a number of differ ent material s -science concepts. A working knowledge of general chemistry, phy s ic s, and calculus is required but little or no organic chemistry, phy s ical chemistry, or differ ential equations are employed Textbook s such as that of Calli s terl 11 are excellent in thi s approach, especially si nce they are frequentl y updated and thu s expose s tudent s to the late s t trend s in material s sc ience They are usually written b y material s sc ienti s t s, metallur gists, or ceramists, but rarely by chemical engineers A s a result there are a number of concepts that are important to chemical engineers working in the materials field that must be t a ught eit her one-on-one with the graduate student, dur ing group meetings or in a narrower graduate-level course. There are a number of excellent text s for s uch courses, on topi cs ranging from polymer rheology ,l 21 to ceramics pro cessing, l3J to electrical propertie s of material s. 141 There i s very little in between The undergraduate s urv ey text i s not appropriate for a graduate-level course, yet to focus on a s pecific topic (while it may be well-taught and of academic importance ) may not provide exposure to a s ufficient number of concepts to be useful to gra duate s tudents conducting widely v aried materi al s research Finally and perhap s mo s t importantly the se narrower s ubject courses do not address or di sc u ss the way in which a number of important material s have been devel oped: through de s ign of material s for a s pecific app li cation. The course outline for a graduate-level chemical engineer ing course, "Advanced Materials Design ," is shown in Table 1. Four features of this course will be highlighted here: one lecture on the hi s tory of material s development ; a list of se lected advanced topic s; a di sc u ss ion of the de sig n proce ss; a nd examples of materials design project s. HISTORY OF MATERIALS DESIGN There are a number of truly fascinating s torie s related to the development of certain types and classes of material s. Copyright ChE Division of ASEE 1999 262 C h e mi c al Engineering Educat i on

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[~ ___________________________________ G_T<_wl_u_a_te_E_d_u_ca_ti_o_n~ For example the work of Wallace Carothers at DuPont on the develop ment of neoprene and nylon demon s trates not only how materials ( in thi s case polymers) were developed as sub stitutes for specific naturally occurring materials such as rubber and silk but also how their development was spurred by historical events (World War II in this case). This is not very technical information of course, but student s should be made aware (or at least re minded) that technological advance s occur as a result of a number of differ ent driving forces including chance, theoretical predictions and necessity. There is a particularly good book by Although an undergraduate-level survey course in materials engineering and science is a good place to start, what is often needed is a second, "advanced-level survey course," if there is such a thing to prepare graduate students to do research in a wide variety of materials related areas. Ivan Amato called Stuf/l 51 that provide s .------T-A_B_L_E_l _____ _, a great deal of historical information and perspective on the development of materials science a s a discipline, and of specific materials. Although I stop short of making this a required text for the Advanced Materials Design course due to its lack of technical content, it is nonetheless on the must read" list for anyone in the materials area and it is worth recommending to all science and engineering students It also show s how some prominent chemical engineer have played important roles in devel oping new materials and how they em ployed design principles to accompli s h their task. An excellent example is the work of Ilhan Aksay of Princeton Uni versity on biomimetic structures Course Outline for Advanced Materials Design I. Selected Advanced Topics in Malerials Science A. The History of Materials Science B. Crystallography C. Structure of Glass D. Structural Imperfections E. Phase Equilibria F. Phase Transformations G. Advanced Characterization Techniques H. Mechanical Properties II. Malerials Design A. The Design Process B. Metals C. Inorganic Materials Ceramics (lowand high-tech) Glasses Glass-ceramics, ceramers, and cermets D. Polymers E. Composites F. Case Studies, Design Projects ADVANCED TOPICS and a semester-long course in crystal lography This topic is of use to those students who will be conducting re search in practically any materials area, including polymers. In addition to re viewing the seven crystal systems, the reciprocal lattice Miller-Bravais indi ces, symmetry operations, and X-ray diffraction are discussed. The advanced content comes from such exercises as calculation of single crystal X-ray dif fraction patterns from unit cell dimen sions which can be done on a spread sheet. C61 The lectures on the crystalline state lead naturally into lectures on the amor phous, or glassy, state. Again, discus sions of radial distribution functions, the glass transition, and phase transfor mations are equally applicable to inor ganic glasses as well as polymers. Struc tural defects often receive a great deal of attention in an undergraduate mate rials science course-deservedly so since they directly affect many physical properties. One topic on structura l defects that does not receive a great deal of attention except in courses on ceram ics is point defect equilibrium and Kroger Vink notation _l7 1 Once Kroger Vink notation has been described, the determination of equilibrium point de fect concentrations is particularly relevant for graduate-level chemical engineers, since the point defect species are treated like any other chemical species, and de fect reaction equations are like any other chemical reaction. A graduate-level chemical engineering course should be more than a history lesson of course One of the primary purposes of an advanced materials course should be to teach advanced topics-those that are only introduced at the un dergraduate level or that are not covered in sufficient detail. The difficult question is which topics those should be. At Tulane University, we have faculty conducting research in such areas as heterogeneous catalysis, molecular dynamics simulations of thermophysical properties in polymer single crystals, nanostructured ceramics, and tissue engineering. Some of the advanced topics we have selected to address are shown in Table 1 Lectures on crystal structure are given at a level some where between the undergraduate materials science co ur se Phase equilibria is also an area that most chemical engi neers get a great deal of exposure to at the undergraduate level. Most of it deals with the liquid and vapor states, however, and is mostly applied to binary systems. Ternary condensed-phase diagrams are described in Advanced Mate rials Design. Although this is not mathematically challeng ing material, terms and concepts such as conodes, isopleths, coprecipitational di variant equilibria lines and alkemade lines take a bit of practice to fully understand. As a final example of the advanced survey format of this course, a number of lectures are spent on advanced materials characterization. Once again, this can be a course in-and-of itself but there are a few techniques that are of particular importance to our department and its researchers. Tulane University has a comFall 1999 263

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[ Graduate Education plete thermal analysis laboratory. It contains, among other things, a differential scanning calorimeter (DSC), differen tial thermal analyzer (DT A), thermogravimetric analyzer (TGA), dynamic mechanical analyzer (DMA), thermo mechanical analyzer (TMA), dielectric analyzer (DEA), and various combinations of these instruments A number of graduate students in the department wish to use the thermal analysis facility, and without turning a graduate level course into a technician training session, the students are introduced to the operation of these analyzers and the theory behind selected instruments is discussed. THE DESIGN PROCESS It makes sense in a course on "materials design" to discuss not only the materials part, but also the "design" part The design aspect of engineering education has certainly not been lost on other parts of the chemical engineering curricu lum, such as process design, and has in fact been emphasized more recently across the curriculum through emphasis of design-oriented problems at all levels and in all subject areas The design approach has not been taken to any appre ciable extent in materials science courses. In the Advanced Materials Design course, general design methodologies such as Cross s methodology, [ 8 1 concurrent engineering/ 9 1 and market-driven designC I0I are discussed. More materials-oriented design methodologies are then de scribed in which Ashby's dated, yet still appropriate, text on mechanical design is usedY 11 Not all materials design prob lems, especially newer ones require a significant mechani cal property component, so students are encouraged to use the more general design strategies to carry out materials selection and development. An excellent text on materials design that contains a great number of case studies is by Lewis.c I 2 1 This book offers a wealth of information and emphasize s cost analysis-some thing that is often lost in academic environs The remainder of the course is spent reviewing the traditional grouping of materials science topics, with an emphasis on physical prop erties that can be exploited from a design standpoint. THE DESIGN PROJECT As with many chemical engineering courses, the heart of the materials design course is the design project. The design project topics for Advanced Materials Design are gleaned from the recent literature (see Table 2 and references 13-28). The Materials Research Society Bulletin is a particularly useful source for these topics, as the articles in this monthly journal tend to be of intermediate technical difficulty, yet represent some of the most current, cutting-edge materials research being conducted These articles also generally have excellent bibliographies, thus providing a good starting point for the students' literature reviews. The students get to choose 2 64 TABLE2 Sample Design Project Topics Grouped by Traditional Subject Areas Polymm Properties and applications of dendrimersJ1 3 Graded-index optical fibers 1151 Molecule-based magnetsl' 61 Electrically-conducting polymers 1171 Materials for flat panel displays1 1 s. 19 1 Cerruniq Ceramic thin films using self-assembled monolayers 1201 Artificial bone 1211 Semiconductor nanocrystaJsl 22 1 Nanoceramics 123 .2A 1 Compovt,1 Discontinuously reinforced metal-matrix composites' 25 Biomimetic transducers' 26 Ms/6.. Metallic glasses 1271 Properties of quasicrystals' 281 TABLE3 Design Project Requirements Qldective To develop a specific application for the material in the selected topic area. For some topics, this will be evident; for other topics, some creativity will be required. Rqain,,,,,.,, for Minimwn Gmd, Ten-page report with at least one figure and complete bibliography that conforms to the following outline: [I Abstract [I Keywords [I Introduction [I Background Review of pertinent literature, important physical property data [I Proposed design Design methodology Material selection and justification Advantages and disadvantages of selected material Alternative materials [I Conclusion Cl Bibliography [I Appendix Twenty-minute presentation Ch e mical En g in ee rin g Edu c ati o n

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the topic, with the stipulation that it be outside of their research area. Some of the topics are very general, such as nanocerarnics; others are more specific, suc h as discontinu ously reinforced metal matrix composites. Some of the top ics already have an application associated with them, such as materials for flat panel displays; others are still in search of break-through applications. The project topics are selected and assigned early in the course. For the first homework assignment the students must find three additional articles for their topic, preferably varied in scope; e g., one review article one on molecular mechanisms, and one on processing. They must also write a brief summary of the potential significance of the topic and areas where it can be applied. The requirements for the final report are listed in Table 3. The goal is to come up with a specific application for their material-all the way down to drawing a schematic of the apparatus or article and describing how it works. This may seem trivial for a topic like "Materials for Flat Panel Dis plays, but in this case the student must reverse engineer the component, determine what the specific materials constitu ents are, and more importantly, why they were selected. In either scenario, the student must come up with a justifi cation for the selected materials. In doing so, the stu dent applie s the design criteria, or sees how others applied them uses advanced materials science concepts in the analysis of the application and thinks practically, yet critically, about how newly developed materials can be used. CONCLUSION Graduate courses need not emphasize the use of elliptical integrals, nor be as narrow as the instructor's most recent grant proposal in order to be considered advanced. The three highest level s of Bloom's taxonomy of Education Objec tives-analysis, synthesis, and evaluation l 291 are sufficiently challenging for graduate students, even in a survey-type course, when the technological content of the system being analyzed and evaluated is sufficiently complex. Today's materials applications certainly meet the technological re quirement, and a design project for chemical engineering graduate students on advanced materials applications chal lenge s the s tudents to use many of the chemical engineering principles they have learned as undergraduates REFERENCES 1. Callister, William D Materials Scienc e and Engineering: An Introduction, 4th ed., John Wiley & Sons, New York, NY ( 1997 ) 2. Bird R.B ., B.C Armstrong and 0. Hassager Dynamics of Pol yme ri c L i quid s, John Wiley & Sons New York NY ( 1977 ) 3. Reed J S., Prin ci pl es of Ceramics Pro cessi ng John Wile y & Sons, New York NY ( 1995 ) Fall 1 999 Graduate Education ] 4. Solymar, L ., and D Walsh Lectures on the Electrical Prop erties of Materials, 5th ed., Oxford Science Publications, Oxford England (1993 ) 5. Amato I ., Stuff-The Materials the World is Made Of, Basic Books, New York, NY ( 1997 ) 6 Shapiro, F R. "The Calculation of Crystal Diffraction Pat terns Using a Spreadsheet," J. Mater. Educ., 14 93 ( 1992 ) 7. Kingery W.D., H.K. Bowen and D.R. Uhlmann Introduc tion to Ceramics 3rd ed., John Wiley & Sons, New York NY ( 1993 ) 8. Cross, Nigel Engineering Design Methods John Wiley & Sons New York NY ( 1989 ) 9. Winner, R.I. J P Pennell H.E Bertrand, and M.M.G. Slusarczuk, "T he Role of Concurrent Engineering in Weap ons System Acquisition," IDA Report R-338 ( 1988 ) 10. Pahl, G ., and W Beitz Engin ee ring Design translated by K. Wallace The Design Council London and Springer Ber lin, Germany ( 1984 ) 11 Ashby Materials Selection in Mechanical Design Butterworth-Heinemann Ltd., Oxford England ( 1992 ) 12 Lewis G ., Selection of Engin ee ring Material s, Prentice Hall New York, NY (1990 ) 13 Stinson S ., Delving into Dendrimers ," Chem. Eng. News p 28 September 22 ( 1997 ) 14 Freemantle, M. Potential Trigger for Dendrimer Switch," Chem. Eng. News, p. 30, May 26 ( 1997 ) 15 Service R.F ., Paving the Information Superhighway with Plastic," Science 267, 1921 ( 1995 ) 16 Miller J S ., and A.J. Epstein Designer Magnets ," Ch e m. Eng. News, p 30 October 2 ( 1995 ) 17 Epstein A.J ., "Electricall y Conducting Polymers : Science and Technology, MRS Bull. 22 ( 6 ), 16 (1997) 18 Rothberg L .J., and A J Lovinger Status and Prospect s for Organic Electroluminescence," J Mater. Res. 11 (12), 3174 (1996) 19. Hanna, J., and I. Shimizu, Materials in Active-Matrix Liq uid Crystal Displays," MRS Bull. 21 ( 3 ), 35 ( 1996 ) 20 Agarwal M., M.R. DeGuire, and A H Heuer, Synthesis of ZrO 2 and Y 2 O aDoped ZrO 2 Thin Films Using Self-Assembled Monolayers ," J. Am. C eram. Soc. 80 ( 12 ), 2967 ( 1997 ) 21. Ritter S.K. Boning Up ," Chem. Eng. News p. 27, August 25 (1997 ) 22. Alivisatos A.P ., Semiconductor Nanocrystals ," MRS Bull. 20 ( 8 ), 23 ( 1995 ) 23. Mitomo, M. Y-W Kim and H. Hirotsuru, Fabrication of Silicon Carbide Nanoceramics ," J Mater Res. 11 ( 7 ), 1601 ( 1996) 24. Rittner M.N ., and R. Abraham, The Nanostructured Ma terials Industry ," Am. Ceram Soc. Bull. 76 ( 6 ), 51 ( 1997 ) 25 Kevorkijan, V M ., "An Ideal Reinforcement for Structural Composites, Am Ceram. Soc Bull. 76 (12), 61 ( 1997 ) 26. Newnham R.E "Molecular Mechanisms in Smart Materi als ," MRS Bull. 22 (5), 20 ( 1997 ) 27 Greer A.L ., "Metallic Glasses ," Science, 267, 1947 ( 1995 ) 28 Archambault, P ., and C. Janot Thermal Conductivity of Quasicrystals and Associated Processes ," MRS Bull ., 22 ( 11 ), 48 ( 1997 ) 29 Bloom B.S. ed., Taxonom y of Edu catio nal Obj ec tive s Hand book I: Cogniti ve Doma i n David McKa y Co., ( 1956 ) 0 265

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[ G r aduate Education A SURVEY COURSE IN PARTICLE TECHNOLOGY JENNIFER L. SINCLAIR Purdue University West Lafayette IN 47907-1283 I n the spring semester of 1998 an overview course in patticle technology was launched in the School of Chemi cal Engineering at Purdue University The student en rollment in the initial offering of this course was relatively high (25 students) for an elective course; hence the course is now being offered yearly in Purdue's spring semester. It will also be taught s tarting in the spring semester of 2000 via videoconferencing as a part of Purdue 's continuing educa tion program for practicing engineers, so me of whom are working part-time towards their Master s of Engineering de gree at Purdue. The objective of the course is to provide a broad overview of the field, with emphasis on concepts and practical appli cations. Specific topics include particle characterization, sedi mentation, gas fluidization pneumatic conveying, gas-solid separation, particle storage mixing, size reduction and en largement and dust hazards and explosions. About one week of coverage is given to each of the above topics; the empha sis is clearly toward breadth rather than depth At Purdue as well as at most other universities in the U.S., the current educational treatment of particle technology is limited to a one-semester course. This constraint dictates that the time available in a single-semester course is best spent in an overview fashion. Hence, emphasis is on relating to the students an appreciation for the many aspects of this complex field and on developing an awareness of the resources available to them if they find themselves working in industies involved with the processing of particulate solids. The overview course in particle technology is offered as a 500-level course available to junior and senior undergradu ates as well as to graduate students. Enrollment in the two offerings of the course to date has been an even mix of undergraduate and graduate students from a range of disci plines that includes chemical engineering, mechanical engi neering, food science, agricultural and biological engineer ing civil engineering, and pharmacy The textbook used in the course is Introduction to Particl e Technology by Martin 266 Rhodes (Wiley, 1998). The course includes guest speakers from several industrial companies such as Dow and DuPont. At least one field trip to an industrial company involved in solids handling is in cluded each semester so that students can see first-hand the many unit operations discussed in the lectures The course schedule for the spring 1999 offering of the course can be found in Table 1. Slurry flow is the only subject covered in the course that is not treated in the Rhodes text. Reading for this material is given as handouts and i s based on the text Bulk Solids Handling by Woodcock and Mason (Blackie Academic, 1987) Supplementary material for other lectures is taken from the following texts: Principl es of Powder Technology, Rhodes; Wiley 1990 Processing of Particulat e Solids, Seville, Tuzun, and Clift; Blackie Academic, 1997 Principl es of Gas-Solid Flows, Fan and Zhu ; Cambridge University Press 1997 Particl e Si ze Measurement, Allen; Chapman & Hall, 1997 Fluidization Engineering, Kunii and Levenspiel; Butterworth-Heinemann 1991 Pneumati c Conveying of Solids, Marcus Leung, Klinzing, and Rizk; Chapman & Hall 1990 Jen ni fe r L. S incl a ir is Associate Professor of Chemical Engineering at Purdue Univer sity. H er research interests are in the areas of gas-solids flow fluidization, and partic l e mechanics. She is the recipient of several teaching awards the NSF-PY/ award, and currently serves on the Executive Committee of the Particle Technology Forum Copyrigh t ChE Division of ASEE 1999 Chemical Engineering Education

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[ Graduate Education ) ~-----------------_.) INTRODUCTORY LECTURE The a im of thi s lecture i s to con vince s tudent s of the critical im portance of particle technolo gy and also to clearly show them that the concepts they learned in a typical engineering fluid s co ur se may not necessarily tran s late to the flow and storage of particle s. Thi s lecture se t s the stage and motivation for the course If done well with lot s of visuals, it is highly effective in imparting to st udents the importance of knowledge in thi s technical area. This same lecture works well as a recruiting tool to attract st ud e nt s to the course. At Purdue chemical engineering undergraduate s mu s t take a chemical engineering semi nar course every semester. During part of one class period in the semi nar co u rse, I pre se nt some key con cepts from this introductory par ticle technolog y lecture to all of the chemical engineering stude nt s. Many of the st udent s end up regis tering for the particle technolo gy course becau se of the material co tained in this presentation. I have also given the le ct ure to indu strial visi tor s to our university; they are usually "so ld on particle technol ogy after hearing it. The ba sic components of this lec ture are a definition of particle tech nology a presentation of the im portance of particle technology in industry and a presentation of ex amples in which particles behave in a unique way, often very differTABLE 1 Co ur se Sc hedul e January 12 introduction 14 Particle characterization 1 9 Particle characterization 21 Particle size mea s urement 26 Sedimentation 28 Sedimentation February 2 Packed bed s 4 Fluidization 9 Fluidization II Exam#l 16 Pneumati c co n vey ing 18 Pneum atic co nv ey ing 23 Ga s-so lid se paration 25 FIELD TRIP: ational Starch March 2 FIELD TR I P: Cargill 4 Slurry flow 9 Part icle mixing II Exam#2 23 Guest Lecturer: R ead ing in Rhod es Chapter 3 Chapter 3 Chapter 3 Chapter 3 Chapter I Chapter 2 Chapter 4 Chapter 5 Chapter 5 Chapter 6 Chapter 6 Chapter 7 Notes Chap t er 9 Rachel Anderson, Dow Chapter 8 Design of Particle Storage D ev ices 25 Guest Lecturer Rachel Anderson D ow Chapter 8 De s i g n of P a rticle Stora ge D ev ices 30 Guest Lecturer : Moh se n Khalili DuPont "Case Studie s in Particle Technology Apri l I Gue s t Lecturer: Moh se n Khalili DuPont Case Studies in Particle Technology 6 Particl e s i ze reduction Chapter IO 8 Particl e size en lar ge ment Chapter 11 13 Gue s t Lecturer : Profe sso r Was sg ren, MechE Purdue Simulation of Particle Flow" 15 Du s t hazards/explosion s 20 Oral pre se ntation s Project 22 Exam#3 27 Oral presentation s Project 29 Oral presentation s Project Chapter 12 project s tudent s work in team s to investigate one s pecific topic i n par ticle technology in detail. The team project comprises one-third of the course grade, and the last lecture s of the course each semes ter are de voted to presentations of the gro up projects The project brings depth in one particle technology topic to a course that emphasizes breadth. The project also provide s ad diti ona l ex perience for the s tudents in the team work and communication skills that are essential on the job. A course project is very attractive to the st udent s because they can work in an open-ended fashion on a particle technology s ubj ect of their choosing Most undergraduate s en joy the team aspect of the course project since they are accustomed to working in teams in their se nior engineering de sig n courses and, for some, in their co-op position s. The grad uate students like the course project becau se they are given the opportunity to probe topic s dis cussed in lecture in more detail. Many of the graduate students who enroll in the course want s pecific topics along the lines of their grad u ate research developed in grea ter detail than the treatment give n in the lecture s. Since this is not pos sib le in th e lecture s, given the time constraints, the course project of fers another format for meeting these s tudents expectations for the co ur se. In the course project, the s tudents ently than fluids. In most of these examples, I give a vis ual picture to the a udience either b y illu strating with a real particulate material o r through the use of a graph, photo graph, etc. are engaged in both background re sea rch and in makin g a forward step, that i s, moving beyond what is c urr ently known and putting forth so mething n ew. The "somet hing new can take the form of a research pro posal, new theory, new insight, new calculations, new data (some st udent s have access to appropriate experimental fa cilities in their research gro up ), etc In the course at Purdue the weighting on the background research vers us the "so me thing new portion of the project i s approximately 75/25% An outline of the introductory lecture can be found m Table 2 ( next page) COURSE PROJECT One of the key components of the overview course in particle technology, in addition to the traditional lecture homework, and exam format, i s the course project. In the Fall 1 999 Students work in teams of three to four people. The teams and their presentation dates are chosen randomly b y picking number s out of a hat during the first class meeting. At least 267

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[ Graduate Education fifteen minute s i s allocated during the fir s t lecture period for the group members to exchange contact information and class schedules, briefly get to know one another and to decide on a group leader. Other opportunitie s are given during the semester toward s the end of cla ss periods for group di s cu ss ion s students s eem to be relieved when a project direction i s decided on quickly and ea s ily The only group conflict that has arisen to date ha s been when two graduate student s were on the s ame team and the y had area s of graduate re se arch specialization in particle technology that invol ve d little over lap. For that team coming to an agreement on a project topic required a lot of compromi s ing among the group member s The teams are given three weeks to decide on a project topic. Student s are instructed to peru s e the titles of article s in the journal s of Powd er T ec hnolog y and Particl e S c i e n ce & Technolo gy to s timulate idea s for projects Often when a graduate s tudent is one of the team member s, he or she take s on the leader s hip role and guides the c ourse project to a topic related to his or her graduate research. This pattern of the graduate s tudent taking charge of the team ha s not yet cre ated any group conflicts; rather many of the undergraduate Focu s areas for project topics have spanned the s pectrum of particle sizes and particle science and technology applica tions. Representative topic s have included Use of Electrokinetic Sonic Amplitude in th e Characterization of Colloidal Susp e nsions Particl e Size Di stri buti o n Effects in Pn eu mati c Conve y ing Novel D es ign s for FCC R eac t o r s Use of Simulation T ec hniqu es to Imp rove Cyclone D esign TABLE2 Outline of Introductory Lecture Particle Technology Particl e t ec hnolo gy r efe r s t o th e sc i e n ce a nd t ec hn o l ogy related t o th e handlin g a nd processing of particl es and powders Also kn o wn as powd e r t ec hnolo gy (so metime s when th e parti c l e s i ze i s l ess than I 00 mi cro n s) Powder s or p arti cle s a l so r efe rr e d to as part i c ulat e so lid s, bulk so lid s, a nd granular so lid s Particl e t ec hnolo gy in c lud es so lid particl es as well as liquid dropl e t s, e mulsion s, a nd bubbles Wet/dry particulate syste m s-w ith a nd w ith o ut liquid Importanc e of Particle Technology 62 % of DuP o nt s 3000 produ c t s inv o l ve particl es (C hE Pr og r ess, 1 99 4 ) 50 % of D ow Chemical 's product s R a nd Corporation Stud y (C h E Pro gress, 1 985) 37 so lid s pro cess in g plant s s tudi e d 2/3 o p era ted a t l ess th a n 8 0 % d esig n capaci t y 1/ 4 opera t e d a t l ess th a n 4 0 % d es i g n capac it y (9 5 % i s average for th e CPI as a w h o l e) I g n orance of p ar ti c l e technology often res ult s in l oss of p rod u ct i o n poor produ c t qu al it y, he a lth ri s k s, du s t exp l os i o n s, a nd s torage s il o co ll apse T yp i ca ll y, 20-25 d ea th s occ ur eac h year du e t o failures in parti c l e technology o p era ti o n s. Particl e t ec hnolo gy impa c t s fields of c h e mic a l e n g ineering, m ec hani ca l e n gineer in g, agric ultu ral e n g ineerin g, food e n g in eering a nd food sc i e nce, e l ectrica l e n g ineerin g c ivil e n g in ee rin g, pharmaceuticals, m e tallur gy, and min e ral s e n g ineerin g In eac h of the se fi e ld s I g i ve exa mple s o f proce sses involving particle t ec hn o l ogy. I also ask th e s tud e nt s fo r input here b eca u se th e students in th e co ur se co m e from a di verse set of science and e n g in ee rin g b ackgro und s. Particles Do Not Necessarily Behave Like Fluids 268 P a rticl es expan d in a dry bulk asse mbl y when s h eare d. W a lkin g o n sa nd at th e b eac h i s a good exa mpl e of p a rticle ex pan s ion durin g s h ear. The ability of particl es t o form a heap. Visual-tw o diff e r e nt t y p es of particulat e m a t e rial and a di sc u ss i o n of the a n g l e of r e p ose a nd h ow p arti cl e co h es i v it y influenc es fl ow behavior. Difference s in pr ess ur e drop b e h av i or in pipelines in a s in g l eph ase gas ve r s u s a gas-partic l e mi xture. Visual Show a nd di scuss a grap h of h ow it i s p oss ibl e in d e n seph ase co n veying of particulates to h ave a r ed u c ti o n in pr ess u re drop with a n in crease in gas ve l oc it y a t a co n s tant so lid s flowrate. Also di sc u ss h ow th e a dditi o n of a s mall fra c tion of ve r y fine particl es t o a turbulent fluid m ay ca u se a reduction in th e pr ess ur e drop Particle flow behavi or in bends can b e very probl e matic Visual -A n illu s tration of th e roping phenomena; a n ac tual pipe bend ruin e d b y eros i o n Parti c l e s t orage in hopp e r ca n also b e problematic Visual -Mass fl ow ve rsu s funn e l flow -s t ag nation r eg ion s d o n o t occur in fluid s t o r age in a s imil a r vesse l ; plu gg in g of th e outlet of a h o pp e r. Particl e fl ow rat e out o f h o pp e r as th e h ea d d ec r eases. Visual -C l ea r hopper and observation of o utl e t fl owra te as a functi o n of h ea d -co ntra st with fluid fl ow out of a t a nk as he a d d ecreases. P article bulk density var i es w ith tapping ." Visual T a ppin g of a fine particul a t e material in a via l a nd obse r va ti o n of vo lum e occ upi ed by particulate material -co ntr as t w ith a s in g l epha se fluid in a via l. Large particle placed a t th e b ono m of a co nt a in e r of a dry gra nul ar m a t e ri a l will ri se t o t he s ur face if the co nt a in e r i s v ibrat ed in a vertical plane Visual -S hakin g of a parti c ul a te mat er i a l in a vi a l co nt a inin g one lar ge r particl e and observation of th e l arge particl e mov e m e nt. Fi LI vo lum e of two t y p es of particle s can depend on th e order of fillin g of the co nt a in e r. Visual -F illin g a j ar with t wo sizes of nut s a nd o b se r va ti o n of vo lum e occ upi e d -co ntr ast wi th co mbinin g two fluid s a nd th e re s ultin g vo lum e. Stirring a mixture of two types of p articles of diff e r e nt sizes m ay re s ult in segrega ti on rather th a n impro ve d mixing qu ali t y Visual Ph o t ogra ph s of seg r ega ti o n pattern s b efo r e a nd afte r a bl en din g o perati o n -co ntr ast with mi x in g of two fluid s Chemica l E n g in ee rin g Educa tion

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Probing the Mechanisms of Particle Charging Ultra High P e ,fonnan ce Electrostatic Precipitators Moisture Content and Caking in Foodstuffs There are four aspects to be graded in the overall course project: 1. The first is a written report of at least ten pages prepared by the group that summarizes the background information on the topic and the novel aspects of the investigation 2. The second is an oral pre se ntation of the topic, thirty to forty five minutes in length All of the group members are required to participate in the oral presentation Typically one student outlines the discussion points in the beginning of the pre senta tion and then the team members take turns speaking on each of the presentation bullets. Often the pre se ntation s are supplemented with visual aids or a short demonstration to introduce the topic and capture the attention of the audience. The oral presentation is followed by a questioning period. During the questioning period each of the project teams in the audience is required to ask at lea st two questions of the presenting team This requirement is highly s uc cessfu l in keeping the class engaged in the presentations; the students also often generate outstanding question This peer que stio ing is one aspect of peer review (see task #3 below) that is incorporated into the course project to help develop the communications skills of the students. After the questioning period is over, the instructor gives the presenting team immediate feedback, both positive and negative in front of the entire class. This helps to improve the quality of the subse quent presentations since s tudent s get a better understanding of what i s s ucce ssfu l what are some of the pitfalls, and what are the standards expected for the presentations. 3. Every team performs a peer evaluation of each of the other teams The peer evaluation is on both the written and oral presentations of the course project. In the written report, eac h team serves as a reviewer of the other team report s, marking grammatical and typographical errors directly on the manu script. They write a short summary of the manuscript that includes an overall evaluation, specific positive aspects, constructive criticisms and suggestions. For the oral pre se nta tions a structured evaluation form i s u sed that i s provided by the in s tructor. Therefore at the e nd of the peer evaluation proces s, each team ha s a large amount of anonymous feed back-a written and oral report from each of the other team s. Although these peer evaluations do not influence the grade of the team being eva luated they are very in str uctive; the students tend to listen and readil y accept the comments from their peers. The peer evaluations prepared by each team are graded for thoroughne ss and level of in s ight by the instructor. The value of peer review has been documented in the litera ture ,ll 5l and it s benefit s are abundantly evident in the particle technology course. Perhaps this i s due to the fact that the course is an elective course. Presumably students already have some interest in the topic when they enroll in the course and the peer review merely enhances their involvement in it. Students take the reviewing task seriously. T h ey do an excellent job in identifying the stre ngth s and weaknesses in the Fall 199 9 Graduate Education ] work of th eir fellow st ud e nt s. The peer review also aids th e stude nt s in recognizing the stre ngth s and weaknesses of their own oral and written r e port s. 4. Finally each team member s ubmit s to the instructor a s ummary report of the relative co ntribution s of each of their own group member s, including an assessment of their own contribution to the team effort. This help s the in st ructor assign appropriate individual gra de s to the gro up project. Aside from the technical benefit s a particle technology project brings to the course there is the additional, more general benefit of improving team ski lls Team skills are a requirement for a s ucces sfu l workforce; about 80 % of U.S organizations use teams to accomplish tasks.l 61 In technical fields, teamwork i s particularly crucial as engineers and scientists become more s pecialized. Students through the course project gain more experience in how to capitalize on the unique skills of others and, in tum, they often learn more about their own capabilities. In addition, they learn better how to motivate others, how to organize a group effort, and how to manage in difficult team s since team members are not reassigned even if a team is having problems working together. In fact, student feedback indicate s that while being a member of a problem team" is certainly not a pleasant experience, those team members are the ones that make the s trongest comments about their huge learning experiences in team skills. SUMMARY A s urvey course in particle technology is a highly effec tive way to introduce the basic s in this field to a diverse group of students. A "gee -whiz -type introductory l ecture help s sell the importance of particle technology to different audiences. Visuals enhance presentation of the unique fea tures of particulate systems. Incorporation of a team project into the course allow s for s tudents to focus on one particular topic in particle technology and adds depth to the breadth of material covered in thi s s urvey course. Also, the course project bring s many positive factors to the learning experi ence of the students. REFERENCES 1. Elbow P., Writing Without T eachers, Oxford University Press New York NY (1973 ) 2. Grimm, N ., Improving Students Responses to Their Peers' Essays, Colleg e Comp. and Comm., 37 91 (1986 ) 3 Herrington A., and D Cadman, Peer Review and Revising in an Anthropology Course, College Comp. and Comm., 42, 184 ( 1991 ) 4. Holt M ., "The Value of Written Criticism College Comp. and Comm 43 384 ( 1992 ) 5. Newell J. "Using Peer Review in the Undergraduate Labo ratory," Chem. Eng. Ed ., 32 194 ( 1998 ) 6 Robbins S Organi za tional Behavior, 8th ed Prentice-Hall Upper Saddle River NJ, 284 ( 1998 ) 0 269

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[ Graduate Education ] '------------------~ EXPERIENCES WITH AN EXPERIMENTAL PROJECT IN A GRADUATE CONTROL COURSE EDWARD P. GATZKE, RAJANIKANTH V ADIGEPALLI, EDWARDS. MEADOWS, FRANCIS J. DOYLE, III University of Delaware Newark, DE 19716 A graduate-level class on process control traditio~ ally employs a standard lecture-style course, possi bly coupled with an independent course project car ried out in a simulation environment. If one steps back to critique this approach, it is important to first address the skills required by a practicing process-systems engineer. As a guide to the requisite abilities required of a process systems engineer, one may consult the list of control design steps provided by Skogestad and Postlethwaite 1 1 1 shown in Table 1. Is the typical engineering graduate well prepared to accomplish these tasks? There have been no comprehensive studies to answer this question, but Kheir et al.,C 2 1 reported the results of an informal survey of industrial employers of control engineers. The highest rated aspects of the current methods of control education were control-system knowl edge, job preparation, and curriculum. The analytical skills of the students were considered strong. Such responses seem to indicate some success for items 7 through 9 of Skogestad' s list of control-design steps, areas that correspond to skills Ed Gatzke received his BSChE from the Georgia Institute of Technology in 1995. After two years of graduate study at Purdue University he moved to the University of Delaware for completion of his PhD. He has held intern ships with Teledyne Brown Engineering Mead Paper and Honeywell His interests include process control optimization and artificial intelligence Raj Vadigepal/i received his BTech from the Indian Institute of Technol ogy, Madras in 1996, and began his PhD research in chemical engineer ing at Purdue University in the fall of 1996. He moved to the University of Delaware in 1997 to complete his doctoral degree with Professor Francis J Doyle His research focus includes modeling and analysis of control mechanisms in biological systems and distributed hierarchical methods for control of large-scale process systems. Edward S Meadows is a postdoctoral fellow at the University of Dela ware working in the areas of modeling and control of polymerization reactors as part of a broader research program in optimization and control of chemical processes. He received his PhD degree from the University of Texas in 1994 Frank Doyle received his BSE from Princeton in 1985, his CPGS from Cambridge in 1986 and his PhD from Caltech in 1991 all in chemical engineering He was an Assistant Profe ssor at Purdue University before coming to the University of Delaware as an Associate Professor in the fall of 1997 and his research interests are in the areas of process and biosystems analysis and control typically emphasized by a theoretical, textbook-and-lec ture control course Unfortunately, existing approaches to control engineering education are not necessarily producing engineers who are as knowledgeable in other areas. The Kheir survey respon dents reported that control engineers received lower ratings in the areas of laboratories, hands-on experience and inter personal skills. The course described in this paper uses both a standard lecture class and an experimental group project related to the course material. This provides an opportunity to address the deficiencies identified by Kheir and colleagues while reinforcing the positive aspects of traditional control engineering education methods COURSE DESCRIPTION In the latest (fall, 1998) offering of this course, Advanced Process Control there were seven students enrolled for a grade and five students auditing the class. Of the seven students taking the class for a grade five were University of Delaware graduate s tudents and two were industrial profes sionals enrolled for continuing education credit. As a main reference, the course used the text by Skogestad and Postlethwaite,l 1 1 and the major topics covered in the course included Classical multivariable control Analysis of performance limitations Uncertainty characterization Robust controller synthesis Control structure selection and plant-wide control One of the key strengths of the Skogestad and Postlethwaite text is the treatment of performance limitations and this topic was covered in depth in the lecture and reinforced via the experimental project. The course project was assigned in Copyr i gh t C hE D iv i s i o n of ASEE 1999 2 7 0 Ch e mi c al En g in ee rin g Edu. c ation

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the middle of th e se m es ter and the s tudent s were given th e choice of a theoretical independent course project (related to their the s is r esearc h ) or the opportunity to work on the experimental sys tem as a group project. Of the fi ve on-site students four elected to cruTy out th eir project using the experimental four-tank sys tem EXPERIMENTAL SYSTEM An interacting four-tank proce ss i s currently u se d in both the e le c ti ve multidi sc iplinar y undergraduate control laborator y a nd the a d va n ce d graduate control course. The de s ign i s in s pired by the benchtop appara tu s de sc ribed in Johan sso n and Nune sY 1 A s imple sc hematic i s s hown in Figure 1. Two voltage-controlled pump s are used to pump water from a basin into four o ve rhead tank s. The two upper tank s drain freely into the two lower tank s, and the two bottom tanks drain freely into the re se rvoir ba s in The liquid level s in the bottom two tank s are dir ec tl y me as ur e d with pre ss ure tran s ducer s, and the top tanks ha ve hi g h-lev e l alarm signals generated by electro-optical se n so r s. As can be see n from th e schematic, the piping sys tem is configured s uch that each pump affects the liquid level s of both mea s ured tank s. A portion of the flow from one pump flow s directly into one of the lower-level tank s where the l eve l is monitored The re s t of the flow from a single pump i s diverted into an overhead tank which drain s into the other monitored t a nk. By adjusting the bypa ss valves on the syste m th e amount of interaction between the two pump flowrate s ( input s) and the two lower t a nk level height s (o utput s) can be va ri e d For this work it i s ass um ed that an external unmea s ur e d di s turban ce flow m ay also be pr ese nt that drains or fill s the top tank s. The original work of Johan sso n and Nune sl 31 employed tank s with a volume of 0 5L. The pre se nt work u ses l 9L ( 5 gallon) tank s, attempting to create a visual impre ss ion of practical realit y for the s tudent s. Th e scale of the apparatus i s indicated in Figure 2. In the lower right-hand TABLE 1 Steps in Control System Design I Stud y th e sys t e m ( pl a nt ) t o b e contro ll ed a nd ob t ai n initial in format i on abou t th e co ntrol ob j ec ti ves. 2. M ode l th e sys t e m and si mplif y th e m ode l if n ecessary 3. A n a l yze th e r esu ltin g model ; de t ermi n e it s propertie s. 4. D ec id e w hi c h var i a bl es are to be co ntr o ll ed (co ntroll ed o utput s). 5. Select th e co ntrol configuration. 6. D eci d e on the type of contro ll er to be used 7. Decide on p e rforman ce s pe c ifi ca tion s, b ase d on the ove rall co ntr o l o bj ec ti ves 8. Design a co ntroller. 9. Analyze th e resulting co nt ro ll ed system t o see if the s pecifications a re sat i sfied; an d if th ey a r e not sa ti sfie d m o dif y th e spec ifi ca tion s or th e t y pe of co ntroll e r. 10 Simulate the r es ultin g co ntroll e d sys t em, e ith er o n a co mput e r or pil o t plant. I I. R e p ea t from ste p 2, if necessary 1 2. Choose h a rd wa r e and so ftware, and impl eme nt the contro ll er. 1 3. Test a nd va lid a t e th e co ntrol sys t e m a nd tun e the contro ll er o n-line if neces sa ry F a ll 1 999 Graduate E d ucation ] co rn er of th e photograph o n e can see the di s play of a computer co ntrol sys t e m u se d as an interface to the ex periment. A Baile y Freelance Di s tributed Con trol S ys tem ( DCS ) was employed to introduce the s tud e nt s to act u a l operating sof twar e employed in industry Furthermore the PC-ba se d architec tur e mad e th e sys tem cos t-eff ec tive for a univer s it y ap pli ca ti o n a nd facilitates h a rdware and sof ware up gra d e path s. Th e experimental pack age consists of three se paFigure 1. Schematic of the four-tank system. _1__11 ~;:/' -~-, -. :1.I t I I ~ ff~ -~ :~--~-..~, .. Q~ ,r ~ .. .: p~/' .J ~ '; I "\. II ~ ,:. '--. t _.:,4 -. t:' ~,;\:;;: r.:. ,, I Figure 2. Laborator y apparatus. 27 1

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[ Graduate Education rate components, as shown in Figure 3: 1. Experimental Station: tanks l eve l sensors, level alarms valves, and pumps 2. Pro cess Station: hardwar e that c arries out the c ontrol input-output and communicates between the E x peri mental Station and the Operator Station 3. Operator Station: PC-based sys tem were Process Station information is monitored and modified The Process Station communicates with the Operator Sta tion over a private TCP/IP network The Freelance applica tion package DigiTool was used to create a process database that i s loaded onto the Process Station. The DigiVis applica tion allows operator interaction with the Process Station and process database Operator displays were created that al lowed the students to operate the four-tank system (see Fig ure 4) as well as to track the trends of key operating variables (see Figure 5) For the graduate control class it is necessary to use more complex control algorithms than can be easily implemented using the Freelance packages. Matlab/Simulink can be used to calculate the control moves needed for the experimental system. A Dynamic Data Exchange (DDE) interface is used to link Matlab/Simulink with Freelance. The Simulink dis play ( Figure 6) emulates a standard s imulation flowsheet. By default the Bailey DCS controls the process using manual or PID control. Once the student ha s "toggled" control (to Matlab from Bailey), however, the Simulink "simulation" drive s the inputs to the Bailey system as the simulation proceeds This creates a very flexible environment for imple menting complex control algorithms on a moderately com plex experimental system. M ATHEMATICAL DESCRIPTION OF THE PROCESS Both a nonlinear model and a linearized model are given in Johansson and Nunesr 31 for the four-tank system. The models used for this work include the disturbance effects of flows in or out of tanks 3 and 4. The nonlinear differential equations governing the heights in this four-tank system are given in Table 2, and the linearized version is seen in Table 3. The liquid levels in tanks one and two, h 1 and h 2 are considered measured variables. The speed of the pumps, v 1 and v 2 are considered as manipulated inputs. The pump s peeds are manipulated as a percentage of the maximum pump speed. The disturbances d 1 and di model the unmeasured disturbance effect s of flows in or out of tanks three and four This model is a simple mass balance assuming Bernoulli's law for flow out of the orifice. The gamma values 'Y ;, correspond to the portion of the flow going into an upper tank from pump i. In Johansson and Nunes,r3 1 it is shown that inverse response in the modeled outputs will occur when 272 J Operator Station Process Station Expe rim e nt a l Station -----I ............ ,. ............................ CANB TCM, l ,---,;;,--; o[Q et_ Matlab DigiT oo l ________ .,_ Process St a tion Pr ocess Measurments "" DigiVi s ----D a tab ase ---- Proces s Inputs "DigiDDE _.. .Figure 3. Schematic of the con trol system. Fig u re 4. Scre ens hot of Fr eel an ce four-tank schematic Fig u re 5. S c reenshot of Freelance tank-lev el trends. Chemical Engineering Education

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[~ ___ ______ _______ _____ _____ ______ ____ G ra d u a t_e_E_d_u_c_a_u__o_n _~] dx = dl Fall 1999 TA B LE3 y 1 + y 2 < 1 A modification introduced by the s tudent s in the clas s was t h e pre se nce of a di s turbance introduced b y a s ubmer s ible pump in the upper tank s The se di s turbanc es' effects are modeled as a constant leak into or out of the upp e r tank s. PROJECT SUMMARIES To illu stra te th e u se of the four-tank syste m in the graduate control course, th e following project s are briefly de sc ribed It s hould be noted that each of the four elements ( modeling analy s i s, sy nthesis a n d imple mentation ) was performed b y each s tudent group. A more detai l ed theo retical treatment of the re s ults can be found in Vadi ge palli et al. l 4 l L in ea r ize d Mo d el E qu a ti o n s PROCESS IDENTIFICATION I 0 0 0 -T1 0 I 0 0 -T 2 0 0 I 0 -T 3 I 0 0 0 ---ON -1--. -i-. ,-1 .-mi--2-12 nN .......... ........ 2-DlokWe t; ock to~ MA-tu.a takM--dDC I c ........ T 4 Y1k1 0 A1 0 0 0 Y 2 k 2 0 0 A 2 -~ 0 x + (l-Y 2 )k 2 u+ 0 A 3 A 3 0 k d, (l-Y1)k1 A 4 0 A 4 Ti=~ thi ( O ) a i g 1----.i .. ,. '---F igur e 6. S cree nshot of the Matlab interface. d Although the fundamental model de sc ribed earlier i s a r easo nably accurate de sc ription of t h e system dynamics ma n y of the parameter s are not availab l e a priori which r e quired estimation of several model par a meter s. The tank areas Ai can be mea s ured directly from the apparatus Using tank dr ai n age dat a, the cross-sectional out let areas a i ca n also be determined. The s teadys tate operating points of v 1 = 60 % and v 2 = 60 % were use d for s u bseq u ent ....... .. re s ult s. The sys tem valves were se t s uch that the operating point exhibits inverse re s pon se ( y 1 + y 2 < 1 ). Time constants T i, for the lin ear sys tem model were on th e order of 40 seconds The s tudent s designed a suit able te s t input sequence to gen erate data for the estimatio n of the remaining parameters. In this case, they elected to identify the parameter s of the original non linear model requiring the solu tion of a nonlinear optimization problem The problem was for mu l ated to minimize t h e 2-norm of the difference between t h e nonlinear model a n d actual mea surements, searching over fo u r parameter s Using dy n amic data from the experiments, the optimi zation routine found the optimal pump gai n s ki and gamma values y i as depicted in Table 4 A simi lar routine was employed to model the characteristics of the distur bance introduced by the submers ible pump s, kct and kct 2 273

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[ Graduat e Edu c ation A critical step in any identifica tion procedure i s validation of the model against novel data The s tu dents were successful in validating the model that resulted from the pre vious optimization problem They were able to capture the known in verse response in the system and they also were able to compare the nonlinear model response to a lin ear approximation which was sub sequently used for analysis. TA B LE 4 and the four-tank system in particular i s the location and direction of multi variable proce s s zeros. For the operat ing conditions in this study, the multi variable zeros are found to be at-0 0791 and 0.0285 rad/sec The input zero di rection corresponding to the right-half plane (RHP) zero is [-0 715, 0 699] T, and the output direction is [0 718 0.696] T From these directions one can s ee that forcing one pump up while the other is forced down causes the sys tem to display inverse re s ponse The presence of the RHP-zero could al s o Model Parameters ACCEPTABLE CONTROL ANALYSIS As mentioned earlier one of the a 1, a 2 a A l A, A A v 1 ( 0 ) v 2 ( 0 ) T l T T T 2 3 cm 3 2. 3 cm 2 7 3 0 cm 60 % 60 % 53.8 se c 48.0 se c 3 8.5 sec 3 1.1 s ec key insights derived from this course is the limitation to achievable closed-loop performance due to intrinsic system properties. Once the students had obtained the physical mod els of the system they computed a linearized approximation at a steady-state operating point and analyzed the controlla bility propertie s of the resulting linear s ystem. The inputs and outputs of the system were appropriately scaled before the controllability analysis was carried out. The first metric considered was the relative gain array (RGA) as a function of frequency. For the system configura tion employed in this study the students found that the diagonal RGA elements were very near to 1 at low fre quency suggesting an easily decoupled system. But as the frequency increased to the bandwidth region, the students discovered that the diagonal RGA values de creased significantly indicating the importance of multi variable interactions in the bandwidth of interest. Such an insight is particularly valuable at the graduate control level to highlight the limited interpretation of the s teady state RGA value. Additional insight is derived from an analysis of the singu lar values of the system. More specifically their ratio (the condition number) gives an indication of the sensitivity of the plant to uncertainty The condition number at low fre quencies was small between 1 and 3. But it decreases with frequency implying that the plant is more sensitive to uncer tainty at steady state than at higher frequencies. In addition the low frequency minimum singular value is above 1. This means that adequate control action should be possible; the input moves will be able to move the outputs a sufficient amount to track setpoints The minimum singular value of the plant is greater than 1 up to the frequency of oo=0 007 rad/sec. Thi s indicates a poten tial constraint on the controller bandwidth because of high frequency input saturation Another quantity of interest in control systems in general, 27 4 kl k, g h 1 ( 0 ) I h ( 0 ) h ,( 0 ) h .( 0 ) 5 51 cm 3 /s 6 58 c m 3 /s 9 8 1 e mf s 0 333 0 307 14 1 cm 11. 2 cm 7 .2 c m 4 .7 c m be seen in a plot of the RGA in that the elements of the RGA change sign from frequency oo =0 to frequency oo = ~. The lesson that the stu dents will take away from this analysis is that the RHP-zero also limits the controller bandwidth. UNCERTAINTY CHARACTERIZATION For completene s s in the overall project de s cription the topic of uncertainty characterization is briefly mentioned The technical details can be found in Vadigepalli, et al. l 4 l The emphasi s was on bounding the uncertainty between the approximate linear model that was used for controller syn thesis and the actual physical system with parametric uncer tainty. A multiplicative input uncertainty s tructure was de termined by the students to adequately repre s ent the actual non-ideal behavior of the system. After subjecting the linear model to parametric variations ( % in Y; and k;) approxi mate bounds were determined from the corresponding fre quency plots of the multiplicative uncertainty This uncer tainty characterization i s central to the robust controller de sign task that is described below ROBUST CONTROLLER DESIGN AND IMPLEMEN T ATION The students employed robust control theory to initially design an H = controller following the procedures detailed in Balas et al Y 1 Using a D-K iteration procedure a robu s t 12t11-order controller with a structured singular value, less than 1 was obtained. The controller was implemented in the real system As one might expect with a physical s ystem the simulations did not precisely match reality. The nonidealities of the pumps level s ensors and head losses in the piping all contributed to these discrepancies Other unmodeled phe nomena witnessed by the students include the formation of vortices in the upper water tank s above the drainage hole s and spontaneous triggering of the level alarms due to con densation Despite the Jack of perfect agreement between theory and practice the students were able to generate conC h e mi c al E n g in ee rin g Edu ca ti o n

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[ Graduat e Education ] ~---------------' trailers with robust performance guarantees. Representative results demonstrating the disturbance rejection capa bility and setpoint tracking performance of one controller design are shown in Figures 7 and 8 respectively. This controller was designed for disturbance rejection which results in excessive input moves for setpoint moves. A robustly performing setpoint tracking controller was also implemented. This design requires an additional setpoint filter in order to satisfy the constraints on the input moves. The students clearly mastered a moderately complex control problem. ::: r= :: =;?~~ '. =?::=1 0 500 1000 1500 2000 2500 3000 ,: ._______._t : .........______I : ______.__i __.___._._: __._____.: l 0 500 1000 1500 2000 2500 3000 l~ ~~-,~--~,-~,.4:r bloN~ 0 500 1000 1500 2000 2500 3000 Time (seconds) Fig ur e 7. Disturbance rejection using robust controller. 13 f:: t~1 00 ~------------r :;-w;., l 0 500 1 000 1500 2000 2500 3000 ,uj 1500 2000 2500 3000 Time (seconds) F i g ur e 8 Reference tracking using robust controller. Fall 1999 SUMMARY We have described the use of an elegant experi ment for reinforcing the theoretical content of a typical graduate control course Although the over all physics of the process are not very sophisti cated, we have shown that the system exhibits rich behavior that can be used to e~ercise principles in modeling, analysis, and advanced control design. The use of a PC-based DCS coupled with MATLAB/Simulink was particularly effective in the implementation of the laboratory control pro cess. The PC-based system was more flexible than traditional DCS systems and the DDE interface facilitated a range of complex control designs t h at are appropriate for the graduate level. Our ongoing efforts with this experiment in clude the use of the four-tank system in a multidisciplinary control engineering laboratory. The course was first offered in the spring of 1999 as a senior-level elective and drew students from chemical electrical, and mechanical engineering. We plan to report our experiences with this imp l mentation in a future publication ACKNOWLEDGMENTS We would like to acknowledge the support of our former Dean Stuart Cooper who first encour aged us to create such a lab and provided the initial funding The continuing support of our department Chair Eric Kaler, and Dean, Andras Szeri, is grea t ly appreciated. None of this work wou l d have been possible without the expert craftsmanship of George Whitmyre who constructed the four-tank system. We would also like to acknowledge the additional graduate students who worked on the four-tank sys tem-Luis J. Puig and Radhakrishnan Mahadevan. REFERENCES 1. 2 3 4 5. Skogestad S and I. Postlethwaite Multivariable F e edback Control John Wiley & Sons New York, NY ( 1996 ) Kheir N.A., KA .Astrom D. Auslander KC Cheak, G F Franklin, M.M Masten and M Rabins, "Con trol Systems Engineering Education, Automatica, 5 1(8), 147 (1995) Johansson, K.H., and J.L.R. Nunes, "A Multivari able Laboratory Process with an Adjustable Zero," in Proc Am e rican Control Conf ( 1998 ) Vadigepalli, R., E P Gatzke, and F.J. Doyle III, Robust H Control of a Multivariable Experi mental 4-Tank System ," in preparation ( 1999 ) Balas G J. J.C Doyle K. Glover A. Packard, and R. Smith, -Analysis and Synthesis Toolbox User's Guide, The Mathworks, Natick, MA (1995) 0 275

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Random Thoughts .. FAQS II Active Learning vs Cover i ng the Syllabus and Dealing with Large Classes RICHARD M. FELDER, REBECCA BRENT North Carolina State University Raleigh, NC 27695 I n an earlier column,l 11 we listed the top ten questions we get at teaching workshops and responded to the first one ("Is there any hard evidence that the instructional meth ods we recommend actually work?") In this column we consider two more questions. Early in our workshops-usually within the first 15 min utes-we suggest that instructors include brief active exer cises in their lectures. Some participants invariably express concern that they have to present a lot of material in their courses, and one of them poses Question #2 : How can I take the time for those exercises and still cove r the s y llabus ? Another follows up by observing that he or she teaches a lecture class to 175 students and raises Question #3: Can you use these methods in large classes? Can you use active learning and still cover the syllabus? A huge volume of material can be "c overed" in a short period of time. If you put all of your lecture notes in PowerPoint or on transparencies and flash through them in class, you can get through several hundred pages of text in a month. The question is, what is your objective ? If it i s simply to present all of the prescribed course material, re gardless of how much or little of it the students actually absorb, then you should not use active learning exercises they do indeed slow things down. On the other hand if the objective relates to what the students learn as opposed to what you present, then the goal should not be to cover the syllabus but to uncover the most important parts of it. People acquire knowledge and develop skills only through repeated practice and feedback, not by watching and listen ing to someone else showing and telling them what to do .' In For th eo r et ical and empirical support of this claim, see any text on cognitive psychology written in th e last twenty years, e.g., Pressley and McCormick J 2 1 276 lecture classes most students are neither practicing nor re ceiving feedback on anything. They are just sitting there sometimes watching and listening to the lecture, sometimes thinking of other things sometimes daydreaming or sleep ing. Mo s t of them would learn just as much if the classes were cancelled and they were simply given the lecture notes and homework assignments and perhaps review sessions before the tests. It' s a much different story if lectures are punctuated with brief active exercises that call on students-working indi vidually or in small teams-to answer questions, begin prob lem solutions, fill in mis s ing steps in derivations brain storm, formulate questions about material just presented summarize, or do anything else that they may subsequently be asked to do in homework and on tests Y 1 The exercises energize the students (sometimes literally waking them up), direct their focus to the most important points in the lecture, and increase their subsequent concentration when the lecture continues. They give the students practice in the methods and skills the course is intended to teach them and immedi ate feedback on their efforts, thus meeting the criteria for learning to occur. Even if some material were dropped from the course syllabus to make way for the exercises, the in creased learning would more than compensate for the loss But there is no need to s horten the sy llabus. Suppose that instead of saying every word and writing every statement and drawing every diagram and deriving every equation in class, you were to put a lot of the material in class handouts that include gaps-skipped steps in derivations, axes with no curves showing-and exercises with spaces left for re sponses. "E stimate the solution of thi s problem. If you increase the temperature how would you expect the product y ield to vary? Wh y?" Draw the free-body diagram" "Fill in the missing steps between Eqs. (4) and (5)." Further suppose you announce that you will not go over most of the Copyright C hE Division of ASEE 1999 Chemical Engineering Education

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details in the handout s in c la ss, but any of it -es peci a ll y the gaps and questions-could s how up on the te s t. Mo s t of the s tudent s will then actually read the handout s-a t lea s t after the first te s t when they di scove r that yo u meant it. Thi s s tr a teg y acco mpli s he s severa l things. By eliminating th e need to say and write and dr aw everything in cl ass, yo u buy yourself many classroom hour s that can b e de vo ted to the thin gs that make learnin g happ e nspe ndin g mor e time on conceptually difficult mat eria l giving mor e examples, asking and answering que s tion s, a nd implementing active learning. You can fill in so me of the gaps in the handout s in cla ss; get the students to fill in others in active learning exercises; and leave so me for th e m to work out for them se lves before the te s t. The s tudent s learn mor e (we learn b y doing not b y watching and li s tening ), the classes are more li ve ly daily attendance incre ases, and the sy llabu s i s safe. Do active learning methods work in large classes? The larger a cla ss, th e mor e esse ntial it i s to u se act i ve learning 14 71 In a traditional le c tur e class with 15 s tud e nt s, it is not too difficult to get almost everyone actively invol ve d in asking and answering que s tion s and participating in di s c u ss ion s of course material. In a class with 40 s tudent s it i s extremely difficult to do so, and in a class of 75 or more it is vir tually impo ss ible. Few st udent s ha ve the se l f co n fi d e nce to ri s k looking foolish by asking or answering qu es tion s in front of a large number of cla ss m a tes and the traditional pep talk s proclaiming that there are no dumb que s tion s and that wrong answers are al so valuable ge nerall y ha ve little effec t. On the other hand when a class is periodicall y give n so me thing to do in group s of two or thre e, th e risk of embarrassment i s minimal-the only real differ e n ce bet wee n a cla ss of 20 and a class of 200 i s th a t th e l a tter class is noi sier durin g activ itie s A ke y to makin g active learnin g work in lar ge classes i s to s top th e activity after th e pr esc rib ed tim e interval a nd ca ll o n individual s tudent s or team s to s tate th e ir re s ult s .* If yo u only call for vo lunteer s t o provid e responses after a gro up exercise, many s tudent s will not parti ci p ate in the activ it y, knowing that sooner or lat e r another s tudent or the in str uctor will s uppl y the answer. If they know that any of them co uld b e called on, the same fear of embarrassment that keeps them from volunteering responses in the whole cla ss w ill prompt mo s t of them to work with th e s mall gro up so they will be ready with so mething if they are picked. In s tructor s who have never u se d active learnin g in a l arge Wh e n we do thi s, we tend to overload on the back of th e c lass room where many students go to avoid the inst ru cto r 's attention In our classes the students quickl y l ea rn that they can run but t h ey can't hide. class u s uall y e nvi s ion two problem s. They worry that some s tudent s will refu se to participate under any circumstances and that th e noi se level during the activity will make it diffi c ult to r ega in control of the cl ass. In our experience, more than 90 % of the s tudent s in a clas s routinely participate in active learning exercises after the first few (w hen the y feel awkward and un s ure about what th ey are s uppo se d to do ), and the u s ual involvement is closer to 100 % Nevertheless, it di s turb s in s tructor s to see even one s tudent si ttin g with arms crossed, pointedly refusing to par ticip a te and the in s tructor s often take such observations as evidence that the method i s failing. That 's th e wrong way to look at it. Suppo se a full 10 % of your s tudent s s it on their hands during an active learning exercise Thi s mean s that 90 % of your s tudents are engaged in thinkin g about what you want them to think about and trying to apply the concepts you have been teaching so that the odds are 9 to I in yo ur favor. In a typical traditional lectur e, the percenta ge of the clas s actively engaged in think ing a bout the lectur e content at any given time let alone trying to apply it i s ge nerall y very low Even if it is as high as 10 %, which i s unlikely the odds are 9 to l against you. No in s tru ctio nal method-lecturing, active learning, multimedia tutorial s, or anything else-is guaranteed to reach every stu dent. As an in s tructor the be s t you can do i s go with the odds. It is true that in a lar ge class the noi se level can make it more difficult to bring the students' attention back to you which make s it important to establish a s ign a l (e.g., a buzzer whistle, or handclap ) for them to finish their sentence and s top th e di sc u ss ion After the fir s t few exercises, we have ne ve r had to wait for more than 10 seco nd s for the room to qui e t down even with 400 people there. Be s ides if you are teachin g a cla ss in which the s tud e nt s are so involved in answering yo ur qu estio n s or working out yo ur problems that you h ave trouble ge tting them to s top, there are far wor se probl e m s yo u could ha ve. REF E R E NCES I. Felder R M and R Brent "FAQs," Chem. En g. Ed., 33(1 ), 32 ( 199 9) 2 Pr ess ley M ., a nd C. B. McCormick Cognition, T eac hin g and Assess ment, H arperCo llin s, New York, NY ( 1 995) 3. Felder R .M., (i) "A ny Questions ?" Chem. Eng. Ed. 28 (3), 174 ( 1 994); ( ii ) H ow About a Quick One ?" Chem Eng. Ed. 26 (1 ), 1 8 (1992) 4 McKeachie W.J. T eac hing Tips : Strate g i es, R ese arch and Th eory for College and University Teachers, I 0 th ed., Houghton Mifflin Co., B os t on, MA ( 1 999) 5. Felder R M ., B ea tin g the Number s Game : Effective T eac hin g in Large C l asses<' Pro c 1 997 Ann u al ASE Conj, American Society for Eng in eering Education ( 1 997) < http: //www2. n cs u. e du/unit y /locker s/ u se r s/f/fe ld er/p ubli c/ P apers/Largeclasses. htm > 6. On Tea c hing Large C l asses," < http ://ase. tufts .e du/ct e/ occasional_papers/large_classes.htm> 7. Teaching Large C l ass Sections ," Th e P e nn State T eac her II Leamin g t o T each; Teaching t o L earn All of the R a nd om Thoughts columns are now available on the World Wide Web at http://www 2. nc s u edu/effective_teaching/ a nd at http : //ch e. ufl .e du/~cee/ Fa /11 999 277

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kid class and home problems ) The object of this column i s to enhance our readers collections of interesting and novel problems in chemical engineering Problem s of the type that can be u s ed to motivate the s tudent by presenting a particular principle in clas s, or in a new light or that can be as s igned as a novel home problem, are requested as well a s those that are more traditional in nature and that elucidate difficult concepts. Manuscripts should not exceed ten double-spaced pages if possible and should be accompanied by the originals of any figures or photographs. Please submit them to Professor James 0. Wilkes (e-mail: wilkes@engin.umich.edu) Chemical Engineering Depart ment, University of Michigan Ann Arbor MI 48109-2136 BEWARE OF BOGUS ROOTS WITH CUBIC EQUATIONS OF STATE RONALD M. PRATT National University of Malaysia Bangi, Selangor, Malaysia 43600 T 1 =430K P 1 = 60 bar n-butane T he Peng-Robinson equation of state and its close kin, the Soave-Redlich-Kwong equation are simple yet very effective tools for s olving phase equilibria prob lems involving hydrocarbon s and other nonpolar and slightly polar species. Being cubic equations when s olved for the compressibility factor Z they will either yield three real roots or a single real root and a complex pair. It would be most convenient and is sometimes believed that one single root implies a single phase while three real roots imply liquid and vapor phase s are in equilibrium Sadly such i s not the case. Care must always be taken to extract the correct root. Major blunders can be made as we will show in the following problem Figure 1. Throttlin g of n-butan e to known final pressure perature of the s tream as it exits the valve ? Use the Peng Robinson equation of state to model the PVT behavior of butane. ( PROBLEM STATEMENT) Pure n-butane at 430K and 60 bars is throttled to a final p r essure of 10 bar as shown in Figure 1. What is the ternRonald M. P ratt is a lecturer in the engineering department at the National University of Malaysia He obtained his BS in mathematics and in chemical engineering at the Colorado School of Mines his MS in mathematics at the Fuxin Mining Institute in Liaoning Province China and his PhD in chemical engineering at the Colorado School of Mines Research interests involve molecular dynamics and fractal modeling and his teaching responsibilities have included undergraduate gradu ate and statistical thermodynamics courses and molecular simulation. Copyrigh t ChE Division of ASEE 1 999 278 C SOLUTION) The Peng-Robinson equation is written as p = RT a v b v( v + b) + b( v b) where R univer s al g a s c on s tant T ab s olute temperature v molar volume a a c [1+m(l .fT/T c )]2 a 0.45723553 R 2 T 2 /P C C C (I) C h e mi c al En g in ee rin g Edu c ati o n

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m 0.37464 + 1.54226 ro-0 .26992 ro 2 b 0.077796074 RT /P C C ( I ] T c critical temp era tur e = 425.1 K for n-but a n e P c critical pre ss ure= 37.96 bar for n-butan e 1 1 1 ro pitz e r ace ntric factor= 0.200 fo r n-but a n e 1 1 1 It i s common to rewrite the Pen g -Robin s on equation a s a cubic polynomial f(Z) = z 3 + az 2 + pz + y = o where a = B-1 p = A-2B-3B 2 y = B 3 + B 2 AB and A= aP/ ( RT )2 B = bP/RT (2) Since an energy balance written across the valve (ass um ing residence time of the fluid in the va l ve i s so s hort that heat los s through the v alve cas ing i s negligible ) s tate s that = 0 we therefore need to find the exit temperature T 2 that sa tisfie s thi s condition. Thi s requires that we be able to calculate the enthalpy change acro ss the valve, L'1H. We will consider L'1H to be the sum of two parts an ideal gas contri bution and a residual correction for non-id e al behavior (3) The ideal g a s contribution i s determined from ide a l gas (low pres s ure ) he a t capacity data : (4) Heat capacitie s for gases in th e ideal gas s tate are func tion s of temperature only and are u s ually given by correla tion s. A common correlation 1 11 i s (5) Table l shows the coefficients for n-but a ne in th e ideal gas s tate. The residual contribution i s calculated u s ing s t a ndard equa tion s1 2 3 1 derived from the Peng-Robin s on equation of s tate (6) where R T a -a H = ----r,;fn ( ) + RT(Z-1) b-v8 (7) and Fall / 999 TA B LE 1 TABLE2 Ideal Gas State Heat Ent h alpy C h a n ges Capacity Coefficients for n-b u tane I / Kl ~H(.J/mole) n-butane 400 1810 13 A 1 935 375 5508.98 B 36.9 15 X 10 3 350 2394 94 C 11.4 02 X 10 6 325 -683.42 D 0 330.53 1 0 .00 d a ma a = dT = [ I + m( I / T c ) HF and H f are evaluated from Eq ( 7 ) u s ing the compress ibilit y factors corresponding to the initial and final states, re s pecti ve ly A temperature for the s tream lea v ing the valve may be g ues se d a nd ca lculated as indicated above. Proceeding b y trial and error ( the sec ant method 141 could be u se d to impo se se lf-consi s tency and avoid a trial-and-error solu tion) we obtain Table 2. We see that a value ofT 2 = 330.53 lK g ive s a L'1H equal to zero (w ithin two decimal place s accu racy). The "so lution i s that the exit s tream is n-butane vapor at 330.53 lK. All done right? Not quite. Everything s eems well until one look s at a pha se diagram for n-butane or notice s that the temperature i s well below it s boiling point at 10 bar pre ss ure ( T sa =35 2.4 75K ) a nd therefore at these exit condi tion s ( 10 bar 330.531 K ) n-butane is a s ubcooled liquid This i s s hown in Figure 2. The actual state of n-butane at 10 bar Figure 2. Pre ssure-e nthalp y dia gra m for n-butane. 279

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and 330 531K is shown by them in Figure 2, obviously far from the correct so lution (Point 2 in Figure 2), which indi cates that the exit stream i s a mixture of vapor and liquid. The calculation has been deceiving u s with bogus qua s vapo r roots. Vapor roots can only be used for temperatures above the boiling point. Below this temperature, liquid roots must be u se d. Therefore, to proceed with the so lution to thi s problem, we s hould first determine the boiling point T 1 for n-butane at 10 bar Since at the boiling point liquid and va por phases mu s t be in equilibrium we mu s t find the tem perature at which the chemical potential s of both pha ses are equal. For a pure component, this is equivalent to say ing that the Gibb s free e nergie s mu s t be equal for the two pha ses. Since the ideal gas contribution to the Gibb s free energy is the same for each pha se, we only need concern ourselves with the re s idual contribution At the boilin g point we re quire that {8) The residual Gibb s free energies are calculated from the Peng Robin so n equation of s tate u s ing the s tandard derived formuJa 2 3 l R a G =-.e n----RT{Z-B)+RT{Z-1) Z + B( I {9) The vapor GR in Eq. (8) is computed from Eq. (9) u s ing the large s t compressibility factor root. Similarly the liquid G R should be calculated using the s malle s t root. Different tem peratur e values may be se lected on a trial-and-error basi s until the equivalence of Eq (8) is satisfied to within some tolerance. (Agai n the seca nt method can be used to facilitate coding of thi s algorithm.) Proceeding in this manner, we find that at 352.475K G R = G L = -540 .2 8 J/mole and there fore T 1 = 352.475K. For thi s problem, one will find that ~H is positive when u s ing the vapor roots at r 1 and m is large and negati ve when u si n g the liquid root at r 1 Therefore the exit stream is a mixture of liquid and vapor in just the right combination to make ~H = 0 Equation (6) mu s t be modified to include both a vapor and liquid contribution to the enthalpy of the exit s tream R R ( ) R R Aff = xH 2 v + 1x H 2 L H 1 {10) TABLE3 T 280 293 352.475 396 600 280 Computed Compressibility Factors ZL Z mi ddl e Z v vL(m 3 /kmol ) v middl,( m 3 /kmol ) v y( m 3 /kmole ) 0.03982 none non e 0.09270 non e 0 03907 0.442 2 1 0.48898 0.09617 1.0 7724 0.03880 0.13666 0.79982 0.11370 0.40048 0.05482 0.05694 0.86624 0 .1 8048 0.18746 none non e 0.96897 n o n e n o n e 12 11.5 T=Tc Satu:ated Liquid 11 10 5 Bogus ... Bogus 293K .. Good Ill 10 a:293K 9 5 P=10 Ba-, T=352.475K Good 9 Satt..raled Saturated I 8 5 Liquidl\/clar Vaporl\/clar Vdure=0 1137 Vdurre = 23438 1 8 I -0 5 0 0 5 1 5 2 2 5 V' m"3/krrd Figure 3. Magnified pressure-volume diagram in the region P= lO bar for n-butan e 3 n o ne 1.19116 2.34383 2.85197 4.83360 C h e mi ca l Enginee ri ng Education

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where x is the quality or percent vapor in the two-phase exit stream When the calculation is made using Eq. (7), the exit stream is found to have a quality of 0.8434. Therefore the correct solution to the problem is that the exit s tream is at its saturation temperature of 352.475K and consists of 84.34 % vapor and 15 66 % liquid (as s hown in Figure 2). DISCUSSION To illustrate more clearly what has happened here we will look at solutions of the Peng-Robinson equation for Z (and v) at 10 bar at various temperatures Obviou s ly at 10 bar, butane exists as a superheated vapor above T and as a s ubcooled liquid below T '. At various temperature s at P=l0 bar we obtain Table 3 from Eq (2) Which roots are valid? Certainly we can rule out all of the intermediate or middle values (These in termediate roots that lie within the saturation en velope are of use in sta bility analysis, 151 some thing we are not con cerned with here .) Also any liquid roots above the boiling point must be ruled out, and any vapor roots below the boiling point must be eliminated. Only the values in bold print hold any physical significance for u s (The .;.Q 02 -1---N ;;:-0 06 0 0.1 0 2 0 .3 0.4 trated in Figure 4, which s hows the cubic polynomial in Z (E q 2) as a function of Z This area is marked "Danger!" in Figure 4. The polynomial crosses the zero horizontal axis three times within the danger region 293K:5:T:5:T There fore, in our example above at 330.531K the Peng-Robinson equation cheerfully provided an erroneous vapor root that gave us a nonsense so lution to the problem. A similar situation exists at temperatures above the boiling point. Between the boiling point and temperatures as high as 396K (a 43K spread), bogus liquid roots are calculated. This dangerous region is also marked on Figure 4. At tempera tures over 396K, only a single (va por) root is calculated, and there is no danger of bogu s roots. The key point i s that before we can decide which roots are Danger! 0 5 z 0 6 0 7 0.8 0 9 valid and which are bo gus, we mu st already know the boiling point. An equivalent procedure would be to select the value of Z that corre sponds to the lowest re s idual Gibbs free energy or fugacityl 6 1 since the liquid and vapor free en ergy curves cross at the boiling point. Without taking these steps, it is easy to end up in big trouble. CONCLUSION In conclusion, it is not Peng-Robinson equation is not recommended for calculating subcooled liq uid values, but values are physically significant Figure 4. The Peng-Robinson polynomial f(Z) = z 3 + aZ 2 + ~z + y possible to assume sim ply that large roots of Eq. (2) are vapor values and that small roots are for as a function of Z for n-butane at 10 bar for various temperatures. even if they are of low accuracy.) Figure 3 is a magnified PY diagram in the region of IO bar and shows the bogus liquid root at 396K (0. 18048 m 3 /kmol) and the bogus vapor root at 293K (1. 19116 m 3 /kmol). Their respective valid superheated vapor and subcooled liquid vol ume roots are also shown. The saturated molar volumes are also indicated in Figure 3. Note that the bogus roots lie within the phase envelope The danger is that we obtain what appear to be liquid and vapor roots in regions quite far from the boiling point. A value of 293K is the minimum temperature (rounded to a whole number) that will still yield a bogus vapor root. At temperatures lower than this the Peng-Robinson equation will provide just one real (liquid) root, and there is no dan ger. In this region between the boiling point and 293K (about a 60K spread), bogus vapor roots will appear This is illusFall 1999 the liquid. There is a large margin on both sides of the boiling point where bogus liquid or vapor roots are calcu lated Selection of the correct root requires additional infor mation and considerable care must be taken. REFERENCES 1. Smith J M ., H C Van Ness and M.M. Abbott, Introduction to Chemical Engineering Thermod y namics, 5th ed McGraw Hill New York, NY ( 1996 ) 2. Sandler S.I. Chemical and Engineering Th ermodyn amics, John Wiley & Sons New York NY ( 1999 ) 3. Kyle B .G., Ch e mical and Process Thermodynamics Prentice Hall Englewood Cliffs New Jersey ( 1992 ) 4. Carnahan B H.A. Luther and J.O. Wilkes, Applied Nu m e ri c al Methods John Wiley & Sons New York, NY ( 1969 ) 5 Walas, S.M ., Phase Equilibria in Chemical Engin ee ring Butterworth-Heinemann Boston, MA ( 1985 ) 6 Savage, P E ., "Spreadsheets for Thermodynamics Instruc tion," Chem. Eng. Ed., 2 9 262 ( 1995) 281

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.t3 .... 51111i3._c u rr_i_c u_l u m ______ __. ) PARTICLE TECHNOLOGY ONCD M ARTIN J. RHODES Monash University Clayton, Victoria, Australia 3168 T he importance of particle technology to the practic ing chemical engineer has been highlighted by ar ticles such as those by Ennis et al.,l 1 1 which drew attention to the legacy of neglect in the U.S. and Nelson, et al.,C 2 1 which invited us to "teach 'em particle technology These articles and the excellent series of articles on particle science and technology in the spring 1998 issue of CEE have done much to raise awareness in industry and academia of the importance of particle technology to the process indus tries, of the initiatives that have been set in place to address the problem and the need to teach it in chemical engineering courses. Several of the CEE articles drew attention to the shortage of educational resources for particle technology. Davis and Fan 1 3 1 highlighted the lack of suitable teaching materials and recommended that booklets of homework problems, soft ware CD-ROMs, laboratory demonstrations experiments, and textbooks were required Nelson and Davies 14 1 announced the establishment of a web site for gathering multimedia ed u cational modules prepared by experienced people in the particles field for dissemination to educators in chemical engineering. Chase and Jacob 151 reported on their successful introduction of a solids processing course team-taught by academia and industry to senior undergraduates at the Uni versity of Akron. These authors highlighted the need to use a range of pri mary references and reported on students strongly voiced opinion that better textbooks are needed on the subject. Donnelly and Rajagopalan 1 6 1 reported on the development of a series of instructional modules on particle technology top ics at the Engineering Research Center for Particle Science and Technology The objective of the module series pro gram is to permit particle technology topics to be squeezed in small doses, into the already overcrowded chemical engi neering curriculum This article will focus on educational resources for teach ing particle technology and, in particular, on laboratory and 282 classroom demonstration s, which highlight important phe nomena and the ways in which the behavior of particulate solids is surprising and often counter-intuitive when intu ition is based on our experience with fluids Personal experience gained from teaching particle tech nology over a period of fifteen years at two institutions taught me that in order to get student s' attention it was often necessary to do some demon s trations to show how powder s behave differently from liquids and gases. A dust explosion, for instance is impressive and never fails to grab attention. A good-sized fluidized bed preferably with a floating plas tic duck is another good one for audiences of all ages and backgrounds. A large steel ball that rises to the top of a beaker of sand upon shaking is a favorite and since it is the only one that is readily portable I tended to rely on it more and more as I grew older and lazier. I realized at an early stage that demonstrations of the many interesting phenomena in particle technology are time con suming to set up in the lecture theater or the laboratory. Therefore, I made short videos of the more interesting phe nomena and those that are the most difficult to explain through the spoken and written word, diagrams or photo graphs. I also borrowed video clips from others who are more talented at setting up the demonstrations (Profes s or Derek Geldart of Bradford University on fluidization and NEU Engineering on pneumatic transport). Mart i n Rhode s is Reader in the Department of Chemical Engineering at Monash Univer sity in Australia With a keen interest in par ticle technology education he has directed continuing education courses in the area and is author of the undergraduate textbook In troduction to Particle Technology. His re search interests include f/uidization gas-par ticle flows interparticle forces and particle mixing. Co p yr i g ht C h E Di vis i o n o f ASE E 1 999 Ch e mi c al En g ine e ring Edu c ati o n

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The CD-ROM medium al lowed me to combine video clips and explanatory text in a form that is easy to use by both the educator in the classroom and the student at home. The result ing CD-ROM of "Laboratory Demonstrations in Particle Tech nology" was compiled with the assistance of one of my research students, Alfi Zakhari, over a period of several months. I I during discharge powder flows along this surface ; the only sol ids in motion are those flowing along these surfaces and down the central channel or core; the regions of powder lower down in the hopper are stagnant until the hopper is almost empty I I l J CD-ROM OF LABORATORY DEMONSTRATIONS IN PARTICLE TECHNOLOGY ', // ~=0 2 7 Whether we get mass flow or core flow depends not only on the slope of the hopper wall, but also on the properties of the powder and the interaction of the powder with the hopper wall's material of construction Thi s fact is demonstrated in a third video sequence in which a different sand (mean size of 100 m) gives core flow in the ,,.,t : -"' _.. The topics covered in the labo ratory demonstrations featured on the CD-ROM include flow Figure 1. Core flow of solid s in a hopper Solids ar e 250-mi c ron sand with s om e particl e s c olor e d to a c t as tra ce rs s teep-angled hopper. patterns in hoppers, fluidization phenomena hindered settling, ga s cy clones, dust explosions, pneumatic trans port, size and density segregation, and stresses developed in particulate solids. The user can easily navigate the topics on the CD by using mouse-activated but tons. An explanation of what is featured under each topic is given below. Mass Flow and Core Flow in Storage Hoppers Fluidization Ge/dart Classification of Powders Geldart 181 classified powders into four groups (A B C D) according to their fluidization properties at ambient con dition s The Geldart Classification of Powder s i s now used widely in many field s of particle technology. Mass Flow In perfect mass flow all the powder in a storage hopper is in motion whenever any of it is drawn from the outlet. Mass-flow hoppers are smooth and steep. A video sequence shows sand of mean particle size 250 m in mass flow. The use of alternate layers of col ored powder in this sequence clearly shows the key features of the flow pat terns: the powder surface remains level Figure 2. A G e ldart GroupA po w d e r fluidiz e d in a 2-D b e d [] Group A : Powders that when flu idized by air at ambient conditions, give a region of non-bubbling fluidi zation beginning at the minimum flu idization velocity Umr followed by bub bling fluidization as fluidizing veloc ity increase s, are classified as Group A. A video clip show s cracking cata lyst a typical group-A powder, exhib iting a region of non-bubbling fluidi zation a s ga s velocity i s increased from zero through U mr and on to the mini mum bubbling velocity umb Expan until it reaches the sloping section; the flowing channel coincides with the walls of the silo; all the powder is in motion; particle velocity profiles are flat in the parallel walled section of the hopper. Core Flow This occurs when the powder flows toward the outlet of a silo in a channel formed within the powder itself The second video sequence shows the same sand (250 m) discharging from a hopper where the sloping walls are less steep. Core flow results (see Figure 1 ) Alternate layers of colored powder highlight the important features of core flow: the surface of the powder forms an inverted cone; Fall 1999 s ion of the non-bubbling bed as the gas velocity is increased is clearly seen A second video sequence shows that when the air supply is interrupted the bed level initially drops abruptly as the bubbles escape and then more slowly as the gas escapes from the expanded emulsion phase-another characteristic of Group-A powders A third video shows a Group-A powder in a backlit two dimensional fluidized bed showing splitting and coales cence and maximum stable bubble size (see Figure 2). [] Group B: The first video shows beach sand, a typical 283

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Group-B powder, fluidized by air. The video demonstrate s that with Group-B powders bubbles appear as soon as the powder fluidizes, ie., at Um r A second video clip shows Group-B powder in a two dimensional fluidized bed and demonstrates that in Group-B pow ders bubbles continue to grow as they rise and as gas velocity is increased never achieving a maximum size (see Figure 3 ) [] Group C: These are very fine powders that because of the domi nance of interparticle forces, are incapable of fluidization in the strict sense. Bubbles do not occur. The gas flow forms channels through the powder. Cracks form and sometimes discrete plugs of solids are lifted by the gas flow. The video shows the formation of cracks, channels and rising plugs as an attempt i s made to fluidize a Group-C powder (see Figure 4) [] Group D: These are powders made up of large particles which like Group-B powders give only bubbling fluidization when fluidized by air at ambient conditions but are distinguished by their ability to produce deep spouted beds The video clip shows a deep spouted bed of rice grains a typical Group-D material (see Figure 5). Slugging When the size of the bubbles is greater than about one third of the diameter of the fluid bed vessel, the bubble rise velocity is controlled by the vessel itself. The bubbles become slugs of gas and the bed becomes a slugging fluidized bed. A slugging fluidized bed is shown in the video sequence Pneumatic Transport of Powders The pneumatic transport of particulate solids is broadly classified into two flow regimes : dilute (or lean) phase flow and dense-phase flow [] Dilut e -pha s e transport: Under these dilute-phase flow conditions the solid particles behave as indi viduals, fully suspended in the gas, and fluid-particle forces dominate. This is simulated in the first video sequence [] Dens e -phase transport: At the opposite end of the scale is dense-phase flow characterized by low gas velocities ( 1-5 mis) and high solids concentrations (greater than 30 % by vol ume) In dense-phase transport particles are not fully suspended and there is much interaction be284 Figure 4. Attempting to fluidize a G e ldart Group-C powder (wheat flour). Figure 3. A G e l dart Group-B p o wd e r fluidiz e d in a 2-D b e d. Figure 5. A spouted fluidiz e d b e d of ri ce, demonstrating typi c al G e ldart Group-D beha v ior Ch e mi ca l E n g in ee r i n g Edu c a t i on

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tw ee n the particl es. Examples of horizont a l a nd vertical den se-p ha se tran s port are s hown in vi d eo se qu e n ces. Size and Density Segregation [] P ouri n g P owder into a H e ap: Th e vi deo se qu e nce d e onstrates th e segregatio n that occurs w h en a mixtur e of two diff e rent s ize s or particle s i s poured into a h eap Fine p ar ticle s are colored diff e rently from lar ger particle s The mi x tur e i s poured int o a narro w Pl ex i g l as b ox. The c h ar acteristic "C hri s tma s Tr ee" segrega tion patt e rn with th e fine s occupying the center of the h ea p i s clearly ob se r ve d (see Figure 6). The domin a nt seg r ega tion m ec h a ni s m in thi s case i s per co l at ion. [] Segregation in a R otating Drum : The v id eo se quence s ho ws a mixtur e of di ffe r e nt -s i ze d particl es rotated in a Ple x i g l as drum a t around 60 rpm Band s of finer particle s ( dark co lored ) d eve lop over a period of a minute or two (see Figure 7 ). Th e dominant seg regation m ec hani s m i s again prob a bl y per co lation although ot h er m ec hani s m s a re likel y to be involved [] Segregation b y Vibration: A stee l ball bearing about 2 5 mm in diameter i s placed at th e b ot tom of a beaker a nd the beak e r i s filled with sa nd (a bout 250 but size i s not too critical). Th e b eaker and contents are s hak e n ve rticall y b y 'I I ,. t --Figure 6. Segregation pattern formed by pouring a free flowing mixture of two sizes of particles into a h eap (the fine particles ar e the darker ones). Figure 7. Segregation pattern formed by rotating a free flowing mixture of two sizes of particles in a horizontal drum (fine particle s are darker) Fall 1 999 hand. After a few s hake s, the steel ball has risen to the top of the san d Smaller and le ss -den se ball s may be u se d to dem onstrate that the s peed of seg regation in thi s case increases with s ize and den si t y of the ball. Several mechanism s have b ee n prop ose d to explain thi s effect, e.g, (a) the steel ball i s dri ve n b y co n vec tion currents se t up in th e sa nd ; ( b ) sa nd flow s into voids created beneath the ball, causing it to rise; (c) the lar ge momentum of the ball compared to that of the san d particle s drive s the ball upward s during the upward motion of the beaker. A further video sequence shows a two dimen s ional version of the steel ball experiment described here A s teel di sc is s hown rising through a bed of glass b ea d s in a narrow Plexigla s box that i s v ibrated vertically. Colored tracer particle s s how the motion of the glass ballotini as the s teel di sc ri ses A s trobe effect on the video camera allows the motion of th e bo x to be eliminated. Fire and Explosion Hazards of Fine Powders Finely divided combustible so lid s, or du sts, disper se d in a ir can give ri se to explosions in much the same way as flammable gases Du s t explosions have been known to give rise to serio u s propert y damage and lo ss of life. Most people are probabl y aware th at du s t explosions have occurred in gra in s ilo s a nd flourrnill s, and in the proce ss ing of coal. But ex plo s ion s of di s per s ion s of fine particle s of metal s (e.g., aluminum), plastic s, agricultural product s, s ugar and phar maceutical product s can be particularl y potent. Proces s ing s tep s where fine powder s are in dilute s u s pensions or are heated h ave a s trong association with dust explosions; ex amples in c lude dilut e pneumatic conveying and spray dry in g, which in vo lve s he a t and a dilute s u s pen sio n In the v ideo se quence the explosive potential of a few g ram s of brown coal i s demon s trated in the vertical tube apparatus. Com flour wheat flour and ground sugar may also be used. Thi s apparatus i s u se d to classify the powder as ex plosible or non-explo s ible and to determine the minimum du s t concentration for ex plo s ion minimum energy for i g nition a nd in a modified form for minimum oxygen for combustion Such information i s required for the design of safe pl a nt and e quipment for h a ndlin g and proce ss ing com bu s tibl e fine powders Gas Cyclone Separators Th e reverse-flow gas cyclo ne i s a commonly used device for se parating fine so lid s from s uspension in a gas. Inlet gas i s brought tangentially into the cylindrical se ction and a s tron g vo rte x i s thu s created in s ide the cyclone bod y. Par ticles in the gas are s ubject e d to centrifugal forces that move them radially outwards, agai n s t the inward flow of gas and towards th e in s ide s urfac e of the cyclo ne on which the so lids se parate. The direction of flow of the v ortex re ve rses near the bottom of the cylindrical sec tion and the gas leave s the cyclone v i a the outlet in the top ( the so lids outlet is sealed to gas flow ). The so lid s at the wall of the cy clone are pu s hed 285

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downwards by the outer vortex and out of the solids exit. The video sequence shows a Plexigla s cyclone separating cracking catalyst from suspension in air. The sequence shows the flow of the suspension into the cyclone and its transport in the vortex to the solids exit. Batch (Hinde r ed) Settling of a Suspension The simple batch-settling test can supply all the informa tion for the design of a thickener for separation of particles from a liquid In this test, a suspension of particles of known concentration is prepared in a measuring cylinder. The cyl inder is shaken to thoroughly mix the suspension and then i s placed upright to allow the suspension to s ettle The posi tions of the interfaces that form are monitored in time The video sequence shows the type of settling in which three zo n es of constant concentration are formed-a top zone of clear liquid a middle zone of concentration equal to the initial suspension concentration, and the lower zone of final sediment concentration Stress Developed in a Powder The variation in stress with depth of powder in the case where no force acts on the free surface of the powder i s shown in the video sequence. A force is applied to the lower surface of the bed of particles via a piston and a spring The degree of compression of the spring gives an indication of the force required to move the bed of particles Stress is developed within the bed of particles The magnitude of the wall friction opposing motion of the bed i s proportional to the stress developed within the bed and increases with bed depth The video sequence s hows that beyond a certain depth the wall friction is so great that the bed of particle s cannot be moved Most of the applied force is transmitted to the tube walls. In the case of powder s s tored in a bin the walls of the bin support mo s t of the weight of the powder. USE OF THE CD-ROM The CD-ROM is intended for use by s tudent s on their own time although it can equally well be u se d by the educator in a clas sroo m equipped with a video projector linked to a computer with a CD drive It i s intended to be complemen tary to the textbook Introdu ct ion to Particle T ec hnolo gy. 17 1 The primary objective of thi s textbook i s to introduce the s ubject of particle technology to students s tudying chemical engineering The approach taken is to take a number of key topics in particle technology, giving the fundamental science involved and linking this wherever possible to indu s trial practice. The coverage of each topic i s intended to be exem plary rather than exhaustive. The topic s give coverage of broad areas within particle technology: characterization (size analysis) processing ( flu idized bed s, granulation), particle formation (granulation, s ize reduction), fluid-particle se paration (fil tration, sett ling gas cyclones), safety ( dust explosions) tran s port (pneumatic 286 tran s port and s tandpipes). The topic s included demon s trate how the behavior of powders is often quite different from the behaviorofliquid s and gases The book include s 37 worked examples and 76 homework exercises with answers. A solution manual giving fully worked so lution s to all the homework exercises i s now available from the Depart ment of Chemical Engineering at Monash University ( http:/ /www .eng.monash.edu au/chemeng/). COMPUTER REQUIREMENTS Hard wa re: 486 CPU ; 66 MHz ; 4 MB RAM ; VGA moni tor Op erat in g S y stems : CD is self-launching on Microsoft Windows 95 or NT. ACQUIRING THE CD The purpose of putting the demonstrations on CD-ROM was to be able to make them readily accessible and available to educators and students. The CD-ROM is available from the Department of Chemical Engineering at Monash Univer si ty Multiple copies are available for distribution to s tu dent s Those interested s hould contact the author at e-mail : martin.rhode s@e ng.monash.edu au fax : Int+61-3 9905-5686 ACKNOWLEDGMENTS The a uthor i s grateful to Alfi Zakhari for putting together the CD-ROM under the author 's guidance, and to re se arch ers John Sanderson Igor Sidorenko and Mao Qi Ming for setting up demon s tration s and making videos. The author would also like to thank Profes s or Derek Geldart of the University of Bradford England for permission to u se his video clip s on fluidization, and to NEU Engineering Woking Surrey England for permission to use their video clips on pneumatic transport. REFERENCES 1. Ennis, B J ., J Green, and R. Davi es, K ey Challenges in P a rticl e T ec hnology : The Legac y of N eg lect in th e U.S Chem En g. Pro g., 32, April ( 1994 ) 2 Nelson, R.D ., R. D avies, and K. Jacob Teach 'e m Particle Technology, Ch e m Eng. Ed. 29 12 ( 1995 ) 3 Davie s, R.H ., and L-S Fan Teaching Fluid-Particle Pro cesses," Chem. En g. Ed ., 31 (2), 94 (1998 ) 4 Nelson R.D. and R. Davies, Industrial Perspectiv e on Teaching Particle Technology ," Chem Eng Ed ., 31 ( 2) 98 ( 1998 ) 5. C has e, G.G. and KV Jacob "Un dergraduate Teaching in Solids Proc essing and Particle Technology: An Academid Industrial Approach ," Chem. Eng Ed. 31 ( 2 ), 118 ( 1998 ) 6. Donn e ll y, A., and R.J Rajagopalan Particl e Science and Technology Education Initiativ es at the University of Florid a," Ch e m Eng. Ed ., 31(2 ) 122 ( 1998 ) 7. Rhodes M.J Introduction to Part icle T ec hnolog y, John Wiley and Sons Chichester England ( 1998 ) 8. Geldart D ., Types of Fluidization ," Powd e r T ec h. 7 285 ( 1973 ) C h e mi ca l En g in ee rin g Education

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Ray W. Fabien Award Presented to Robert P. Hesketh Rowan Unjversity Thi s aw ard w a s es t a blish e d in 1 996 t o h o n o r th e m e m o r y of Ra y Fahi e n e dit o r of Ch e mi c al En g ineering Edu ca ti o n fro m 1 9 6 7 until hi s d e ath in I 9 9 5 H e w a s effec ti ve l y th e fo undin g fath e r o f th e j o urna l, es tablishin g it as a pr e mi e r publi c ation ve hicl e in th e .fi e ld of c h e mi c al e n g ine e rin g e du c ati o n. H e se lfl ess l y gave hi s tim e and tal e nt s t o ad v an ce p e da gog i ca l sc ho o lar s hip parti c ularl y in th e c ar ee rs of yo un g e du c ator s thr o ugh hi s d e di c ati o n t o th e j o urnal and t o th e pr o f ess i o n Fall 1999 Gi v en annuall y t o an e du c at o r w h o has d e mon s trat e d a sc holarly appr o a c h to t e a c hing and l e arning and w h o ha s s h ow n ev id e n ce of v i s i o n and co ntributi o n t o c h e mi c al e n g in ee rin g e du c ati o n Edu c at o r s who h ave b ee n fac ul ty m e mb e r s fo r no t m o r e than t e n yea r s as of Jul y I s t in th e ye ar of th e a w ard w ill be e li g ibl e No min ees are ev aluat e d ba se d o n I ) o ut s tandin g t eac hin g effec ti ve n ess a nd 2 ) e du c ati o nal sc h o l a r s hip Th e a wa rd r ec ipi e nt s h o uld ha ve mad e s i g nifi c ant co ntributi o n s t o c h e mi c al e n g in ee ring e du c ati o n that go b ey ond hi s o r h e r ow n in s tituti o n Prior Winners: Kirk H. Schul z (1997 ) ; Dou g la s E Hirt (199 8) William H. Corcoran Award pre s ented to John M. Prausnitz U. of California-Berkeley Union Carbide Lectureship Award pr e sented t o Liang-Shi Fan Ohio State University ASEE Fellow Member Honorees Joseph J. Martin Award pr e sented to Robert P He ske th and C Stewart Slater R owan University R. Neal House Purdue University J ohn W. Pr ados University of Tennessee Donald E. Marlow e Award James E. Stice, University of Texa s Ch es ter F. Carlson Award C Stewart Slater Rowan U ni versity General Electric Senior Research Award Art hur W. Westerberg, Carnegie-Mellon Univers ity ASEE Section A wards Dow Outstanding New Faculty Awa rd Ro cky Mountain Section Kristi S Anseth, University of Colorado St. Lawrence Section P aschalis Alexandridis, State University of New York-Buffalo Southeast Section Kimberly E. Forsten Virginia P o l ytec hnic Institute and State University Outstanding Teaching A ward Middle Atlantic Section Andrew L. Zydney Midwest Section Frank Manning U ni versity of Tulsa North Midwest Section Kirk H. Schulz Michigan Technological University Pacific Northwe s t Section Willie (Skip) R ochefort, Oregon State University Outstanding Campus Representative A ward Middle Atlantic Section Deran H anesia n New Jersey In st itut e of Technology Effective Teaching Award Engineering Francis Manning Tulsa University Thomas C. Evans Instructional Unit Award Douglas E. Hirt, Clemson University 287

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.t3 ... 51111i3.._e_s_s_a.....:y:_ _________ __.) UNIVERSITIES WHY? J.M HAILE Clemson University Clemson SC 29634 A s the twentieth century draw s to a close, the situa tion in many institution s of higher education might be characterized as one of general frustration frustration not only among faculty and students but also among administrators and the society that supports those institutions. Students see k to reduce frustration by refusing to take responsibility for their learning, by ignoring the advantages offered by the university or, in short, by relegat ing education to the periphery of their lives Faculties seek to reduce frustration by shifting their focus from teaching to "researc h and by narrowing the definition of education; now its meaning is largely confined to the transmission of knowledge sufficient for s tudents to enter a profession. Ad mini s trators and state legislature s seek to reduce t h eir frus tration by imposing regulations and accountability on uni versities in the form of m a n age ment models transferred from busine ss. In previous generations, faculty were largely un hindered because, in the public 's view, universities made only marginal contributions to society. But today, even the routine activities of faculty are presumed to be too important to remain unfettered. The the sis of this essay is that the problems and frustra tion s now besetting institutions of higher education stem l argely from a misunderstanding of what such institutions are supposed to be and misdirection relative to what they are able to accomplish. Such misunderstanding and misdirec tion promote short-term demoralization of students, fac ulty, and administrators and lead to long-term degen eracy of the entire e n terprise.[1 1 So what are universities supposed to be about? HISTORICAL SKETCH In We ste rn cultures, formal schooling first appeared in the ancient civilizations that thrived along the Tigris, Euphrates and Nile Rivers of mid-ea s t Asia. Those sc hools trained a class of scri bes some of whom would later become religious leader s a nd advisors to the ruling class. The instruction centered on reading writing the arithmetic needed for ac counting, and simple reasoning ski ll s that applied to rule s for conducting religious ceremonies and civil actions In other words, from the beginning, a formal procedure was deemed necessary to help students learn to recognize and interpret abstract symbols and to develop the thought pattern s re quired to manipulate those sy mbol s. But ancient soc ieties needed only a few symbol manipulators: the large bulk of humanity had no use for training in abstractions, for their needs were fixed on the concrete problem of s u s taining life. Such needs could be met by informal instruction provided by family and by apprenticeship to craftsmen for learning specialized skills. By the Age of Pericles in ancient Greece (ca. 430 BC) education had s pread from the clerics to the youth of a leisured class. Naturally this change brought with it a s hift in focus ; leisured youth ha s little patience with the intrica cies of either clerical accounting or religiou s dogma. In stead, those ancient youths, like ours today sought to understand their relations with the physical world and their relations with others. The first forms the basis for scientific inquiry; the second pertain s to the proper struc ture and function of socie ty The ancient Greeks had a genius for reducing matters to their essentials, and they u se d education as a ve hicle for seeking s uch simplifications Thus, they found that abstract reasoning simplifies when abstractions are placed in context. Context simplifies because it shifts our point of view from an inward one in which the abstraction is a central issue to an outward one in which an abstraction is seen as part of a larger whole. In her book, The Greek Way, Edith Hamilton explained this by the following metaphor .c2 1 J M. Haile Professor of Chemical Engineering at Clemson University is the author of Molecula r Dynam i cs Simulation published by John Wiley & Sons in 1992 and is the 1998 recipient of the Corcoran Award from the Chemical Engineering Division of ASEE. Copyr i gh t ChE Division of ASEE 1999 288 Ch e mi c al Engine e ring Ed u c ation

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In medieval and Renaissance Europe many communities undertook wondrous feats of architecture and engineering that culminated in great cathedrals-complex vast and in tricate structures of wood, stone, iron, masonry, and glass woven into arcs columns domes, naves, towers, ribs vaults, and flying buttresses By the 14th century the elaboration had extended to decoration of metaphor is to liken education to drawing water from a well ( students might prefer to liken it to extracting a tooth). Such an interpretation s erves as the basis for the Socratic method of teaching, exemplified by any of Plato's dialogs, but most explicitly in the Meno l 4 l Thus, edu cation is more than transmitting information the interiors including reliefs on walls stained glass richly detailed mouldings s urface pat terning networked vaultings and highly or namented interior columns. What remains in congruous about these impressive structures is that they were not placed within the con text either of their physical surroundings or of the socioeconomic conditions of their so cietie s. They did not blend into the environ ment but rather dwarfed it-arising from the earth to intimidate their mode s t neighbors and the surrounding landscape A cathe dral can be beautiful, yet terrifying-inter nally consistent yet elusive-but it always draw s attention to itself to its own logic and grandeur and away from the world in which it sits. In contrast, with the temples of the ancient Greeks we have beauty of a very different kind-a beauty ba s ed on simple and re s trained proportion (The ancient Greek s did not even have the arch ; rather, they had to rely on the po s t and lintel.) Those proportion s extend be y ond the geometry of the building to include The thesis of this essay is that the problems and frustrations now besetting institutions of higher education stem largely from a misunderstanding of what such institutions are supposed to be and misdirection to students ; rather, to educate means to draw students out so their minds surround knowl edge, embrace it and make it a part of them selves. For the instructor this means that sim ply telling ideas to students is not enoug h ;l5 1 for students it means that merely adding to their store of knowledge is not nearly enough To paraphrase Alfred North Whitehead, the merely well-informed person is the most u se less bore on earth l 61 From ancient times and languages, let us now shift to the mid-nineteenth century In 1852, the Church established the Catholic University in Dublin so that Catholic youth might have access to the same advantages of education as their Protestant neighbors. But although the University was new the educa tional challenges it faced were neit h er n ew nor parochial. Indeed certain of those cha l lenges are with us still. On the occasion of assuming the position as the first Rector of the Univer s ity John Henry (Cardinal) Newman observed, with dismay that l 7 l relative to what they are able to accomplish. the context into which the temple wa s placed. The Parthenon was beautiful not merely because of the precise proportions and optical illusions that were built into its structure, but also because it was designed to occupy the Acropolis-the high est point in ancient Athens The Greek temple had no need of elaborate ostentation for it s beauty was reinforced by its environment. The s e same qualitie s implicity proportion, and context-characterize s ound engineering practice ; thus, Petroski has observed that 131 Good e n g in e ering blend s into th e e n v ironment b ec omes a part of society and c ultur e so naturall y that a spe c ial effort is r e quir e d to notice it. But the development of mind s that can recognize simplic ity proportion and context as well a s manipulate the ab stractions that pertain to them is no small task; a process of formal education is required as the ancient Greeks realized How can this be done ? Perhaps etymology can offer a hint. Although the fundamental idea s about education are Greek our word e du c ation comes from Latin : the sources are the Latin verb s edu c are meaning to rai s e or bring up and e du c er e, meaning to lead or draw out. Thus an appealing F a ll / 999 All thin gs n ow a r e to b e L e arned at on ce, n o t .fi rst one thin g, th e n anoth e r, n o t on e well but man y badl y learning is to b e without exe rtion without att e ntion without toil ; w ithout grounding w ith o ut ad v an ce without.finishing. Th e r e is t o be nothin g individual in it ; and thi s f o rsooth is th e wo nd e r o f th e a ge. "Nothing individual in it -fear s ome words that are indica tive of our age By the mid-twentieth century, the scenes and the players had changed again, but the challenges remained. In address ing the deplorable state of Spanish society between the World Wars Jose Ortega y Gasset asserted that a pri n cipal p u rpose of the university is to teach the vital ideas of the society. llJ Vital idea s include those of cience and engineering, which interpret the physical world; those of politics and law which formulate how society is regulated; those of economics and business which try to explain the trade for goods and ser v ice s; those of the humanities which try to help us under stand ourselves and our relations to one another; and those of the arts which foster self-expression. Note that this purpose is concerned solely with ideas for the mind can grapple only 289

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with ideas, and it is only the mind that can be the recipi ent of the teaching. (For a readable introduction to the connections among objective facts, concepts, and soci ety, see Bronowski r 8 1 ) The sum total of the vital ideas of a society comprises that society's culture so even more important than training pro fessionals, universities are to transmit the culture of a society to succeeding generations. This has become an exceedingly difficult task, for many reasons One is the sophisticated abstract thought that is required to describe and understand modem societies. E. 0. Wilson has pointed out that cultures evolve in tandem with advances in scientific understanding and with increased facility at manipulating abstract symbols that represent those understandings_f 9 J This means that, rela tive to earlier generations, we have more to do to bring students to an appreciation of the culture in which they live. More here refers not only to the number of abstractions, but also to the complexities inherent in the network of those many abstractions by which we represent and manipulate our environment. Thus, in 1999 a committee of the National Research Council asserted that U S students have a poor understanding of basic scientific principles and their relation to everyday life;f 101 further, that Institution s of higher e ducation should provid e diverse opportunities for all undergraduates to study science, math e mati cs, engineering, and technology. Note this plea applies to all undergraduates. CHALLENGE TO ENGINEERING EDUCATION We now want to extend the general comments from the previous section to the education of engineers. To prevent the discussion from becoming too abstract, we present it within the context of a hierarchical cognitive model for learning. In recent years, several such models have been proposed; at least three are similar and closely related al though they were proposed independently and are based on different kinds of evidence. Thus the cognitive hierarchy proposed by Egan f 111 is based on studies in educational psy chology; the hierarchy proposed by Donaldr 1 21 is based on studies of cultural evolution, and that by Hailef 1 3 151 is based on studies of brain function. The se hierarchical models are all integrative; that is, the progression to a higher level requires the individual to master skills and to reorganize knowledge gained at lower level s. THE PHILOSOPHIC LEVEL OF UNDERSTANDING Egan 's version of the cognitive hierarchy contains five levels:L 111 somatic, mythic, romantic, philosophic, and ironic. Each level corresponds to a specific mode for getting thoughts out of the mind and into forms by which they can be dis sected, analyzed, and reassembled. Thus, to oversimplify 290 considerably, the somatic level includes tactile leaming ,r 161 mythic corresponds to oral learning, romantic involves graph ics and written learning philosophic refers to learning by formal reasoning, and the ironic level encompasses excep tions limitations, and learning by modeling. In this hierarchical model it is the philosophic level that contains the basic skills required of engineers. At the philo sophic level knowledge and skills mastered at lower levels may promote development of higher-order thinking skills: inductive and deductive logic inferential rea so ning math ematical reasoning, analysis and synthesis, critical thinking, creation of theoretical constructs, and generalizations. These operations relate simplify, and extend knowledge gained at lower levels. To maintain control over the material, we seek simplifications via patterns theories and schema that orga nize knowledge into useful structures; that is in the words of Mach,l1 71 we seek economy of thought. The reorganization of knowledge into abstract and economical structures i s the characteristic activity of learning at the philosophic level. Note that philosophic understandings may develop, but they do not necessarily do so. Of the numerous human cultures that have appeared throughout history, only one the ancient Greek---developed to the level of philosophic understanding Over the years there has been endless specu lation as to why this is so: What was unique to Greek society? Donald offers the persuasive answer that the break through came when the Greeks combined writing with for mal logic .(1 21 Making logic visible through writing clarifies analysis and communication, and it stimulates further men tal growth to levels that, apparently, cannot be reached in any other way. The consequences of these observations are profound : individuals cannot complete the transition to the philosophic level by themselves To do so, people must live in a commu nity of philosophic and ironic thinkers and learn from them .L 11 1 This is the sine qua non of the university IMPLICATIONS FOR ENGINEERING EDU C ATION The traditional view has been that engineers are problem solvers; hence, engineering was traditionally taught by hav ing students solve many many problems. In recent years, this view has broadened to encompass a variety of reasoning skills that are captured under the general rubric of "critical thinking ." But based on their experience, many engineering educators have come to believe that today 's st udents are generally weak problem solvers and poor critical thinkers. To cite just one example, Wankat 1 1 81 has noted that M y personal observation is that the average engineering student of 20 yea rs ago was a bett e r problem solver but not as sk ill e d at ca l culati n g as the average eng in eer in g student now. This observation has provoked educators to s ubject students Chemical Engineering Educa ti on

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to more problem solving and more thinking exercises. Thus, we find recitation sections, s tudent workshops, and s pe cialized courses devoted explicitly to problem solving, and we find problem-based learning discovery-based learning, and web-based learning intended to develop and exercise critical thinking It is my contention that more of the same" will not prove to be the most effective way to overcome these educational difficulties. Instead, before we can expect students to func tion properly at the philosophic level we must address their deficiencies at the somatic, mythic and romantic levels For example, the use of equations in deriv a tions, proofs, and problem solving are logical exercises and, hence are philo sophic activities ; however, equations themselves are collec tions of abstract written symbols and, hence are romantic devices. Further individual terms and sy mbol s in an equa tion are usually interpreted at cognitive levels other than the philosophic; thus the interpretation might be in relation to equipment (somatic), or in terms of a narrative that describes a process or procedure (mythic), or it might invoke sche matic diagram s and plots (romantic). If we ignore the se lower levels of understanding or if we tacitly assume that students can invoke these level s on their own initiative then their success in such philo so phic exercises as performing derivations and solving problem s will be fragmentary. Similarly manipulations of data-the inferences and de ductions that attach meaning to data-are logical exercises and, hence invoke philosophic understanding However the steps used to acquire and organize data combine lower level s in the cognitive hierarchy. Collecting the data involve s so matic activities using instrument s attached to a n apparatus or processing equipment; narrative description s of the proce ss and the experimental protocol are mythic activities; organiz ing the data into tabular and graphic forms is a romantic activity. Many sophomores and juniors fail to find meaning in data because they cannot organize the data into table s or plots that reveal patterns or trends. With the activity we call problem solving, s uccess re quires a much more complex array of cognitive skills than i s usually required to manipulate equations and analyze data. Problem solving is obviously philosophic : we use abstract symbols to represent quantities and processes and we ma nipulate those symbols according to logical rules to extract unknowns from knowns But to find an algorithm for solving a problem, we appeal to more cognitive level s than just the philosophic Thus Wankat 11 8 1 notes Th e expert problem solver wr ir es things down, draws sketches, co nstructs a variety of different representations of the problem .. expects the problem to eventually mak e sense and is looking for this sense ... The expert expects that finding a sensible interpretation of a problem will also indicate a direction toward a solution; in Fall 1999 pursuing that search, the expert appeals to many levels in the cognitive hierarchy For example, sketches, schematics, and plots are romantic device s; connecting the problem to hard ware and equipment appeals to somatic understandings; nar rative description s of proce sses and re s ponses to changes in variables are mythic activities; models introduced to achieve appropriate sim plification s are ironic device s. In contrast to the expert, many sophomores flounder at solving problems because they fail to sketch the situation, or to articulate a s tory about the situation, or to connect the situation to hard ware, or to recognize what equations might apply-their low-level cognitive skills are insufficient for the task. The se examples s ugge st that success at the philosophic level requires facility with understandings at other levels. If we accept that the fundamental purpose of the university is to develop and exercise philosophic under s tandings then our responsibility to today 's students seem clear: we m u st pay more attention to developing lower-level cognitive s kills rather than s imply intensifying our emphasis at the philosophic level. CONCLUSION The purposes of a univer s ity are to develop in students the ability to interpret and manipulate abstract symbols that pertain to the vital ideas of modem soc iety. The manipula tion of such symbols involves a suite of high-level, critical thinking ski ll s; however critical thinking apparently devel ops only when the student lives among, and learns from, those who not only have mastered critical thinking but who also can s hift effortlessly among cognitive levels; these are attributes of ironic thinkers. Thu s, a university faculty is a community of ironic thinker s intent on elevating students to high cognitive level s. To become adept at such high-level s kills s tudents mu s t develop a foundation of low-level cog nitive skills; but compared to previous generations, today's st udent s need more help from university instructors in devel oping that neces sary foundation. From Plato to Bacon to Jefferson to Ortega y Gasset to the present informed thinker s in Western cultures have argued that the life of the mind is not merely worth living, but that it is indispensable for society to flourish: every society needs philosophic and ironic thinkers who understand how the world works, how soc iety functions, and how abstract rea soning can be deployed to improve society. Today, universi ties are the only institutions that can possibly develop the necessary understandings: church, government, and industry have all abandoned attempts to develop human potentia l in favor of feel-good policie s, s pecial intere s ts and the bottom line. Universities are under attack to do the same But if we succumb to these pressures, if we teach skills that expand pocketbooks but not mind s, if we are satisfied to help stu dents feel good rather than challenge them intellectually ______________ Continued on page 299. 291

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.t3 ... blllii._c_l_a_s_s_,.,_o_o_m ___________ ) A PHENOMENA-ORIENTED ENVIRONMENT FOR TEACHING PROCESS MODELING Novel Modeling Software and Its Use in Problem Solving ALAN S F oss, KEVIN R. GEURTS, P ETER J G ooDEVE, KEVIN D DAHM University of California Berkeley, CA 94720 G EORGE STEPHANOPOULOS, JERRY B IESZCZAD, ALEXANDROS K ouLOURIS Massachusetts Institute of Technology Cambridge, MA 02139 N ew avenues to teaching process modeling are sorely needed in our discipline. The methods we have been practicing seem to have been ineffective; they have not been active and concerted. We have instead de pended too much on students individually inventing some sort of approach as they struggle to find their way through t h e modeling maze in homework assignment after home work assignment. Missing has been an articulation of a na t ur'al and intuitive hierarchy and its use in declaring the character of a process representation, a hierarchy comprising such matters as conservation principles, thermody n amic con straints phase conditions, phase equilibria reaction phe nomena, and transport phenomena. Missing also is an aware ness of many in academia that process models are presently at t he heart of industrial control systems and optimization methods for process operations, and that our graduates ought to be prepared to contribute to that technology. In an attempt to address this shortcoming, we propose a new avenue for teaching modeling and have brought into being new software embodying a model-building hierarchy that can guide students in using their engineering science background in crafting models for problem solving. Our approach is unconventional, and the opportunity extraordi nary for breaking through this instructional omission and breaking through hurdles that students see in their path. Our motivation further derives from having observed that many students are at a loss in identifying the physics and phenomena operative in a process and how to use their background in engineering science to make an integrated representation of the process. Moreover, many se n se their 292 weakness or lack of confidence in writing the equations to represent the physics. A disciplined focus on stating the physics and a release from incessant equation writing is t h e major contribution that this software brings to stu dent learning. Through a selection of examples, we illus trate how t h e teaching of mode l ing can be enhanced with features of the software. "ModelLA is the name we have given to this program Be prepared for something different. The program offers students a phenomena-oriented envi ronment expressed in the fundamental concepts and lan g u age of c h emical engineering, such as mass and energy Alan Foss has co n d u cted beginni n gand senior-level courses in chemical engineering at Berkeley for three decades, experience that has motivated this new approach to teaching modeling and this new modeling software. Kevin Geurts earned his PhD degree at the University of Washing ton in the mathematical modeling of polymer flows and is now a process systems analyst and modeler at the Exxon Corporation in Houston, Texas Peter Goodeve earned degrees in psyc h ology and h u man factors e n gineering and is a freelance software developer and programmer. George Stephanopoulos is t h e A.O. Little Professor of Chemical Engineeri n g at MIT H e has been teaching a n d researching various aspects of process systems e n gineering for 25 years at the Univer sity of Minnesota N ational T echnical University at Athens and MIT Jerry Bieszczad is a PhD candidate in chemical engineering at MIT working on the logic of mathematical modeling. He is the principal desig n er of Mode/LA. Alex Koulou ri s earned his PhD at MIT where he is a Research Associate. He has been working on the development of Mode/LA multi-scale systems for estimation and control, and the development of mode l i n g lang u ages for process systems e n gi n eering. Co p yr i g ht C hE Di v i s i on of AS EE 1999 Ch e mical Engin ee rin g Edu ca tion

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balancing phase equilibria, reaction s toichiometr y and rate modes of heat and s pecies transport. Through a freely ac cessed hierarchy of declaration s of s uch elements of engi neering science, the u se r is assisted in recognizing for ex ample, that energy balances must be declared that chemical equilibrium constrains species behavior a nd that a zero en tropy increase must be imposed to attain minimum compres sion work. All level s of the hierarchy are acces s ible at any time by user reque st. Unlike th e rigid lists of earlier model ing software, elements of the hierarchy are not pre-wired. It is just the phy sics that has to be declared-no equations; the so ftware writes the equations. That i s what is unconven tional. And by simply requesting a so lution, the equations are solved numerically in a few seconds without user inter vention in the numerical method. The results are displayed graphically for rapid assessment of the characteristics of the model. The feedback about misinformed declarations of the physic s i s instantaneou s-certa inl y a major improvement over the one-week tum-around time of homework se ts Such modeling capability can complement instruction in modeling throughout the curriculum. Modeling, in our opin ion s hould be a part of all instruction in engineering, and it should be done in the context of resolving an engineering problem By teaching modeling in a problem-solving con text one can better demonstrate how the nature of model s is influenced by the context, how model s serve problem so l v ing and how the s tructure of efficient problem so lving is shaped by the use of model s. The program can be especially helpful in the process-design course as a complement to the use of process simulators such as Aspen and Chemcad, providing students, through model building a means for understanding the nature of the relation s hidden in the si mu lator modules ModelLA is different having modeling rather than simulation objectives; its modeling capability i s what complements. Equilibrium Va porization of Sea Water Steam Generator Air HELPING STUDENTS IDENTIFY THE PHYSICS AND THE PHENOMENA Knowing where to start i s not easy for beginning and inexperienced s tudent s. Take, for example, the double-effect evaporator proce ss in Figure 1 There i s a lot going on here. In the first place the instructor will have introduced this project as one of trading off energy and equipment costs in sy nthe sizi ng an economical process for the desalination of sea water. To build a model for deci s ion making about a proce ss design s tudent s will need to recognize the presence of the phenomena identified in the ellipsoidal bubbles. We emphasize that the evaporators have to be modeled. Unlike the process units displayed on the screens of process-simula tion programs the pictorial icons here are empty shells; there is no model associated with them The model has to be built. Through interactive Q-and-A with the instructor and concur rent u se of Mode!LA to declare the phy s ic s in the bubbles s tudent s can build a model s uitable for inve stigati ng for ex ample the influence of the temperature drop across the train the degree of concentration of the brine and other deci si ons A perennial difficulty in assigning such a project is the lack of phy s ical feel of many students for the qualitative cause-effect relation s of the process variables to one an other. With the availability of the software, those students can explore an instructor-built model and acquire insight into the effect of changes in operating conditions before attempting to craft hi s or her own model. Figure 2 shows one s uch set of explorations: the effect of condenser coolant flow rate on pressure s and vapor flow rates in the various units Pressures Generator IOI. kPa 97.6 Eva orator I 31 27 Eva orator 2 9.9 I kP a ~l ~ 7.0 ::.~'.7 LSJ S.7 I 000 mol/min 2000 m ol/min 1.0 Vapor Flow Rates Generator 1.44 0.096 m3 / min ~~ ~ --' 1000 mol / min 2000 m ol/ min Figure 1. Double-eff ec t evaporator modeling project iJJustrating the spectrum of phenomena for incorporation in a model Figure 2. Students can gain familiarity with the evaporat ion process by interrogating an instructor-built model for the effect of coolant rate on pressures and vapor rates Fall 1999 293

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All this is calculated in a few seconds with a single request for such an analysis. The results reveal perhaps for the first time for some students, that pressure in the condenser de creases with increasing coolant flow that the pressure de crease propagates upstream to the steam generator, that there is a pressure gradient from one unit to the next, and that vapor rates in the units differ. Then the question for the students i s, Why does all this happen ?" With such knowl edge, students should be able to make intelligent declara tions of the physics far better than had they not explored the behavior. PUTTING THOSE INSIGHTS TO WORK IN MODELING THE EVAPORATOR Exploration of the instructor-built model alerts students that there are two component parts of the evaporator, that they are linked by heat exchange, and that they are differ ent---one a boiling liquid mixture and the other a condensing pure vapor. Such recognition suggests that declarations about the internal structure and the character of the evaporator parts need to be made in crafting a model. This is accom plished in ModelLA by disaggregation of a process unit into its internal parts. Figure 3 shows how a modeler would u se the disaggregation window (Level 2) to s tate his or her view of the evaporator internals through placement of a mixture unit, a tubes unit and linkages of convective flows to tho se of the parent ( Level 1 ) located on the edges of the di sagg re gation window. A heat flux between the tubes and mixture i s declared as an essential linkage for effecting evaporation One can see that all of this is done in a visual graphical manner a feature quickly grasped by the u se r. At this level, declaration s can also be made about the phases present in each subunit, the s pecie s Vapor Sea Wate Steam Condensat data particular to the proce ss being modeled. It is at this level where the engineering science concepts and facts are introduced into the model. To accomplish this in an organized manner students need disciplined guidance in an environment familiar to chemical engineers. They get it through the hierarchy of declarations of s tructure and phenomena s hown in the right side of Figure 3 That se t of hierarchical elements applies to ju s t the declarations needed for this part of the model. The full s et avrulable in ModelLA is much more extensive The Modeling Assistant s hown at the bottom in Figure 3 guides the user in branching to the major elements of the hierarchy Learning about the physics of the process takes place very rapidly here becau se the guidance given by the program at each juncture is centered on the logical consistency of the declarations made and becau s e the feedback about inconsis tency i s essentially in s tantaneou s. One of our student evalu ators remarked that ModelLA guards the user from accumu lating mistakes A good amount of self-learning takes place about the modeling process without instructor prompting PROCESS SYNTHESIS EXECUTING A TOP-DOWN APPROACH The top-down synthesis of a proce ss system can be shown to s tudent s as an orderly and rational way to evolve the s tructure of a proce ss 1 1 and provide s a good example of the u se of the hierarchical structure of the s oftware. Unlike the bottom-up approach usually employed with process-simula tion programs, the top-down approach affords the user a view of the direction of subsequent development and the type of model needed to support that development. Some Disaggregation Window -! waee.r j v:po.r s "" T (mid] bnne .. I I heael I condens a te : __ whd-1 -Hierarc h ical E l e m e n ts Accessed Process Structure Internal Structure Placing Subunits Declaring Fluxes Materials Declaration Species Phases Transport Processes Heat Flow Va or Flow in them equations of state, the equi1 i bri um relations between the phases, and the mechani s ms" for heat transport and vapor flow Such declarations are made through a hi erarchy of dialogs. As these decla rations of s pecies and phase equi librium are made a linkage i s es tab)jshed to a physical-properties data base for the estimation of quantities such as vapor pressures activity coefficients, densities and enthalpy of phase change that are eventually needed in the numerical solution of the model equations We have operated with a relational database containing data for over AddNowP,oceuUri<, l,\ddN ,wFi.1 s.,.a,Speae, andR-., E dlf'lo=,Unb l E dlFi.1 Edl C.,... dLooo,I Modd s1 2000 chemical compounds. The user may also supply any s pecial 294 un1 UrilwihV_t.i, >< m, ........ l!ll S_D ...... odUril I Uril'MhVapoiPhase Unh MhLJq..iLiQl.idEQl,.lilbun II UrifromTemplalelhllf)I UrilwihLioudF'hM IIH Stao,dUril 'j> Hol> Figure 3. Th e s ubunits of th e evapora tor are id entifie d in a di s ag grega tion window fluxes stated and mat er ial prop e rties d ecla red C h e mi c al Engineering E du ca tion

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describe it a s a target-dire c ted approach. In a top-down approach, th e pro gress ion of one's thought s about crea tin g proce ss str ucture is intuitively or g anized as a hierarch y, proceedin g from overall ( top le ve l ) objectives a nd successively broken down into le ve l s of finer detail. That hierarch y m a t c h es exactly ModelLA 's hierarch y of decl ara tion s of proce ss str ucture and con tent. As an exa mple of how a top-down sy nth esis can evolve with th e u se of ModelLA we s how three l eve l s of the sy nth esis of a proce ss for th e hydrodealkylation of toluene to b e nzene th e HDA proce ss t 1 1 The sy nthe s i s s tarts at Le ve l l in Fi g ure 4 with sim ple declaration s of the product s to be produced from candidate raw material s, the c h e mical s p ecies present in the proces s, the ex pected chemical r eac tion s, the expected by product s and waste product s and energy fluxes bet wee n the proc ess a nd environment. Mod e lLA 's hierarchical e lem e nt s accesse d for s uch declara tion s are s hown to the right of th e Level l depiction in Figure 4 Next, wit h an appreciation that a reaction sec tion and a se paration sec tion would b e needed a modeler would place s uch elements in Le ve l 2 a di saggrega tion of Level 1 as s hown in Figure 4 Such a s tep is a top-down s tep in the synthesis, the educational benefit being an opportunity for the s tudent to Hydrodealkylation HDA Level 1 Purge Benzene H y dro ge n Level 2 Y Purge --Rec c l e Byproducts Heat a nd Work Hierarchica l Ele m e n ts Accessed Glo a species ec ared Global rea ctio n s defin e d Placin g flo ws Co n vective Heat Shaft work H i erarc h ica l Eleme n ts Accesse Internal Structure Placin g Subunits Pl ac ing Flows Convective Heat Shaft Work F i g u re 4 Pro cess synt h es i s pursued through successive sub l eve l s correspo ndin g to the multilevel hi erarc h y of ModelLA. Hierarc h ical Tree Hierarc hi cal Elements Accessec y Level3 HDA_plant Int erna l S tru cture Reaction Section Placing Un i ts H eatX Materials A s sig n ed Coo l e r Ph ases Furnace Pha se E quilibrium eacto r R eac ti ons in Phases Qu e n c h R eac ti o n R a t es Pl acing Flows Convect i ve Heat Shaft Work Species Cons i stency Check Fig u re 5. Successive disa gg r ega tion s brin g o n e to the point at w hi c h pro cess subunits ca n be fully d efi n ed and modeled Fall / 999 ex pr ess hi s or her perception of the big pic ture. Such declaration s are made by access in g the hierarchical elements s hown to the right of L eve l 2 in Figure 4. Th e bi g picture now ha s t o be fleshed out w ith so m e definite propo sals for accomplish ing th e reactions and the se paration s A fle s ing out of the reaction sec tion is illustrated by th e di saggregatio n of Level 2 in Figure 5. In Le ve l 3 of thi s example the modeler must function in a bottom-up mode, placing and co nn ec tin g process unit s whose functional it y th e m o d e ler mu s t eventually de sc ribe s t a tin g s ub s tru c tur e s pecie s, pha ses, reac tion s and fluxe s Thi s i s the level where proc ess inventions a re made The e duc at ional v alue here i s the direction of attention on a well-defined segment of the en tire proce ss so that deci s ion s about proce ss str u ct ure a nd the mod e ling of the se t of units in that seg ment can b e made and te s ted without interf ere nc e from other seg ment s For example, the type of reactor model ways to prevent ca tal ys t co kin g and conditions to enhance re action se le c tivity can be scouted. There i s plenty of opportunity here for the in str uctor to point out the pl ace and need for a model in problem so lving and sy nthe s i s. The opportunity is also there to p o int out the s tructure of problem so l vi ng The top-down s trategy comes to meet th e bottom-up inventions of the s ub le ve l s as the proce ss is further and further di saggrega t e d into elementary operations and b asic ph e nomena. One can also see her e an opportunity for co llabo ra tion among team member s in a net wo rked environment say in th e de s ign course, where one member would develop the reactor sec tion and another the se paration sec tion. As the u ser s invention of model s tructure proceed s the sof tware assembles information a bout the hierarchy of model unit s and their connections and di s plays it as the hierarchical tree of model unit s s hown in Figure 5 for the purpo se of keeping the user up-to-date on the model so far constructed. Such a display i s es p ecia ll y u se ful when movin g back and forth between seve ral level s of the model. Completion of the model s of the unit s placed in L eve l 3 of Fi g ure 5 is acco mpli s hed through the hierarchical modeling elements s hown at the right. A particularly essential element is 295

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the species consistency check. It scans the model units of each level to determine whether the distribution of spe cies declared by the user makes physical sense. If it does not, guidance is then given to assist the modeler in recti fying the omissions. SATISFYING THE DEGREES OF FREEDOM A very considerable amount of insight and knowledge about the qualitative cause-effect relationships in a process system is needed to identify quantities that without user intervention by a state-of-the-art numerical en gine, gPROMS,r2 3 1 and for the double-effect evaporator, are completed in 4 or 5 seco nd s Students and instructors like to see trends of process vari ables over ranges of operating and design conditions like those shown in Figure 2 because insight about the process is more easily grasped. Trends can be calculated and displayed for all variables very quickly. The numerical data of s uch calculations can be used in deciding on operating conditions or examining the trade-offs among design de fully specify the operating conditions of the process. It is in this aspect of modeling that the students' engineering ability is thoroughly taxed and in the taxing, further developed. T h is is also where the instructor can help de velop that insight through questions and an swers in interactive sessions with the students. Complex processes often bring to the fore per plexing conflicts in satisfying the degrees of freedom, particularly when energy and mass fluxes interact. This is certainly the case in a process as complex as the HDA process "ModelLA" is the name we have given to this program. cision s The engineering problem can be ad dressed in thi s way. BUT THE EQUATIONS WHAT ABOUT THE EQUATIONS? By all means, have the s tudent s write the equations-but only after they have gained an understanding of the physics and an apprecia tion of the qualitative cause-effect relation ships among the variables. Be prepared for something different. Even models of modest size can have a dozen or more degrees of freedom. Without some assistance, satisfying these with statements of operating conditions and physical parameters would be a daunting and likely an unavailing task. It is neither of these with the ModelLA program. Candidate quantities are identified for user consideration, unit by unit, flux by flux, phase by phase, variable by variable, species by species. A running count of the degrees of freedom yet to be satisfied is dis played as the user makes selections. This DOF The program offers students a phenomena oriented One might think that an assignment in writ ing the model equations after having crafted a model with Mode!LA and after having re solved an engineering problem would be un necessary and anticlimactic. It is neither. First it i s necessary because there ha s to be a clo sure to the project that i s satisfying to the students. We found that students in our trial group wanted to write equations and to con firm that their model and calculations matched those of ModelLA Second, one will find that even after having articulated the physics, not everyone is sure-footed in identifying a model environment expressed in the fundamental concepts and language of chemical engineering ... analytical engine also identifies conflicts in the user's selec tions and offers a list of alternative quantities that can be swapped with the current selection. In the case of dynamic models, the DOF analytical engine simultaneously also makes an analysis of the index of the set of differential algebraic equations and informs the mode l er when the index exceeds 1. Such an analysis is necessary because selection of a certain combination of q u antities to satisfy the degrees of freedom can sometimes result in a large index. Current numerical integration algorithms cannot integrate a differential algebraic equation set with an index greater than 1 Information regarding the source of the high index is reported so that the modeler may reconsider the set of design variables. CALCULATIONS AND THEIR USE When it is confirmed that the index is I or less and all degrees of freedom have been satisfied, t h e u ser may launch a calculation of the model equations Calculations are made 296 envelope and subunit envelopes. That i s, some run off in wrong directions. Further, one will find a significant fraction confused about representing s uch things as the rate of accumulation of internal energy in a mass of material in terms of the proce ss variables and the flux of energy in and out of the proce ss Instruction is assuredly needed to straighten out those basic matters. That instruction is one of the activities that sustains an interest in writing equations and saves it from being anticli mactic. We recommend that the instructor work through the equation writing with the students in an interactive work shop environment because many will still need help with matters such as tho se just mentioned and because there is not much incentive to have students s truggle alone through the equation maze at this stage. Focused and concentrated in struction in formulating model equations reinforces an instructor 's continuing admonition for physical thinking at all stages of modeling and that the equations are just a symbolic statement of the physics. That will be a revela tion to students who have the impression that equation Che mi cal E n g in eering Education

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writing i s all mathematic s An alternative approach, which we think ineffective, i s to have the software display the equations to the student piece by piece as he or she make s declarations of the process attributes, that is, the material s, phases, fluxe s, and reac tion s. Such di s play s are unguided and ph ys ically uninterpreted and are not a n effec ti ve ped agog ical method. In the workshops there is th e further opportunity for the in s tructor to point out the character of the se t of equations, how a choice of variables can tran sfo rm a nonlinear model into a linear model how natu ra l divi sio ns in the proce ss s tructure re s ult in se parate block s of equations, and how one can order the term s of the equations to form an easily computable s tructure, as for example, the s tructure of a linear se t. Students left a lone in a sea of equations se d om are aware of the equation s tructure They can ben efit from th e instructor's in s i g ht here cesses b y placing control sys tems around dynamic process model s. Spatially D istributed Processes Tubular reactor s, ab sorption columns, cooling towers, adsorption beds and tu bular heat exchangers all need at lea s t a one-dimensional s pati a l representation of s pecies behavior and energy flows ModelLA ha s 3-D s patial modeling capability, offering rect angular, cylindrical, and s pherical coordinates. A s an ex ample of that capability the temperature distribution in a 2D model of a phthalic anhydride reactor produced by ModelLA is shown in Figure 6 Dynamic Processes Instruction in modeling the dy namic behavior of processes can be introduced profitably in the first course in material and energy balancing. We simply remark that early experience in dynamic sys tem modeling gives s tudent s an early under s tanding of interaction s in process systems and potentially an ap A full set of note s for the in s tructor about writing the equations for eve ry model i s given in a se t of course mod ule s de scri bed in a later sectio n. The e quation s are l a id out following the lo g i c a nd ca u se -effect relations articu lat e d in an earlier sec tion of the module and thu s s hould appeal to the ph ysic al und e r s tandin g d eve loped there Two methods of so l v ing the equations are developed in the course module s for every model. A paper-and-pencil method follows directl y s tep-b y-ste p the articulation of the ph ys ic s th e iden tification of the unknown s, and the n a tur e of the r e lation s needed to complete th e model. Solution by u se of ge n era purpo se num e rical so lv e r s s u c h as Matlab, Mathc a d and Pol y m a th is also pre se nted. In the case of linear d y namic model s of a s ingle s tate variable, a clo se d-form analytic solution i s deri ve d. Numeri c al calculations of the derived equations are pre se nted for a ll models and compared with the ModelLA cal culations. Thu s, the instructor ha s ma terial to clo se the loop for the s tudent s. T Tube_react o r _rz m etl(r z) preciation for the evolution of the steady-state condition. Declaration of the attribute s of a dynamic pro cess model proceed s in the s ame way as that of a s teady-state model with additional attention needed to s pecify the initial conditions. Spa tially di s tributed dynamic pro cesses can b e modeled. CURRICULUM-W I DE MODELING CAPABILITIES Modeling of s patiall y di s tributed and d y n a mic pro cesses i s a frequently en countered challenge for s tudents throughout the curriculum ModelLA h as the capability for both. Further s tu dents can in ves ti ga t e control of proFall 1 999 _, .,,,. _/ 63 5 C 6 3 0 ; ;; 62 0 Fl ow 6 15 Ra d ial Figure 6. Two-dimensional temperature profile in a phthalic anhydride reactor ca l c ulated b y a ModelLA mod e l Af Bf .. cw out Figure 7. Cas ca d e c ontrol system for a CSTR is constructed after identifying var iabl es that c an be measured and manipulated Multiloop Control Systems Con trol loops can be placed on the pro cess flow diagram as shown in Fig ure 7 for example, by the cascade sys tem on a CSTR The u se r can select a PID controller algorithm or craft a custom controller action in volving, for example, logic elements and actions triggered by a time se quence. The salie nt educational merit of Model LA s u se in configuring control systems is the challenge to identify which variables should be mea s ured which s hould be manipu lated and how to link them Other types of proce ss models in other types of sof tware b y nece ss it y re veal the mea s urement transducers and control valves, thus surrender ing the educational benefit of this intellectual challenge. COURSE MODULES FOR ASSISTANCE IN MODELING INSTRUCTION To assist in s tructor s in u s in g the sof tware for in s truction in model297

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ing, we have developed several course modules that can be used in concert with two of the most popular texts on mate rial and energy balancing, namely those written by Felder and RousseauC 4 l and Himmelblau.CS 1 Several modules on more advanced topics have also been developed. The modules treat the modeling of process systems presented in those texts, some being simple "warm-up" exercises of the single-answer variety, and others involving analyses of trade-off in operating costs with product value in a search for optimum operating conditions. One of the important components of each module is an articulation of the physics and the qualitative cause-effect relationships of the process, thus giving the insttuctor back ground about the project. Because students can benefit from such an analysis as well, students are asked in a preliminary homework assignment to identify the process variables, what affects them, how they might be determined, and to name the relations that fully define a model. Students can benefit from a Q-and-A session with the instructor following such an assignment and before embarking on building a model. The modules also lay out a completed ModelLA model, showing all subunits, fluxes between them phases, reac tions, and transport relations. The full set of design variables and initial conditions is given and the full set of ModelLA declarations is provided on a disk file so that a numerical simulation is ready for execution. For each ModelLA model tips and reminders are given to the instructor concerning certain declarations that may not be obvious or that might be overlooked. These can be passed on to the students as they develop the model. Some models may be crafted in more than one way. In those instances, we have included a discus sion of the philosophy of the approaches and have given the rationale for the approach selected. Results of the numerical simulation of all models are given in graphical or tabular form and are discussed in relation to the physics and cause-effect characteristics treated in the preliminary homework assignment and also in relation to questions asked in other assignments. Projects involving design or operating trade-offs show the behavior of an ob jective function as a function of split fractions and fraction conversions, for example. As a means of getting students "up to speed in use of the program we have prepared an on-screen tutorial that guides the learner through the several types of declarations in the hierarchy interactively with a "live" ModelLA program run ning concurrently Our experience is that students pick up the general structure and features of the program in about a 2-hour session with the tutorial and the finer details with subsequent use in modeling projects SUMMARIZING THE EDUCATIONAL INITIATIVES This phenomena-oriented and hierarchically structured soft ware propels students quickly into model building and prob29 8 lem solving. The model can be built expeditiously because the focus is on the phenomena and because students need not struggle with equation writing. The hierarchical structure of the software embodies the same hierarchy used by engineers in declaration of model characteristics and thus promotes a natural and intuitive flow of model development. The release from equation writing permits the students to push ahead with model development and problem solving and helps them build a "can-do" confidence in completing an engineering project. Writing equations is deferred to the end of the project. Students at that point are much better informed about process character and more receptive to in struction about formulating model equations. Further, the instructor has the opportunity to describe the structure of the model a matter rarely treated, but one of value when consis tently brought into view across the curriculum. Thus, we favor the inversion of the usual order of equation writing and problem resolution. The ability to build a model quickly and efficiently with ModelLA is a major contribution to student learning. Stu dents are steadily engaged with the physics and are given instant feedback about inconsistencies or just plain impos sible constructions. Waiting for instructor approval is thus unnecessary Efficiency is very important also in satisfying the degrees of freedom through identification of design and operating variables There is a good amount of qualitative cause-effect analysis needed on the part of the student in this and ModelLA helps one to move through selection of design variables rapidly in an orderly sequence. This new avenue to teaching modeling can speed student grasp of using engineering science concepts in any course environment. Inasmuch as our current method of instruction rests heavily on quantitative models of fundamental phe nomena and on models of process systems, there is consider able incentive to improve the efficiency and effectiveness of that instruction. There is a marked commonality of modeling needs across the curriculum that can benefit from this hierar chical modeling environment. AVAILABILITY OF THE PROGRAM ModelLA and several course modules will be available in the near future to faculty members interested in helping us evaluate its effectiveness in teaching modeling. Re quests should be made on departmental letterhead to Pro fessor George Stephanopoulos at MIT. The program will be available to all interested persons following the evalu ation period. ACKNOWLEDGMENT OF OUR HELPERS Miklos Gerzson assisted in scouting some early ideas for familiarizing students with process behavior. Michael Lasinski assisted with coding of some of the graphical dis plays. Berkeley junior-year students Adam Cate Valerie C h e mi c al En g in ee rin g Edu c ation

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Grill, James Comb, and Ryan Over s treet assisted with evalu ation of the software and with the de ve lopment of process models P rofe ssor Terje Hetzberg of the Norwegian In s titute of Technology Trondheim in a sa bbatical year at Berkeley assisted the Berkeley team with modeling technique s and evaluation of the software. THANKS TO COLLEAGUES ABROAD We benefited significantly from the help of Professor Costa s Pantelides and hi s associates at Imperial College, London whose state-of-the-art numerical so l ve r (a component of gPROMS) added importantl y to this proje ct. Software for the analysis of the index of differentiala l ge braic equations, generously provided by Profe ssor Wolfgang Marquardt of the Lehrstuhl Fuer Prozesstechik, RWTH, Aachen, Germany was a key element in assessing the numeric a l so lvability of the equations. Profes so r Rafiqul Gani of the Chemical En gineering Department Lynb y, Denmark helped u s with es timating pha se conditions in our early sco uting work. SUPPORT BY THE NATIONAL SCIENCE FOUNDATION We are appreciative of the s upport of the Directorate for Education and Human Re so urces of the National Sci ence Foundation for the development of thi s so ftware a nd course module s. REFERENCES 1. Dougla s, James M. Conceptual D esign of Chemical Pro cesses McGraw-Hill, New York, NY (1988 ) 2. Barton P.I., and C.C. P ante lid es, Modeling of Co mbin ed Di screte / Contin uou s Proc esses AIChE J 40 966 ( 1994 ) 3 Oh, M., an d C C. Pantelides, "A Modeling and Simulation Language for Combined Lump ed and Di strib u ted P aram eter Systems," Comput. Chem. Eng., 20 611 ( 1996 ) 4. Feld er, Rich ar d M., and R ona ld W. Rousseau, Elementary Prin ciples of Chemical Engin e ering 2nd ed. John Wiley & Sons, New York, NY ( 1986 ) 5 Himm e lbl au, David M ., Basic Principl e s and Calculations in Chemical Engineering 6th ed., Pr entice Hall ( 1996 ) U ni v ersitie s Wh y ? Continued from page 29 1. then not only do we hinder st udent growth, but we also undermine the university and ultimately, corrupt soc iety. If this seems farfetched, consider the catastrophic conse quences of the Soviet experiment in w hich a soc iet y at tempted to provide economic sec urity while s uppressing intellectual growth and development. Consider further the grave difficultie s now bein g face d b y co untrie s of the former Soviet Union-difficulties engendered becau se too many of their people fail to underst a nd how modern Fa/11999 societies function In our socie t y, the diffi c ultie s of educating are exacerbated b y an astonishing degree of se lfsa tisfaction It is pos s ib l e to operate cars computers, and microwave ovens without know ing anything about how they work; pos si ble to vote and pay taxe s without under s tanding the rudiment s of government ; po ssi ble to work at a job without comprehendi n g the larger workings of the economy; po ss ible to be courteous and well meaning while ignoring the deeper implicatio n s of hu ma n p syc holo gy In other words, it is po ssi ble for many to live only at the s urface of the culture and to be unconcerned about the underpinning s b y which the soc iety functions The operative question i s thi s : For a soc iety to survive and its culture to continue to evolve, what i s the smallest fractio n of the population that mu s t comprehend how t h e society functions? In modem societies, it is the unique responsibility of uni ve r si ti es to keep that fraction above the minimum. REFERENCES 1. Ortega y Gasset Jose Mission of the Unive rs ity, Princeton University Press, Prin ceton, NJ ( 1944 ) 2. Hamilton E ., The Gr e ek Way Norton, New York NY ( 1930 ) 3 Petroski H Th e Pencil A.A. Knopf New York, NY ( 1990 ) 4. Hamilton E ., and H. Cai rns eds, Th e Collected Dialogu es of Plato, Princ eto n University Press Princ et on NJ ( 1961 ) 5. Wilson, F.R., Th e Hand P ant h eon New York, NY ( 1998) 6 Whitehead Alfred North, "T he Aims of Education," presi dential a ddr ess to t h e Mathematical Association of England 1916 ; reprinted in Alfred North Whitehead, An Anthology, edited by F.S.C. Northrop an d M .W. Gross, Macmillan, New York, NY ( 1953 ) 7. Newman John H enry, Th e Scope and Nature of University Edu c ation, 2nd ed., Longman Green, Longman and Rob erts, London ( 1 859 ) 8 Bronow s ki J., Science and Human Values, Harper & Row New York NY, C h 2 ( 1956 ) 9. Wilson, E.O ., Consili e nce, A.A. Knopf New York, NY ( 1998 ) 10. Committee on Undergraduate Science Education, Trans forming Und e rgraduat e Education in Science, Math e mat ics Engineering and T ec hnology, National Res ea rch Coun cil National Academy Pre ss Washington DC ( 1999 ) 11. Egan, K. The Edu cated Mind University of Chicago Press, Chicago IL ( 1997 ) 12 Don ald, M. Or igins of the Modern Mind, Harvard Univer sity Press, Cambridge MA ( 1991 ) 1 3. H ai l e, J.M., Tow ar d Technical Understanding. I. Brain Structure an d Function Chem. Eng. Ed ., 3 1 152 ( 1997 ) 14 Haile J.M. To war d T ec hnical Understanding. II Elemen tary Levels, Chem Eng. Ed 3 1 214 ( 1997 ) 15. Haile J.M. To ward Technical Understanding III Advanced Levels ," Chem Eng. Ed ., 32, 30 ( 199 8 ) 16. Petroski, H "Work and Pl ay," Am Sci., 87 208 ( 1999 ) 17 Mach, E., Th e Science of Mechanics, 6th ed., Open Court Publishing, LaSall e IL ( 1960 ) 18. Wankat, P C., R eflective Analysis of Student Learning in a Sophomore Engine er ing Course," J En g Ed ., 8 8, 195 ( 1999 ) 299

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~9=1 classroom ) --------------COMPUTER SIMULATION OF TRACER INPUT EXPERIMENTS J.A. CONESA, J. GONZALEZ-GARCIA, J. lNIESTA, P. BoNETE, M. INGLES, E. EXP6srTo, V. GAR ciA -GAR ciA, V. MONTIEL Universidad de Alicante Alicante, Spain I ncorporating a personal computer in the classroom has brought a new quality to the study of chemical engineer ing that was unthinkable just a few years ago. Due to its mathematical calculation powers the comp uter allows us to study complicated experimental systems that are unapproach able from an analytical point of view, and its rapid results are especially beneficial in chemical engineering Experi mental results of several systems can be simulated by using the theoretical equations that govern the process. This meth odology permits us to quickly analyze the influence of differ ent variables that affect the system behavior without the long and hard experimental testing that can distract a student. This paper proposes a practical class for undergraduates in their first year of chemical engineering where the character ization of a reactor is ac hi eved through recording the resi dence time distribution (experimental response obtained from a typical test stimulus-response for the hydrodynamic c har acterization). The distributions are simu l ated with a theoreti cal model allowing the quantification of the parameters c h ar acterizing the reactor behavior as a function of the operating conditions (flow rate) Specifically, this paper provides the particulars for a prac tical session using a versatile computer program that simu lates the tracer input experiments It is necessary howe ver, that the studen t s have prior knowledge of reactor design theory. This background material should have included the ideal reactor models and the so lution s to problems where several curves were analyzed using the momentum method or through simple iteration .(1 1 The practical lesson described here has been designed for two students working together for a period of approx imately four hours. The students should h ave some knowledge of how to program in the BASIC language but it is not abso lutely necessary. The experimental work is short a nd repeti tive so the students ca n center their attention more com300 pletely on the simulation This obliges the st udents to make deci s ions concerning the design and plan of the lesson in the following way s: The y must elect the number of flow rates to study. The y must perform small modifications in the BASIC program in order to extend its application (with instructor supervision) Finally a student must hand in a report detailing the ex perimental procedure its results, the conclusions gained, and the important and useful modifications that were made to the BASIC program Once the reports have been pre sente d and the program modifications detailed, the instructor can propose extending the program to the study of even Juan A Conesa is Professor of Chemical Engineering at the University of Alicante where he received his Chemistry Science degree in 1992 and his PhD in Chemical Engineering in 1996 He co ndu cts research on combustion and pyrolysis of different materials and also focuses on characterization of chemical reactors and activated carbon production Jose Gonzalez-Garcia received his degree in Chemistry in 1990 and his PhD in 1998 from the Universit y of Alicante where he is currently a member of the academic staff. His research interests are in electrochemi cal engineering and applied electrochemistry Jesus lniesta is a doctoral student at the Uni versity of Alicante where he obtained his Master s degree in Electrochemistry His interest is in elec trochemical treatment of hazardous organic compou nds. Pedro Bonete received his degree in Chemistry in 1990 and his PhD in 1995 from the Univers i t y of Alicante where he is currently a member of the academic staff. His academic research involves organic and electroorganic synthesis Marina Ingles received his bachelor degree i n 1996 and his Master s in 1998 from Alicante University. His academic research involves organic electrosynthesis Eduardo Exp6sito received his Master s degree in 1994 from Cordoba University and his PhD from the University of Alicante His academic research involves wastewater treatment and organic electrosynthesis Vincente Garcia-Garcia received his PhD in che mistry in 1991. His research interest is applied electrochemistry. He has worked with labor tory and pilot-plant experiments Vincente Montiel Leguey is Associate Professor in the Department of Physical Chemistry at the University of Alicante His research interests are in electroorganic synthesis and wastewater treatment by electro c hemical methods Copyright ChE Division of ASEE 1999 Chemical Engineering Edu ca ti on

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more complicated systems. The main objective is to demonstrate how the personal computer can help in the quantitative characterization, de sign, and scale of a reactor-a matter of some difficulty when other techniques are used. From the technical point of view, it is interesting to identify the flow pattern, to analyze the reactor behavior when the flow rate is varied, and to classify the reactor when the objective is to optimize the chemical process inside the reactor. BACKGROUND AND THEORY There are two standard models for the ideal behavior of a continuous chemical reactor: the piston plug flow and the backmixed reactor (widely studied in specialized litera turel 2 31 ). Nevertheless, real reactors show deviation s from this ideal behavior for a wide number of si tuations. A vari ety of theoretical approaches have developed in the litera ture for thi s non-ideality. The dispersion model for a tubular reactor i s presented by Levenspiell 21 in considering a hydrodynamical behavior with plug flow and axial dispersion: ac = 0 a 2 c v ac ( I ) ot ax oz 2 oz where C concentration of property measured time z length in the flow direction v linear flow rate D ax axial dispersion coefficient Equation (1) i s u s ually expressed in dimensionle ss form as ac ac 1 a 2 c a8 = oz + P e oz 2 ( 2 ) using the Peclet number Pe=vL/D ax, where L is the total length of the reactor in the flow direction. The dimensionless time, 0, is defined as 0=~ 't (3) TA B LE 1 -r the mean residence time is L t= v (4) Z is the dimen s ionle ss length ( =z/L ), and C is the normalized concentration of the measured property (C is the conductiv ity in this paper ). The so lution of Eq. (2) depends on the boundary condi tions for the input and the output.l 4 l Some of these solutions are analytical. For the resolution of Eq. (2) it is intere s ting to consider whether or not the dispersion degree is high On the other hand the boundary conditions must be kept in mind i.e. if the system can be considered open or closed. Table 1 shows a scheme of the different cases that can be presented. This disper sio n model defines with great exactness several practical situations, especially when the shape of the experi mental curves is Gaussian with a high symmetry (if the di s per sio n degree is low ) or with a tail (if the di s persion degree is high) Y 1 The model presented in this paper considers a more global non-ideal situation: coexistence of a dead volume inside the reactor and two flow path s, each modeled with an axially di sperse d plug-flow model. Thus, Eq. (2) is the differential equation defining the disper sio n model for each flow In this paper we considered the most common situation: open-open flow (inlet and outlet do not change the flow pattern) and a high axial di s persion degree. Equation (2) has in this case, an analytical so lution. The so lution for the residence time distribution i s, for each flow, (5) Other model s are ava ilable in the literature as the simple tank s in series mode1 c 5 J with just one parameter or more complex multi-parameter differential model s l 61 The former is not attractive from the didactic point of view, since it is les s intuitive. The latter allows a better explanation of the mass transport phenomena, but it must be u s ed only when there is evidence of s uch phenomena, or Different Mo d e l s fo r Non-I d ea l F l ow when the simpler model s are not able to reproduce the experi mental data. Open/Open Closed/Closed Fall 1999 High Dispersion Degree l ( (1-0)2 I C( 8 ) = / Pe expl40 / Pe j Numeric integration. Boundary co ndition equations: 1 dC Z = 0 then D( 0) = C Pe dZ Low Dispersion Degree 1 ( (l-e)21 c(e) = 2.Jrc I Pe expl 4/ Pe j EXPERIMENTAL DESIGN AND RESULTS In the proposed simu lation model (see Fig ure 1) there are two flows and a dead volJO I

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ume, with five fitting parameters to optimize. The five pa rameters are: two mean re side nce times, two Peclet num bers, and the ratio between the dead volume and the total vo l ume (V/V). From these parameter s the ratio between the volume used by flow 1 (flow rate= Q 1 ) and the total volume (V 1 N) can be calculated by u si ng V = V 1 + V 2 + Yd Q= QI +Q2 V 't =-) I Qi (6) (7) (8) The optimization method used is the Flexible Simplex method l7 1 and the objective function (O.F.) i s the sum of the square of the differences between experimental and calcu lated values of the residence time di s tribution E(t) (9) The computer program estima t es the best parameters to fit the experimental data provides them calculates the E(t) curve, and u ses the value of the objective function. DESCRIPTION OF THE EXPERIMENTAL SYSTEM Figure 2 shows a schematic diagram of the experimental system used to measure and analyze the st imulus-respon se curve. The procedure i s based on the instantaneous modifi cation of a property of the fluid in the reactor inlet and recording the variation of this property with time at the outlet of the reactor. In thi s case, the electric conductivity of the fluid is modified by the injection of a sma ll volume of saturated solution of the tracer. Thi s response will be the data file for beginning the parameter-estimate calculation. Of course, the data acquisition could be computerized and the data analyzed on the same computer. Any kind of reactor could undergo thi s analysis. The sole condition for the reactor is to know the total volume. In the practical example that follows, a built-in-house filter-press electrochemical reactor (UA200.08) is used. The compartment for the fluid i s a drum of dimensions 18xl2x0 .8 cm. A more detailed description of thi s reactor can be found elsewhere. 1 8 1 The design of the hydraulic part of the system is a typical configuration: a deposit for the fluid (water), pump s, and flow-rate measurement units controlled by valves permitting flow-rate adjustment in each experiment. More details can be found in the literature. 191 EXPERIMENTAL DEVELOPMENT Pr evious to the Experiment Before experimental record ing of the curves, it is important to calibrate the measure ment apparatus. The conductivity probe and the flow-mea surement units must be calibrated for the fluid and tempera ture of the experiment. An erroneous measurement of the 302 flow rate would lead to an overflow situation. In this particu lar case the students must calibrate the probe, so the flow rate calibration is given to them It is important to keep the solution temperature constant during the experiment because conductivity depend s on the temperature This is atta ined with a thermostat heat exchanger in the reservoir. Curve Response Measurement Once the flow rate, the temperature, and the other conditions are s tabilized the pul se of tracer can be rapidly injected collecting the conductivity time data s hown in Figure 2. The injection of the tracer must be done as close as possible to the reactor inlet. In this case, the tracer was 2 mL of a saturated KCI so lution (4 .3 M). A conductivity probe (Ingo ld ) mea s ure s the conductivity of the outflow stream reactor. Thi s probe is connected to a conductivity meter with an analog output of Oto 10 V (erro r Axially di s per s ed plu g flow Volumen V1 Stagnant zone Q Axially dispersed plug flow Fig u re 1. Sketch of the model for flow characterization ~----to waste 9 8 10 C:=Jooo EH 7 2 3 6 = 1 11 4 Figure 2. Diagram of the experimenta l set up : 1. reservoir; 2. thermometer; 3. heat exchanger; 4 pump; 5. valve; 6 flowmeter ; 7 injection of tracer; 8. reactor; 9. conductivity probe ; 10. co ndu ctimeter; 11. computer. Chem i cal Engineerin g Education

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less than 1 % ). The conductivity meter, through a data acqui sition card (12 bits, monopolar channel input free tension 0lOV), permits saving the data in an ASCII file in the com puter (PC-compatible system, at least 80386 processor 2 MB RAM memory). Recording the response must be done until the value of the conductivity signal reaches the initial value. This simple procedure is repeated for every flow rate studied. Analysis of the Response The computer program pro posed in this paper needs the data collected in an ASCII file with names RV ** .GEX, where the flow rate must be in cluded. If the experimental system is similar to the one in this paper (with the data acquisition card), the conductivity time curve will be recorded automatically by the computer The experiments can also be done by simply recording the analog X-t curve and digitizing it. The computer program is written in BASIC; a copy of it can be requested by e-mailing JA.CONESA@UA.ES. The program needs the reactor dimensions, the name of the data file, the flow rate, and the initial value of the parameters to be fitted (in part II of the program). E(t) 0 .2 5 0.20 0.15 0 .1 0 0.05 105 Uh RTD exptal RTD calc E1 E2 0 00 ........ -----~--.,---~--~--~ 0 10 15 20 25 tis Figure 3. Superposition of experimental and calculated curves Volumetric flow 105 L/h. TABLE2 Estimating Model Parameters for Different Volumetric Flow Rates QjLh -' 't I / S Pe 't z / s Pe V 1 N VrfV 0 F 66 3 84 15.46 12.72 2.76 0.33 0.42 1.5 10 3 105 3-38 20.11 8.74 3.58 0 43 0. 2 1 5.0 10 3 155 2.41 22.38 6.65 3.39 0 43 0.10 3.3 10 3 Fall 1999 The s olution i s not s trongly dependent on the initial values of the parameters Thus the initial values for the mean resi dence time could be selected as the ratio between the total volume and the flow rate (the same value for both ways) On the other hand typical values of the Peclet number are between 1 and 50 and the initial value of V ctfV could be selected as 0 5. When these initial parameters, experimental conditions and response curve value s are entered, the program can be run. Using the initial values of the parameters, the suc cessive iterations will diminish the value of the objective function. After each iteration, the program shows the new value of the parameters the current value of the objective function, and the minimum value O.F. achieved until this iteration The simulation ends when the value of the O F minimum reached is repeated and the variations of the parameter val ues do not change. The program generates an output data file (with ASCII format and name RV **. CAU) with five col umns of data : time experimental residence time distribu tion calculated residence time distribution, calculated resi dence time distribution for flow through path 1, and calcu lated residence time distribution for flow through path 2 In addition the optimized parameters are also saved at the end of the output file (Pe and average residence time for each path, and V,N), and with the value of the dead volume (Vi V) and minimum O.F. reached ANALYSIS OF RESULTS The experiments were carried out with three different flow rates (66 105 and 155 1/h) Figure 3 shows the experimental and calculated E(t) curves, E 1 (t), and Ei(t), respectively, for the flow rate 105 1/h. The optimized parameters for the three experiments are shown in Table 2 In the Table, "Q" is the flow rate, 't; is the average residence time of the path i", and V d N and O.F were defined previously Analyzing the results we can conclude: [] An increase in the flow rate produces a decrease of the residence time in both flow paths, favoring path 1 (of minor residence time and a higher Pe i.e., greater plug flow behavior) versus path 2, with low Pe. This conclusion is obtained from the value of the parameter V,N. The flow circulating through path 1 can be calculated using the relationship between the average residence time and the flow rate (Eq. 8). [] The flow rate also affects the percentage of dead volume, decreasing as the flow rate increases. This is a very important conclusion. DISCUSSION The practical lesson proposed in this paper allows the Continued on page 309. 30 3

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.tA ... 5-.._e t h ic s ____ ____ ) HOW TO LIE WITH ENGINEERING GRAPHICS P. ~NE VESILIND Duk e University Durham NC 27708-0287 T he essence of e ngineerin g is truthfulness. If we are truthful in all of our cond u ct, then we are mo s t likely acti n g ethically. While thi s may seem like an over si mplification the idea of truthfulne ss certainly addresses the central issue of engineering communication. The nega tive si d e of truthfulness is a bit more ethically complicated. What does it mean to not tell the truth? Are all non truth s lie s? Are a ll lie s unethic a l ? In engineering communication, as in all communication, there are two basic types of non -tr uth s: lie s and deception s. In both cases the intent is to have the recipient of the infor mation draw a fa l se conclusion from the available informa tion. While both method s of eliciting false conclusions may be morally wrong, there is a well-defined operational differ ence between a lie and a deception. A lie is a categorical s tatement known by the teller to be untrue An engineer who tells a client that the client's report has been m a iled for example, while knowing full well that it is s till being prepared is telling a lie. Most lie s are verbal, but lie s may also be told by body lan g uage s uch as nodding the head or by g raphic s when, say, s ome data points are intentionally omitted to make the graph look better. Lying requires only that incorrect information i s inten tionally transmitted. If I say I am ten feet tall," that is a lie, regardle ss of who I tell it to In contrast to a lie a deception is an action that begins with a s tatement (verbal or graphical) that may be true, but the intention is for the listener or reader to draw a false conclu s ion If an anxious client asks an engineer for the status of a report, the engineer can say that it is essentially finished." The client might interpet this as meaning that it will be collated in time to be picked by by FedEx that afternoon, but the fact might be that not all of it h as yet been written. If, by using s uch a phrase as "esse ntially finished," the engineer D e partm ent of Civil and Environmental Engineering 304 know s that he or s he is creating a false impression (wi thout overtly lying ), he or s he is g uilt y of intentional deception, and deception with an intent to mislead or obfuscate is not honorable behavior. If the client is savvy enough to ask what the engineer mean s b y "esse ntiall y finished," the e n gineer ha s a chance to t ell the truth o r to lie. Deception in the hands of a professional s u ch as an engi neer can have serio u s repercussions. For example, s uppo se an engineer writes a technical article about an explosion at a chemical plant and intentionally u ses incomplete informa tion that ha s the result of deceiving the journal readership. The engineer is not actually lyin g, but rather is u sing partial data without reporting that other data h ave been omitted. To publish s uch misleading information i s unethical behavior. Other engineers can draw unwarranted conclusions from s uch an incomplete report and the result could be additional indu stria l accidents. Just as words can be u sed to mislead a reader unscrupu lou s or incompetent illustrators can di stort engineeri n g illus trations with both lie s and deceit. Thu s, we must judge engineering illu s trations not only on the value of their infor mation and on their appearance, but also on their integrity In mo s t cases, graphics ha ve a certain sacred value to engineers, and illu stra tion s are se ldom bl a tant li es. Few en gineers and scientists w ill intentionally misplace a data point Aarne Veslllnd received his PhD in environ mental engineering from the Univer sity of North Carolina in 1968 Following a post -doctoral year with the Norwegian Institute for Water Research and another as a research engineer with Bird Machine Company he joined the faculty at Duke University He is presently i nvol ve d in research on waste management including pro cesses for dewatering was tewate r residues, management of municipal solid waste, treat ment of industrial wastes, and environmental ethics in engineering. Co p yr i g ht C hE Divi s i o n of A S EE 1 999 Chemical Engineering Education

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on a graph or add point s w ithout h avi n g the d ata. For thi s reason, mo s t engineering reader s pl ace a great d ea l of weight and credibility on dat a point s. P syc holo g i s t s ha ve identified at lea s t five different visual illusions :C 1 l 1. Illu sions of extent-the s i ze or length is misjudged Sometime s, how ever, so m e researchers or practitioners fai l to include all the relevant dat a points or wi ll move data point s to improve the gra ph. O ccasio n a ll y, data p oints a re so far off the line that the re searc her i s tempted to either discard them as "so methin g went wrong her e" or not e th e m as "rog ue point s." Th e re even exists a s tati s tical test that can b e u se d for removing (w ith full statistica l justification) the data point from the gra ph. Thi s i s a risky bu s ine ss si nce the one "rog ue point may in 2 Illusions of direction-the orientation of a line or fact h ave b ee n an indicator of so methin g very important a nd tot a ll y une x pected Fortunately, in s tance s where engineers and sc ienti sts have u se d graphs for tran smi tting in correct information (lies) see m to be rare, and in cases where there have been fabrications of d a ta the scie ntific co mmunit y ha s properl y condemned the actions. A much mor e in s idi ous (and more common) mi s communication of gra phical information i s the u se of illus tr a tion s for purpo ses of decep tion Graph s don 't hav e to ac tually lie t o express incorrect information si nce it is the per ceived information that matters Most mi s leading illustrations are deception s rather than li es Such deception can be ac hiev e d by several unethical techniques including optical illusion, in appropriate cause and effect unwarranted v isual e mbelli s ment, and misuse of dat a. OPTICAL ILLUSIONS Optical illu s ion s in engineer ing drawing create mi s per ceptions that can cause mi take s. En gi neerin g drawing s must not only be accurate but they must a l so be percei ve d ac c uratel y b y others. Our eyes can play tricks on u s, and it is the re s pon s ibility of the com munic a tor to minimize the po tential for mi s perception Fall 1999 figure is misjudged 3. Illu sions of shape 4. Illu sions of brightness 5 Illu sions of motion Figure 1 s how s so me < ) >---( A (Q) < > C > < B Figure 1. Illu sions of extent. 1 2 3 4 5 exa mple s of the first illu si on illu s ion of extent. In Figure lA th e length of the s traight line between the arrows is equal but the optical illu sion i s that the lower one is longer Thi s same trick can be applied to space, shown in Figure 1B. Figure 1 C shows that the outer circle of a concentric pair is un der es timated while the in ner circle is overestimated. Figure 1 D s hows that for two equal figures between converging lines, the one neare s t the "vanishing point is perceived as larger. Illu s ion s of extent can be u se d to draw graphics that mi s repre se nt the facts Fig ur e 2 is a n example of such a misrepresentation. Draw ing the bar graph inside di verging lines suggests a de crease that in fact i s not true. Figure 2. Using illusion of extent to deceive the reader Figure 3 s hows sev eral examples of the illusion of direction in which the ori entation of a line or figure is misjudged. Figure 3A shows that although the two line A I I 1 1 I 1 I I I I I 1 1 I 1 I I I I I 1 I I I I I I 1.1 1.1 I B Figure 3. Illu sions of direction C seg ment s intersecting the parallel line are actually on the sa me straight line they do not appear that way to the eye. Figure 3B shows how the sequence of white and black s quares can make the line s between them ap pear to bend. Figure 3C s hows two parallel lines that certainly do not appear to be parallel. 305

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The illusion of direction can be used in a graphic as shown in Figure 4. Even though the two lines are parallel, the illusion is that the lines are diverging and the casual observer is left with the impression that the number of people smoking cigarettes has grown at a faster rate than the number of people not smoking Illusions of shape are illustrated in Figure 5. The straight lines on top of the pointed arch in Figure SA appear to bend to make a sharp point. Figure SB shows three arcs of equal sized circles. The more of the arc that is shown, the more the arc appears to curve. All arcs have, however the same radius. Figure SC is an amazing figure showing how the circle can appear to be distorted. The illusion of shape can be shown by the embellished bar graph in Figure 6 Not only is the last bar fancied up, but the chevrons also give an optical illusion of fatness on top, suggesting growth that isn't there in reality Illusions of brightness can be illustrated by the block diagram in Figure 7 A. If you look at the figure for a while you will see darker spots in the white spaces at the corners of the black squares Illusions of motion are often used to trick the eye. Air plane pilots have long been aware of the apparent motion of spots of light during a dark night, called autokinesis. In one interesting experiment, the subjects were placed in a very dark room and asked to focus on a tiny spot of light on the far wall. They were told that the light would be moved to spell words and the test (they thought) was for them to try to read the words. All subjects read what they wanted to read, while in fact the light never moved! Figure 7B shows an example of autokinesis. If you stare at the figure for a while, you will see swirling motion. Motion is optically created while the figure is obviously not moving. I MPLIED CAUSATION Another way graphics can deceive is by implying causa tion where none is warranted Figure 8 shows the correla tion between the rate of typhoid fever deaths and the fraction of the population with public water supplies. Such graphs have been repeatedly published by environmental engineers who want to convince the world that they have performed magnificently and should receive due credit for their efforts. There is no doubt that the construction of clean public water supplies helped reduce the typhoid death rate, but this graph does not prove it. An excellent correlation also results from plotting the reduction in the typhoid death rate and the decrease in the manufacture of buggy whips The conclusion if causation is mis taken for correlation, is that either buggy whips cause typhoid or the reduction in typhoid deaths resulted in the decrease in buggy whips 306 number of people smoking and no t s moking c i garettes 9 6 97 98 99 Fig u re 4. Using illusion of direction to deceive the reader A B C Figure 5. Illusions of shape. P ric e ( $ ) Y ea r Fig u re 6. Using illusion of shape to deceive the reader. A B Figure 7, Illusion of brightness and illusion of motion. Ch e mi c al Engin ee rin g Education

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50 40 Typhoid Fever 30 Deaths (num ber per 100,0 00 20 population) 10 75 80 Population Served 85by Public Waler Supplies 90(%) 95 0 .__ __ .._ __. __ __,_ __ ...;c::,,,,,,-= 100 1890 1900 1910 1920 1930 1940 Year Figure 8. Correlation between population with public water supplies and the typhoid fever death rate in the United States. (After Whipple and Horwood, from Fair, G.M., J.C Geyer, and D .A. Okun, Water and Wastewater Engineering, John Wiley &Sons, New York, NY 1966) 4.5 lb/cap/day 3 lb/cap/day 1960 1990 Figure 9. Deceptive use of two-dimensional pictures to represent one-dimensional data 30 25 Number of Nobel 20 Prizes Awarded to Americans15 10 O 190119111921193119411951196119711910 1920 1930 1940 1950 1960 1970 1974 Figure 10. Misleading line graph due to uneven scale. (National Science Foundation Science Indicators, 1974, Washington DC, 1976) Fall 1999 VISUAL EMBELLISHMENTS A third common source of misperceived (and thus un ethical) graphics is the use of visual embellishments. One oft-used visual embellishment technique is the two-dimen sional bar graph A bar in a bar graph is one-dimensional, showing the quantity as its height. But the bar can also be shown as a two-dimensional picture Figure 9 shows how trash cans represent the bars, but these are actually two dimensional pictures. From this figure we see that even though 4.5 is only 50 % larger than 3.0, the appearance is much greater since the reader sees the area of the trash cans, not just the height. MISREPRESENTATION OF DATA Some graphs are clearly intended to mislead. For ex ample Figure 10 shows a notoriou s graph that appeared in a government document arguing that the United States was losing its edge in scie nce and technology since our share of the Nobel prizes seemed to have dropped precipitously. The truth is that the last data point (1971-1974) is the total number of Nobel prizes for only a five-year interval whereas all the remaining points represent Nobel prizes received during ten-year intervals Some graphs deceive becau se the data are plotted cumu latively, and the reader is not sufficie ntly warned to inter pret the graph in such a fashion. Figure 11 shows the use of various forms of power for electricity production. A quick glance suggests that nuclear power is the most important energy source and continues to provide the greatest share of electricity. The data in this graph are however, plotted cumulatively so that the energy pro duction from various sources is the difference between the adjacent lines Annual Energy Use (J oules X 1016) 400 300 200 0 L---L--.....1--.....1-----L--.....l 1900 1920 19 40 19 60 1980 2000 Year Figure 11. An example of a deceptive graph where the data are summed. 307

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Broken scales can also convey misleading information. Broken sca le s occur ei th er when a n ax i s does not start at zero or when t h e sca le i s temporarily di sconti nued Note how Figure 12A creates a mistaken im pression by not start ing at zero and thus conveys a very different impre sio n from the more hone st Figure 12B. Good practice requires that all broken sca le s be clearly indicated Sometimes it i s pos s ible to conceal data point s in s uch a way as to mak e the rest of the dat a appear much more impressive a nd thereby mislead the reader. Like Figure 13A, Figure 13B shows acc u rate points but with the abscissa moved so that the points are concea l ed Sometimes the aut h ors of a graph read more i nto t h e data than a reason a ble per so n might. Figure 14A shows data u se d as the fo und ation for a 4 8 .-----------, Solid 4 6 Waste Production ( lb/cap/day ) 4 4 4 2 6 5 4 3 2 4 0 .__.....___.....__ _._ ___., __, 0 1960 1 970 1980 1990 2 000 Year A 1960 1970 1980 1990 2000 Year B Figure 12. Data as presented b y the authors (AJ and a mor e hon est presentation without the broken sca l e (BJ. y 8 8 6 ... 0 0 6 0 0 0 4 ... 00 4 00 2 2 0 I I I I 1010 11i2 1d 10 16 1d 8 010 10 1d 2 1d 10 16 1d 6 X X A 8 Figure 13. Data o btain ed in a research experi m e nt (AJ and the plot presented by the authors (BJ. 8 0 8 6 o) 6 00 0 4 0 00 4 0 o 0 2 2 0 0 6 12 Oo 18 20 24 0 0 6 12 Oo 18 20 24 X X A B Figure 14. Data obtained in a research experime nt (AJ and the lin e as drawn by th e authors (BJ. 308 complex theoretical model. Figure 14B shows the same data with the line as drawn by the authors. There is no reason to draw s u c h a line except that the model de veloped by the authors predi cte d that this would occur. The mo st that can be sai d in s uch cases is that the data cer tainl y did not disprove the model. Claiming that the data offer proof of the model is however unwarranted Statistics can be used to suggest causation where none exists. The famous Briti s h prime minister Benjamin Disraeli is s uppo sed to have said that there are three kinds of li esI i es, damn lie s, and s tati stics. Di sraeli notwith standing, as long as s tati stics are calculated accurately, the result cannot represent lie s On the ot her hand, statistics opens up a tremendou s opportunity to deceive There is no doubt that the inter pretation of sta ti s tics can be manipulated to serve the de sired end. One of the mo st u se d (a nd abused) s tati stica l techniqu es is the lea s ts quare s fit of data The theory is that the be st fit is obtained when the sum of the squares of the vertical distances be tween the ex perimental values of Y and the line representing the relationship between X a nd Y is minimized. If the s um of the sq uare of these di s tance s approaches zero, then the fit is perfe c t. The sta ti s tic used to measure thi s goodness of fit is known as R 2 If the calculated R 2 = 1.0, then the data fit perfectly T h at is we ge t a perfect straig ht line and all of the data points 15 10 y 5 R' = 0 67 O 0 5 10 15 15 10 y 5 R 2 = 0 67 0 0 5 10 15 X 15 .-------, 10 5 R = 0 67 0L--------l 0 5 10 15 :: 5 : 0 R = 0 67 0 5 10 15 X Figure 15. Four plots with data showing identical R2 values (After Anscombe F.f., "Graphs in Statistical Analysis, Am. Statistician, 27 17, 1973J. Che mi cal En g in e ering Education

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fall exactly on the line If R 2 = 0, then there is no fit whatso ever; there is no correlation between X and Y. Shady ethics enter whe n R 2 is u sed to determine the good ness of fit wit hout also including the plotted data, or without using common sense. Figure 15 shows how statistical cor r lation can be s ub vertedY 1 The four data sets ca n be plotted to yield exact l y the same R 2 = 0.67. Each data set has the same mean and is described by the same least-squares equation. And yet the data when plotted and viewed on the plot s, represent four totally different populations Only by plotting the data would the reader understand the actual relationship betwee n the two varia bl es. CONCLUSION Depicting the truth by avoiding both lies and decep tions in e n gi n eering graphics is invariably the safest course of action for engineers. Or, as Mark Twain suggested, "A l ways tell the truth. That way you don t have to re member what you said." REFERENCES 1. The psychology of optical illusion has been studied for over 200 years. Many of the examples used can be found in two excellents books: J.O. Robinson Th e Psy c hology of Visual Illusion Dover Publications, Mineola, NY ( 1992 ), and M. Luckiesh, Visual Illusions Dover Publications Mineola, NY ( 1965 ) 2. Anscombe, F.J., "Gra phs in Statistical Analysis, Am Stat istician, 27 17 ( 1973 ); as described in Betthouex P .M., and L.C Brown, Statistics for Environmental Engineers, Lewis Publishers Boca Raton FL ( 1994 ) Tracer Input Experiments Continued from page 303 student to und erstand and complete the theoretical lessons concerni n g c h emica l reactor design. The versa tilit y and ra pidity that comes with using a per so nal comp ut er has exce l l ent pedagogical aspects. It must be remembered, however that it is necessary to refer constantly to the suitability of using more simple models (lower number of parameters ), making some of the variables in the program constant. In this way, we avoid the problem of using models with more parameters than degrees of freedom of the system. The time ne cessary for recordin g the responses and s imu l atio n of one c urve of residence time distribution, once the preliminary steps are finished, is estimated to be between 10 and 15 minutes for a reactor of dimension s similar to the one described in this paper. This allows the s tudent to perform a se ries of eight different flow rates in two hours using the first hour to prepare and calibrate the sys tem as well as to prepare the tracer solution. The la s t hour can be used to discuss different aspects wit h the teacher, proposal of pro gram modifications a nd other applications. Fall / 999 CONCLUSIONS Thi s class was designed for st ud ents to familiarize them with the concepts of reactor design and characterization. The reasonably goo d agreement between experime ntal a nd cal culated values of the RTD makes them fee l co nfident about applying engineering concepts The students find the experimental procedure relatively uncomplicated and possible to complete within the labora tory period. Using personal computers to study an electro chemical reactor rather than s imply studying the theoretical co n cepts provides better comprehension of the reactor flow pattern and the model development. It is important that the theoretical concepts b e explained in class before the stude nt s at t e mpt the laboratory exercises. Operational problems also become clear while th e s tudent s are performing the experiments. For examp le the impor tance of rapid injection of the tracer was discovered by severa l s tudents who found t h at the response was "ab nor mal" in the sense that many peak s were found when non instantaneous modification of the conductivity was achieved in the input. Another important concept involved in this practice is th e optimization method and its st ru ct ur e in the BASIC pro gram. Students appreciate when so m eo n e exp l ains how to run an optimization method such as the Simplex u sed in thi s lab session. Student s find the sessio n interesting and enjoyable, and they relate well to the engineering principles invo l ved. The le sso n allows them to perform and validate what they h ave learned in class. REFERENCES 1. Davi s, R.A ., J.H Doyle and O.C. Sandall, Liquid-Phase Axial Dispersion in a Packed Gas Absorption Column," Chem Eng. Ed., 27 20 ( 1993 ) 2. L evens piel 0 ., Th e Chemical R eactor Omnibook, OSU Book Store, Corvallis, OR ( 1979) 3. Nauman E.B Ch e mical R e actor D esign, John Wiley & Sons New York, NY ( 1987 ) 4. Westerterp K.R. W P M. Swaaij, and A.A.C.M Beenackers Chemical R eacto r D esign and Operations, John Wiley & Sons Amsterdam ( 1984 ) 5. Levenspiel, 0. Chemical R eaction Engin ee ring John Wiley & Sons, New York, NY, p 253 ( 1972 ) 6. King, C.J., Separation Process es, McGraw-Hill, N ew York, NY, 570 (1980) 7 Himmelblau D M ., Process Analysis Statistical Methods, John Wiley & Sons, New York NY ( 1968 ) 8 Gonzalez -G arcia, J ., V. Montiel A. Aldaz J.A. Conesa, J R. Perez, and G. Codina Hydrod ynamic Behaviour of a Filter Press Electrochemical R eactor with Carbon Felt as a Three Dimensional Electrode," Ind. Eng. Chem Re s., 37 4501 ( 1998 ) 9 Ingles, M., P Bonete E. Exp6sito V. Garcia Garcia, J Gonzalez-Garcia, J. Iniesta, and V. Montiel Electrochemi cal Regeneration of a Spent Oxidizing Solution: An Ex ample of a Clean Chemical Process, J. Chem. Ed ., (i n press ) 309

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.t3.-5 111111 .._ c_l_a_s_s_,-,_o_o_m _________ ) INTRODUCING PROCESS CONTROL CONCEPTS TO SENIOR STUDENTS Using Numerical Simulation MOBOLAJI E. ALUKO, KENNETH N. EKECHUKWU Howard University Washington, DC 20059 A mong all the courses in the chemical engineering curriculum, students generally find process control the most challenging. Perhaps one reason is that it is one of the final courses of their undergraduate curriculum. Our observation, confirmed by another source,c1 1 was that s tudents oftentimes characterize the course as an abstract study with extensive mathematical derivations that bear little or no relevance to the practice of chemical engineering. This has prompted a re-examination of process control instruc tion at Howard University, with interest focused on how knowledgeable the graduating students are with respect to being able to apply their process-control knowledge when they leave for industry Although this re-examination is still proceeding we want to share some of our experience s with a learning module that was introduced for the purpose of helping students rethink their views about process control. Understanding how the subject of process control was viewed, we felt there was a need to stimulate interest in the course by adapting the course materials in a manner that makes learning exciting. We have done this through an assignment involving model ing and simulation using the Mathcad software package. The typical tasks covered in the assignment range from routine material, component, and energy balances to numeri cal simulation of uncontrolled and controlled systems. The assignment thu s formulated substantially covers most of the major topics in the undergraduate process control curricu lum. The only set of new material that is needed to comple ment the students' knowledge in order for them to be able to do the assignment is the control law, under which a brief explanation of the effects of proportional integral, and de rivative control modes are explained As for modeling and simulation, the knowledge the s tudents have gained from prior courses in chemical engineering calculations,r2 1 kinet ics ,l3 1 heat transfer, r 41 and advanced calculus are more than 3 10 enough to get them through the assignment. The instructors' responsibility lies solely in guiding the students so that they will be able to synthesize ideas based on what they have already learned in these prior courses. With proper guidance a successful modeling and simu lation of the system was found to be beneficial to the st udent s in introducing various aspects of process control, such as the concept of a closed feedback control loop Y 1 PROBLEM STATEMENT The simulation assignment was taken from established sourcesl 6 71 with slig ht modification. Given was a CSTR equipped with a cooling jacket in which a first-order exo thermic reaction of decomposition of hydrogen peroxide into water and oxygen occurred in the presence of excess sodium hydroxide, which acted as a catalyst. 1 H 2 0 2 + (NaOH) H 2 0 + -0 2 + (NaOH) 2 Mobolaji E. Aluko is Professor and Chair of the Department of Chemical Engineering at Howard University He received his BSc from the University of lfe Nigeria his MSc DIC from the Imperial College London and his PhD from the University of California Santa Barbara His research interests are in the math ematical modeling of chemical reactors mate rials processing, and coal-related technolo gies. Kenneth N Ekechukwu is a lecturer and se nior research fellow at Howard University He earned his MSc and PhD from Warsaw Uni versity of Technology Poland He joined Howard s Department of Chemical Engineer ing in 1992, where he has been pursuing re search activities in coal-based technologies materials science engineering, and develop ment of new products via environmentally be nign processes Copyright ChE Division of ASEE 1999 Chemi c al En g in ee ring Education

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The reacti n g mixture flowed in through a linear v alve while the product was discharged through a sq uare root valve. We wanted to investigate the uncontrolled and the co ntroll e d dynamic b e h avior of the conce nt rat ion of H 2 0 2 and the temperature of the reactor from time t = 0 to some time after fust filling (starting with an empty reactor ), following which control was initiated. The need to formulate the re l evant mas s, component, and e n ergy balances in a manner t h at was fair l y ge n era l and ca pabl e of accep tin g different parameter va lue s s uch as inlet concentration, temperature reactor vol ume and others was emphasized. The parameters of the sys t em are presented in Table 1. The mean tem perature difference b etween the reacting mixture and the coo lant was expressed as a function of difference in temperature of the reacting mixture and the inlet tem perature of the coolant as T-T c=A l lTFc) where F 2QcCP C UAc The students were asked to s how all steps of the formu l ation i n cluding the sys tem diagram ( Figure 1) a nd to s t a t e a ll ass umpti ons clearly. We pointed out that the units of the data provided were all mixed up, which meant that conversion to a uniform sys tem of unit was required before s imulation. The problem as signment was to culminate in s howing the reactor 's liquid h eight, conce ntration a nd temperature profiles as a function of time with a short comment on the s tability of the syste m TABLE 1 Values of Parameters Used in Simula tion V 16.2 liters CLASS ORGANIZAT I ON The class was organized into teams averaging four to five stu dents for the assig nm ent and met three times a week ( u s u ally before noon on Monday Wednesday and Friday) for one-hour lecture s, which was in addition to a 3-hour laboratory period per week, scheduled on Monday afternoon A s ubstantial portion of thi s open-ended assignment was treated within the framework of the laboratory The importance of team work was stressed, with an emp h asis on including the workload distribution in the final report as a req uir ement. The team members were also asked to exclude the name s of any inactive participant in the report ( the s tudent in question would receive a failing gra d e). One of the item s in the list of topic s to be discu sse d each week was h ow well th e team members interacted and w h et h er there was a need to either exclude or s plit any team into s mall number of st udents Usually, the students refrained from creating conditions that would precipitate splitting their team s in ce it wo uld amount to a heavier workload per student left on the team. Perhaps as a result of these prior arra n geme nt s, no team was split. THE MODELING The model of the CSTR system was expressed in dimensionles s s tate-space form, in term s of liquid height (e quivalent to liquid vol um e for the reactor vessels that were not uniform in cross sec tional area), concentration, and temperature. Eq u atio n s (1) and (2) (see Table 2, next page ), respectively designated th e dimen sio nless state space of the syste m under uncontrolled and con trolled conditions with appl i cab l e initial conditions a nd Jaco bi an defined by Eqs. (3) a nd (4), re s pectively. These syste m s c h arac t er ize the time variations of th e state s pace whic h belong to a class of nonlinear autonomous equations in which there was no t ime vari able involved in the definition. Large nonlinear sys tem s occur in many important applicat i o n s s u c h as the s imulation and contro l of chemically reacti n g systems Final Control Element 1 1<1 1-----.., Contr~ler k o E Cp c 5.04 x I 0 1 0 I/sec 18 .620 cal/mo l 0 865 ca l/ g C 62 5 BTU/(hr ft 2 F)/(lb/min ) 11 3 ,, r 1 c, cp 1,e -+~ Temperature y Setpo i nt u C Q.,' 13 T 22 c T c in 10 c T se 14 c C AO 11 .5 mo l /liter F 0.5 li ter/min p I. I 081 g/cm 3 t,H -22.6 kcal/mo! Q., 900-3600 lb/min K v 0 .9 cm 25 /min Kp 3 liter/min K D 25.2 cm A 3.18 ft 2 Symbol names are s tated in the nomenclature Fall 199 9 __. O c, T cin Coolant Out Oc Tc ~ Thermocouple Figure 1. A closed feedback control loop of the modeled CSTR showing the essential components and parameters. 3 11

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whose solutions sometimes precipitate what is known as "still problems ." The still problems usually arise from mix ing of terms of fast and slow dynamics with the consequence that the use ofRunge-Kutta's fixed-step technique will yield unsatisfactory results. Students were therefore reminded that stiff problems are more competently resolved by employing varying-step methods such as the modified-adaptive step, Brulisch-Stoer or Rosenbrock techniques, all of which are built into the Mathcad software package (see Table 3). Most s tudents were already familiar with Mathcad and the decision to use it for the problem assignment enabled a focused attention on the problem solution rather than be ing worried with writing a correct high-level program ming language. Additionally it enabled a different under standing of other process control simulation modules, such as the use of Process Identification and Control Loop TABLE2 (1) (2) (3) df 1 d0 dX 1 dX 2 dX 3 J= df 2 df 2 df 2 df 2 d0 dX 1 dX 2 dX 3 (4) df 3 df 3 df 3 df 3 d0 dX 1 dX 2 dX 3 h C T X C A i T x,=Xz=-X 3 =2 in-c x 3 in =~ h o CA O T o 0 0 X T se t X TCin 0 =~=Ah o F U=~C 1 F I se t T o C tn To F o F o in o -F 0 kv0 k c T 0 0 UA c 0 -E (5) a=-b = k 0 0 c=-d= y = RT AFo Ah 0 I pCpAh 0 l+ 0 F e (-1'.'iH)bCAo UAc0 P1 = P z = pCpT O pCpAh 0 3 12 C h e mi c al En g in ee rin g Edu c ati o n

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Explorer sys tem PICLES ,l 8 1 and MA TLAB/SJMULINK ,C 9 11 1 which were introduced later for different process-control problem assignments. Advanced control syste m 11 2 1 is a simi lar sof tware package that i s also available. CASE STUDIES The tasks of the problem assignment en compassed si mple case stu die s aimed at determinin g the dynamics of the OBSERVATIONS AND CONCLUSIONS Our observations can be summarized in two categories: the pedagogical value of the approach and the usefulness of si mulation as a powerful tool in learning various concepts in process control. From the s tandpoint of pedagogy it was TABLE3 Various Built-In Solution Tools of Mathcad Outputs Uncontrolled system during fill-up Uncontrolled system at constant liquid height Varying Step Technique Z=Rkadapt(X 0 ; e r, npoints D( 0 ,X)) Z=F( 0 .x,.x 2, X) Z=FC e .x,.x .x ) Z=FC e .x,.x ,. x ) Z=FC e .x,.x .x ) Rosenbrock Technique Z=stiffr ( X, 0 ; e r npoints D( 0 X),J ) P-onl y contro ll ed system at constant liquid height Fixed StepTechnique Z=rkfixed(X, 0 ; 0 r npoints, D( 0 ,X)) Burlisch-Stoer Technique Z=stiffb(X, 0 ; e r npoint s D( 0 X) J) P-only controlled system right from start-up Effects of multiple-fold increase in cooling rate Typical s imulation conditions associated with each case s tudy are explained in Table 4, with representative graphi cal results s hown in Figures 2 through 4 Prior to sim ula tion, it was in s tructional for the st udent s to make the equations dimensionles s and to prepare a table of vari ables detailing the input values assigned to each param eter under each case study, as s ho w n in Table 5. TABLE4 Various Simulation Case Studies Invest i gated Case Studies Unc o ntrolled dynamics during fill-up Il Uncontrolled dynamics at constant height ill P-only controlled sys t em a t constant height Co11ditio11s ( I ) X =0; X 2 =1; X 3 =1 ( 2 ) F ;.., =F 001 ; X 1 =1 ; X 2 =1; X 3 =1 ( 3) F ; =K c (X 3 -X ,.,.) and (2) IV P-only co ntr olled syste m at s tartup (4) F; ,. =K c (X 3 -X ,. ,.) and (I) V Effects of multiple-fold increase in cooling rate ( 5 ) n=l 2 .. N; Qc=nQc and (2) TABLES Input Values Used in the Calculation Parameter l 0 0/5 a 0 b l.63El3 C d e l.5EI 3 9.342 -31.78 ll 0/5 0 01 l.63EI3 I. SE 13 9 342 -3 I. 78 III 015 0 01 l.63El3 49 17 0 907 l.5El3 I l .5El3 9.342 -31.78 Case Studies l.l'.'. }'. Description 015 0/5 Time (Initial/F inal ) 0 01 0.01 Coefficie nt l.63El3 l.63EI3 Coefficient 49.17 49 2 245.8 Coeffic ient 0.907 0.91 1.55 Coeffic i ent I.SE 1 3 l.5El3 Coefficient I I Flow rate l.5El3 l.5EI 3 Coefficient 9.342 9 342 14 .83 Coefficient -31.78 -31.78 Arrhenius Number Inlet Concentration inl et Temperature 0.959 0 959 0 959 0 959 0.959 inl et Coolant Temperature 0 973 0 973 0.973 Setpoint o < > 1 <2> o <'> o < > lnjtial Hei gh t initial Concentration initial Temperature < >> To avo id sing ularity problems the actual number used was I x I o 6 < 2 > Liquid le vel was fixed at constant height while temperature was being controlled Fall 199 9 3 1 3

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&-G-e Feed Height &+--e Concentration Temperature Dimen s ionl ess Tim e Figure 2. Case Study I : The d y namic response of the uncontrolled system during startup, with no effluent output. The tank fills at dim e nsionless time=l. 1.4 ~--.,---~----,-----,----, i i 0 84 I u EJ-oa U ncontrolled Temperature 0-00 P-Only Controlled Temp ., Kp = 3 Liter / min*K >< ><--X C oncentration Without System C ontro l e-e-e Concentration With System Control c 0 56 1------,,--\. -+-----+----+---+--------, ~ C Cl V o ~~-~~-----~ -~ 0 Dimen s i o nl ess Time Figure 3. Comparison of Case Studi e s I (uncontrolled) and III ( c ontrolled) for t e mperatur e and c on ce ntration d y namics Appli c ati o n of proportional c ontrol eff ec ti ve l y remov e d the oscillations in both v ariabl e s. 314 observed that the problem assignment formulated in this manner gave the students a lot of confidence by focusing their attention on the subject of the problem which was to model and simulate the system There was an opportunity to investigate as many case studies as possible, the result of which advanced general understanding of the concepts that are vital to learning of the course materials. Toward the end of the assignment, the preconceived no tion of the course being a means of learning mathematics was suddenly changed to the use of mathematics as a tool in learning process control. Consequently there was a general feeling of "I can do it on my own among many students. This was the kind of confidence we wanted them to develop and our feeling was overwhelming when we saw it work. Secondly, breaking up the assignment into various case studies enabled the students to answer s imple what-if ques tions as s ociated with them For example, Case Study I dealt with investigating the dynamics of the uncontrolled system during fill-up, with the outlet valve closed (see Figure 2) It was learned that so long as the valve remained closed, the liquid level in the reactor would continue to rise, the effect of which would possibly lead to overflow The evidence of the system attaining stability in concentration and temperature i.e., X 2 and X 3 eventually settling at certain bounded levels as time approached infinity even as the liquid level increased 1. 6 ~----,-----.-----~----,----~ Q. E i 0 96 ~ Q 8 g u <> 0 0 C oncentration at c oolant rate Qc = 900 lb / min Concentration at coolant rate 2*Qc Concentration at coolant rate 4 *Qc Temperature at coolant rate Q c T e mperature at coolant rate 2 Q c Temperature at coolant r a te 4* Q c Dim e n si onle ss T im e Figure 4. Case Stud y V: Th e e ff ec ts of multipl e -fold in c reas e in flowrat e of the c oolant is mark e d b y d e cr e a se d fr e qu e n cy in o sc il latory b e havior o f t e mperatur e and c on ce ntrati o n w hi c h eve ntu all y l e d t o th e di s app e aran ce of o s cillation c ompl e t e l y. Chemical Engin ee rin g Edu c ation

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was seen. When a proportional control was applied for con trol of temperature using the inlet flowrate of the feed as the manipulated variable (see Figure 3), the oscillatory behavior in both concentration (X 2 ) and temperature (X 3 ) was re moved. The controlled system experienced gradual decay rather than oscillatory changes that marked the behavior of the uncontrolled system. In Case Study V where the flowrate of the coolant was increased in m u ltiple-fold of up to four, the system experi enced pronounced oscillation in temperature and concentra tion despite the fact that control was applied. But the charac ter of the oscillatory behavior was marked by a decrease in frequency, which eventually disappeared with increase in coolant flowrate (Figure 4). This was an indication that flowrate of the coolant could alternatively be used as a manipulated variable to control the system temperature. The students learned at this point that there was more than one way of achieving control of the system, having discovered the two candidates for manipulated variables, i.e. the feed inlet stream and the flowrate of the coolant. The assignment also gave the students the opportunity to revisit past courses such as kinetics, heat transfer, and calcu lus, and gave them the chance to apply the knowledge they have previously learned to this assignment. Since this as signment was given in the fust two weeks of the course, many students recognized the need to review some of the earlier course materials they had taken prior to process control. Overall, this problem assignment received positive com mendations from over two-thirds of the class with many of them stating that it helped them integrate ideas and to use them to study typical problems that occur in many chemical industries. From our point of view, the project was worth while considering the foundation work it laid for better understanding of various topics taught in other courses in the past. Most important in our estimation, however, was its value in fostering understanding of the subject of process control as a course ACKNOWLEDGMENTS Grateful acknowledgments are hereby made to all students who took the course in chemical engineering process control. Our spe cial thanks go to Masiane Kabelo, Olive Sikem and Bashir Elabor for providing in-depth responses about the course NOMENCLATURE A cross sectional area of the tank cm 2 A surface area for heat transfer, cm 2 a coefficient (see Eq. 5 ) b coefficient (see Eq. 5) C A concentration of component A in tank (Hp 2 ), mole/liter C A, inlet concentration of component A (~ 0 ), mol/liter C P s pecific heat capacity Jig K C 1 parameter associated with heat removal rate BTU /( hr ft 2 F)(lb/ min) 113 c coefficient (see Eq. 5) Fall 1999 D diameter of the reactor c m D ( 0 ,X) vector valued function of the state-space variables d coefficient (see Eq. 5) E energy of activation, J/m o l F sys tem paramet e r associated with coo ling dimen s ionless F 00 dimensionless flowrate F 1 inlet flow rate liter/min h height of the liquid in the tank, cm Jacobian matri x k 0 pre-exponential factor I /sec K controller gain liter/min K K P proportional gain K valve constant cm 2 5 /sec P I coefficie nt (see Eq. 5) P 2 coefficient (see Eq. 5 ) R universal gas constant J /mo l K Q coolant vo lum etric flowrate, liter/min T temperature of the r eac ting mixture in the tank C T temperature of the coolant in the jacket C T 1 inlet temperature of th e reacting mixture in the tank, C T ," se tpoint temperature of the reacting mixture in the tank, C U overall heat transfer coefficient, J/cm 2 K V vo lume of the reacting mixture liter s X dimen sio nle ss height X 2 dimensionless concentration X 3 dimensionless temperature ~'" dimensionless inlet conce ntration X 310 dimensionle ss inlet temperature X e,. dimensionless inlet temperature of the coolant X "' dimensionless temperatur e se tpoint y Arrhenius number dimen s ionle ss MI enthalpy of reaction J / mol p density of the reacting mixture in the tank g/cm 3 0 re s idence time min REFERENCES I. Lant P. and B Newell, Problem -Ce ntered Teaching of Process Control and D y n a mic s Ch e m Eng. Ed. 30 (3), 228 ( 1996 ) 2. Himm el blau D .M., Ba sic Prin c ipl es and Calculations in Chemical Engineering, 6th ed., Pr e ntice H a ll ( 1996 ) 3. Fogler, H.S. Elements of Chemical R eactio n Engineering, 3rd ed., Prentice Hall Chapter 9 ( 1999 ) 4. Ru sse ll T.W .F and M .M Denn In t rodu ction to Chemical Engi neering Analysis John Wiley & Sons New York NY Chapters 12, 13 (I 972) 5. Stephanopoulous G., Chemical Pr ocess Control: An Introdu c tion to Theory and Pra c tice Prentice Hall Chapter 14 ( 1984) 6. Ramir ez, W.F. Pro cess Simulation, Heath Company, p. 81 (1976) 7. Ramire z, W.F. and B .A. Turner "T he Dynamic Modeling, Stabil it y and Control of a Continuously Stirred Tank Chemical Reactor ," A!ChE J ., 15 (6), 853 ( 196 9) 8. Cooper, D.J ., PICLES : A Simulator for 'V irtual World' Education and Training in Proces s Dynamics and Control," Comp. Applica tions in Eng. Ed. 4(3 ), 207 ( 1996) 9. Doyle III F.J., E.P. Gatzke and R S. Parker Practical Case Stud ie s for Undergraduate Process D y namics and Control Using the Proce ss Control Modules ( PCM) Comp. Applications in Eng Ed. (in press, 1999 ) IO. Bequ ette, B .W K D Schott V. Pra sa d V. Natarajan, and R R. Ra o Case Study in an Undergraduate Proce ss Control Course ," Chem. Eng. Ed., 32(3 ), 214 ( 1998 ) 11 Bequette B .W Case Study Project s in an Undergraduate Process Control Course ," Proceedings ofControl-97, Sydney, p. 212 (1997) 1 2 Koppel L.B ., and G.R. Sullivan "Use of IBM s Advanced Control System in Undergraduate Process Control Education," Chem. Eng. Ed., 20 70 ( 1986 ) 3/5

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A ... b ... 311-c_l_a_s_s_r_o_o_m ________ __,,) USING A COGENERATION FACILITY To Illustrate Engineering Practice to Lower-Level Students ROBERT P HESKETH, C. STEWART SLATER Rowan University Glassboro, NJ 08028-1701 A !mo s t every univer s ity ha s a power plant facility that i s an excellent re s ource for students of engi neering processes and equipment. These physical plants contain many unit operations such as heat exchang ers, combustors turbines and boiler water-treatment sys tems that may include membrane devices! The systems are equipped with pumps, compressors fans, pipes atomizers, tanks, finned boiler tubes, inner-wall transfer surfaces, valves, etc. In addition a modern facility includes a data-acquisition system to obtain data to control the plant consisting of ori fice plates, pressure transducers thermocouples level gauges and vibration meters Concentration measurements are made using NDIR gas analyzers for CO CO 2 and total hydrocar bons. And oxygen is measured using paramagnetic analyz ers and NO using chemiluminescence. Concentration mea s ur eme nt s are also made of impurities in the boiler water. These plants are a rich source of engineering examples that are readily accessib l e to engineering students. At Rowan University, we use our cogeneratio n facility in our freshman and sophomore chemical engineering courses In the freshman year we introduce our students to measure ment devices, process flow diagrams and process simula tion This is accomplished in the freshman engineering course in a three-week module on process measurements. ROWAN ENGINEERING CLINICS The Rowan e n gi ne ering facu lt y are taking a lead ership role by using innovative methods of teaching and learning as recommended by ASEE, 111 to better prepare s tudent s for entry into a rapidly changing and highly competitive market place. Key program feature s include Interand multidisciplinary edu c ation created through c ollaborative laboratory and course work Str e ssing teamwork as th e necessary framework for solving complex problems 316 I n c orporation of stat e o f-th e -art t ec hnologi e s through out the curricula Cr e ation of c ontinuou s o pportuniti e s for t ec hni c al com munication To best meet these objectives the four engineering pro grams of chemical, civil, electrical and mechanical have a common engineering clinic throughout their program of study. In addition to the engineering clinic they share a common first year of courses. Our first three classes of entering fresh men are between l O I and 115 students with a n average SAT score of 1252 and who graduated in the top 14 % of their high school class The primary goal of Rowan University s freshman engi neering course is to immerse students in multidisciplinary projects that teach engineering principles using the theme of engineering measurements in both laboratory and real-world settings. Many fres hm an programs focus on either a design Robert Hesketh is Associate Professor of Chemical Engineering at Rowan University He received his BS in 1982 from the University of Illinois and his PhD from the University of Delaware in 1987. After his PhD he conducted research at the University of Cambridge, En gland His teaching and research interests are in reaction engineering freshman engineer ing and mass transfer C. Stewart Slater is Professor and Chair of Chemical Engineering at Rowan University He received his BS MS and PhD from Rutgers University His teaching and research interests are in separation and purification technology laboratory development and investigating novel processes for interdisciplinary fields such as biotechnology and environmental engineering He has writte n over 70 papers and several book chapters Copyr i g h t C h E D i v i s i o n of AS E E 1 999 Ch e mi c al En g in ee rin g Edu c ation.

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proj ect or a se rie s of di sci plines p ec ifi c experiments that may not be cohesively inte grated. Some institutions h ave u se d traditional discipline -s pecific laboratory experi ment s at the fre s hman level 121 while others engage students in di sc iplines pecific fres h man engineering design project s.r3 1 One of the NSF coalition s, ECSEL, ha s major efforts i n freshman desig n that have been widely reported. 14 51 At Rowan freshman engineers are introduced to indu s trial problem s through a se rie s of four module s and interactive lecture s on problem so l v ing, safe t y, and ethics. In thi s paper we will di sc u ss a portion of the pro cess engineering module that u ses the ve hicl e of a cogeneration plant. Freshmen c an be overwhelmed when introduced to real engineering proce sses, and it is important to ha ve well-defined objectives. The y need to under s tand that they are only being introduced to the problem s and are not expected to know all of the engineering princ i p l es of the processes. Our overall objectives for the fall-semester fre s hman engi neering clinic are [I E n g in ee r i n g Meas ur e m ents Students will understand and apply the concepts of accuracy, preci sio n re so lution a nd lin earity; calibrate device s; h ave a knowledge of the ba sics of data acquisition; a nal yze a problem and se lect appropriate mea s urement device s for actual e n g in eeri ng processes. [I Engineeri n g Com m unication Student s will produce plot s u si n g Excel to illustrate engineering principle s; u se PowerPoint for pre se ntation s; u se word proce ss ing for report s of actual engineering problem s. Student s will develop the ability to work in multidi sc iplinar y team s, have effective meetin gs, and u se a prob l em-solving strategy on real engineering problem s [I Engi n eering Fund am e n tals Students will convert unit s, examine equations for dimen s ional homogeneity ; u se e n g ineerin g equations, apply ba s ic concepts (e g., h y dro s tatic pre ss ure, Hook e's l aw, Ohm 's law ) applied to actual e n gi neering problem s. Four mea s urement mod u le s are e mplo ye d in thi s freshman engineering clinic: manu facturing, s tructural proce ss, and e lectri cal e ngineering. Spatial measurements and mea s urement fu n damental s are introduced to fre s hman engineering s tud e nt s as the y fabricate a MAG-type fla s hlight from an aluminum rod. Se vera l str uctural measure ment s are s hown to the s tudent s u s in g a brid ge module. Students first s ur vey a bridge s ite conduct s train measurement s on a model bridge, and s imulate the brid ge. The univ ers ity cogeneration plant i s u se d to s how the u se of temperatur e, pre ss ure flow and co ncentration mea s urement s. The s tudent s tour the cogeneration plant and record data of temperature pr ess ure and flowrate of the water in the cogeneration unit. They then return to the computer l a borator y and s imulate two heat exc han gers, u s ing their readings a n d perform hand calculations for homework Thi s i s followed by two weeks of experiments u si n g temperature pre ss ure and flo wra te de v ices see n in the cogeneration plant. The final module ha s the s tudent s co n st ruct a temperature alarm circuit and investi gate the u se of C++ programmin g in mea s urement s. Thu s, the clinic focuses on mea surements in the fie l d and a l so in tr a ditional laboratory se tting s Field trip s tend to excite s tudent s by breaking down the monoton y of being indoor s and he l ping them prepare for realistic engineering mea s urement s. PROCESS MEASUREMENTS MODULE The proce ss mea s urement s module presents a da y in th e li fe of an e n g ineer to fre s hman engineering students A problem is po se d to s tudent s requirin g them to visi t the uni ve r s ity cogeneration facility At this si te b ot h traditional (ga u ges and thermom eters) and data acquisition mea s ur eme nt sys tem s are employed to monitor the s team and electricity ge neration proce ss. Thi s l a borator y and homework sess ion i s followed by Fall / 999 These [cogeneration] plants contain man y unit operations such as heat e x changers combustors turbines and boiler water-treatment s y stems that ma y include membrane de v ices! The s y stems are equipped with pumps compressors fans pipes atomizers tanks finned boiler tubes inner-wall transfer surfaces v al v es etc. In addition a modern facility includes a data-acquisition s y stem to obtain data to control the plant consisting of orifice plates pressure transducers thermocouples le v el gauges and v ibration meters 317

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two more laboratory sessions in which students make pro cess measurements using similar equipment to that seen in the cogeneration plant. The module lasts three weeks, with each week having a 1-hour and a 3-hour session. Preceding the cogeneration s ite visit, students are given lec tur e and problem sessions on teamwork, safety, system of units and unit conversions, dimensional homogeneity, and significant figures. On the week of the site visit, the students are given a brief introduction to the cogeneration process and are shown photographs of equipment that they are re quired to identify on the site visit. At the completion of this module on the cogeneration facility, freshman students should be able to Convert units of simple dimensions Convert units of a variable, such as flowrate. Calculate the temperature of saturated steam when given a gauge pressure and an appropriate equation. Examine an equation for dimensional homogeneity. Obtain mea s urements of temperature, pressure and mass flowrate and perform an energy balance on the heat exchangers in the cogeneration syste m Create a s imple heat exchanger network using the chemical process simulator HYSYS Identify from a photograph the following: orifice plate pre ss ure transducer thermometer, and pressure gauge. De sc ribe the proces s of cogeneration to a high school s tudent. Natura l Gas 0 (!) m 2 E "'0 zu Water Injection for NOx and Fuel Oil Reduction Power Generation Air From Roof Vent Compressor Turbine for Generation of Electricity Bypass Stack t II) II) ::, Q) "'II) _,:; "' in (!) 0 .. / .g Liquid Blow-off Electricity Generation Exhaust Gases N 2 CO 2 H 2 0 0 2 NO CO, HC's $ Steam to Buildings ----------+! Building A Steam & Electricity Generation Plant Fuel & Air Building B Bu i lding C 1----1----Condensate Return to Plant (Steam condensed to water) Figure 1. Overall schematic of Rowan University Steam & Electricity Generation Feed Water from Deaerator Tank Exhaust Gases to Stack Room Air 0 0 0 0 0 Hot Exhaust Gases To Main Steam Line Heat Recovery Steam Generator (HRSG) m n 0 ::, 0 3 i" Liquid Blow-Off Figure 2. Rowan cogeneration plant fabricated by Energ y Recovery International 3 18 Chemical Engineering Education

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Feed Water Tempera tur e Feed W ater Flowra l e Feed Wate r Press u ,. Bo il e r He a t Reco v ery S te am Gener a t o r (H RS G) B o il e r In let Wate r T emperature trum is the advanced data-acqui s ition sys tem which records 65 c hannels of informa tion including vi bration s, power voltage, amperage, temperature, pre ss ure gas, and flowrates. Students are able to see the advan t ages of u s ing both mechanical gauges and pres s ure transducers. Also given t h roughout thi s module is the cost of various type s of mea s urem e nt equipment. SITE VISIT Fig u re 3. Cogeneration process water flow diagram. Student s are given the proces s flow dia gram s hown in Figure 2 to illustrate the com plexity of a relati ve l y s mall portion of the s team plant pertaini n g to the cogeneration. Figure 3 is a l so given to the s tudents and s how s only the s team production si de of the coge neration unit. Using thi s relatively s imple figure, s tudent s relate their knowledge of boiling water to produc e s te a m to that of s t ea m production in a cogeneration unit. The s tudent s obtain readings (s hown in Table l) from every device marked in Figure 3. Obtainin g reading s in the plant turn s the plant trip into an active l ea rning experience. They need to obtain information from thi s trip that t h ey w i ll u se immediatel y in the si mulation and homework. In addi tion a quiz i s given showing photograph s of some of the common mea s urement equipment. A map of the cogenera tion facility is also give n to the s tudent s to s how placement of the equipment and measurement device s in the building Using these figures, s tud en t s are guided by profe sso r s and upper-di v i s ion chemical e ngineering s tudent s through the combustion proce ss and the production of s team and elec tricity. TA B LE 1 Plant-Trip R ea d ings Reading Reading Value Feed-water tlowrate to coge n eratio n fac ilit y 2 5 1 St ea m tlowrate from cogeneration faci lit y 21 6 F ee d-water temperature 2 1 6 Feed-water pre ss ure 250 Boiler-inlet water temperature 330 Steam pr ess ur e from coge neration system 150 U nits 1000 lb m /hr 1000 lb m /hr o p p s i g o p p s i g COGENERATION PLANT INTRODUCTION Rowan University uses steam for both heating and cooling of its building s An additional benefit to the process is th e generation of electricity We explain to the st udent s that the process of electricity and steam generation is called cogen eration. It is obvious to mo st s tudents how a building i s heated with steam u s ing radiators but it is not obvious how to cool a building with steam! Profe sso rs are probably aware that s team is used with absorption refrigeration 16 81 and we are very plea sed to see that one of the be s t treati ses on this subject is in Perry 's handb ook! 1 91 The overall flow diagram for the u se of steam at Rowan University i s shown in Figure 1. In the Steam Plant steam is produced by thre e conventional boiler s and a cogeneration unit. Steam flows through under ground pipeline s to each of the univer sity buildings through radiator units or the refrigeration absorption units (air cooling), and then is returned as condensate to the steam plant. In our new engineering building th ese unit s are located on the fourth floor and we are attempting to modif y thi s laborator y to u se thi s floor for future engineering cla sses. These reading s are u sed as input to a chemical proce ss si mulation pack age, HYSYS and as input to a set of ha n d feed water economizer @M IO NW 1 \ d l Heat From Slack Gases boiler feed Heal From Turblne Exhaust co g en steam co~enerat i on boiler econom i zer cogeneration boiler 1.614e+06 kJ/h ----------- 101.7 C 173.9 C ~-~ r----Otty 1 066e + 07 kJ/h -. Feed Temperature 173 9 C ----------------Product Temperature 183 3 C __ An advantage of using thi s steam p l ant i s that both traditional (ga uge s and thermometer s) and data-acqui s ition mea s urement sys tem s are employed Mo s t of the traditiona l gauges are for measuring temperature presp~--s ur e, and liquid h eig ht. At the other end of the s pecFa ll 1999 Fig ur e 4 HYSYS-generated process flow diagram with summary tables. 3 1 9

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calculations for a homework assignment. In both the HYSYS simulation and homework assign ment, the students determine the heat duties of two heat exchangers. Upon completion of this short site visit, stu dents have seen actual process equipment and obtained readings from a real process. The stu dents now have motivation to perform engineer ing unit conversions and calculations described in the next two sections. PROCESS SIMULATION At the end of the site visit, students return im mediately to the computer room and are led through a simulation program of the two heat exchangers. The students follow a self-paced tu torial on using HYSYS to simulate their process. They start the computer program and select the ASME steam tables as the thermodynamic prop erty package. Next they simulate the two heat exchangers as heaters. After installing each heater they enter the readings obtained in the plant. From this simulation, they obtain the tempera ture of saturated steam and the values of the heat duties of both heaters A process flow diagram, generated by HYSYS of these two heaters is shown in Figure 4 After completing this laboratory students have experienced two of the activities in the day in the life of an engineer." They have visited an actual plant and then have returned to the computer to simulate a portion of this process. HOMEWORK For homework, students must calculate by hand the heat duties on both heat exchangers and the temperature of the saturated steam. In this assign ment, they must show all unit conversions and calculations, and all equations must be dimen sionally homogeneous. To aid the students in these calculations, the answers to most of their calcula tions are obtained from the HYSYS simulation printouts These printouts contain the plant read ings in both the English and SI system of units. So the student will obtain agreement between the heat duty on the economizer but will not get an exact agreement with the simulated boiler heat duty. It is very important to give all the necessary equations to the freshmen with a clear explana tion of the variables We have also found that the description or name of each measurement must be identical to both the HYSYS variable names 3 20 and the equation variable names. Finally the variable names must be explicitly given in each equation. For example, instead of T in heat capacity heat capacity expressions must be given for all of the tempera tures (T FW T t c um, Ts,). The heat capacities of the water vapor and liquid were obtained from empirical correlations based on the ASME steam tables which are valid in the range 373 ::; T ::; 470 K. In each of these equations the units for each constant are explicitly shown Thi s allows the freshman to deter mine if each equation is dimensionaliy homogeneous. FW J J 3 J ( ) 2 ( ) CP =4788.26---3.4297-2 TFW+4 885 x 10 -3 TFW I ~K ~K ~K A FW HFw =Cp (TFw -273 16K) (2) The temperature of saturated steam is calculated as 1 = -2.075 X 10 -4 J_ Rn( P S ea m 5 J + 2 683 X 10 3 J_ (3) T s t e am K 1.01325 X 10 Pa K An enthalpy balance on each heat exchanger is calculated from (4) Using the results of these energy balances, an estimate of the energy recovered using the economizer was conducted. This exercise shows the students the equations that the computer simulation has used to perform engineering calculations. This removes the magic of the computer and s how s student s the equations that the computer is using in the simulation After completing this session the students have the advantage of seeing a proces s familiar to them (boiling water), performing an advanced computer simulation and then conduct ing hand calculations of the process. SECOND AND THIRD WEEK LABORATORY EXPERIMENTS In the next two laboratory sessions four experiments are conducted in which the students use equipment similar to that observed in the cogen eration plant. The experiments performed are Flowrate measurement: rotameter operation and calibration Temperature measurement: immersion heaters Pressure measurement: tank efflux and implosion of a 2-L soda bottle The rotameter operation and tank efflux experiments are classic chemi cal engineering experiments that have been adapted from Perna .r 21 The tank efflux experiment is modified by adding 3 pressure-measurement devices; a sight gauge, a pressure transducer, and a low-pressure dia phragm gauge. The implosion experiment employs a vacuum pressure gauge, water aspirator, and a 2-L soda bottle to graphically show stu dents the effect of vacuum. The immersion water heater experiment is unique in that domestic electric kettles are employed and the students determine that dT/dt = Q i /mC / q for most of the heating process SECOND-YEAR EXPERIMENTS USING THE COGENE R ATION FACILITY The use of the cogeneration facility continues into the mas s and Ch e mi c al En g in ee rin g Edu c ati o n

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energy balance course typically taken by students in their second year Once again students and professors have an excellent example of real-world mass and energy balances. They learn the approximate compositions of natural gas (fuel oil has a much higher complexity!). Students use their knowledge of oxidation stoichiometry to determine percent excess air and predict outlet concentrations. The students check their answers by comparing them to gas analyzer measurements of oxygen, carbon dioxide and carbon mon oxide. Water produced is usually not measured, but if de sired a gas stream sample can be obtained and either the water condensed or a hygrometer can be used to determine water concentrations Additionally mas s balances can also be performed on water-treatment systems, including con ventional systems and novel membrane systems Since these balances are based on actual measurements students find they are not able to obtain an exact balance on mass and energy. They learn that measurement devices have a limited accuracy and may need to be recalibrated This was the case the first time we tried to complete a mass balance on the cogeneration fuel stream Our industrial sponsors are very excited to hear that students conduct balances on actual systems because many of the problems in a real plant are related to a faulty or out-of-calibration measurement device The energy balances on the sy s tem were started in the freshman year to see that heat flows from the hot gas to the water. Steam tables are introduced and students use their knowledge of heat capacity and enthalpy gained from chem istry and this course to perform energy balances In thi s sophomore course, they now understand the equations that were employed in the freshman engineering module. In the sophomore course students calculate the source of energy production from the combustion reactions. They use stan dard heats of combustion fluid flowrates and chemical com positions to determine outlet gas temperatures. Using mea sured values students determine the magnitude of the en ergy losses in a cogeneration system They can now under stand in more detail why an economizer was added to re cover additional energy from the exiting gases. In addition they can conduct simulations to examine the effect of in creasing the surface area of the two heat exchangers on the energy recovered This brings engineering economics into their coursework! SAFETY AND ENVIRONMENTAL CONCERNS The cogeneration plant is also an excellent vehicle to introduce safety health, and environmental concerns. All freshmen are required to wear safety glasses hard hats, closed-toe shoes ear plugs (near turbine s ) and clothing that covers all limbs Safety features are shown to students dur ing the introductory lecture and tour such as guards for rotating equipment and pressure-relief valves The required EPA monitoring system is shown in which both a continuFall 1999 ous paper printout and electronic data are produced. The stack emissions sampling point is readily identified from the catwalk around the stack Starting freshmen to think about safety and environmental issues in a plant is an excellent reinforcement to their use of laboratory safety CONCLUSIONS The university cogeneration or physical plant is a rich and diverse resource that should be used in many chemical engi neering classes The plant is on campus and is easily acces sible. In addition to the time savings in not having to travel to an off-campus site, students can be used as tour guides to minimize group size. Using small groups to tour a facility allows students to hear the tour guide as well as to ask questions about the process By using real-world examples of engineering the student's level of understanding and motivation to learn new material increases dramatically. The use of a cogeneration facility in chemical engineering courses is designed to immerse students into multidisciplinary real world, laboratory projects that teach engineering principles. Students are excited and challenged by working in real world settings and are motivated to learn the underlying engineering principles. ACKNOWLEDGMENTS Special thanks are given to the physical plant staff headed by Glenn Brewer for help in preparing the cogeneration module, Mark Showers, chemical engineering students, and faculty for giving tours of the facility. Funding for this work was made possible through a grant from the DuPont Educa tional Aid Foundation. REFERENCES 1. ASEE Engineering Education for a Changing World," Joint project report by the Engineering Deans Council and Corpo rate Roundtable of the American Society for Engineering Education Washington DC ( 1994 ) 2 Perna A. and D. Hanesian A Discipline Oriented Fresh man Engineering Measurement Laboratory, 1996 ASEE Annual Conference 2326a Washington DC. June (1996) 3 McConica C ., "Freshman Design Course for Chemical Engi neers ," Chem Eng Ed ., 30 ( 1 ), 76 ( 1996 ) 4. Dally J W. and G.M. Zhang "A Freshman Engineering Design Course, J. Eng. Ed. 82 ( 2 ) 83 ( 1993 ) 5 Regan, T M. and P.A. Minderman, Jr. "Introduction to Engineering Design: A Major Engineering Education Pro cess Improvement, Proc. 4th World Con{. on Eng. Ed ., 3, 243, St Paul, MN ( 1995 ) 6. McQuiston F.C. and J.D. Parker, Heating, Ventilating, and Air Conditioning : Anal y sis and Design 4th ed. Wiley, New York NY 659 ( 1994 ) 7. Moran, M., and H.N Shapiro, Fundamentals of Engineer ing Th e rmodynamics 3rd ed. Wiley New York, NY 659 (1996 ) 8 Smith J.M ., H.C. Van Ness M M. Abbott Introduction to Chemical Engineerin g Th e rmod y namics 5th ed ., McGraw Hill New York NY 305 ( 1996 ) 9 Perry, R.H and D. Green Perry s Chemical Engineers Hand book 7th ed., 11 (1996 ) 321

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.,a .. 5_._c_u_rr_i_c_u_l_u_m _________ ) DESIGNING A PETROLEUM DESIGN COURSE IN A PETROLEUM TOWN H W YARRANTON, W.Y. SVRCEK University of Calgary Calgary, Alberta Canada T2N 1N4 U ntil recently the Department of Chemical and Pe troleum Engineerin g at the University of Calgary offered undergraduate degrees only in Chemical Engineering and Chemical Engineering with a Petroleum Minor As a re s ult of a joint uni versity and industry initia tive, however a new degree in Oil and Gas Engineering was added to the program in 1998 The curriculum of the new Oil and Ga s Engineering De gree was largely based on the advice of an industry advisory committee consisting of representatives from severa l major companies in Calgary 's oil and gas secto r. The committee identified the fourth-year Petroleum De s ign course as a key component of the new curriculum. This provided an opportunity for creating a course that draws on the hi g h concentration of oil and gas companies and petroleum profe ss ional s in Calgary Now it was up to us to design the design course First we considered why design is taught at universities WHY TEACH DESIGN? Perhap s the best way to answer the question is to examine the difference between undergraduates without design train ing and practicing engineers. "Aca demic undergraduates will have taken a number of courses, each dealing with a specific topic area s uch as heat tran sfe r thermodynamics, or reservoir engineering. They s hould be familiar with funda mental principles of engineering scie nce and are well versed in solving narrowly defined problems based on those prin ciples. For example they can find the pre ss ure drop of a s pecified si ngle-pha se fluid in a given pipeline at given conditions. They will also have received so me training in writing reports and making presentation s. Academic undergraduate s are probably not fully aware of the interrelation of many topics covered in the undergradu ate program. They have been trained to tackle problem s 322 individually and, at least in technical courses, they are rarely ca11ed upon to pre se nt their result s in any format other than written assignments, s hort reports, or examinations. They have little or no experience with managing parti a l or contra dictor y data conducting economic evaluations, and so l ving de sig n problems. Here, a de sig n problem is a problem that requir es the devising of an artifact, system, or process to best meet a sta ted objective." 111 For instance design a proce ss to produce s tyrene for the Alberta market that meet s the corporate economic hurdle s." Note that design problems are open-ended; that is, the number of options and amount of detail that can be considered is limitl ess. Practicing engineers deal primarily with design problems. The y are u s ua1ly se l ec tin g processes or choosing between competing technologie s. Most of the methods and theories they learned in college are embedded in s imulation software. Their hard-earned univer si ty knowledge is u sed primarily to check the simulation results for implausible results. But they must be aware of the interaction of all facets of their under graduate knowledge. For exa mple i s there he a t lo ss from the pipeline and doe s the flowing fluid enter the twoHa r ve y W. Ya rran to n is Assistant Professor of Chemical and Petroleum Engineering at the Uni versity of Calgary He received his BSc (1985) and his PhD ( 1997 ) degrees in Chemical Eng neering from the University of Alberta H is re search interests are in the thermodynamics and transport of hydrocarbons and the treatment of water in oil emulsions William Y S vr c ek is Professor of Chemical and Petroleum Engineering at the University of Calgary He received his BSc (1962) and his PhD (1967) degrees in Chemical Engineering from the Uni versity of Alberta His teaching and research interests center on process con trol and design. Chemical Engineering Education

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phase region? Is erosion or corrosion possible at the operating conditions? U se of c ommercial software Writt e n r e ports The university experience has been designed to give prac ticing e n gineers the tools to analyze problems and to adapt to new circumstances for they will face new circumstances Practicing engineers will often work on projects and tech nologies that were barely mentioned in college. Oral presentations We then selected projects and structured the course to i n clude all the above elements. PROJECTS They will usually be part of a team and will be expected to h ave good interpersonal and com munication skills. They will often evaluate eco nomics and will frequently present the results orally and in written form Until design was introduced into the engineer ing curricu l a, there was a glaring difference be tween the training undergraduate engineers re ceived and the work they did as practicing engi neers In fact, universities are still criticized for training potential graduate students rather than potential industrial engineers .'2 1 Universities have responded in several ways. Some have intro duced design case studies that are introduced in the first year and worked on in more detail throughout the program Y 1 Many, including Calgary, have added a co-op or internship pro gram where students work in industry jobs for terms of four to twelve months. Now all accred ited North American universities are required to offer design courses. The final-year design course provides the best opportunity to teach design principles and bridge the gap between the university and industry By this time, the students have learned many of the scientific principles they need to solve engineer ing problems. Many have completed an intern ship work term and are at least familiar with the industrial environment. The design course allows them to integrate the material from other The projects had to be of sufficient scope to require the work of a team of students for two four-month terms and yet not overwhelmingly complex for a group of inexperienced engineers. Most importantly, we wanted the students to deal with real data with all its contradictions and omissions. The elements listed above apply equally well to any design course The next step was to develop projects from the petroleum area that met the requirements of the course. What is involved in petroleum engineering? It encom passes a broad range of activities just as chemi cal engineering does Petro l eum engineers may be called upon to estimate the size of a reser voir and to predict production from a well or the reservoir. They may design waterfloods, miscible floods, steam floods or even firefloods (underground combustion) to dis place oil from the reservoir. They may drill complete or s timulate wells. They may de sign pipelines or separators or work in a gas plant. Economic evaluations land sale evalu ations, and negotiation with joint-interest own ers are also part of the job Petroleum engi neering even extends to offshore produc tion and oil sands processing. What projects should we draw on from the broad range of activities? To apply all the undergraduate material and gain a per s pective of the industry, we desired projects that included downhole (reservoir) as pects a s well as facilities (oil batteries, gas plants etc.) and the wellbore (drilling and completions ) The projects had to be of suffi cient scope to require the work of a team of courses and to work on a open-ended design problem. For this reason, it is sometimes referred to as the capstone course of an undergraduate program C 4 l s tudents for two four-month terms and yet not overwhelmingly complex for a group of inexperienced engi neers. Most importantly we wanted the students to deal with real data with all its contradictions and omissions. ESSENTIAL ELEMEN T S OF DESIGN COURSE PROJE C TS The comparison of an "academic undergraduate with a practicing engineer highlighted the elements we wished to include in the design course. They are An open-ended design problem Real data Experience rel e vant to industry Application and integration of all undergraduate material Teamwork Economic e valuations Fall 1999 We decided to concentrate on projects involving relatively straightforward reservoirs such as a sandstone reservoir or a homogeneous carbonate reservoir. But the projects them selves are broad and open-ended. We ask the students to examine an existing reservoir and evaluate its reserves and existing production s cenario. The student s then have a choice they can recommend strategies to increase the value of the reservoir in its present state, or they can re-engineer the development of the reservoir. In other words, they could take all the knowledge of today and develop the reservoir as if it had just been discovered The advantage of the second option is that depleted reservoirs with little remaining poten tial can s till be used a s project s 323

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In either case, the students are asked to design appropriate facilities, construct a drilling and completion program and generate production forecasts as well as capital and operat ing cost estimates. They then compare the economics of several strategies and recommend the optimum development strategy for their reservoir. As in real life, the design problem statements are deceptively simple D esign and Economics for Chemical Engineers. L 7 l The s tu dents are assigned group projects worth 25% of the course grade A chemical engineering project involves optimizing a given process and a HYSYS 1 8 1 simulation of the process is provided An oil and gas engineering project involves as sess ing various strategies for developing a given reservoir. (see Table 1). Note that the progre ssio n from design s tatement to problem definition to evaluation of alternatives re se mbles typical chemical engineering design processes, l 5 l al though the details differ. With the help of several Calgary companies, L 6 J we assembled data sets that included the same information that practicing engineers deal with to assess reservoirs; that is well logs conven tional and special core data pressure data (in cluding build-up test data) and PVT data The students were able to access any other required data, s uch as well location s, completion data and production rates, from a commercial data base available at the department or from the AEUB (Alberta Energy and Utilities Board), a provincial regulatory agency. It is these data sets that make our design course unique. In petroleum engineering, a ma jor issue is describing the reservoir, its size, thickness, porosity and permeability distribu tions, etc. This description and the associated re servoir maps are constructed from well logs and other available data These data represent a tiny fraction of the reservoir and are often con tradictory or incomplete. Hence judgment and interpretation are critical. A considerable part of the first term of the design course is spent characterizing the reservoir. Thi s evaluation draw s on many of the petroleum engineering courses in our program, listed in Table 2. PROGRAM STRUCTURE The Department of Chemical and Petroleum Engineering at the University of Calgary has a four-year undergraduate program (not includ ing time spent on internship work terms). The program includes a three-part series of single semester design courses starting in the second half of the third year and concluding at the end of the fourth year. Both chemical and oil and gas engineering undergraduates are enrolled in the same third year design course. Equipment sizing, cost esti mation, and profitability analysis are introduced in this course, and the textbook used is Plant 324 TA B LE 1 Exam p le D esig n Pro bl e m State m e n ts [] Desi g n a gas-cycling scheme for the Brazeau Nisku D retrograde condensate reservoir. [] Desi gn a waterflood for th e Countess YYY sandstone reservoir. [] Optimize the waterflood on the Black Butt e stratified sands ton e r eservoir. [] Evaluate a steam flood for the Sparky A h eavy-oi l sa nd s ton e r eservo ir. TA B LE2 Required 3 rd and 4 th Year Oil and Gas Engineering Courses 3'd Year _______ Numerical Methods in Engineering Heat and Mass Transfer Chemical Engineering Th ermo dynamic s Partial Diff e r e ntial Equation s Separation Processes I Drilling and Completions Oil a nd Gas Engineering Economics (3 1 Year D es i g n ) Oil and Gas R eservoir Engineering Petrol e um Production Engineering 4' 1 Year _______ Flow in Porous Media Oil a nd Gas Treating Pro cesses Well Lo gg in g and Formation Evaluation Introdu ct i o n to Well Testing Petroleum Design I Petroleum Design 11 Petroleum Engineering Laboratory .__ __________ __. In this case, an EXODusr 9 l simulation of the reservoir i s provided The project s give the students an opportunity to practice engi neering de s ign principles and engineering economics on a problem of limited scope. The projects also serve to introduce the simulation software used in the fourth-year design courses. In the fourth year, the chemical engineer ing and the oil and gas engineering students enter different design classes : Process Design I and Petroleum De sig n II respectively The students taking a petroleum minor can choose between the two design courses. While the design courses are run separately, we mod eled the structure of the petroleum design course on the longs tanding and very suc cessful chemical engineering process design course. 1101 In both cases, the De s ign I course is in tended to be a first-pass design where the students can evaluate their process or reser voir and perform preliminary design costing, and economics. The level of detail is similar to a budget cost estimate; that is shortcut methods are employed and costs are accurate to approximately %. In the second fourth year course, Design II the students work on the same project but to a greater level of detail similar to an AFE (authorization for expenditure) cost estimate. In this case, de tailed de sig n methods are employed and manufacturer 's quotes are obtained on major equipment, and costs are expected to be accu rate to %. STRUCTURE OF PETROLEUM DESIGN COURSES Petro l eum Design I The students are given one week to form a group (3-4 students per group) and choose their top three projects from a list provided in the first class. The key here is that the students are free to make up their own gro up s. We do not force students into groups, thu s avoiding per so nality con flict s during the term. The project s are allo cated as much as po ss ible on a first-comeChemical Engineering Edu ca tion

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first-served basis. As a re s ult, the better-organized s tudent s tend to get the projects of their choice. One disadvantage of thi s approach is that the poorer st udent s tend to get concen trated into groups that will str uggle with the course. On the other hand these sa me st udent s cannot coast through the course hidden in a group of otherwise good performers. Once the projects are chosen, the students review their data se ts, analyze what they can, and searc h for missing information from a petroleum database AccuMap,[I 1 in the literature, at the AEUB, or through industry contacts. They use well log s and core data to construct cross-sections, struc ture maps and appropriate pay map s of their reservoir They determine volumetric reserves and u si ng pressure and pro duction hi sto ry, they perform a material balance to obtain a second reserves estimate. They u s ually reach this point at the midterm of the course. After the midterm, they u se analyti cal techniques (such as decline analysis, so lution gas mod els, and Buckley-Leverett-Welge waterflood prediction s) to assess various development scenarios.f 1 2 141 They also size and cost s urface facilities (such as oil batterie s, gathering systems, water plants and gas plant s), estimate drilling and completion costs, and evaluate project economics usin g the technique s learned in the Design I co ur se. The students are required to meet once a week with their project supervisor, a faculty member. T ypica ll y, each fac ulty member involved with the course manages two to four projects The students, individually or as a group, are free to visit the supervisor more frequently. The se visits tend to increase exponentially as the midterm approaches. The mid term consists of a six -page report and a five-minute oral presentation given to four s upervi so r s or faculty members. One repre se ntative of each group presents a GANTT chart of their work sc hedule di sc u sses findings to date and indi cates what each member of the group i s working on. The s upervi sors can then ask any group coordinator to identify "coasters," stude nt s who did not con tribute to the project and they give each stude nt practice in making individual pre se ntation s The final pha se of the Petroleum Design I i s a preliminary de s ign report. This brief typed report s ummarize s the reser voir evaluation, development stra te gy se lection forecasting, facilities de s ign and costing, and preliminary economic indi cators. The st udent s are also expected to produce cross sec tion s, reservoir maps and facility sc hematics. Petroleum De sign II By the end of Petroleum Design I, the s tudent s are expected to have a good understanding of their reservoir description a nd history and to have come up with some promising development stra tegie s. In Petroleum De sign II they correct errors from Design I simulate the reservoir u s ually on EXODUS, and s imulate their facilities on HYSYS. With the reservoir simulator, they are expected to obtain a histor y match of the pool production to date and to generate forecasts for several development s trategie s. They are asked to create a PFD of the facilities, a P&ID drawing of one piece of equipment s uch as a heater-treater and to obtain quotes for major pieces of equipment. They are also asked to prepare a s imple drilling and completion program and estimate capital and operating costs for the project. They then evaluate the project economics and perform some risk and se n si tivity analysis. The De sign II course is intended to duplicate as closely as po ss ible the s teps an engineer em ployed by an oil and gas producing co mpany goes through to evaluate capital projects. The De sig n II course include s weekly meetings with the s upervi sor, a midterm, individual presentation, and a final report. A final oral group pre se ntation is also required after the winter term exams are fini s hed. It consists of a half-hour formal pre se ntation followed b y a fifteen-minute question period. We describe it as a "for mal presentation because not only are supervisors and stu member a question on any part of the project. The group members are ex pected to be familiar with all aspects of their project although leeway is given for detailed questions. TABLE3 Grading Scheme for Petroleum Design II % of Fi n al Grade A. Design Project R eport Proje c t Organization 5 % The midterm ha s a number of posi tive aspects. It informs the supervi sors of the progre ss of each group. It is a milestone that forces the group to have achieved some results ; other wise, the s tudent s ( being human ) might leave it to the end. Finally the midterm allows the course coordina tor to identify any personality prob lem s within the groups. The students also make individual in-class pre se tations on their part of the project. The presentation s allow the course Proce ss Flow Diagram ( PFD ) and P&ID 5 % dent s pre se nt but also other fac ulty members and practicing engi ne ers from indu s try. In fact, as many as 300 letter s go out to major companies inviting them to send interested engineers to the se final project presentations; typically 20 to 30 practicing engineers attend. The atmosphere i s one of thesis defense. The students all partici pate in the presentation and then collectively face questions, first from other students and guests (in dustrial participant s and other faculty), and finally from the project s upervisor s. Students are graded for the final presentation as well as the midterms and Fall /999 Reservoir Maps Technical Content Calculations, diligence, a11d ac c ura cy; d es ign methods and approach; fig u res and g raphs; clarity of approximations a11d design factors Economics Summary, conclusion s, recommendations Total Report B. Weekly Meeting s C. Midterm Examination D. Classroom Presentation E. Final Oral Presentation and Project Defense Total 5 % 25 % 5 % 5 % 50 % 5 % 15 % 10 % 20 % 100 % 325

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proj ect re p o rt s. A n exam pl e of the gra din g s ystem i s s hown in T a ble 3. OTHER CONSIDERATIONS Use of Software A sig nificant i ss u e in und ergra duat e e ducati o n i s th e u se of co mm e cial s oftware especially proce ss and reservoir s imulation pa c k ages Mo s t practicin g e ngineer s u s e co mmer c ial software rather than writing their own pro gra m s or s olving lengthy calcula tion s b y hand yet it is vital to under s tand enough of the underlying theory to recogni ze when the simulation re s ult s are mi s leading and to identify appropriate optimization s trategie s to te s t on the s imulator. As educator s, we want to avoid promoting the blind acceptance of the result s obtained from commercial so ftware We avoid thi s potential trap by emphasizing hand calculations in the De s i g n I course. Ap plying hand calculations to a re servoir prob lem for examp l e force s the s tudent s to think TABLE4 Commercial Software Used in Petroleum Design II course AccuMap 1 1 we ll informati on data b ase EXODUS 191 r eservoir s imul a ti on IMEX STARS a nd GEM 1 1 reservoir s imul ation HY SYS 181 pro cess s imulation FAS1' 161 we ll t es t anal ys i s WELLFLO 1171 we llb ore h ydrodynamics PIP E R 1 61 a nd PlP EFL O 1171 pipelin e h y drod yna mi cs PE EP 1 1 81 petroleum econo m ics TABLES Lecture Topic s Design I Design II P roject Managem e nt Digitizing Geol ogy/Geo ph ys i cs Co nin g Core Analysis Drilling L og Int e rpretation Com pl e ti ons Mappin g a nd Yolumetrics Ar tifi c i a l Li ft PVT and Material B a lan ce PFD s and P&lDs Prim ary Production Forecas tin g Separators W a t er fl oo d D esign Compressors R eservoir Simulation Pumps Blo ck Di agrams a nd PFD s Ri sk a nd Eco n o mi cs Gas Treating Pr ocess Design Calcu l atio n s Petr o l e um Economics 326 about the principle s of fluid flow thermod y namic s, and materi a l balance s With hand calcu l ations, it is often easier to recognize a result that violates common se n se, s u c h a s an unr ealistica ll y high injection rate for a g i ve n permeability-pay Th e hand calculations also provide a c heck on the simula tion results of the De s ign II course. For ex ampl e, if a 30 % reco very factor is pr e dicted by hand and a 50 % recovery is pr e dicted in a s imul a tion can the simulation output be believed ? With a ppropriate hand c alculation s and co mmonse n se checks, the s tu dent s can u se the commercial software li s ted in Table 4 Training is provided for AccuMap, EXODUS and PEEP. Th e s tudents u s ually hav e been ex po se d to FAST, WELLFLO, and HYSYS in other co ur ses Th e sof twar e training i s given outside normal cla ss time Since si mply learning to u se co mmercial sof t ware can be time consuming (es pecially reservoir simulators), it is critical to have teaching assistants who are well versed in the u se of the s oftware Our teaching assistants are graduate s tudent s currently enrolled in petroleum engineering. One challenge facing the program is securing a s tream of graduate students with suitable background s to act as de s ign-cour se teaching assistants. We are attempting to attract part-time Ma s ter s of Engine e ring s tudent s who work in local indu s try. Use ofLectures The st udent s entering the petroleum de sig n co ur se have quite varied ba c kground s. Some are in the o il and gas program while others are talcing the petroleum minor. Some ha ve intern s hip or other indu s try experience while others have none A s a result, there are diff ere nt gaps in the knowledge and experience of each s tudent. In De s ign I we u se th e lecture s to fill the se gaps, with a str ong emphasis on applied engineering. For in s tanc e, we s pend several lecture s on waterflood de s ign leading to the programming of a waterflood foreca s t on a spreadsheet. The program i s based on the Buckley-Leverett Welge method 1121 Voidage replacement injectivity calculations, swee p effic ien cy es timation and waterflood pat tern se lection a re also covered. Ther e are a l so severa l lectur es de vo ted to proce ss de s ign Since the nece ssa ry material i s already covered in the proce ss de s ign course, the se lecture s are held in common. A li s t of lecture s ubject s i s given in T a ble 5. In De s ign II the lectures are even more applied, s uch as artificial lift de s ign Mo s t lecture s in the seco nd term are given b y industry or service Seotember October November December ID TASK NAME 1 2 1 2 1 2 1 Log Interpretation "" I Core An al ysis 2 Mapp ing I GO Pressure Analys i s Assign Pool B o unda ries 4 Test Interp retation Prod uction P lot s "" Poo l History CP 7 Ba se Case Strategies c,,/ALL Rese rves tJ 10 Production Forecast I 11 F acilit i es 12 Econom ics "" Midterm Report Due Nov 2 F i na l Report Due M i dterm Oral E xa m Nov 5 D ec 8 Figure 1. GANTT c hart for a P etro l e um Desi g n I project C h emical Eng in ee ring Edu c ation

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company repr ese ntati ves. Hence the s tud e nt s can learn from ex pert s in a given field and develop contacts for work on the project or in the future. Proiect Management Another i ss ue in a de s i g n course i s how much tim e to devote to proje ct m a nagement. I s it a ppro priate for the s tudent s to prepare detailed sc hedules, critical path analysis etc., for their project ? In our opinion, the s tu d e nt s hav e too little ex perien ce to prepare a m e anin g ful sc hed ule at the be g inning of the project. In stea d we ask them to prepare a simp le GANTT chart outlining the major ta sks a nd ass i g nin g dutie s and target date s to each group memb er. An exa mple chart i s given in Fi g ure l We have found that thi s s imple chart i s s ufficient to identif y potential bottleneck s and ensure a fair allocation of ta s k s It also demon s trat es that unl ess certain tasks, s uch as log interpret a tion are completed early in the project it will be nearly impo ss ible to complete the project on time. SUMMARY AND FEEDBACK The major advantages and di sa d van ta ges of the approach to design taken at the University of Calgary are summarized in Table 6. In general, the feedback from the s tudent s ha s been very po s itive. Examples of anonymou s s tudent comments are An excellent co urs e that provid es an overview of industry tasks r equ ir e d for oilfie l d de ve l op m en t ... Course ge n era ll y cove r ed at a high pa ce Challenging but very interesting and mak es students look for other resour ces of information Course provides oppo rtuni ty to l e arn a lot about ge n era l engineering practi ces (petroleum). In co rporates all asp ec ts of reservoir engineering to produ ct ion eng ineering. Good course to get ex perience of what working as a reservoir engineer is like Very useful for "hands on" experience that wi ll be us e d in industry Ma ybe a little too much work. TABLE6 The se comments are repre se ntative of th e s tudent s' response s to th e request to ple ase provide ge neral co mment s about the course." Negative responses have not been withheld. In all 13 stu dent s out of 20 r es ponded to the reque s t and half of the re s pon ses referred only to other is s ue s, s uch as teaching. The course was rated as 6.1 out of 7 compared with a faculty average of 5.5 out of 7. The comments and ratings indicate that s tudent s believe they have gained broad and relevant experience. ACKNOWLEDGMEN T S We thank Richard Baker Ste ve Gordon Linda van Gastel a nd Dave Douceur for providing data se t s for design projects. We are indebted to Michael Aikman, the first teaching assis tant for the de s ign course REFERENCES I Biegler L.T ., I.E Grossman, and A .W We s terberg, Systemat i c Meth ods of Chemical Proc ess Design, Prentice-Hall, New J e r sey ( 1 99 7 ) 2 Horwitz B .A a nd L.G Na ult R et hinkin g Academia; R e l a t e to th e Real World ," Chem. En g. Pro gress, p 84 October ( 1996 ) 3. Hirt D .E Int egrating Design Throughout the C hE Curricu lum ," Chem. Eng Ed. 32 (4), 290 ( 1998 ) 4. Rock s traw D.A ., J. Eakman, N. Nabours, a nd S. Bellner "A n Int gra t ed Cour se a nd D esig n Project in Chemical Pro cess D es i g n ," Chem. Eng Ed. 31 (2), 94 ( 1998 ) 5 Brennan D.J C h emical Engineering De s ign and U nd ergra duat e Ed u cation ," Chemica 1 995 Pro ceed in gs of t h e 23rd Austral i an C h e mi c al Engineering Conference, Adelaide Septembe r 24-27, 2 p. J 87 (1995 ) 6. Personal communication w ith P etro Ca n ada Oil and Gas, PanCan a dian Petrol e um Ltd Altana Exploration Co a nd Epic Consulting Ser v i ces Ltd 7. Peter s, M.S. a nd K.D. Timmerhaus Plant D es i gn and Eco n o mi cs for Chemical Engineers, 4 th ed McGraw-Hill New York NY ( 1990 ) 8. HYSYS R eference Manual AEA Engineering Technology Soft ware, Ca l gary, Alberta Canada T 2E 2 R 2 ( 1 999) 9. EXODUS R eference Manual T.T. & Associates In c., CanTek Group, Ca l gary, A lb erta, Canada T2P 3N3 ( 1 999) 10. Svrcek W Y ., M.F Mohtadi, P.R Bishnoi and L.A Advantages and Disadvantages of the Petroleum Design Courses B e hi e, "U ndergraduate P rocess Design : An Open Ended Approac h ," ASEE Conference At l a nt a, Geor gia June 16-20 ( 1 985) Pros Use of industry data ----------------------realistic de s i g n problem s time co n s uming to prepare d a ta se t s students faced with real data dependen t on industry cooperation T ea m teaching ________________________ topic s taught by industry experts difficu lt t o maintain co ntinuity in lectur es s tud e nts interact with practicin g engineers lecture s not always delivered at opti mum time Use of faculty s upervi sor ---------------------a ll ows close s upervi sio n of each gro up increases teaching lo ad of faculty gradi n g by co n sens u s Use of analytical methods _____________________ e n co ura ges under s tanding of und er l ying physics e n co ura ges "c ommon-sense c h ecks limit ed a ppli cat i on to comp l ex s ituation s typically face d b y d esign e n g ine ers Use of software ------------------------broad a ppli ca tion e n co ura ges button-pu s hin g so luti o n s training for work in industry learning software i s time inten s i ve an experienced TA i s essential Fall 1 999 I I. Acc uM ap '" R efere n ce M a nu a l EnerDa t a Co rp ., Ca l gary, Alberta Canada T 2N I X7 ( 199 9) 12 Dake L.P. Fundam e ntals of R eservo ir Enginee ri ng, E l sevier, Amsterdam ( 1 978) 13 Bradley H B. ed., Petroleum Engin ee ring Handb ook, Society of Petroleum Engineers, Ri char d so n TX ( 199 2) 14 Cra i g F.F. Jr. The R eservoi r Aspects of Water flooding ," SPE Monograph 9, H e nr y D o h erty Series, New York Y (197 1 ) 15 [MEX STARS '", GEM R efere n ce M a nual s, Com puter Modeling Group Calgary Alberta, Canada T2L 2A6 (1999) 1 6. FAST '", PlPER D', Reference Manuals Fekete Asso ciates In c., Calgary Alberta, Canada, T2G 0M2 ( 1999 ) 17 WELLFLO '" PIPEFLO "', Reference Manual s, Neotechnology Consultants Ltd. Calgary, Alberta, Canada T 2E 8A4 ( 199 9) 18 PEEP Reference Manual Merak Proj ec t s Ltd. Calgary A lb e rt a, Canada T2P 3 R 7 ( 1999 ) 327

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.m .. n.a.._.:.:Ja :.: b=-=o-=-r.=a..:to:.r :..: y~---------) LOW-COST EXPERIMENTS IN MASS TRANSFER Part 5. Desorption of Ammonia from a Liquid Jet M.H I. BAIRD, I. NIRDOSH McMaster University Hamilton, Ontario, Canada T he rate of gas-liquid ma ss tr a nsfer absorption or desorption is controlled by diffusional ( film ) resis tance s in the gas and liquid pha ses. The overall resi s tance i s the s um of the two film resistances. If one film re s istance is much larger than the other, the mass transfer rate is controlled mainly by the larger resi s tance. As di s cussed in the s tandard texts s uch as Geankoplis ,[1 1 the con trolling resistance depends on the solubility of the transfer ring gas in the liquid phase. For some typical solute gases transferring between air and water at ambient conditions, controlling resistances are Controllin~ resistance Liquid diffusion Solute ~ases Oxygen, car bon dioxide (s paringl y so luble ) Liquid a nd gas diffusion Sulfur dioxide (modera tely so luble ) Gas diffu s ion Ammonia, hydrochloric acid gas ( hi g hl y so lubl e) Previou s papers in thi s seriesl 2 3 1 have de sc ribed s ome s imple undergraduate-level experiments with liquid-phase control, using oxygen or CO 2 as the tran sfe rring gas It is also desirable to s tudy cases in which mass tran s fer i s controlled by the gas phase but as the above table indicates, the highly water-soluble gases are hazardou s substances. Some years ago, students at McMaster University operated a packed-absorption tower in which an ammonia/air mixture was sc rubbed with water. Much care was needed in the control of the ammonia stream to make up the gas mixture and there was so metime s trouble with leaking valves on the ammonia gas cylinder. Eventually the experiment was dis continued for safety rea so ns. Thi s paper describes a replacement experiment that was recently developed in which ammonia is desorbed from an aq u eous solution into a s tream of air. This is inherently safer s ince the ammonia level s in the gas phase are limited by the ammonia concentration in the aqueous feed s olution. The experiment doe s not require pure ammonia gas. The objec* Address: lakehead University, Thunder Ba y Ontario, Canada 328 tive of the experiment is to mea s ure ma ss tran sfe r coeffi cients for the de so rption of ammonia from a liquid jet, at different liquid flow rates and for different jet length s. Recommended time for the experiment i s two laboratory periods of three hour s. EXPERIMENT DESCRIPTION The schematic flow diagram is s hown in Figure 1. The main item s of equipment are mounted on a vertical wooden panel about four to s ix feet from floor level. The feed so lu tion i s a 1 5 mol/L s tandardized so lution of ammonia in water that can be made up by the laboratory technician prior to the experiment. This concentration was chosen as a com promise to balance the need s for rapid rates of ma ss tran sfe r (favored by higher concentration) and safety (fav ored by lower concentration) At ambient temperature s the equilib rium mo! fraction ammonia in the gas pha se above thi s so lu tion is between 2 % and 3% Accurate values are avai lable from the literature l 4 l for the temperature of the ex perim e nt. The a mmonia so lution is fed from an overhead reservoir through a s tainle ss s teel needle valve a nd rotameter to a desorption cell. Typically, the feed liquid flow is in the range Malcolm Ba i rd received his PhD in chemical engineering from Cambridge University in 1960 After some industrial experience and a post doctoral fellowship at the University of Edinburgh he joined the McMaster University faculty in 1967 His research interests are liq uid-liquid extraction oscillatory fluid flows and hydrodynamic modeling of metallurgical pro cesses. lnder Nlrdosh received his BSc and MSc in chemical engineering from Panjab University (India) and his PhD from Birmingham Univer sity (United Kingdom). He joined Lakehead Uni versity in 1981 and his research interests are in the fields of mineral processing a nd electro chemical engineering. Copyr i g ht C h E Di vis i o n of AS EE 1 999 Chemical Engineering Education

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of 50 to 300 mL/min. The de so rption cell consists of a vertical 15-cm sec tion of 5-cm internal diameter glass tub ing closed at each end by rubber sto pper s. The feed solution enters the top of the cell through a glass nozzle of internal diameter 1.4 mm which can be made easily by a glass blower from standard glass tubing. The free jet of so lution falls from thi s nozzle to a collector tube (see Figure I ) located at a measured distance (L) below the nozzle The col lector tube should be slightly larger in diameter than the jet ; an internal diameter of about 2.5 mm is recommended. At steady s tate, the liquid level in the collector tube should come right up to the open end, and there should not be any gas entrainment. This control can be quite easily achieved by means of a manually ad justable overflow leg as ri~~e s hown in Figure 1. Some lateral adjustment of the po s iAir+ NH 3 Acid bubbler by a semi-continuous chemical method by scrubbing with dilute hydrochloric acid. Before the experiment, a standard fritted-glass bubbling tube is filled with a known volume (ty pic a lly 100 mL ) of 0.01 mol/L dilute hydrochloric acid, with a few drops of methyl red indicator, and is connected to the sys tem as shown in Figure 1 The gas analysis is begun by turning a 2-way cock to divert the exit gas through the Solution flow 1.5 mol/L NH 3 soln receiver NV (li q ) bubbling tube. As the cock is turned, a stopwatch must be started. Because of the large tions of the jet and the collec tor can be made by hand since the tubes are held by a rubber Figure 1. Schematic flow diagram. gas-liquid interfacial area pro duced at the bubbler, the ab sorp tion of the ammonia from the gas phase is extremely ef ficient and it reacts stoic h io metrically with the acid. After sufficient time has elapsed, all the acid will be consumed and the pH of the liquid in the bub bler will rise sharply, accom panied by a change in the me thyl red color from pink (acid) to yellow (alk aline) The color change occurs over a period of 1-2 s, which is much smaller stopper that has some flexibility. The variation of jet length can be achieved by extending or retracting the jet nozzle between experiments. It i s inevitable that some drop s of so lution will occasion ally spill over the collector tube, and for this rea so n a few mL of kerosene are placed at the ba se of the cell to provide a mass-transfer barrier. There i s also provision to occasionally drain off any large amount of spilled ammonia from the base of the cell, as shown. The main liquid flow leaving the cell still contains most of the ammonia feed, and it is collected in a receiver for reuse. It is important to avoid the use of copper or brass in any of the valves or line s handling ammonia solution s ince these metals are s lowly attacked by aq ueou s ammonia; this is apparent from a blue coloration of the solution with cuprous ammonium sal t s A continuous flow of atmospheric air is drawn through the cell, entering from the bottom. The exit air, containing de orbed ammonia gas, leaves the cell from the top. During the preliminary adj u stment of the system it flows through a bypass line to a trap, and then to a rotameter, needle valve, and water aspirator (ejector). The air flow is adjusted to a fixed value (ty pically between l and 5 L/min) by mean s of the needle valve and rotameter. The sys tem s hould be run for three to four minutes at the adjusted liquid and gas flows, to reach a steady state before gas analysis is begun. The air leaving the cell contains a s mall amount of ammo nia, typically no more than 1 mo! % Analysis is carried out Fall 1999 than the neutralization time of 100 s. At the above endpoint, the stopwatch is stopped and read, and the gas flow is then diverted to the bypass. The rate of mas s transfer is calculated from the moles of acid neutralized in the bubbler and the neutralization time (1) The molar concentration of ammonia in the exit gas from the desorption cell can be obtained from the mass transfer rate and the gas flow rate (2) At the end of each experiment, the liquid and gas flows are s hut off and the bubbler is removed for rinsing with distilled water. EXPERIMENTAL PLAN A typical plan for two 3-hour laboratory periods calls for measurement of the mass transfer coefficient at three differ ent jet lengths (for example, 3, 5, and 7 cm) and three or four different flow rates within the operating range. In addition, at least some of the experiments s hould be replicated with different concentrations of acid in the bubbler. Changes in c A would affect t N but would not be expected to affect the value of kg obtained at the same liquid flowrate and jet lengt h Because of time constraints, the jet diameter and the air flowrate are the same in all experiments. An average time of 15 to 20 minutes is spent on each 329

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experiment with students working in groups of two Al though the mass-transfer measurement itself takes only one to three minutes additional time is needed for adjustment of the operating conditions and for achieving steady state Also from time to time the ammonia-feed reservoir has to be refilled. Goggle s and gloves should be worn by the students when they are handling the ammonia and acid solutions, e g., when they are recharging the bubbler. The ammonia levels in the ambient air are low but minor discomfort may be experienced if there is not adequate ventilation in the laboratory. CALCULATION OF MASS-TRANSFER COEFFICIENTS FROM DATA The mass-transfer rate m ', is the product of the mass transfer coefficient, the interfacial area and the concentra tion driving force (3) The terms m' and c 2 have already been obtained through Eqs. (1) and (2). The interfacial area A can be calculated from the jet length L and the orifice diameter d. For precise work allowance should be made for the acceleration of the jet due to gravity. But for short jets and high velocities (keeping in mind that this is only an undergraduate-level experiment) the acceleration effect can be ignored There fore we use A= 1tdL (4) The equilibrium concentration of ammonia in the gas phase c *, can be obtained from standard sources. 1 41 For 1.5 mol/L ammonia in the solution the values of c at 20 C and 25 C are, respectively, 0 837 and 1.076 mol/m 3; these values are less than 0.1 % of the liquid phase concentration illustrating the very high solubility of ammonia The back-concentration term is taken as c 2 (calculated from Eq 2) based on the assumption that the gas space within the cell i s "well mixed ." This was found to give consistent results, and it is rea s onable to expect that the combined effects of gas and liquid flow would result in a well-mixed gas phase in the cell Rearranging Eq. (3), the mass transfer coefficient can be obtained from known data as EQUATIONS FOR PREDICTION OF MASS-TRANSFER COEFFICIENT (5) The conditions of the experiment do not correspond ex actly to any of the commonly available predictive equations because little is known about the hydrodynamic conditions in the gas space in the cell. It is thought that the gas is circulating due to the action of the liquid jet and the throughflowing stream of gas, and the flow is likely to be weakly turbulent. There are two simple equations that can at 3 30 least provide an approximate comparison with the data HIGBIE PENETRATION MODE Ll 51 Thi s well-known equation is ba s ed on the simple concept of unsteady diffusion into the gas phase during the contact time, 't for which the liquid is exposed to the gas In using this equation it is assumed that the gas film adjacent to the liquid jet is moving down with it at the same velocity namely U=Q L !(nct 2 / 4) (6) The contact time between liquid and ga s i s LIU or (7) According to the penetration model ( ) 0 .5 k g = 2 D g / 1t't (8) where D g is the molecular diffusivity of ammonia in air which can be estimated from the method of Fuller e t al. as cited in Perry 's Handbook .' 61 Value s ofD g at 20 C and 25 C are, respectively 2 36 x 10 5 and 2.43 x 10 5 m 2 / s Equation (8) can also be expressed in dimen s ionless form a s (9) where the Sherwood and Reynolds numbers are based on jet length Equations (8) and ( 9) can only be regarded as ap proximate for the present case s ince they assume that the gas is moving down at the same velocity as the liquid jet ; no allowance i s made for a developing boundary layer or the effects of turbulence in the bulk gas flow. BOUNDAR YLAYER MODEL [7] As an alternative to the penetration model it could be assumed that the air is dragged down in a developing lami nar boundary layer adjacent to the interface with ammonia diffusing through the boundary layer. For this ca s e ShL = 0 664 Rei 5 S c" 3 (JO) In this work, ReL is alway s well below the critical value of 500,000 at which there is a transition to turbulent flow in the boundary layer. But the use of Eq (10) is also open to criticism since it was developed for a flat plate whereas the interface in thi s case is cylindrical. Moreover the bulk gas may be turbulent, which could affect the boundary layer. RESULTS AND DISCUSSION Figure 2 shows 12 directly measured ma ss -transfer coeffi cients from a typical student project, c s J plotted against jet velocity on a linear scale It can be seen that k g always increases with the velocity and in general it decreases with increasing jet length. The results can be expressed in dimensionless form by C h e mi c al En g in ee rin g Edu c a t i o n

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conversion to Sherwood number, which can then be compared with the model Eqs. (9) and (10). The Schmidt number is essentially con stant (:a:0.65) except for minor ef fects of temperature between differ ent experiments. E 0 035 C: ~ 0 030 8 0 025 "' C g "' "' 0 020 o L = 0.03m D. L = 0.05m o L =0.07m 1.0 1.5 2.0 2 5 Gatt who assembled the apparatus and mounted it on a panel. In addition, the authors are grateful to the Natural Sci ences and Engineering Research Coun cil of Canada for providing financial resources for the preparation of this pa per. NOMENCLATURE A interfacial area, m 2 C A initial concentration of acid in bubbler, mol/m 3 c 2 co ncentr a tion of ammonia in exit gas, mollm 3 Therefore, a plot of Sherwood number versus Reynolds number al lows the data to be compared with the two model equations, as shown in Figure 3. Both models predict that Sh L oc Re ~ 5 so they appear on the log-log scale as two parallel straight lines which are shown dashed The data points fall between the two pre dictions ; lower than the penetration theory but higher than the boundary layer prediction Jet velocity, U, m/s c eq uilibrium concentration of Figure 2. Effect of jet velocity and jet length on mass transfer coefficients. D am moni a in gas mollm 3 rnolecular diffusion coefficient of g ammonia in air, m 2 ls I I I_,,,.. d jet diameter m _,,,..~ 80/ D .> k mass transfer coefficient mi s g When students are confronted with a case like this in which the results do not agree very well with the theo retical predictions they are apt to find fault with the experiment and the accuracy of their data. But when an analysis of measurement errors is done the measurement accuracy for k g is found to be better than % Then a que s tion for the students is: why are there deviations of 30 % or more between the results and the models ? ..J .c (/) ,'?J' / A ~,o{'/AAA / L jet length m / m' mass transfer rate molls ,_ ,:,_-vO / 0 / 11) e,;..--o / / Q G air flow rate m 3 ls .D 40E / o ,,,...,,o' ::, 0 ~,o{' QL water flow rate, m 3 ls C -0 --;,o_-vO 0 / 0 / 11) 20.c Re L Reynold s number pUL I Sc Schmidt number / (pD g) (/) ShL Sherwood number k & L/D g lr; time to neutralize acid in bubbler s I I I 1000 2000 5000 1opoo u jet velocity mi s Reynolds number, ReL V A vo lum e of acid in bubbler m 3 Greek Sy mbol s The students are encouraged to dis cuss ways in which their actual ex periment departs from the se ts of idealizing assumptions built into the Figure 3. Dimensionless plot of data showing comparison with Eqs (9) and (10) p 't v is cosity of air Pa .s density of air kglm 3 contact time s Symbols are the same as in Figure 2. two simple theoretical models. The curvature of the jet sur face and the complex and probably turbulent gas-flow pat terns in the cell have already been mentioned. If the theoreti cal treatment could be "fine tuned" to account for these effects, better agreement could be expected but that would take us into the realm of graduate research. This low-cost experiment can be se t up with normal labo ratory glassware and fittings. It provides students with a reasonably accurate method of measuring gas-film controlled mass-transfer coefficients that can then be compared with simple (though approximate) theoretical predictions ACKNOWLEDGMENTS The apparatus was built with financial s upport from the Department of Chemical Engineering at McMaster Univer sity The authors are grateful to Ms J Derkach and Mr. Paul Fall 1999 REFERENCES 1. Geankoplis, C.J., Transport Processes and Unit Op erations, 3rd ed., Prentice Hall Englewood Cliffs, NJ p. 600 ( 1993 ) 2 Nirdosh, I. and M.H.I. Baird Low-Cost Experiments in Mass Transfer Part l. ," Chem Eng. Ed. 30 50 ( 1996 ) 3. Nirdosh I. L.J Garred, and M H.I Baird "Low-Cost Experi4 5 ments in Mass Transfer Part 3. Mass Transfer in a Bubble Column ," Chem. Eng. Ed 32, 138 ( 1998 ) Perry R.H and D. Green, eds., Perry s Chemical Engineers Handbook, 6th edn McGraw-Hill, New York NY pp 3-101 ( 1984 ) Geankoplis C.J. Transport Proc esses and Unit Op erat ions 3rd ed., Prentice Hall Englewood Cliffs, NJ, p 478 (1993) 6 Perry, R.H., and D Green, eds., P erry's Chemical Engineers 7. Handbook 6th edn. McGraw-Hill, New York NY, pp. 3-285 ( 1984 ) Geankoplis, C.J., Transport Process e s and Unit Operations 3rd ed., Prentice Hall Englewood Cliffs, NJ p. 477 ( 1993 ) 8. Rajkovic A., Ammonia Desorption from a Jet ," McMaster University Chemical Engineering Report March 19 ( 1998 ) 33/

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.ta ... 6_._c_l a s s_,-,_o_o_m _________ ) Activities to Enhance UNDERSTANDING OF THE MOLE AND ITS USE IN ChE DUNCAN M. FRASER, JENNIFER M CASE University of Cape Town Rondebosch 7701 South Africa M oles are a fundamental unit of measure in chemi cal engineering. Our students learn about moles (in the form of gmol) in chemistry, both at school and during their first year at university. In chemical engi neering, we introduce them to the new units of kmol and lbmol, and the problems that arise highlight a general lack of understanding of the mole concept. We have been aware for some time that our students have difficulty with moles, and this led us to tackle student under standing of mole s as a research project in which we first quantified the nature and extent of the misunderstanding and then set out to design and implement a set of activities to promote conceptual change in this area. The intervention also dealt with a number of other concepts related to the mole. Following implementation of the intervention, stu dents were again tested to measure the extent of improve ment in their understanding D u n can Fra ser holds degrees of BSc and PhD both from the University of Cape Town where he has been lecturing since 1979. He has taught a wide range of courses from first year to fourth year including mass and en ergy balances, thermodynamics transport phenomena solid-fluid operations optimiza tion process control and design. His pri mary research interests are in engineering education and process synthesis Jenn i fe r Ca s e obtained her BSc (Hons) de gree in Chemistry from the Universi t y of Stellenbosch after which she taught for a few years in a high school She became interested in the field of educational research after doing an MEd degree in Science Education at the University of Leeds, and she currently serves as the Educational Development Officer in the Department of Chemical Engineering at the University of Cape Town. All of this took place in the context of a new course for freshman chemical engineering students in which they are introduced to the ba sic concepts in chemical engineering as well as helped in developing certain key ski lls for the subse quent s tudy of chemical engineering. l 1 J One of the skills developed i s unit conversion, and the different mole unit s are introduced here. A central element of the course i s intro ducing students to unfamiliar concepts through the use of familiar objects. The full details of this research project are reported else whereY1 The main objective of this paper is to present an overview of the test (used to determine under sta nding) and the intervention activities, together with evidence for their effectiveness in dealing with the misconceptions with the hope that other chemical engineering educators would be encouraged to try them out or to use them in a modified form. TESTING FOR UNDERSTANDING Group interviews were used to explore possible miscon ceptions that s tudents might hold about moles Analysis of these transcripts identified three common misconceptions: 1 The amounts kmol lbm ol, and gmol are seen as mass es 2 The amounts kmol lbm ol, and gmol are all th e sa me because th ey are all mol es. 3. The volume of a gas is not seen as proportional to its amount. In order to be able to measure the extent to which these misconception s were held in the class, a conceptual te s t was developed, based on the above research findings For ex ample, Question 1.2 tested mi sco nception #1 : 1 2 60 lbmol of N 2 weighs 60 lb. True/ Fal se? Copyr i g ht C h Di v i sion of ASEE 1999 332 Chemical Engine e ring Edu ca tion

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The main objective of this paper is to present an overview of the test (used to determine understanding) and the intervention activities, together with evidence for their effectiveness in dealing with the misconceptions, with the hope that other chemical engineering educators would be encouraged to try them out or to use them in a modified form. Question 2.1 (in multiple choice format) is typical of a number of questions that probed misconception #2: 2.1 Consider the following p Q R 1 kmol of CO 2 1 lbmol of CO 2 1 gmol of CO 2 Which one of the following statements is true ? a) P Q and Rall have the sa me number of molecules b) P and R have the same number of molecules c) P and Q have the same number of molecule s. d) They all have different numbers of molecule s. e) None of the above statements are true. Question 3.1 tested misconception #3: 3.1 Consider the following 50 m 3 vessels, each contain ing gas with the given composition: Vessel A B Volume Composition (by volume) 50 m 3 25 % CO 2 25 % CH 4 50 % H 2 50 m 3 100 % CO 2 A and B are at the same temperature and pressure. Which one of the following statements is true ? a) A contains more molecule s than B b ) B contains more molecule s than A c) A and B contain the same number of molecule s. d ) None of the above statements is true. This test was specifically designed so that no numerical calculations were required in answering the questions (as can be seen in the sample questions above). Despite this, it was interesting to observe during the administration of the test that many of the students tried to u se numerical calcula tions to find the answers Even though calculators were not permitted, many students covered their question papers with calculations. The results of the test confirmed that misconception s were widespread in the class : 38 % of the students s how ed evi dence of misconception #1 (tested by one question); 28 % s howed misconception #2 ( thi s was averaged over five quesFa/11999 tion s); and 27 % showed misconception #3 (average d over two questions) .12 1 When the same test was administered again after the intervention activities ( de scri bed in the next sec tion) it revealed a significant increase in under s tanding. INTERVENTION ACTIVITIES We designed a series of intervention activities to address the misconception s that had been identified during the inter views and the conceptual test. At the same time we took the opportunity to deal with other related que st ions, albeit in a les s focused manner. The major objective in designing these activities was to give s tudent s a concrete vis ual or experiential point of refer ence for their understanding. This approach was based on recommendation s in the literature concerning the general u se of tangible objects in helping learners develop appropri ate mental representation s of chemical systems C3 5 l as well as more specific recommendations regarding their use in devel oping the mole concept. 1 6 7 1 Where it was not possible to use concrete objects we u sed thought experiments instead. The activities were designed to follow one another. Stu dents performed them in group s of three and were encour aged to discuss their findings with one another and with the tutors. Multiple sets of apparatus were available so that five groups could perform them si multaneously A class of ninety st udent s co uld then be handled in six batches over the course of one afternoon. The activities pre se nted here are a refine ment of the original set of five activities described by Case and Fraser .12 1 Activity #1 The purpose of thi s activity is to help s tudent s see the difference between the different kinds of moles they will need to work with as chemical engineers (gmo l lbmol and kmol ). They measure out I gmol, 1 lbmol and 1 kmol of water, using a scale, and then are asked a series of questions to help consolidate what they have observed. The activity ends with an in s pection of a display of bottles each contain ing 1 gmol of a different substance to provoke thinking about mole s, molar ma ss, den s it y, form, etc. Activity #2 This activity i s aimed at helping s tudents make sense of gas volumes and mixtures of gases The first task involves a box containing a mixture of s quash balls and ping-pong balls which have approximately the same diameter but sig nificantly different mas ses. Thi s provides an analogy for a mixture of different gases, s uch as oxygen and hydrogen 333

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that occupy the s ame volume but have different masses The second task help s them vi s ualize the volume occupied by 1 gmol of any gas at STP using a 22.4-litre Perspex box. They are al s o asked to calculate the masses of two different gases that would fill this box at STP This is followed by a third task in which they calculate the mass of air occupying the room where they are working and then are asked what would happen to the mass of air in the room if its composi tion were different. Activity #3 This activity is a thought experiment in which the students are asked, fir s t to calculate the kinetic energy of 1 kmol of each of three different gases, using their molar masses and average velocities This leads to a discussion of why dif ferent gase s all occupy the s ame volume at STP using the assumption that thi s i s related to their having the same kinetic energy. The second task here involves determining the volume occupied by the actual molecules (from their molecular di ameter ) and hence the fractions of both water vapor and liquid water that are empty s pace This is to help clarify the difference between liquid s and gases. Activity #4 The final activity simulate s chemical reactions using nut s and bolt s The concept of moles is further reinforced by getting students to weigh out a large number of each of the reactant s" on the basis of an average mass per nut or bolt (in the same way that coins are "counted" by weight at a bank). One bolt is "reacted first with one nut and then with two nuts. The difference between reacting numbers of each re20 18 16 I~ -........ This figure also s how s that there wa s no difference between the s tudents who were inter v iewed and those who were not which indicates that it wa s the intervention rather than being sensitized to the issues, that made the difference Table 1 gives a complete question-by-question analysis of the preand post-te s t re s ults arranged according to whether the questions covered the mi s conceptions being directly tack led or not. The shift of s tudents from wrong to right answer s, Course tutor, holding the "mole" box. actant and masses of each reactant is emphasized by the last two tasks in which they weigh out equal ma s se s of nuts and bolts and then react them 14 12 EFFECT OF INTERVENTION When the s tudents were tested again to gauge if their understanding had improved there was a significant in crease in their level of under standing. Figure l compare s the preand post-test scores of all the s tudents It shows that those who could improve the mo s t had done s o, and that the average improvement is half the maximum possible. 3 34 0 u "' .5 Q) Cl C: ca .r:. u 10 8 6 4 2 0 -2 5 10 .~ -~ -I>"-.. .---" "" -"' --::~ --t>___ 15 Pre-test Score 20 25 Figure 1. + Interviewed Not Interviewed -Maximum Change Average Change C h e mi ca l En g in ee rin g Edu c ati o n

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as well as from right to wrong, i s also shown. The shift from right to wrong i s taken as a mea s ure of the randomness of answering; this was consis t ent across the different gro up s of questions and averaged 6.4 % over a ll the question s. Table 1 shows clearly that the intervention h ad a much greater impact on the three mi sco nception s directl y tackled ( net shift from wrong to right of 17 l ) than on the other i ss ue s tackled ( net s hift of 5 8) Thi s i s to be expected, given the clearer foc u s on them in the de s ign of the intervention When the data in Table 1 is analyzed according to the TABLE 1 Q u estion-by-Question Analysis of Result s (" W to R m eans Wrong to R ight: R to W means Ri g ht to Wrong ) I Pr e-1 P ost-1 Test Te st Shift Item ToQic Mi sc. % cor % cor. W t o RI R t o W I Net Misconceptions Tackled in Interv e 11ti o 11 1.2 lbm ol 64 % 76 % 1 9 9 10 1. 5 kmol/gmo l 2 76 % 88 % 16 7 9 1.9 Avogadro's numb e r 2 51 % 90 % 34 3 31 I. I O km o l/ g mol gas 2 69 % 80 % 16 7 9 2. 1 mo l es a nd m o l ec ul es (sa me ) 2 65 % 91 % 22 21 2.6 A voga dro 's num be r 2 44 % 8 5 % 36 3 33 2 8 mo l e s a nd gas vo lum e 2 56 % 83 % 26 5 21 3 1 diff gases a t s ame conditions 3 63 % 7 1 % 15 8 7 3.6 gas mixture co mp os iti on 3 59 % 75 % 20 7 1 3 Average 6 1 % 82 % 22.7 5 6 1 7. I Other I ss ue s Tackled in Int e rve11tio11 I.I kmol 6 1 % 98 % 3 1 2 29 1.3 m ma ss kmol 68 % 53 % I O 22 1 2 1. 8 molecul e and co mp o nent s 68 % 75 % 1 0 4 6 2.2 m o l es a nd m ass (sa m e) 89 % 93 % 8 5 3 2.3 mole s and molecule s ( diff) 76 % 84 % 9 3 6 2.4 m o l es and m ass ( diff) 83 % 85 % 1 2 I O 2 2.5 doe s P affec t lbm o l 63 % 73 % 1 6 8 8 2.7 k m o l of diff. s ub s t ances 66 % 68 % 1 2 II 2. 9 reaction s t o i c hiom e tr y 93 % 9 1 % 5 6 I 3.2 m ass of gas mixture/pure gas 6 1 % 78 % 1 5 2 13 3 3 gas mi x tur e composit i o n 70 % 6 1 % 5 1 2 -7 3.4 gas mixture co mpo si tion 56 % 75 % 20 5 15 3.5 pure gas cf mixtur e 74 % 90 % 1 8 5 1 3 Ave ra ge 7 1 % 79 % 1 3.2 7.3 5.8 Not tackled i11 Intervention 1.6 unit c onv 98 % 93 % I 5 4 1. 7 unit co n v 75 % 83 % I O 4 6 Average 86 % 88 % 5.5 4 5 1. 0 Overall Average 69 % 81 % 16.1 6.4 9 .7 Error in Pr e -T est 1.4 m ma ss lb m o l 46 % 98 % 42 three mi sco nception s (see Ca se and Fraser 121 for details of thi s), mi sco nception #1 dropped from 38% to 22 % mi s con cep ti on #2 from 28 % to 9 %, and misconception #3 from 27 % to 22%. The first two c h a n ges (16 % a nd 19 % ) are significant compare d to the ra ndomn ess of answeri n g (6%), w here as the third one i s not ( 5 % ). Thi s means th at mi conceptions #1 and #2 s howed significant increa ses in under s tanding, whereas mi sco nception #3 did n ot. Thi s point s to the effectiveness of activity #1 in addre ss ing misconceptions #1 and #2. Perhap s even more important than this analysis was fee back over the past three years from those w ho te ach the s ub se quent mas s and energy balance co ur se. They have not ed a s i g nifi cant decrease in problems concerning moles CONC L USIONS What s urpri se d and encouraged u s was how enthusias ti cally all the s tudents engaged in the activities--even the more advanced st ud ents, w h o we th o u ght might find them trivial or boring. It appeared that none of the s tud e nt s had encountered s imilar activities at s chool indicating that their previou s experience in learning chemistry had be en quite deficient in the u se of tan g ible objects Wh y not try out the mole te s t on your s tudent s? You might be intere s ted in the results. You m ay a l so find so m et hin g in the mole activities that would be u se ful to try in yo u r class, or u se them as a springboard for developing ot her activities (we found developing them to be an exciting and crea t ive cha ll e n ge). Full copies of both the concept u a l test and the intervention activities may be obtai n ed by co ntactin g the first author at dmf @c hemeng uct.a c .za REFERENCES 1. Fraser D .M ., "Introducing Students to Basic ChE Con cepts : Four Simple Experiments, Ch e m Eng Ed ., 33 (3), 190 ( 1999 ) 2 Case, J.M and D M Fraser "An Inv estigatio n into Chemi cal Engine ering Stud ents' Understanding of Mol es and the Use of Concrete Activities to Promote Conceptual Change ," Int e rnational Journ al of Sci e nce Edu cation, in press 3. Lythcott J ., Problem Solving and R eq uisit e Knowl e dge of Chemistry ," J. of Chem. Ed. 67 ( 3 ) 248 ( 1990 ) 4. Raghavan, K. and R. Glaser, "Model-Based Analysis and Re asoning in Science : The MARS Curriculum ," Sci. Ed ., 79 ( 1 ), 37 ( 1995 ) 5 Garnett P ., P Garnett, and M H ackling, St ud ents' Alter na t i ve Co nceptions in Chemistry : A Review of Research and Impli cations for Te aching and Learning ," Studies in S ci Ed ., 25 69 ( 1995 ) 6. Spargo P ., T eaching the Mole Concept ," Higher Education Diploma co ur se not es, School of Education University of C ap e Town ( 1987 ) 7 Staver J.R. and A.T. Lump e, T wo Inv estigat ions of Stu d ents Understanding of the Mol e Conce p t a nd Its Use in Probl e m Solving ," J of R es. in Sci T e aching, 32 ( 2 ), 177 ( 199 5 ) Fall 1 999 335

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Gra duate Education Adver t i s em e nt s Akron Univer s ity of. ...................... .. .. .................. 338 Dartmouth College .................................................. 364 Alabama University of ... ... .. ......... ...... .............. 339 Delaware Univer s ity of.. ...................... .................. 365 Alabama Huntsville University of ... ........ .............. 340 Drexel Universit y .................................................... 443 Alberta University of .... ....... ................... ........... 341 Ecole Polytechnique, University of Montreal ......... 366 Arizona University of .............. .. ..... ....................... 342 Edinburgh, University of .. .. ......... ........................... 443 Arizona State University ... ..... ............ .. .. .. .. .......... 343 Engineering Research Center for Particle Science .. 444 Auburn University .. ..... ............. ...................... ... .. 344 Florida, University of ............................ ........ ... .... 367 Brigham Young University .. ... ............ ... ... ......... 441 Florida State Univer s ity/Florida A&M University 368 British Columbia University of ................... ..... ... .. 441 Florida In s titute of Technology .. ........ ..................... 369 Brown University .......... .. .. .. ... ............ .. .. .. .. ........... 456 Georgia Institute of Technology .................... ...... 370 Bucknell University .... ......................... ... ............ 442 Houston University of ............................... ........... 371 Calgary University of ..... .... ...... ... ...................... 345 Howard University .. ... .. ...... ... . ... .. .. .. .. ... .. 372 California Berkeley Univer s ity of .. ... .. ... ............ 346 Idaho University of .................................................. 444 California Davis University of ..... ............. ... ........ 347 Illinoi s Chicago Univer s ity of .. ................. ........... 373 California Irvine, Uni v er s ity of .......... ..... .. ....... ...... 348 Illinoi s Urbana Univ e r s ity of .. .. .... ... .. .. ................. 374 California Los Angeles University of ... .. ... ........... 349 Illinoi s Institute of Technology ................... .. .. .. .... 375 California, Riverside University of ..... ................. 350 Iowa University of ......................... ........................ 376 California Santa Barbara University of ....... ... .. .... 351 Iowa State University ... .......................... ............... 377 California Institute of Technology ... ..................... 352 Johns Hopkins University ... .. ............................. .. 378 Carnegie-Mellon University .. ............... .... .. .. .. .. 353 Kansas University of ..... ... ....... ....... .. .......... ...... 445 Case Western Reserve University .. ............... ... ... 354 Kan s a s State University . ..... .. .. .. .. ...... ............ ... 379 Cincinnati University of ............ ... ..... .................... 355 Kentucky Univer s ity o f ................................ ......... 380 Clark s on University ............ .. ..................... .... ...... 356 King Fahd Uni v er s ity of Petroleum and Mineral s .. 381 Clemson University ................... ....... ..................... 357 Lamar University ..................................................... 445 Cleveland; University of.. .......... .. .. .. .. .. .. .. .. ............. 358 Laval University ................................. ........ ...... ... .. 382 Colorado, University of ...... ... ......................... .. .. 359 Lehigh University ........ ...... .... .. .. .. ....... ... ......... ... 383 Colorado School of Mines ......... ... ..... .. .. ... ............. 360 Loughborough University ................................... .. 446 Colorado State University ......... .................. ..... ... 361 Loui s iana State Universit y ...... .. .. ................... .. .... 384 Columbia University .. .. .......... ..................... .. .. ... 442 Loui s iana Tech Uni v er s ity ................... ..... ...... ....... 446 Connecticut University of.. .. ............... .. ... ... .......... 362 Loui s ville Speed Scientific School Univer s ity of .. 447 Cornell University ... ..... ........ .. ........................ .. 363 Maine University of .... .. ..... .. ...... ... ... ..... .. .. .... .. ... 385 336 C h e mi ca l E n g in ee rin g Ed u cat i o n

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Manhattan College ................................................... 386 Queensland University of ....................................... 415 Maryland, University of .......................................... 387 Rensselaer Polytechnic Institute .............................. 416 Maryland Baltimore County University of.. ........... 388 Rhode Island, University of ..................................... 450 Massachusetts University of .... .................... ........... 389 Rice University ............ ............ .............................. 417 Massachusetts Lowell University of .................... 456 Rochester University of .............. ............................ 418 Massachusetts Institute of Technology ................... 390 Rose-Hulman Institute of Technology .................... 450 McMaster University ............................................... 447 Rutgers University .................. ............................ ..... 419 Michigan, University of.. .......... .............. ................. 391 Singapore, The National University of.. .................. 420 Michigan State University ....................................... 392 South Carolina, University of ............ ........ ...... ........ 421 Michigan Technological University ........................ 393 South Florida, University of .................................... 451 Minnesota, University of .. .. .................................... 394 Southern California, University of .......................... 451 Missouri, Columbia, University of .............. ............ 395 State University of New York at Buffalo ............ .... 452 Missouri, Rolla, University of ................................. 396 Stevens Institute of Technology .............................. 422 Monash University .................................................. 448 Sydney, University of .................................... .......... 452 Montana State University .......... .......... .................... 454 Syracuse University ................................................. 453 Nebraska, University of ........................................... 397 Tennessee University of ......................................... 423 Nevada at Reno, University of ................................ 398 Texas University of ................................................ 424 New Jersey Institute of Technology .............. ........ .. 399 Texas A&M University ........................................... 425 New Mexico, University of .. .......... ................... ...... 400 Texa s A&M King sville, University of .................... 453 New Mexico State University ...................... ........... 401 Toledo University of.. ............................................. 426 New South Wales University of .................. ........... 448 Tulane University ...... ............ ............... ................... 427 North Carolina State University .............................. 402 Tulsa, University of ............................... ... .. ............. 428 North Dakota University of .............................. ...... 456 Utah, University of .................................................. 454 Northeastern University ........................................... 449 Vanderbilt University .............................................. 429 Northwestern University ......................................... 403 Virginia University of.. ....................... ................. ... 430 Notre Dame, University of .... ........ .......................... 404 Virginia Polytechnic Institute .................................. 431 Ohio State University .... .................................. ........ 405 Washington University of.. ..................................... 432 Ohio University ........ .................................. ............. 406 Washington State University ................................... 433 Oklahoma University of ......................... ... ............ 407 Washington University .................. ................. ......... 434 Oklahoma State University .................... ............ ...... 408 Waterloo, University of .. ...... .................................. 454 Oregon State University .................................... ...... 409 Wayne State University ........................................... 435 Pennsylvania, University of.. ............................ ....... 410 West Virginia University ...... .................................. 436 Pennsylvania State University .................... ............. 411 Widener University .......................... ....................... 455 Pittsburgh University of ............................ ............. 412 Wiscon s in University of ......................................... 437 Polytechnic University .................. ................ .......... 413 Worcester Polytechnic Institute ............................... 438 Princeton University ... .................................. ........... 449 Wyoming, University of .......................................... 439 Purdue University ................... ...... ................... ...... 414 Yale University ................................................. ....... 440 Fall 1 999 337

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Graduate Education in Chemical Engineering Teaching and research assistantships as well as industrially sponsored fellowships available up to $17,000 In addition to stipends, tuition and fees are waived PhD students may get some incentive scholarships The deadline for assistantship applications is March 15th. G.G.CHASE Multiphase Processes Fluid Flow, Interfacial Phenomena Filtration Coalescence H.M.CHEUNG Nanocomposite Materials Sonochemical Proce ss ing, Polymerization in Nanostructured Fluids, Supercritical Fluid Processing S.C.CHUANG Catalysis, Reaction Engineering, Environmen tally Benign Synthesis J. R. ELLIOTT Molecular Simulation, Phase Behavior Physical Properties Proces s Modeling E.A EVANS Materials Processing and CVD Modeling L. K.JU Biochemical Engineering Environmental S. T.LOPINA BioMaterial Engineering and Polymer Engineering H.C.QAMMAR Nonlinear Contro l Chaotic Processe s For Additional Information Write Chair man Grad uate Com mitt ee Department of Chemical E ngine ering The University of Akron Akron, OH 44325-3906 Phone (330) 9727250 Fax (330) 972 -5 856 www.ecgf.uakron edu/~chem 338 Chemical Engineering Education

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Chemical Engineering at the University of Alabama A dedicated faculty with state-of-the-art facilities offer research programs leading to Master of Science and Doctor of Philosophy degrees. Research Interests: Biomass Conversion Catalysi s and Reactor Design, Controlled Release Energy Conversion Processes, Environmental Studies Fuel Cells Hydrodynamic Stability, Magnetic Storage Media Mass Transfer, Metal Casting Microelectronic Materials, Microencapsulation Polymer Rheology Process Dynamics and Control Reservoir Modeling Suspension and Slurry Rheology Thermodynamics Transport Process Modeling For Information Contact: Director of Graduate Studie s Department of Chemical Engineering The University of Alabama Box 870203 Faculty G.C. April, Ph D ( Louisiana State) D. W. Arnold, Ph.D. (Purdue) C. S. Brazel, Ph.D. (Purdue) E. S. Carlson, Ph.D. (Wyoming) P. E. Clark, Ph.D. (Oklahoma State) W. C. Clements, Jr. Ph.D (Vanderbilt) W. S. Epling, Ph.D. (Florida) R. A. Griffin, Ph D. (Utah State) D. T. Johnson, Ph.D. (Florida) P. W. Johnson, Ph.D. (New Mexico Tech.) T. M. Klein, Ph.D. (NC State) A. M. Lane, Ph.D. (Massachusetts) M. D. McKinley, Ph.D (Florida) R. G. Reddy, Ph D (Utah) L. Y. Sadler III, Ph.D. (Alabama) Tuscaloosa, AL 35487-0203 An equal employment/equal educational opportunity institution V. N. Schrodt, Ph.D. (Penn. State) J.M. Wiest, Ph.D. (Wisconsin) Phone: (205) 348-6450 Fall 1 999 339

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CHEMICAL& MATERIALS ENGINEERING Grad tta te Progrn1n :_',:~;;" ___ .. he Department of Chemical and Materials Engineering at The University of Alabama in Huntsville offers you the opportunity for a solid and rewarding graduate career that will lead to further success at the forefront of academia and industry. We will provide graduate programs that educate and train students in advanced areas of chemical engineering, materials science and engineering and b i otechnology. Options for an M.S. and Ph.D. degree in Engineering or Materials Science are available. Our faculty are dedicated to interna tional leadership in research. Projects are ongoing in Mass Transfer, Fluid Mechanics, Combustion, Bioseparations, Biomaterials Microgravity Materials Processing, and Adhesion Collaborations have been established with nearby NASA/Marshall Space Flight Center as well as leading edge biotechnology and engineering companies. We are also dedicated to innovation in teaching Our classes incorporate advances in computational methods and multi-media presentations. Department of Chemical Engineering The University of Alabama in Huntsville 130 Engineering Building Huntsville, AL 35899 FACULTY RESEARCH AREAS Ramon L. Cerro Ph.D. (UC-Davis) Professor and Chair Capillary hydrodynamics, multiphase flows enhanced heat transfer surfaces (256) 890-7313, rlc@che.uah edu Chien P. ChenPh.D. (Michigan State) Professor Multiphase flows, spray combustion, turbulence modeling, numer i cal methods in fluids and heat transfer. (256) 890-6194 cchen@che.uah.edu Krishnan K. Chittur Ph.D. (Rice) Professor Protein Adsorption to Biomaterials, FTR/ATR at solid-liquid interfaces, biosensing. (256) 890-6850, kchittur@che.uah.edu Douglas G. Hayes Ph.D. (Michigan) Assistant Professor Enzyme reactions in nonaqueous media separations involving biomolecules, lipids and surfactants surfactant-based collidal aggregates (256) 890-6874, dhayes@che uah.edu James E. Smith Jr. Ph.D. (South Carolina) Professor Kinetics and catalysis, powdered materials processing, combustion diagnostics and fluids visualization using optical methods. (256) 890-6439, jesmith@che uah edu Jeffrey J. Weimer Ph.D. (MIT) Associate Professor, Joint Appointment in Chemistry Adhesion biomaterials surface properties, thin film growth surface spectroscopies scanning probe microscopies. (256) 890-6954, jjweimer@matsci.uah.edu The Unlvarshy ol Alabama In Huntsvlla An Affirm a ti v e A c ti o n/Equal Opp o rtunity In s titution Web page: http://chemeng.uah.edu Ph: 256.890.6810 FAX: 256.890.6839

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The University of Alberta is well known for its commitment to excel lence in teaching and research. The Department of Chemical and Materi als Engineering has 34 professors and over 100 graduate students. Degree s are offered at the M.Sc. and Ph.D levels in Chemical Engineering, Ma terials Engineering, and Process Control. All full-time graduate stu dents in the research programs re ceive a stipend to cover living ex penses and tuition. For further infor mation contact Graduate Program Offi ce r WCM Department of Chemical and Materials Engineering University of Alberta Edmonton Alberta, Canada T6G 2G6 PHONE (780) 492-5805 FAX ( 780) 492-288 1 e-mail: ch e mi c al. e ngineering @ ualberta c a w e b: w ww.ualberta. c a/ch e meng Fall 1 999 CHEMICAL ENGINEERING FACULTY P. CHOI, Ph .D ( Universi t y of W a terloo ) S ta ti s ti c al M ec hani cs of P o l y m e r s P o l y m e r S o lwi o n s a 11d Bl e 11d s K. T. CHUANG, Ph .D ( U ni vers it y of Albe rt a ) Mass Tra11sf e r Catal y sis S e paratio11 Pro c ess e s P ol/111io11 Control I. G. DALLA LANA, Ph D (Un i v of Minnesota) EME RITUS Ch e mi c al R e a c ti o 11 E11 g in e eri11 g H e t e r oge 11 eo u s Catal ys i s J.A.W. ELLIOTT, Ph D. (Uni v er s ity of Toronto ) Th e m wdy 11 a mi cs S ta t is ti ca l Th e rm o d y 11 a mi cs l nterfacial Ph e 11 o m e 11a D. G. FISHER, Ph D. ( University of Michigan ) EME RIT US Pr ocess D y 11ami cs and C o 11tr o l R e al-Tim e C o m p w er A p pli c ati o 11 s J.F. FORBES, Ph.D (McMas t er Un i vers it y ) R ea l-Tim e Opt i mi za t io 11 Co ntr o l of Sh ee t F o n11in g Pr ocesses M. R. GRAY Ph .D ( Califo rni a In st. of Tec h .) DEAN OF GRADUATE STUDIES B io r e a c t o r s Ch e mi c al Ki11 e ti cs Bitum e 11 Pro ce s s i11 g R. E. HA YES, Ph D ( Univers it y ofBa th ) N um e ri c al A11al ysis R e a c t o r M o d e li11 g C o mputati o 11al Fluid D y 11ami c s B. HUANG Ph D (U niver s ity of Albert a) Co nt ro ll e r P erfo nn a 11 ce Assess m e nt Mu l ti va ri ab l e Cont r ol St a ti stics S. M. KRESTA Ph D. ( McMa s ter Univer s ity ) Turb u l e nt & Tran s iti o na l Fl ows Multiph ase Flo ws C FD S. LIU, Ph D (U ni ve r s it y of A lb er t a) Fluid-Part icle D y 11ami cs Tra11 spo rt Ph e11o m e 11a M ass Tra11 sfe r D. T. LYNCH, Ph.D ( U ni versity of Alberta ) DEAN OF ENGINEERING Ca t a l ys i s K i 11 e ti c M o d e lin g N um e ri c al M e th o d s P oly m e ri za ti o 11 J. H. MASLIY AH, Ph D. (University of Briti s h Col umbi a) Tra11 s p o rt Ph e n o m e 11 a Coll o id s Particl e Fluid D y 11ami cs Oil Sa11d s A. E MATHER, Ph D ( Universit y of Mi c hi g an ) Ph ase Equilibr ia Flu id Pr ope rti es a t Hi g h Pr ess ur es Th e m w d y n a mi cs W. C. MCCAFFREY, Ph D ( McGill Uni v er s it y ) R e a c ti o n K i 11 e t ics H eavy Oil U p g radi11 g P o l y m er R ecycl i11 g Bi o t ec h11 o l ogy P. A. J. MEES, Ph D. ( U ni ve r s it y of A lb er t a) C o mput a tio11al Fluid D y 11 a mi cs Tra11 s p o rt Ph e 11 o m e 11 a Pulp a11d Pap e r K. NANDAKUMAR, Ph.D (P rin ce t o n U ni v e r sity) T ra n s p o rt Ph e n o m e 11 a Di s till at i o 11 C o mput a ti o 11 a l Fhiid D y n a m ics F. D. OTTO, Ph D. ( Univer s ity of Michigan ) EME RJTI S Ma ss Tra11 sfe r G as -Liqu i d R eac ti o n s S e p a r a ti o n Pr o c esses M. RAO Ph.D ( Rut ge r s Un i ver s it y) Al I nt e lli ge nt C o 11tr o l Pr ocess Co 11t ro l S. L. SHAH Ph.D ( Uni v er s ity o f Albert a) Co mpw e r Pro cess C o 11tr o l S ys t e m I d e nt ijica ti o 11 A d a pt ive C o ntr o l S. E. WANKE, Ph.D. (U n iver s ity of California D avis) CHA IR H e t e ro g e11 eo us Catal y sis Ki11 e ti cs P o l y m e rizati o 11 M. C. WILLIAMS Ph D (U ni ve r s it y of Wi s co n s in ) Rh eo l ogy P o l y m e r Cha rac t e r iza t io 11 P o l y m e r Pr ocessi 11 g Z. XU, Ph.D ( Virg ini a Polytechnic Institute and S t ate Univer s it y ) S u rface S c i ence & E ng i neering Min e r al Pr ocessi n g W as t e M a 11 age m ent 3 41

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FACULTY/RESEARCH INTERESTS ROBERT ARN OLD Prof esso r (Ca lt ec h ) Mi c r ob i o l og i ca l Ha z ardous Waste Treatm e nt M etals Speciatian and T oxicity CHEMICAL AND ENVIRONMENTAL ENGINEERING PAUL BLOW E RS Assistant Prof esso r ( Illin o i s, Urbana-Champaign ) Che m ical Kineti cs, Catal ys i s, Swfa ce Ph e n ome na JAMES B AYGENTS, Assoc iat e P rofessor ( Prin ce t o n ) Fluid Mechani cs, Transport a n d Colloidal Phenom e na Bi oseparat i ons E l ec trokinetics WENDELL ELA Assistant Professor ( Stanford) P a rri cle-Pa rti cle Int erac tions Environmenta l C h em istr y JAMES FARRELL, Assistant Pr ofesso r ( Stanford) So rpti o n /deso rpti on of Organics in Soils ROB ERTO GUZMAN, Associate Profe sso r (Nort h Caroli n a State ) Pr o t ei n Separation Affinit y Methods ANTHONY MUSCAT Assistant Profe sso r (S t a nford ) at THE UNIVERSITY(sf Kin etics Surfa ce Chemistr y, Swfa ce Engineer in g, S e mi co ndu ctor Pro cess in g, Microcontamination OF KIMBERLY OGDEN, Associate Profes so r (Co l orado) Bi oreac t ors, Bi oremedia ti on Organi cs R e moval from Soils THOMAS W PETERSON Profe ssor and D ean (Ca lT ec h ) Aeroso l s Ha zardo u s Wast e In c in e r at i on, Micro co ntaminati o n ARA PHILIPOSSIAN Adjunct Associate Profe ssor ( Tuft s) Chem i ca l /Mec hani cal P o li shing, S e mi co ndu c t or P rocess in g JERKER PORATH R esearch Profe sso r (U pp s al a) Sepa r at i on S c i ence EDUARDO SAEZ Associ a t e Prof essor (UC, Davi s) Rh eo l ogy, P o l y mer Fl ows, Multiphase R eac tors FARHANG SHADMAN, Prof essor ( B e rk e l ey) R e a c tion Engin ee rin g, Kinetics, Ca tal ys is R eact i ve Membranes, Mi c ro co ntamination RAYMOND A. SlERKA, Profe sso r Emeritus ( Oklahoma ) Adso rpti on Oxidation M e mbran es, Solar Cata l yze d D etox R eac ti o n s JOST 0. L. WENDT, Profe sso r a nd H ea d (Jo hn s Hopkins ) Co mbusti o n-G e n e rat ed A ir Polluti on, In c in e ration Wast e Manag e m e nt DON H WIDTE Profes so r Emeritus (Iowa State) Pol y m e r s Microbial and En zy m a ti c Pr ocesses DA YID WOLF Visiting Pr ofesso r (Tec hnion ) Ferm e ntation, Mixing Energ y, Biomass Convers i o n 342 For further information write to Chairman Graduate Stud y Committee Department of Chemical and Environmental Enginee ring University of Arizona Tucson Arizona 85721 The University of Arizona is an equal opportu nity educational institution / equal opportunity employer Women and minorities are encouraged to apply ARIZONA~-------Th e Chemical and Environmenta l Engineering Department at the Univer s it y of Arizona offers a wide range of r esea rch opport unjtie s in a ll m ajor areas of chemica l engineering and environmental engineering a nd gra du a t e courses are offere d in mo s t of the re se arch areas Jj s t e d her e. The department offers a full y accred it ed undergraduate d eg re e as well as MS and PhD gra duat e degree s. Strong interdi sc iplinar y program s ex j s t in bioprocessing and bioseparations microcontamination in electrorucs manu facture a nd e nvironm e nt a l proce ss modification. Financia l su pport is available through fellowships, government and industrial grants and contracts, teaching and re se arch assistantships. Tu cso n ha s an exce ll e nt climate and man y r ec r ea tional opportunities It is a grow in g modern c i ty of 450,000 that retains mu c h of th e old Southwest e rn atmosphere. Che mi c al Engin ee ring Ed u ca ti on

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CHEMICAL BIO AND MATERIALS ENGINEERING AT ARIZONA STATE UNIVERSITY Chemical Engineering Beaudoin Step h en P. Ph D ., N o rth Caro lin a S t a t e U ni ve r s it y T ra n s p ort Ph e n o m e n a a nd Sur face S c i e n ce co n ce rin g P o lluti o n Pr eve nti o n W as t e M_inimi za ti o n a nd P o llu ti o n R e m e di a ti o n Beckman, James R ., Ph D ., U ni ve r s i ty of Ari zo n a C r ys t a lli za ti o n a nd S o l ar Coo lin g Berman Nei l S Ph D ., U ni vers i ty of T exas, A u sti n F lu i d D y nami cs a nd Air P o llution Burrows Vero ni ca A. Ph D ., Prin ce t o n U ni ve r si t y Sur face S c i e n ce, S e mi co n d u c t or P rocess in g Garcia, A ntoni o A Ph D U.C. B e rk e l ey Ac id B ase Int erac ti o n s, Bi oc h e mi ca l Se p ara ti o n Co ll o id C h e mi s tr y n 0 I: .. 0 .. -:. .. .... .. .. ., .-., <,. CONr"o <,. CROSS DISCIPLJNARY ASEARCH Raupp, Gregory B. Ph.D ., U ni ve r s it y o f Wi sco n s in S e mi co ndu c t or M a t e ri a l s Pro cess in g, S urf ace S c i e n ce, C at a l ys i s zn a R azato s, A nn a, Ph D ., U ni ve r sity of T exas, A u s tin B iotec hn o l ogy Rivera, Daniel Ph.D. C a l T ec h P rocess Co ntrol a nd D es i g n Sater, Vernon E Ph.D ., Illin o i s In s titut e o f T ec h High Technology Torrest, Robert S Ph.D ., U ni ve r s it y of M_inn eso t a Multiph ase Fl ow F i ltr a ti o n F l ow in P oro u s M e di a, P o lluti o n Co nt ro l Environment Bioengineering Gu ilb ea u Eric J. Ph D L o ui s i a n a T ec h U ni vers i ty Bi ose n so r s Ph ys i o l og i cal Sys t e m s, Bi o m a t e r ia l s He Jiping, Ph D ., U ni ve r s ity o f M ary l a nd Bi o m ec h a ni cs, R o b o ti cs, Co mput a ti o n a l Ne u rosc i e n ce, Optim a l Co nt ro l S ys t e m D y n a mic s a nd Co ntr o l Kipke, Daryl R., Ph D ., U ni ve r s it y o f Mi c hi g an Co mput a ti o n N e u rosc i e n ce M ac hin e Vi s i o n S p eec h R ecog niti o n R o b o ti cs N e ural N e tw o rk s Mass ia Ste ph e n Ph D ., U n ive r s it y o f T e x as B io m a t e rial s M o l ec ul a r and Ce llul ar E n g in ee rin g Panitch, A l yssa Ph D. U ni ve r s it y of M assac hu se tt s T iss u e E n gi n eer in g Pizziconi, V in ce nt B. Ph.D. Ari zo na Stat e U ni ve r s ityArtifi c i a l Or ga n s, Bi o m a t e ri a l s, Bi ose p ara ti o n s Sweene y, James D ., Ph.D. CaseW es t e rn R eserve U ni ve r s ityR e h a b E n g in ee r ing Ap pl ied N e u ra l Co ntr o l Towe, Bruce C Ph.D. P e nn sy l va n ia St a t e U ni vers i ty B ioe l ec tri c Ph e n o m e n a, Bi ose n sors, Bi omedica l Im ag in g Yamag u ch i Gary T ., Ph D ., S t a n fo rd U ni ve r sity Bi o m ec h a nj cs, R e h a b E n gi n ee rin g, Co m p ut e r -A id e d S ur ge r y Materials Science & Engineering Ada m s, Jam es Ph D ., Univer s it y of Wi s c o n s in M a di so n A t o mi s ti c Simulati o n of M e t a lli c Surf aces Grain B o undari es Aut o m o bil e Ca ta l ys t s P o l ym e r Meta l Adh es i o n Alford, Te rr y L., Ph D C orn e ll U ni vers i ty E l ec tr o ni c M a t e rial s Ph ys i ca l M e t a llur gy E l ec tr o ni c Thjn F ilm s S u rface frhjn F ilm Dey San dwip K., Ph.D ., NYS C o f Cera mi cs, Alfr e d Unive r s it y Cera mi cs, S o l -Ge l P rocess in g Krause, Ste ph e n L. Ph D ., U ni ve r s i ty of Mi c hi ga n Ord e r ed P o l ymers E l ectronic M a t e ri a l s, E l ectro n X -ray Di ffrac ti on E l ectro n Mi crosco p y Ma haj a n S ubh as h Ph D ., Univ e r s it y o f Mi c hi ga n S e mi co nduct o r D efec t s, Stru c tur a l M a t er i a l s D efo rm at i o n Mayer, James, Ph D ., Pur d u e U n ive r s i ty Thin F ilm P rocessing Io n B ea n M od i ficatio n of M ateria l s For 11u11e detail, rt'f.:ardi111: the 1:nu/11ate de1:re1 prof.:rt/111' 111 /Ill /)eparl111e11t of ( hemical llio, a11d ,\/ateria/1 F111:i11e1'ri111:, pleme call (-1811) %5-3313 or write to : /)1 l : ri,
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faculty Robert P. Chambers University of California, Berkeley Harry T. Cullinan Carnegie Mellon University Christine W. Curtis Florida State University Steve R. Duke University of Illinois Mahmoud EI-Halwagi University of California, Los Angeles James A. Guin Unive rsi ty of Texas, Austin Ram B. Gupta University of Texas, Austin Gopal A. Krishnagopalan University of Maine Jay H. Lee California In stitute of Technolog y Y. Y. Lee Iowa State University Glennon Maples Oklahoma State University Ronald D. Neuman The In stitute of P aper Chemistry Stephen A. Perusich University of Illinois Timothy D. Placek University of Kentucky Christopher B. Roberts University of Notre Dam e A. R. Tarrer Purdue University Bruce J. TatarchukUniversity of Wisconsin Research Areas Biochemical Engineering Biotechnology Pulp and Paper Proce ss Control Catalysis and Reaction Engineering Computer Aided Process Synthesi s, Optimization and Design Environmental Chemical Engineering Pollution Prevention Recycling Materials Polymer s Surface Science Colloid and Interfacial Phenomena Thermodynamic s Supercritical Fluid s Separation Electrochemical Engineering Fluid Dynamics and Transport Phenomena Fuels and Energy

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DEPARTMENT OF CHEMICAL AND PETROLEUM ENGINEERING FACULTY R. G. M oor e, Head (Alberta) J. Az aie z (Stanford) H. Baheri (Saskatchewan) L .A B e hi e (Wes t e rn Ontario) C. Bell e humeur (McMaster) P R. Bi s hnoi (Alberta) R. A Heidemann (Washington U.) C H y ndman (Ecole P olytechniq u e) A. A. J e j e (M IT ) A Kantza s (Waterloo) B. B. M aini (Univ. Washington) A. K. Me hrotr a (Calgary) S A Me hta (Calgary) B. J. Miln e (Calgary) M Pool a di-Dar v i s h (A lb erta) W Y Sv rcek (Alberta) M A T rebble (Calgary) H. W Ya rranton (Alberta) B. Y oun g (Ca nt erbury NZ) L. Z an z otto (S l ovak Tech. Univ. C zec h oslovak i a) The D epartment offers graduate programs l eading to the M.Sc and Ph.D degrees in Chemical Engineering (full-time) and the M.Eng. degree in Chemical Engineering, P e tr oleum R eservoir Engineering or Enginee rin g fo r the Environment (part -tim e) in the following areas: Biochemical Engineering & Biotechnolog y Biomedical Engineering Environmental Engineering Modeling Simulation & Control Petroleum Recover y & Reservoir Engineering Polymer Processing & Rheolog y Process De v elopment Reaction Engineering/Kinetics Thermod y namics Transport Phenomena Fe ll ows hip s a nd R esea r c h Ass i sta nt s hip s a r e ava il a bl e t o a ll qu a lifi e d a ppli ca nt s Fo r Additional In fo rm atio11 W r ite Dr. A. K. Mehrotra Chair Graduate Studies Committee Departm ent of Chemical and P etro l eum Engineering Univers i ty of Calgary Calgary, Alberta, Canada TIN I N4 E-mai l : grads tud @e n c h.u calgary.ca Th e University is located in the City of Calgary the Oil capital of Canada the home of the world famous Calgary Stampede and th e 198 8 Winter Ol ympics. The City combines the traditi ons of the Old West with the sophistication of a modem urban. cente r B eautifu l Banff National Park is 110 km west of the City and the ski resorts of Ban ff, Lake Louise and Kanana skis areas are readily access ibl e. I n the above ph o to the University Campus i s shown wit h the Ol ympic O va l and the stude nt residences in the foreground The Engineering complex is on th e l eft of the picture. Fall 199 9 345

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The UNIVERSITY OF CALIFORNIA at BERKELEY offers graduate programs leading to the Master of Science and Doctor of Philosophy. Both programs involve joint faculty-student research as well as courses and seminars within and outside the department. Students have the opportunity to take part in the many cultural offerings of the San Francisco Bay Area and the recreational activities of California's north ern coast and mountains. RESEARCH INTERESTS Biochemical Engineering Electrochemical Engineering Electronic Materials Proce ss ing Energy Utilization Fluid Mechanic s Kinetic s and C a talysi s Polymer Science and Technology Process Design and Development Separation Processes Surface and Colloid Science Thermodynamics FACULTY ALEXIS T. BELL HARVEY W BLANCH (C hair) ELTON J CAIRNS ARUPK CHAKRABORTY DOUGLAS S CLARK SIMON L. GOREN DA YID B. GRAVES ENRIQUE IGLESIA ALEXANDER KATZ PLEASE WRITE: JAYD KEASLING C JUDSON KING ROY A MABOUDIAN SUSAN J MULLER JOHNS NEWMAN JOHN M PRAUSNITZ CLAYTON J. RADKE JEFFREY A. REIMER DAVID V SCHAFFER DEPARTMENT OF CHEMICAL ENGINEERING UNIVERSITY OF CALIFORNIA BERKELEY, CALIFORNIA 94720-1462 346 Chemical Engineering Education

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University of California, Davis Department of Chemical Engineering & Material s Science Off e ring M.S and Ph.D. degree programs in both Chemical Engineering and Mat e rials Science and Engin ee rin g ------F ac ult y -----Da v id E. Bl oc k As is1ant Pr ofessor Ph D ., University of Minnesota. 1992 lnd11strial fennentarion biochemical processes in pham1ace11tical ind11stry Ro g er B. Boulton Profe sso r Ph D ., University o f Melbourn e 1 976 F e rm e ntati on and reaction kinetics, crystallization S t e ph a ni e R Dun ga n Associate Professor Ph .D., Massachusetts Institute of Technology, 1992 Mice/le tra11Spon colloid and inrerfacial science in food processing Bru ce C. G ate s, Prof essor Ph D ., University of Wa s hin g t o n Seaule 1966 Catalysis solid s 11p eracid catalysis z eolite catalysts bimetallic catal y sts catal y sis by metal c/11sters J e ff ery C G ib e lin g, Professor Ph.D., Stanford University 1979 Defom,ation frac/llre and farig11e of metals, layered composites and bone Joanna R. Groza Profe ssor Ph D. Poly t echnic lnsti t ul e Bu c har es t 1972 Pl asma activated sintering and processing of 1wnostn1ct11red materials Bri a n G. Hi ggi n s, Prof esso r Ph D University of Minn esota, 19 80 F/11id mechanics and interfacial phenomena sol gel processing, coating flows David G Howitt Professor Ph D., U n iversity of California Berkeley 19 76 Forensic and fail11re analysis, electron mi croscopy ignition and comb11stion processes in materials A l a n P Jackman Profe sso r Ph D University of Minn esota 1968 P rotein prod11ction in plant cell c11/t11res bioremediation Ma rj or i e L. Lon go, A ssis tant Prof esso r Ph D University o f California Sanla Barbara 1993 H ydrophobic protein design for actii e cont r ol mrfactant micros/rue/lire, and interaction of proteins and DNA with biologi c al membranes Benjamin J M c Coy, Prof esso r Ph D University of Minnesota, 1967 S11percritical extraction pol/11tant transpon Kar e n A McDon a ld Profes so r Ph D ., U niversit y of Maryland, College Park 19 85 Plant cell C11lt11re biop r ocessing algal cell c 11lwres A mi ya K M ukher jee, Prof essor D Phil U ni versity of Oxford, 1962 S11perplasticiry of intennetalli c allo y s and cerami c s high tempera/lire creep defonnation Zuhair A M unir Profe sso r Ph D University of California B e rk e le y 1963 Co111b11stion symhesis 11111/tilayer comb11s ti on systems fimc ti onall y gradiem materials A le xa ndr a N avro ts k y, Profes sor Ph D University of Chicago, 196 7 Thennodynamics and solid state chemist r y ; high temperat11re calorimet r y A hm e t N. Palazo g lu Profe ssor Ph D. Ren sse la er Polyte chnic ln sti nn e 1984 Pr ocess control and p r ocess design of environmentall y benign processes R o n a ld J Phillip s, Associate Prof esso r Ph.D., M assachuseus In s titut e of Technology 1989 Transpon processes in bioseparations Newtonian and non-Newtonian s11spension mechanics R o b e rt L Pow e ll Prof esso r Ph D Johns H o pkin s University, 1978 Rh eolog y, s11spension mechanics magnetic resonance imaging of suspensions S ubha s h H Risbud Prof esso r a nd Chair Ph D ., University of California B erkeley 1976 Semiconductor quamum dots, high T superconducting ceramics, polymer composi t es for oprics Dew ey D Y. Ryu Professor Ph D ., M assac hu se u s ln s 1i1ute of T ec hnolo gy 1967 B iomolecula r process engineeri n g and recombinam bioprocess technology J a m es F. S hack e lford Profes so r Ph D. University of California Berkel ey, 19 7 1 Struc/llre of materials, biomaterials, nondestn1cti1 e testing of e n g in ee rin g mat e rial s J .M. S mith Profe ssor Emeritus Sc D ., Massachuseus In s titut e of Technology 1943 Chemical kinetics and reactor design Pi e t e r S tr oeve, Pr ofesso r Sc.D. Massachuseus ln s1i1 u1e of Technology, 1 973 Membrane separations Langmuir Blodgeu films c olloid and surface science S t e ph e n W hit a k e r Prof essor Ph D Univers it y of Delaware 1 959 M11/tiphase transport phenomena F a ll 1 999 Th e muhi face 1 e d graduaie st udy experience in 1he D e partment of Chemical Engineering and Material s S cie n ce allows s t udents 10 choose research projects and t h esis advisers from a ny of o ur facuhy with expe rti se in chemical engineering and/or materials scie n ce a n d engineering. Our goal i 10 provide th e financial a nd academic s upport for smdents 1 0 comple1e a s ub sia mi ve research project within 2 yea r s for 1h e M S. and 4 years for 1he Ph D SAN FIIANCISCO L OCATION : Sa c ramento : 17 miles San Francisco : 72 miles Lake. Ta h c>t" : 90 miles Davi s is a sma ll bike-fr i e n d l y uni ve r s it y tow n localed 17 mi l es we s t of Sacramen t o and 72 m il es n ort h east of San Fra n cisco w i t hin dr i v in g d i tance of a mu ll itude of rec r ea ti ona l ac ti vi t ies i n Yosemite, Lake Tahoe, Monte r ey, an d Sa n Fra cisco Bay Area F o r inf o rmation abow our pro gra m, look up our web s ir e at hup :l/www c hms.u c davis edu or co nta c t us v ia e-mai l at c h111s g radass1 @e 11 g r.u c davis .e du 011 lin e appli c ations ma y be submiued v i a hups: l/se cureweb.ucdav i s.edu : 2443 Graduate Admiss i on Chai r Prof essor J effery C. Gibe/i11g D epartmelll of Chemical Engineering & Mat e rial s Science University of Ca lif o mia. Da v is D avis, CA 956/6-5294. USA Ph o n e (530) 752-7952 Fax (530) 752 -10 3 / 347

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UNIVERSITY OF CALIFORNIA Biom e d ical En g in e erin g Bioreactor Engineering Bioremediation Ceramic s Graduat e S tudi es in Chemi c al and Bio c h e mical Engineering IRVINE Combu s tion 348 and Material s Sci e n ce and Engineerin g for Chemical Engineering Engineering and Science Major s Offering degrees at the M S and P h D levels. R esearch in frontier area s in chemical engine e r ing, biochemica l enginee r ing, biotechnology and materials science and engineering Strong physical and life science and engineering groups on c ampus. FACULTY Ying Chih Chang (Stanford University) Nancy A. Da Silva (California I nstitute of Technolog y) James C. Earthman (Stanford University) Steven C. George (University of Washington) Stanle y B. Grant (California I nstitute of Technolog y) Juan Hong (Purdue University) Enrique J. Lavernia (Massachusetts Institute of Technolo gy) Henr y C. Lim (Northwestern University) Martha L. Mecartney (S t anford University) Farghalli A. Mohamed ( University of California Berkele y) Frank G. Shi (California I nstitute of Technology) Vasan Venugopalan (Massachusetts I nstitute of Te c hnolog y) J oint Appointments : G. Wesley Hatfield (Purdue University) Roger H. Rangel (University of California, Berkele y) William A. Sirignano (Princeton Uni ve rsity) The I 510-acre UC I rvine campus is in Orange County five miles from the P acific Ocean and 40 miles south of Los Angeles. I rvine is one of the nation 's fastest growing residential industrial and business a r eas. Nearb y beaches, mountain and desert area recreational activities and local cultural activities make I rvine a p l easant city in which to live and study. For further information and application fo r ms, please visit http : // www.e n g. u ci.e du/ c b e / or contact Department of Chemical and Biochemical Engineering and Material s Scienc e School of Engineering University of California Irvine C A 92697-2575 Compo s ite Material s Con tr ol and Optimization Environmental Engineering Interf acial En gi ne e ring Materials Pro c e ss ing Mechanical Propertie s Metabolic Eng i neering Micr oe lectronic s Proce s sing and Mod e lin g Micro s tructure of Materials Nanocry s talline Ma t erial s Nucleation Chry s tallization and Gl ass Tran si tion Proce ss Po l ymer s Recombinant Cell Technol ogy Separation Proc ess e s Sol-G e l Proces s ing Two-Phase Flow Water Pollution Control Chemical Engineering E du c at io n

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CHEMICAL ENGINEERING AT RESEARCH AREAS Molecular Simulation s Thermodynamics and Cryogenic s Proce ss De s i g n D y namic s, and Control Pol y mer Proce ss in g and Tran s port Phenomena Kinetic s, Combu s tion and Cata l ysis Surface and Interface Engineerin g Electrochemistry and Corro s ion Biochemical Engineering A eroso l Science and Techno l ogy Air Pollution Control and En v iron mental En g ineering FACULTY J.P Chan g P D. C hri s tofide s Y. Cohen M. W.Deem T H K. Frederking ( Pr of Emeritus) S K. F riedlander R F. Hick s E. L. Knuth ( Pr of Emeritus) J C. Liao V M anou s iouthaki s H. G M onbouqu e tt e K. Nob e L. B. Robin s on ( Pr of Emeritus) S. M S e nkan W. D. Van V or s t ( Pr of Emeritus) V L. V ilker ( Pr of Emeritus) A R. Wa z zan PROGRAMS------------------Fall 1 999 UCLA s Chemical En g ineerin g Department offers a program of teaching and re searc h linking fundam e ntal engineering sc ience and indu s trial practice. Our Depart ment ha s s trong graduate re se arch program s in Bioengi neering Energy and En v ironment Semiconductor Manu facturing, Molecular En g ine e rin g of Material s, and Pro cess Sy s tem s Engineering Fellowships are availab l e for outsta n ding applicants in both M.S. and Ph D degree program s. A fellowship includes a waiver of tuition and fees plu s a s tipend. Lo ca ted five mile s from the Pacific Coa s t, UCLA's a ttracti ve 417-acre campus extends from B e l Air to We s twood Village Student s ha ve access to the hi g hl y regarded sc ience program s and to a va riet y of ex perience s in the a tre music art and s port s on campus. CONTACT Admissions Officer Chemical Engineering Department 5531 Boelter Hall UCLA Los Angeles~ CA 90095-1592 (310) B25-9063 349

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University of California, Riverside Department of Chemical and Environmental Engineering Th e Graduat e Pr og ram in Ch e mi ca l and Environ mental En g ineerin g offers training leadin g to th e d egrees of Mast e r of S c i e n ce and Do c tor of Phi lo so ph y. All applicant s are r e quir ed to submit sco r es from the general aptitude Graduate Record Examination (GRE). For more information and application material s write: Graduate Advi s or Department of Chemical and Environmental Engineering Univer s ity of C a lifornia River s ide CA 92521 Visit us at our web s ite: http://www engr.ucr.edu/chemical Faculty a rla n a nd Ro s e m ar y Bo urns Colleg e o f ng1neer1ng Wilfred Chen ( Cal Tech ) Environmental B iotechnolog y, Microbial Engineering B iocatal y sis Marc Deshusses ( ETH Zurich ) Environmental B iotechnology, B ioremediation Modeling Mark R. Matsumoto Chair ( UC Davis ) Water and Wastewater Treatment, Soil R emediation Ashok Mulchandani ( McGill ) B iosensors, Environmental B iotechnology Joseph M. Norbeck ( Nebraska ) Advanced Vehicle Technology, Air P ollution, Renewable Fuels Akula Venkatram ( Purdue ) Micrometeorolog y Air Pollution Modeling Anders 0. Wistrom (U C Da v is ) Particulate and Colloidal Systems, Wastewater Treatment Yushan Yan ( CalTech ) Advanced M aterials, Zeolite Thin Films, Catalysis 350 T h e 1,200 acre Riverside camp u s of t h e University of California is conve n iently located 50 mi l es east of Los Angeles within driving distance to most of the major cultural a nd recreational offerings in S o u t h ern California In addition it is v i rtually equidistant from the desert, the mo u ntains, and the ocean C h e mi c a l En g in ee rin g Edu c ation

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F a ll 1 999 UNIVERSITY (f)F CALIFORNIA SA NTA BARBARA ERA Y S. AYDIL Ph.D (U ni versity of H o u s t o n ) Mi croe l ec tr o ni cs a nd Pl as m a P rocess in g. SANJOY BANERJEE Ph D ( Wat e rl oo) En v i ro nmental Fluid D y n a mic s, Multiph ase Flow s, Turbul e n ce, Comput a tion a l Fluid Dynamic s. BRADLEY F. CHMELKA Ph D (UC. B erke l ey) In o r ga ni cOr ga ni c H y bri d M ate ri a l s, Zeo lit es a nd M o l ec ul ar Si eves, P o l y m e ri c S o lid s, Liquid C rys t a l s, S o lid-Stat e NMR GLE NH. FREDRICKSO Ph D (Stanford) ( Chair ) St a ti s t ica l Mec h anics Glasses P o l y m ers, Com p os i tes, A ll oys. JACOB ISRAELACHVILI Ph D (Ca mb ri d ge) ( Vice-Chair ) Surf ace a nd ln terfac i a l Phen o m e n a, A dh es i o n C o ll o id a l S ys t e m s, Surfa ce For ces, Bi o m o l ec ular Int erac ti o n s, Fri c ti o n EDWARD J. KRAMER Ph D (Carneg i e -M e ll o n ) Mi c ro sco pi c Fund a m e nt a l s of Fra c ture of P o l y m e r s, Diffu s i o n in P o l y m e r s, Polymer Sur faces a nd Int e rf aces. FRED F. LANGE Ph D ( P e nn S t ate) P ow d e r P rocess in g of C o mp os it e C e rami c Liquid Pr ec ur so r s fo r C e rami cs, Sup e r co ndu c ting O xi d es. L. GARY LEAL Ph D. (S t a n ford) Fluid M ec h a ni cs, Ph ys i cs and Rh eo l ogy o f C o mpl ex Fluid s, includin g P o l y m e r s, Su s p e n s ion s, and Emul s i o n s. GLENN E. LUCAS Ph.D. ( M.I. T.) M ec h a ni cs of Mat e ri a l s, Stru c tural R e liabi l it y. DIMITRIOS MAROUDAS Ph D. (M. I .T.) Th eo r e ti ca l an d Co mput a ti o n al M a t e ri als S c i e n ce, Mi cro tru c tur e E vo lu t i o n in El ec tron ic a nd Stru c tu ra l M a t e rial s. ERIC McFARLAND Ph D (M. I .T.) M D ( H arvard) Bi ome d ica l E n g in ee rin g, NMR a nd Ne utr o n Im ag in g, T ra n s p o rt Ph e n o m e n a in Compl ex Liquid s, R a di a tion Int erac ti o n s. DUNCAN A. MELLICHAMP Ph D ( Purdu e) C omput e r C o ntrol Pro cess D y n a mi cs, R e al-Tim e C o mputing. SAMIR MITRAGOTRI Ph.D ( M.l T .) Dru g D e li very an d Bi o m a t eria l s DAVID J. PINE Ph.D. (Cornell) P o l y m e r Surf ac tant an d Co ll o id al Ph ys i cs, Multipl e Li g ht S ca tt e rin g, Ph o t o ni c C rys t a l s, Macrop o rou s M a t e ri a l s. ORVILLE C. SANDALL Ph D (U C. B erke l ey) T ra n s p o rt Ph e n o m e n a, S e p ara ti o n P rocesses. DALEE. SEBORG Ph.D ( P r i nce t on) P rocess C o ntrol M o nit o rin g an d Id e nti fica ti o n. MATTHEW V. TIRRELL Ph D (U. Mass a c hu se tt s) P o l y m e r s, Surf aces A dh es i o n Bi o m a t e ri a l s T. G. THEOFANOUS Ph D (Minnesota) Multiph ase Fl ow Ri s k Assess m e nt a n d Ma n age m e nt W. HENRY WEINBERG Ph.D (UC. B e r ke l ey) Su rface C h e mi s tr y, H e t eroge n eo u s C a tal ys i s, El ec t ro ni c M a t e rial s, Mat e ri a l s Di scove ry u s in g C o mbin a t o rial Ch e mi s tr y JOSEPH A. ZASADZINSKI Ph D ( Minn eso t a) Surfac e a nd Int e rf a ci a l Phenom e n a, Biomateri a l s. PROGRAMS AND FINANCIAL SUPPORT Th e D epa r tment offe r s M .S. and Ph D. deg r ee p rog r a m s F i nan c i a l a id in cl udin g fe ll ows hip s, teac hin g ass i s t a nt s hip s, and r se a rc h assis t an t s hip s, i s ava il a bl e. THE UNIVERSITY On e o f t h e wo rl d's f ew se a s h o r e c ampu ses, U CSB is l oc at e d on t h e Pa cific Coas t 100 m i les n o r t h wes t of Los An ge l es. T he s tu den t e n ro ll me nt is over 1 8,000. T he met r opo l i t an San t a Barb a ra area h as ove r 1 50,000 r es id e nt s and i s f am o u s fo r i t s mild eve n clima te For additional information and applications, write to =..,......,,,.,.,.,,,=--=.....,=--Chair Graduate Admis s ion s Committ e e D e partm e nt of Ch e mical Engin e erin g Univ e rsity of California Santa Barbara C A 93106 35 /

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Chemical Engineering at the I 352 CALIFORNIA INSTITUTE OF TECHNOLOGY '~t the Leading Edge" Frances H. Arnold John F. Brady Mark E. Davis Richard C. Flagan Aerosol Science Applied Mathematics George R. Gavalas Konstantinos P. Giapis Julia A. Kornfield John H. Seinfeld Atmospheric Chemistry and Physics Biocatalysis and Bioreactor Engineering Biomaterials Bioseparations Catalysis Chemical Vapor Deposition Combustion David A. Tirrell Nicholas W. Tschoegl (Emeritus) Zhen-Gang Wang Colloid Physics Fluid Mechanics Materials Processing Microelectronics Processing Microstructured Fluids Polymer Science Protein Engineering Statistical Mechanics For further information, write ________ _________ Director of Graduate Studies Chemical Engineering 210-41 California Institute of Technology Pasadena California 91125 Also visit us on the World Wide Web for an on-line brochure : http :/ /www.che.caltech edu C h e mical Engineering Educat i on

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Va? 1rJTa cARrJc~1c ft\(LLarJ \J ho s ;\~ s ~ou o,) 'jef fiffee'\ Mi'\ufe s of fa Me? As a 'jraduafe dude"f ;" Car"e'ii e M.ell o'\' s DerarfMe"-1 of CheMi<-a/ ('\Ji'\eeri'\J, ~ou "a" rerforM 'jrou'\dbreah'\J re s eare,h i'\ bioe'\Ji'\eeri'\J, e'\uiro"heMi<-af e'\Ji'\eeri'\J, pro e, e ss s ~deMs '"-Ji"-eeri'\'j, so{id dafe Maferia{ s, or 'OMf f e)( ff ui d s e'\Ji'\eeri'\J -1\'\d be Me'\fored b1 our 'o'\feMf orar1 fa {, ulf1 who haue Made resear"h a fi"-e ad. .. : -~ . .. : : .. .. f' : ~~OJ .. '~ .-; Carriegi~: : Mellon >. ~ .. .. ... .... ; ..... : .. '.. l --~;\ ... ; -~...... .. .. . for i'\forMafio'v rl e;),e wrife: \Jiredor of ~raduafe -1\dMi ss io'\ s DerarfMe'\f of CheM i'al ('\Ji'\eeri'\J Car"-e'jie M_efl o'\ U '\ iu enif1 ? i H sb ur'jh, ?A 15zu-J
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CASE WESTERN RESERVE UNIVERSITY 354 M.S. and Ph.D. Programs in Chemical Engineering FACULTY Stuart Adler John Angus Colman Brosilow Robert Edwards Donald Feke Nelson Gardner Howard Greene Uziel Landau Chung-Chiun Liu J. Adin Mann Philip Morrison Syed Qutubuddin Robert Savinell Students i n t h e D epar t me n t of C h em i cal Engineering are invo l ved in state of the-art r e search. H ere, two students make adjustments to a co mponent of a prototype fuel cell Research Opportunities Low Pressure Growth of Diamonds Process Control Colloidal Phenomena and Microemulsion s Electrochemical Engineering Biomedical Sensor s Synthesis of Electronic Material Polymers and Interfacial Phenomena Fuel Cells Catalysis and Reactor Design Separation Proce ss e s Interfacial Tran s port and Liquid Cry s tal s In Situ Diagno s tic s For more information on Graduate Research, Admission and Financial Aid contact: G ra du a t e Coo rdin a t or D e p art m e n t of C h emica l E n g in ee r i n g Case Wes t e rn R ese r ve U ni ve r sity 10900 E u c l i d A ve nu e Cl eve l an d Oh io 44 1 067217 or see our home page at http : // c h e m e cw ru .e du .,,~ aiiiiiiii: :iiiiiiila CWRU C h emical Engineering Education

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Opportunities for G raduate Stud y in Chemical Engineering at the UNIVERSITY OF CINCINNATI M.S. and Ph.D. Degrees in Chemical Engineering Faculty Amy Ciric Joel Fried Rakesh Govind David Greenberg Vadim Guliants Daniel Hershey Sun-Tak Hwang Robert Jenkins Yuen-Koh Kao Soon-J ai Khang Y. S. Lin Neville Pinto Sotiris Pratsinis Peter Smirniotis Finan cial Aid Available The University of Cincinnati is committed to a policy of non-discrimination in awa r ding financial aid Fo r A dmi ss i o n Inf o rm a ti o n Dir ec tor Graduate Studie s Departme n t of Chemical Engi n eering PO B ox 210171 University of Cinc inn ati Cincinnati Ohio 45221-0171 em ail: char@a l pha che uc edu Fa/11999 The faculty and students in the D epartment of Chemical Engineering are engaged in a diverse ran ge of exc itin g research topics. A limited number of assistantships and tuition sc holarships are available to highly qualified applicants to the MS and PhD degree pr og ram s. Biot e chnolog y ( Bio s eparation s) Novel bioseparation t echniques, chromatography, affinity separations, biodegradation of toxic wastes, con.t roll ed drug delivery, two-phase flow sus pension rheology. C hemical Reaction Engineering and Heterogeneou s Catal ys i s Modeling and design of chemical reactors, deactivation of cat al ysts, flow patt e rn and mixing in chemical equipment, laser induced effects C oal Re s e a rch New technolog y for coal combust i on. power plant, desulfurization and denitritication. Material S y nthe s i s Manufacture of advanced ceramics, optica l fibers and pigments by aerosol pro cesses. Membran e S eparation s Membrane gas separations, membrane reactors, sensors and pr obes, pervaporation, dynamic simulation of membrane separato r s, membrane preparation and c hara c t e ri z tion.for pol ymeric and in.organi c materials inor ga ni c m em brane s. Particl e T e chnolog y Flocculation of liquid suspensions, granu lati on. of fine powders, g rindin g of agglomerate particles. Pol y m e r s Th e rmod y nami cs, polymer blends and com posit es, hi g h-t e mperature polymers h ydroge ls, rheolog y, co mputation.al pol y mer science. Proce ss S y nthe s i s Computer-aided design methodologies, design for waste minimi z ation, design for dynamic stability, separation system syn th esis. 355

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Graduate Study in Chemical Engineering at Clarkson University M.S., M.ENG., AND Ph.D. PROGRAMS Teaching and Research Assistantships ava i lable t o M.S. and Ph D. students RESEARCH AREAS: Chemical-mechanical polishing Computer-aided design Corrosion and electrochemical engineering DNS of turbulence Mass transfer Materials proce ssi ng at low and high g Membrane separa tion s Surface and interfacial phenomena Transport phenomena For information, write to: Dr. Gregory A. Campbell D ean of Engineering Clarkson University PO Box 5700 Potsdam NY 13699-5700 315-2687929 Fax : 315-268-3841 E-mail: schofeng@agent.clarkson.edu World Wide Web: http://www.clarkson.edu/ ~chengweb/ .__ ____ Clarkson University is a nondi sc riminator y, affi rmativ e action equa l opportun it y educa tor and e mpl oyer. ____ _, 356 Chemical Engineering Education

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Clemson is a land-grant institution with an enrollment of more than 16.500 students including 3 800 graduate students The 1 400-acre main campus is located in the foothills of the Blue Ridge Mountains. on the shores of Lake Hartwell. midway between Atlanta. Ga .. and Charlotte. N C. The Faculty Charles H Barron Jr (D Sc University of V i rg i n i a ) David A Bruce (Ph D. Georgia Institute of Technology) Dan D Edie (Ph D University of Virginia) Special opportunities: Students can participate in the department's M.S Industrial Res i denc y Program which combines on campus course work with practical work assignments in industry. Students can conduct their thesis research under j o i nt faculty and industrial supervision Research Areas Bioseparations Catalysis Charles H Gooding (Ph.D. North Carolina State University) James M Haile (Ph D ., University of Florida) Engineering Fibers & Films lnterfacial Engineering Membrane Separations Molecular Dynamics Polymers & Composites Rheology Graham M Harrison (Ph.D ., University of California Santa Barbara) Douglas E Hirt (Ph D. Princeton University) Scott M Husson (Ph D. University of California Berkeley) S Michael Kilbey II (Ph D. University of M i nnesota) Stephen S Melsheimer (Ph D ., Tulane University) Amod A Ogale (Ph D University of Dela w are) Richard W. Rice (Ph D ., Yale University) Mark C Thies (Ph D University of Delaware) Supercr i tical Fluids Water Remediation Much of the research in polymers and compos ites is conducted in the Center for Advanced Engineering Fibers and Films, which is funded by the National Science Foundation and indus trial partners. Programs lead to the M S. and Ph D degrees For more information contact: Graduate Coordinator Depart ment of Chemical Engineering Clemson University Box 340909 Clemson, SC 29634-0909, Telephone 864/656-3055, Email address : che@ces.clemson edu Visit our Web site at www.ces clemson.edu CLEMSON UNIVERSITY

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Cleveland State University Graduate Studies in Chemical and Applied Biomedical Engineering Engineering Degr ,.__,e=e=s~---M.Sc. D.Eng. D.Eng. Chemical Engineering Applied Biomedical Engineering Chemical Engineering CSU Faculty A Annapragada (University of Michigan) J.M. Belovich (University of Michigan) G. Chatzimavroudis (Georgia Institute of Technology) G.A. Coulman (Case Western Reserve University) R.P. Elliott (Illinois Institute of Technology) J.E. Gatica (State University of New York at Buffalo) B. Ghorashi (Ohio State University) D.B. Shah (Michigan State University) 0. Talu (Arizona State University) S.N. Tewari (Purdue University) S. Ungarala (Michigan Technological University) CCF Collaborating Faculty J. Frederick Cornhill (University of Oxford U.K.) A. Courtney (Harvard University/Harvard MIT) B. Davis (Pennsy l vania State University) M. Grabiner (University of Illinois) G. Lockwood (University of Toronto Canada) C. McDevitt (University of London U.K.) W. Smith (Cleveland State University) A van den Bogert (University of Utrecht The Netherlands) I. Vesely (University of Western Ontario Canada) For more information. write to: Fenn College has more than 75 years of experience in providing outstanding engineering education. Graduate Studies in Chemical and Applied Biomedical En gineering at Cleveland State University's (CSU's) Fenn Col lege of Engineering offers a wealth of opportunity in a stimulating environment. Research opportunities are available in collaboration with the Biomedical Engi n eering Department of the renowned Cleveland Clinic Foundation (CCF), Cleveland's Advanced Manufacturing Center, local and national industry, and Federal agen cies, to name a few. Assistantships and Tuition Fee Waivers are avail able on a competitive basis for qualified students Cleveland State University has 18,000 students enrolled in its aca demic programs. It is located in the center of the city of Cleveland, with many outstanding cultural and recreational opportunities nearby RESEARCH AREAS Adsorption Processes Agile Manufacturing Artificial Heart Valves Biomechanics Bioreactor Design Bioseparations Blood Flow Computational Fluid Dynamics and Combustion Drug De)jvery Systems Environmental Pollution Control Materials Synthesis and Processing Medical Imaging MEMS Technology Orthopedic Devices Process Modeling and Control Reaction Engineering Graduate Program Coordinator Department of Chemical Engineering Cleveland State University Cleveland, OH 44115 Surface Phenomena and Mass Transfer Thermodynamics and Fluid Phase Equilibrium Tissue Engineering Telephone: 216-687-2569 Tribology E-mail: chemabe@csvax.egr.csuohio.edu Ventricular Assist Devices http://www.csuohio.edu/chemical_ engineering/ Zeolites : Synthesis, Adsorption and Diffusion Assistantships and Tuition/Fee Waivers are available on a competitive basis for qualified students. 358 Chemical Engin ee ring Education

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University of Colorado at Boulder The Boulder campus ha s a controlled enrollment of 20,000 undergraduate s and 5 ,00 0 graduate students. The beautiful 600acre camp u s ha s over 160 buildings of ro u g hc ut sandstone with red-tile roofs. The exce ll e nt ed u cationa l opportunities and beautiful location attract outstanding s tudent s from every part of the United State s and 75 countries. The University of Colorado h as its main campus located in Boulder a n attractive community of 90 ,000 people l ocated at the ba se of the Rocky Mountains Boulder ha s over 300 days of s un s hine per year, with relatively mild and dry seasons. The city is an active and innovative town that provide s a rich array of recreational and c ultural activities .-----Department of Chemical Engineering Faculty and Research Interests Kristi S. Anseth Pol ymers, Biomat e rials Victor H. Barocas Biom echanics, Bi omedical Eng. Fluid Mechanics Christopher N. Bowman P olymers, Membrane Materials David E. Clough Pro cess Control, Applied Statistics Robert H. Davis Fluid Mechanics, Biot echnology, Membranes John L. Falconer Catalysis, Zeolite Membranes R. Igor Gamow Bioph ysics, Hi gh Altitude Ph ysiology, Human P eifo nnan ce Christine M. Hrenya Fluid Mechanics, Fluidization Granular Systems Dkinakar S. Kompala Biopro cess Engineering Animal Cell Cultures William B. Krantz Membranes, Geophysics Global Climate Change Richard D. Noble Membranes Separations W. Fred Ramirez Pr ocess Control, Biote c hnolog y Theodore W. Randolph Bi otechnology, Supercritical Fluids Robert L. Sani Transport Ph enomena, Applied Mathematics Paul W. Todd Biot ec hnolo gy, Bioseparations Low Gravity Alan W. Weimer Ceramic Materials, R eaction Engineering Graduate students ma y participate in the interdis c iplinary Biote c hnolog y Training Program and the interdisciplinary NSF Indu stry/University Cooperative Research Center for M e mbrane Applied Science and Technology Fall 1999 For information and application Graduate Admissions Committee Department of Chemical Engineering University of Colorado Boulder CO 80309 -0 424 Phone (303) 492-747 1 Fax (303) 492-4341 E-mail chemeng@spot.co l orado.ed u www.http//spot.colorado.edu/~chemeng/Home.html 359

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360 COLORADO SCHOOL OF MINES THE FA CUL TY AND THEIR RESEARCH R. M. BAL D WIN, Profe sso r and Head; Ph D ., Colorado School of Mine s. Fuels sc i ence and catalys i s, zeo lites computational chem i stry. A. L. B UNGE, Professor; Ph.D., University of California, Berkele y. Absorption of chemicals i11 skin phannacokinetic modeling risk assessment. J R. D OR GAN, Associate Profes so r ; Ph.D ., University of California, Berkele y. Pol y m er science and e n g in ee rin g, biomaterials molecular simulations. J F. ELY, Professor; Ph.D., Indiana Univers i ty. Mol ec ular thermod y nami cs and transport prop e rti es of fluids, parallel co mputation J H. GA R Y, Professor Emeritus; Ph.D ., University of Florida. Petroleum r efinery processing ope rati o n s J O G O L D EN, Professor Emeritus ; Ph D. Iowa State University. Hazardous was te processing, fluidization e n ginee rin g, inci11 era ti o11. M S G RABO SKI, Research Profe sso r; Ph.D ., Pennsylvania State University. Fuel s synthesis and evalua ti o n e11gi 11e t ech n ology, alternate fuels A J. KID NA Y, Professor Emerit u s; D Sc Colorado School of Mines. Thermodynami c properties of gases and liquids, vapor-liquid equilibria. D .W.M. MA RR Assistant Profes so r; Ph.D. Stanford. l 11terfa c ial statistical m ec hani cs, co mpl ex fluids. R .L. McC OR M I CK, Research As sis tant Professor ; Ph.D ., Wyoming. Catalysis infuel synthesis.fuel ce ll s, low e missions fuels for int e rnal co mbustion e n g in es, i on co ndu cti n g solid cata l ys t s and electrolytes reactor design andfluidizatio11. J .T. M c KINN O N, Associate Professor ; Ph.D. Massachusetts In s titute of Technology. Effects of microgravity high temperature gas phase c h e mi cal kinetics co mbu st i o n hazardous waste destruction R L. MILLE R Professor ; Ph.D ., Colorado School of Mines Int e rdi sc iplinary c urriculum development, innovative p e dagogies, measures of intellectual develop m e nt, ps yc hologi c al theori es of l ea rning multiphase fluid mechani cs M. S. SELIM, Professor; Ph D ., Iowa State University. Heat and mass tran sfer, se dim e ntati o n and diffusion of c olloidal suspensions, inkjet printin g, syn th esis of nano-si ze magneti c particles for colo r toner and laserjet printin g applications mod e lin g of c ra ck in g furnaces and simulation of et h ylene plants. E. D SL O AN, JR. Weaver Di st inguished Profe sso r ; Ph.D. Clemson University. Natural gas h y drates phase eq uilibria ed u cat ion methods r esea r ch J D WAY, Associate Profe sso r; Ph.D University of Co l orado Novel separa tion pro cesses, membrane science and te c hnolog y, m e mbrane rea c tor s, ceramic and m e tal m e mbran es. C. A. W OLD EN, Assistant Professor Ph D., Massachusetts Institute of Techno l ogy. Electronic mat e rials processing, gas-solid r eact ion dynamics. D T. WU, Assistant Professor; Ph.D. University of California, Berkeley Pol ymers, powders theory and simu lati o n of complex fluids and mat erials, phase equilibria, co ntroll e d self-assembly. V. F. YESAVAGE, Profe ssor; Ph D. University of Michigan. Vapor liquid eq uilibrium equations of state for highly non-ideal systems, pro cess simulation, environmental e ngin ee rin g, gasliquid reactions. /"or further program i11/or111atio11 a11d lo ap11ly 011-/111c. \l'l' our wch page, at \I \I \I .mines.Niu 01 H rite lo l"lumil-al Engineering I>epartmlnt Colorado Sd10ol of :\lines (;olden. < o XO~O I Chemical Engineering Education

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Fa/11999 -,tate University M.S. and Ph.D. programs in chemical engineering RESEARCH IN ... Advanced Process Control Biochemical Engineering Biofuels Catalysis Chemical Thermodynamics Chemical Vapor Deposition Computational Fluid Dynamics Environmental Biotechnology Environmental Engineering Polymeric Materials Solar Cooling Systems Semiconductor Processing Thin Films Water Quality Monitoring FINANCIAL AID AVAILABLE Teaching and re se arch assistantships paying a monthly sti pend plus tuition reimbursement. For applications and further infonnation, write Department of Chemjcal and Bioresource Engineering Colorado State Uruversity Fort Collins, CO 80523-1370 CSU is lo cated in Fort Collins, a pleasant commu nity of 100 000 people w ith the spirit of the West the vi tali ty of a g r owing m e tropolitan area, and the friendliness of a sma ll town. Fort Collins is located about 65 miles north of D enve r and is adjacent to the foothills of the R ocky Mountains. Th e cli mat e is exce ll en t wit h 300 s unn y da ys per yea r, mild t e peratures, and l ow humidi ty. Opportunities for hik in g, bikin g, c ampin g, boatin g, fishing, and skiing abound in th e immediate and nearby areas. The campus is within e as y walking or biking distance of the to wn's s hoppin g areas and it s C e nter for the Perfonnin g Arts. FACULTY Laurence A. Belfiore, Ph.D. University of Wisconsin David S. Dandy, Ph.D. California Institute of Technology M. Nazmul Karim, Ph.D. University of Manchester Terry G. Lenz, Ph.D. Iowa State University James C. Linden, Ph.D. Iowa State University Jim C. Loftis, Ph.D. Colorado State University Carol M. McConica, Ph.D. Stanford University Vincent G. Murphy, Ph.D. University of Massachusetts Allen L. Rakow, Sc.D. Washington University Kenneth F. Reardon, Ph.D. California Institute of Technolog y Robert C. Ward, Ph.D. North Carolina State University Ranil Wickramasinghe, Ph.D. University of Minnesota 36 /

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Graduate Study lll Chemical Engineering M.S. and Ph.D. Program s for Scientists and Engineers FOR MORE INFORMATION Graduate Admission, 191 Auditorium Road U-3222 University of Connecticut Storrs, CT 06269-32 22 Tel. (860) 486-4020 362 UNIVERSITY OF CONNECTICUT FA CUL TY RESEARCH AREAS Luke E.K. Achenie Ph.D. Carnegie Mellon University Modeling and Optimization Molecular Design Artificial Intelligence Thomas F. Anderson Ph.D. University of California Berkeley Modeling of Separation Processes Fluid-Phase Equilibria James P. Bell Sc.D. Massachusetts Institute of Technology Structure-Property Relations in Polymers and Composites Adhesion Carroll 0. Bennett Professor Emeritus Ph.D., Yale University Catalysis Chemical Reaction Engineering Douglas J. Cooper Ph.D ., University of Colorado Process Modelinbg Monitoring and Control Robert W. Coughlin, Ph.D., Cornell University Biotechnology Biochemical and Environmental Engineering Catalysis Kinetics Separations Surface Science Michael B. Cutlip, Ph.D ., University of Colorado Kinetics and Catalysis Electrochemical Reaction Engineering Numerical Methods Anthony T. DiBenedetto University Professor Emeritus, Ph D. Univ of Wisconsin Composite Materials Mechanical Properties of Polymers Can Erkey, Ph D. Texas A&M University Supercritical Fluids Environmental Engineering Multicomponent Diffusion and Mass Transfer James M. Fenton Ph.D. University of Illinois, Urbana-Champaign Electrochemical and Environmental Engineering Mass Transfer Processes Electronic Mate rials, Energy Systems Suzanne (Schadel) Fenton, Ph.D. University of Illinois Computational Fluid Dynamics Turbulence Two-Phase Flow Robert J. Fisher, Ph.D. University of Delaware Biochemical / Biomedical Engineering and Environmental Biotechnology Joseph J. Helble Ph D. Massachusetts Institute of Technology Air Pollution, Aerosol Science Nanoscale Materials Synthesis and Characterization, Combus tion G. Michael Howard Professor Emeritus, Ph.D., University of Connecticut Process Systems Analysis and Modeling Process Safety Engineering Education Herbert E. Klei Professor Emeritus Ph.D. University of Connecticut Biochemical Engineering, Environmental Engineering Jeffrey T. Koberstein, Ph.D. University of Massachusetts Polymer Blends / Compatibilization Polymer Morphology Polymer Surface and Interfaces H. Russell Kunz, Ph.D ., Rensselaer Polytechnic Institute Fuel Cells Electrochemical Energy Systems Patrick T. Mather Ph.D. University of California, Santa Barbara Polymers : Microstructure and Rheology Liquid Crystallinity Inorganic-Organic Hybrids Montgomery T. Shaw Ph.D. Princeton University Polymer Rheology and Processing Polymer -s olution Thermodynamics Donald W. Sundstrom Professor Emeritus, Ph.D. University of Michigan Environmental Engineering Hazardous Wastes Biochemical Engineering Robert A. Weiss Ph.D. University of Massachusetts Polymer Structure-Property Relationships Ion-Containing and Liquid Crystal Polymers Poly mer Blends Thomas K. Wood Ph.D. North Carolina State University Microbiological Engineering, Bioremediation with Genetically-Engineered Bacteria Enzymatic Green Chemistry Biochemical Engineering Biocorrosion Chemical Engineering Education

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CORNELL U N I V 1 : R S I T Y Chc111ic11l E11gi11ccring At Cornell University, graduate st udents in chemical engineering have the flexibilit y to de s ign research program s that take full advantage of Cornell 's unique interdisciplinary environment and enable them to pur s ue individualized plans of st udy. Cornell graduate programs ma y draw upon the resources of many excellent depart ments and research centers such as the Biotechnology Center, the Cornell Supercomputing Facility and the Materials Science Center. Degrees granted include Master of Engineering Master of Science and Doctor of Philosophy. All Ph D. st udents are fully funded with tuition coverage and attractive s tipend s R ese ar c h A r e a s Advanced Materi a l s Processing Biochemic a l and Biomedical Engineering Fluid Dynamic s, Stability, and Rheology Molecular Thermodynamics and Computer Simulation Polymer Science and Engineering Reaction Engineering: Surface Science Kinetics, and Reactor Design Situated in the scenic Finger Lakes region of New York State th e Cornell campus is one of the most beautiful in the country. Students enjoy sailing, skiing, fishing hiking bi cyc ling, boating wine -tastin g, and man y other activities. For further information, write: Di sti n g u is h e d F a c ul ty A Brad Anton Paulette Clancy Claude Cohen T. Michael Duncan James R. Engstrom Fernando A. Escobedo Emmanuel P. Giannelis Peter Harriott Donald L. Koch Kelvin H Lee Leonard W. Lion Chri sto pher K. Ober William L. Olbricht Ferdinand Rodriguez W. Mark Saltzman Michael L. Shuler t, t Paul H. Steen 1 m e mb er National Academy of Engine e rin g t m e mb e r, American Academy of Arts & Science Director of Graduate Studie s, School of Chemical Engineering, Cornell University, 120 Olin Hall Ithaca, NY 14853-5201, e-mail: DGS @ CHEME.CORNELL.EDU or "v i s it our World Wide Web se rver at: http ://www.c heme .co rnell.edu Fall 1999 363

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Graduate Study & Research in Chemical Engineering at Dartmouth's Thayer School of Engineering 3 64 The Thayer School of Engineering at Dartmouth College offers an ABET-accredited B.E. degree, as well as M.S., Masters of Engineering Management, and Ph.D. degrees. Just like real world problems our degrees and our graduates are not artificially divided into disciplines. Within thi s interdisciplinary framework, the number of faculty and the breadth of externally-funded research activities and coursework involving c h emical engineering are substantial. Dartmouth and its affiliated professional schools offer Ph D. degrees in the full range of science disciplines as well as M D and MBA degrees. The Upper Connecticut Valley region is an international destination for vacationers and recreation enthusiasts, offering a four season envi r onment and beautiful rural s urr oundings along with easy access to major metropolitan areas (2 h ours to Boston). Faculty & Research Areas Ian Baker ( Oxford) Structure/property relationships of materials, electron microscopy John Collier (Dartmouth) Orthopaedic prostheses, implant/host interfaces Alvin Converse (Delaware) Kinetics & reactor design, enzymatic hydrolysis of cellulose Benoit Cushman-Roisin (Florida State) Numerical modeling of environmental fluid dynamics Harold Frost (Harvard) Microslructural evolution, deformation, and fracture of materials Tillman Gerngross (Tec hnical University of Vienna) Microbial polymer synthesis, metabolic engineering, fermentation technology Urs ula Gibson (Co rnell) Thin film deposition, optical materials Francis Kennedy (RPI) Tribology, surface mechanics Lee Lynd (Dartmouth) Bioma ss processing, pathway engineering, react or & process design Christopher E. Naimie (Dartmouth) Environmental fluid dynamics modeling coastal ocean/estuarine systems Victor Petrenko (USSR Academy of Science) Physical c hemistry of ice Jeffrey A. Proehl (U. Washington) Numerical ocean modeling; flow stability, magnetohydrodynamics Paul E. Queneau (Delft) Mineral engineering, extractive metallurgy process design Horst Richter (Stuttgart) Thermodynamics, multiphase flow, energy conversion, process design Erland Schulson (British Columbia) Physical metallurgy of metals and alloys Bengt Sonnerup (Cornell) Magnetohydrodynamics, fluid mechanics Graham Wallis (Cambridge) Two-phase flow, thermodynamic s, transport phenomena, energy Charles E. Wyman (Princeton) Biomas s pretreatment & hydrolysis, cellulase synthesis & kinetics, process design & evaluation For further information, please contact: Chemical Engineering Graduate Advisor Thayer School of Engineering Dartmouth College Hanover, NH 03755 http://thayer.dartmouth.edu/thayer/research/biotech.html Ch e mi c al Engineering Edu c ation

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University of Delaware Faculty Mark A. Barteau Surface Chemistry, Catalysis, Kinetics Spectro sco py Scanning Prob e Microscopies Materials Antony N. Beris Fluid Me c h a ni cs, Viscoelasticity Nonequilibrium Thermodynamics, N um erica l Method s Parallel Computing Douglas J. Buttrey Oxides Thermodynamics Crystal Growth, Structure Catalysis, Superconductor s Costel D. Denson Materials, P olyme r s, Composites Transport Separations Prasad S. Dhurjati Bi otechno l ogy, Bioreactors, Modelin g, Bioin fo rmati cs, Fault Dia g no sis, Expert Systems Francis J. Doyle Pro cess Control Nonlinear D ynamics, Biomedical, P o lymer s Henry C. Foley Nanoporous Membrane Materials Separations Kinetics, Catalysis www.che.udel.edu/ The Department of Chemical Engineering The University of Delaware offers M.Ch.E. and Ph.D. degrees in Chemical Engineering. Both degrees involve research and course work in engineering and related sciences. The Delaware tradition is one of strong interdisciplinary research on both fundamental and applied problems. Marylin C. Huff Catalysis Reaction Engineering Chemical Vapor Deposition Eric W. Kaler Co ll oids Surfactant s, Polymers Th e rm odynamics Bi o m o l ecu l es Abraham M. Lenhoff Protein Biophysic s, Separations Colloids Thermodynamics and Tr a n s port Raul F. Lobo Absorption Ca t alysis Zeolites Microporou s Materials Inorganic Material s Synthesi s Roy L. McCullough Composite and P olymer Structure-Property R e l ationships, Technical Management and Technolo gy Assessment Jon H. Olson R eaction Engineering, Aerosols Population-Balance Models Anne S. Robinson Bi oc h e mi cal Engineering Bi omo l ecu l e Interaction s, Bioreactor Control, Molecular Engineering Cellular E n gineering T.W. Fraser Russell Ph otovo lt aics Mu ltiph ase Fluid Mechanic s Stanley I. Sandler Thermodynamics, Statistical Mechanics, Computational Chemistry Environment Separations Bioseparations Jerold M. Schultz P o l ymers Crystallization Scattering, Microscopy, Fibers, Structure Annette D. Shine Electrorheo l ogy, Polymer P rocessing, Rheology Supercritical Fluids Norman J. Wagner Colloid and P o lym er Science, Rheology Statistical Mechanics of Complex Fl uid s Thermodynamics B iopo l ymers Richard P. Wool Polymers Composites Adhesion Interfaces, Materials from R enewab l e R esources, Biodegradable Plastic s Andrew L. Zydney Membranes Bi oseparations, Artificial Organs Biomedical Engineering P rotei n s Ultrafiltration Emeritus Faculty Kenneth B. Bischoff U n i d el Pro fessor of Bi ome di cal and Chemica l Engineering Arthur B. Metzner H. Fletcher B rown Pr ofessor of Chemical Engi n eeri n g

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51, ECOLE POLYTECHNIOUE MONTREAL Legenientie .. .. .. .... SDl1S[!'!!; ... ... T'f!S F A C u L Pierre Bataille, Professor, Ph D (Montreal} T Polymer izat ion Processes Physical and Mechanical Properties of Composites E-mail: pierre bataille @ mail.polymtl.ca Michael D. Buschmann, Associate Professor, P.Eng Ph .D (MIT} Tissue Engineering Biomechanics Cartilage Physiology Arthritis Research E-mail: mike@grbb polymtl.ca Pierre J. Carreau Professor, P.Eng ., Ph.D. (Wisconsin, Madison) Head : Center on Applied Research on Polymers (URL : www.crasp.polymtl.ca) Rheological Properties of Suspensions in Polymers and Polymer Blends Modeling of Polymer Processing Mixing of Non-Newtonian Fluids E-mail : pierre.carreau @ mail.polymtl.ca Jamal Chaouki, Professor, Ph.D (Polytechnique) Head: Environmental and Biotechnological Process Engineering Research Centre (URL : www biopro.polymtl.ca) Chemical Reaction Engineering Multiphase Reactors Particle Tracking Tomography Fluidization of Powders E-mail : chaouki@biopro.polymtl.ca Claude Chavarie, Professor, P.Eng Ph D (McGill} Dean of Research Bioreactor Engineering Animal Cell Culture Plant Cell Culture E-mail: claude.chavarie @ mail.polymtl.ca Louise Deschenes Research Associate Ph D. (INRS-Eau} Co-Chair NSERC Industrial Chair on Site Bioremediation Intrinsic Soil Bioremediation Underground Water Treatment Environmental Microbiology Ecoto xico logical Risk Assessment E-mail : deschenes@biopro.polymtl.ca Basil D. Favis Professor Ph D (McGill} Processing-Morphology Property Relationships in Polymer Blends Interface Characterization in Multiphase Systems E-mail: favis @ chimie polymtl.ca Miroslav Grmela, Senior Research Associate, Ph D (Prague} Thermodynamics of Irreversible Processes Molecular Rheological Modelling Flow of Viscoelastic Fluids Polymer Processing E-mail : grmela@chimie.polymtl.ca Christophe Guy, Professor, P.Eng Ph.D (Polytechnique} Department Chairman Natural Gas Technolog ies Odors Treatment of Solid Wastes and Emissions Multiphase Reactors E-mail : christophe.guy@mail.polymtl.ca Mario Jolicoeur Assistant Professor, P.Eng Ph D (Polytechnique} Bioreactor Engineering Mycorrhizal Fungi-Plant Symbiosis Metabolic Engineering Pharmaceutical Engineering E-mail : mario.jolicoeur @ polymtl.ca Danilo Klvana, Professor Ph.D (Prague} Head : Gas Technology Research Group (URL: www.polymtl.ca/udr7.htm} Catalytic Gas-Solid Hydrogenation Storage of Methane Catalytic Combustion Preparation of Catalysts and Electrocatalysts E-mail : danilo.klvana@mail.polymtl.ca Pierre G Lafleur Professor, P.Eng., Ph D (McGill} Assistant Dean Academic Polymer Processing Computer-Aided Design Engineering and Manufacturing E-mail: pierre.l afle ur @ mail.polymtl.ca Robert Legros Professor, P.Eng Ph D (Surrey} Solid Waste Incineration Fluidized-Bed Combustion Fluidized-Bed Drying Spouted Bed Hydrodynamics Expanded Bed Bioseparation E-mail : robert legro s @ ma il.po lymtl.ca Jean R. Paris Professor, P.Eng., Ph D (Northweste rn} Head: Research Group on Pulp and Paper Science and Engineering (URL: www gresip.polymtl.ca} Process Design and Analys is Process Integration System Closure in Mechanical and Chemical Pulp Mills Pinch Analysis Process Simulation E-ma i l : jparis @ gpapetier.polymtl.ca Michel Perrier Professor, ing., Ph D (McGill} Dynamics and Control of Chemical and Biochemical Reactors Dynam ics and Control of Pulp and Paper Processes (URL : www.urcpc.polymtl ca/-perrier} E mail: michel.perri er @ urcpc.polymtl.ca Rejean Samson, Professor, Ph D. (Laval} NSERC Industrial Chair for Site Bioremediation ( URL : www biopro polymtl.ca /bioremediation) Environmental Biotechnology Waste Treatment Air Pollution E-mail : samson @ biopro polymtl.ca Henry P. Schreiber, Senior Research Associate, Ph D (Toronto} Composite Materials Surface and Interface Polyme r Propertie s Microwave Pla sma Surface Treatment E-mail : schreiber @ crasp polymtl.ca Amine Selmani, Associate Professor Ph.D (Montreal} Biocompatible Materials Tissue Engineering E-mail: selmani @ chimie polymtl.ca Philippe Tanguy Professor P.Eng. Ph.D (Laval} NSERC/Paprican Indust r ial Chair on Paper Coating (URL: www urpei.polymtl.ca} Mixing of Rheologically Complex Flu ids Coating Processes Surface Treatment of Paper E-mail : tanguy @ urpei.polymtl.ca For furth e r mf _Q rlll ~ E c m, c Q_n!act u s __ ___ __ ____ __ __ _________ _ ___ Dep,1rtrne1,t of Chernrcal rr1giner11119 Frnle Polytech111que, PO Box 6079 Station Centre-ville, Montreal, Quebec, Canada H3C 3A7 Phone 1 ',14 340 461 l, Fax 1 5 1 4 340 4159, E ma rl chem i cal eng r nee rr ng(lorna r l polyrntl ca Visit our website at: www.gch polymtl ca

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Chemical Engineering at the University of Florida Fall 1999 Graduate Study Leading to the MS and PhD Applications T IM ANDERSON semiconductor processing thermody n amics SEYMOUR S BLOCK biotechnology OSCAR D. CR/SALLE process control semiconductors pulp and paper polymer processi n g R I CHARD 8. DICKINSON cellular engineering, biomedical engineering ARTHUR L. FRICKE polymers pulp & paper characterization GAR HOFLUND catalysis surface science semiconductors LEWIS JOHNS transport phenomena applied mathe m atics DALE KIRMSE computer-aided design, process control TONY LADD statistical mechanics fluid mechanics biomechanics ATUL NA RANG kinetics of microbial growth environmental bioengi n eeri n g RANGA NARA YANAN transport phenomena applied mathematics low gravity proc e sses MARKE ORAZEM el e ctroch e mical engi n e e ri ng CHANG WON PARK fluid mechanics polymer proc e s s ing RAJ RAJAGOPALAN colloid physics particle science FAN REN semiconductor device fabrication and characterization DINESH 0 SHAH surface sciences biomedical engineering SPYROS SVORONOS wastewater treatment particle separations process co nt rol JASON F WEA VER heterogeneous catalysis, dynamics of solid interactions, microelec tr o n ics For more information please write : Graduat e Admi ss ion s Coordinator Department of Chemic a l Engineering University of Florida P O Box 1 1 6005 Gainesvi ll e Florida 3261 1 -6005 Phone (3 52 ) 392 0881 E-mail c h e mi c al @ en g. ufl.edu Website http: // www che ufl edu 367

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Florida A&M UniversityFlorida State Universit} 1:fl.~1 College of Engineering ~ :::= ~ === J Graduate Studies and Research Leading to the .. _,~ ~ 2 MS d PhD Ch IE v' '" 9 an 1n em1ca ng1neer1ng 851 For Information Write: Director of Graduate Studies Department of Chemical Engineering FAMU-FSU College of Engineering 2525 Pottsdamer St. Tallahassee FL 32310 850-410-6151 / 850-410-6150 FAX http://www.eng.fsu.edu/cheme Faculty Rufina Alamo Bruce R. Locke Complutense University of Madrid North Carolina State Pedro Arce Srinivas Palanki Purdue University Ravindran Chella University of Massachusetts Wright Finney Florida State University Stephen J. Gibbs University of Wisconsin Egwu Kalu Texas A&M University University of Michigan Michael H. Peters Ohio State University John C. Telotte University of Florida Jorge Vinals University of Barcelona G. Dale Wesson Michigan State Universif) Research Areas Advanced Materials Biomedical Engineerini Composites Polymers Mixing Drug transport Process Control Cell / Tissue Eng. and Optimization Lung Dynamics MRI Batch and Nonlinear Processes Transport Processes Reaction Engineering Porous Media Pattern Corona reactions, Electrochemcial Formation and Chaos and Polymer Engineering Multiphase Flow MRI Bio-engineering Bioseparations Fermentation Affiliated Programs National High Magnetic Field Laboratory Computational Science and Engineering Program Geophysical Fluids Dynamics Institute Institute for Molecular Biophysics Materials Research and Technology Center

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Graduate Studies in Chemical Engineering Master of Science and Doctor of Philosophy Join a sma ll v ibrant campus on Florid a s Space Coast to reach your full academic a nd profes s ional potential. Florida Tech the o nl y independent sc ientific and technological university in the So u th east, h as grown to become a uni ve rsity of international standi n g Faculty P A. Jennin gs Ph D JR. Brenn er, Ph D D R Mason Ph D M E. Pozo de F e rn a nd ez Ph D M.R. Shaffer Ph.D M M. Tomadakis, Ph.D J.E. Whitlow Ph.D Research Partners NASA / Kennedy Space Center Florida So l ar Energy Center Energy Partners Florida Institute of Phosphate Research Florida Department of Energy Harris Semiconductor For more information contact Florida Institute of Technology Chemical Engineering Program College of Engineering Divi s ion of Engine e rin g Sciences 150 W es t U niv e r s ity B o ul eva rd Melbourne Florida 32901-6975 ( 4 07) 674-8068 GA-298-698 Graduate Student Assistantships/ Tuition Remission available Research Interests Spacecraft Technology Semiconductor Manufacturing Alternative Energy Sources Materials Science Environmental Engineering Expert Systems

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Georgia Dml@UDUOJJU@ @UTechml@D@~W School of Chemical Engineering The Faculty and Their Research A.S. Abhiraman P o l yme r sc i e n ce a nd e n g in ee rin g Pradeep K. Agrawal H e t e r oge n eo u s ca t a l ys i s s urf a c e c h e mi s tr y, r eac ti o n k in e ti cs YamanArkun Pro cess d es i g n a nd co ntrol s p o ut e d b e d reac t o r s Sue Ann Bidstrup Allen Mi croe l ectro ni cs p o l y m e r proc ess in g Charles A. Eckert M o l ec ul a r th e rmod y n a mi cs, c h e mi ca l kin e ti cs, se p ara ti o n s William R. Ernst R eac t or d es i g n ca t a l ys i s Larr y J. Forne y Mech a ni cs o f ae ro so l s bu oya nt plum es a nd j e t s Dennis W. Hess Mi croe l ec tr o ni cs p rocess in g thin film sc i e n ce a nd t ec hn o lo gy, pl as m a p rocesses Clifford Henderson Mi croe l ec t ro ni cs p rocess in g p a tt e rnin g im ag in g m a t e r ia l s thin film s 370 Jeffer y S. Hsieh Pulp a nd p a p e r Christopher Jones Ca tal ys t de ve l o pm e nt for p o l y m e r sy nth es i s, o r ga n o m eta lli c c h e mi s tr y Paul A. Kohl Ph o t oc h e mic a l pro cess in g, c h e mi ca l va p o r d e p os iti o n Charles L. Liotta Sy nth es i s and p ro p e rti es o f p o l y m e ri c m a t e rial s co mput e r m o d e lin g of c h e mi ca l pro cesses Peter J. Ludovice M o le c ul ar m o d e bn g of s y nth e ti c and bi o l ogica l m acro m o l ec ul es Carson Meredith Co ll o id and p o l y mer sc ien ce a nd t ec hn o l ogy r e l a t e d t o thin film s a nd n a not ec hnol ogy Michael J. Matteson Aeroco ll o id a l sys t e m s, i n te r facia l ph e n o m e n a, fin ep a rti cle t ec hn o l ogy Jeffrey F. Morris Fluid m ec h a ni cs, t wo-p h ase fl ows co mpl ex fluid s John D. Muzzy P o l y m e r e n g in ee rin g e n e r gy co n se r va ti o n eco n o mi c s Robert M Nerem Bi o m ec h a ni cs, m a m ma li a n ce ll s tru c tur es Gary W. Poehlein Emul s i o n p o l y m er i za ti o n l a t ex t ec hnol ogy Ma rk R. Prausnitz Bi oe n g in ee rin g dru g d e li ve r y ti ss u e p e rm ea bili za ti on Matthew J. Realff Optim a l p roce ss desig n a n d sc h e dulin g Mary E. Rezac M e mbran e s ep ara ti o n s, m ass tra n sfe r Ronnie S. Roberts Bi oc hemi ca l e n g in ee rin g m ass tr a n s fer r eac t o r d es i g n Ronald W Rous s eau S e p ara t io n proces s e s, crys t a lli za ti o n Athanassios Sambani s Bi oc h e mi ca l e n g in ee rin g, mi cro bi a l a nd a nim a l c e ll c ultur es Robert J Samuels P o lym e r sc i e n ce a nd e n g in ee rin g F. Joseph Sc hor k R eac tor e n g in eer in g, p rocess co ntr o l po l y meri za ti o n r eac t o r d y n a m ics A. H. Peter Skelland M ass tr a n sfe r ex t rac ti o n mi x in g n o nNew t o ni a n fl ow Jude T Sommerfeld P rocess d es i g n a nd si mul a ti o n Arnold F. Stancell M e m b ran es p o l y m e r s, p rocess eco n o mi cs Daniel W. Tedder P rocess sy nth es i s a nd s imul a ti o n c h e mi ca l s e p a rati o n was t e m a n age m e nt r eso ur ce recove r y Am y n S. Teja Th e rm o d y n a mi c a nd tr a n spor t prope rt ies ph as e eq uili br i a s up e r c riti ca l ex t rac t io n Mark G White Ca t a l ys i s kin e ti cs reacto r d es i gn Timoth y M. Wick Ti ss u e e n g in ee rin g bi o r eac t o r d es i gn ce ll -ce ll int erac t io n s bi o flu i d d yna mi cs Jack Winnick E l ec t roc h e mi ca l e n g in eer in g th e rm o d y n a mi cs air p o lluti o n c ont ro l Ajit P. Yoganathan Bi o fluid d y n a mi cs r h eo l ogy tra n spor t ph e n o m e n a For mor e information pl e ase c onta ct Dr. Ronald W. Rousseau Chair School of Chemical Engineering Georgia Institute of Technology Atlanta, Georgia 30332-0100 or visit us atwww.chemse.gatech edu Ch e m i c al En g in ee r in g Ed u c ation

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Fall 1999 UNIVERSITY of HOUSTON Faculty members: eal R. Amundson, Cullen Pro fessor of Chemical Engi neering Professor of Mathematics. Applied mathematics sys tem s with coupled reactions, and transport phenomena Vemuri Balakotaiah, Professor. Oxid a tion of wastes in s upercritical water reaction-induced flow maldistribution s in packed beds pattern formation a nd chemical turbulence, transport coefficients in multipha se sys tem s Michael J. Economides, Profe ssor. Petroleum engineer ing, petroleum produ ct i o n h y draulic fracture me c hanic s, we ll completions, reservoir s timulation, petroleum reser voir exploitation stra te g ie s. Demetre J. Economou Profe sso r. Electronic materials advanced ceramics, hi g h-temperature superconductors, thin films, plasma etching a nd pla sma-ass isted chemical va por deposition pla s ma rea c tor modelin g and di ag nostic s, ato mic lay er processing c hemi ca l vapor infiltration. Ernest J. Henle y, Profe sso r. Transdermal drug transport electrotherapy sys tem reliability Ramanan Krishnamoorti, Assistant Professor. Polymer sc ience with emphasis on under s tanding multipha se poly mer s tructure and dynami cs with s tudie s on well-controlled polymer blends block copo lymer s, and polymer layered s ilicate nanocomposites. Dan Luss, Cullen Profe ssor and Chairman. T e mp era tur e excursions in chemical reactors pattern formation in cata lyti c syste ms impro ved catalysts for trickle-bed reactors, sy nthe sis and processing of ceramic powder s. Kishore K. Mohanty, Associate Profe ssor. Fluid flow interfacial mechanics a nd multipha se transport through po rous media with applications in understanding containment transport, oil recovery and fabrication of composite materi als. Michael ikolaou Associte Professor. Computer-aided pro cess engineering with e mpha sis on process control. Theory and application in oil, c hemi cals, food and microelectron ic s industrie s. James T. Richard son, Profe ssor. Reduction kineti cs of supported nick el cataly s ts catalytic detoxification of chlori nated hydrocarb o n s, impro ved steam-reforming with novel foamed ceramic catalysts large-scale processing of s uper co nductor s. Fuel ce ll s and membrane reactors Frank M. Tiller, M.D. Anderson Professor of Chemical Engineering. Fluid/particle separation and processing, fil tration centr i fugation sed imentation expression, washing, drainage CAT-SCAN analysis of solid-liquid systems, op timization techniques. Richard C. Willson, Associate Professor. Molecular recog nition and c hrom atography, environme nt a l biotechnology. Frank L. Worley, Jr., Professor. Expert systems for pollu tion control and design urb a n/indu s trial pollution transport and diffusion, modeling of destruction of hazardou s waste by incineration. For additional information and an application package, write to Graduate Admi ss ions Counselor Department of Chemical Engineering University of Hou s ton 4800 Calhoun Road Houston Texas 77204-4792 You may also call the Chemical Engineering Graduate Admissions Office at 713-743-4311. The University of Houston i s a n e qual opportunity/affirmative action institution Minoritie s women ve teran s, and p e r so n s witb di sa bifaie s are encouraged to apply. 371

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Chemical Engineering at 372 Howard University Where modern instructional and research lab orato ri es, together wit h computing facilities support both student and faculty research pursuits on an eighty-nine acre main campus three miles north of the heart of Washington DC. --Faculty and Re search Interests------Mobolaji E. Al uko P rofessor and Chair PhD University of California, Santa B arbara R eactor modeling crystallization microelectronic and ceramic materials pro cessing process control reaction engi n ee rin g analysis Jo se ph N. Cannon, Professor PhD U ni ve r sity of Colorado Transport phenomena in environmental systems computational fluid mechanics heat transfer Rame sh C. Chawla, Profe sso r PhD Wayne State University Mass transfer and kinetics in environmenta l systems bioremediation incineration air and water pollution control William E. Co llin s, Associate Profe sso r PhD University of Wisconsin-Madison P olymer deformation, rheology, and surface science biomaterials bioseparations materials science M. Gopala Rao P rofessor PhD University of Wa s hington Seattle Adsorption and ion exchange process energy syste m s radioactive waste management remediation of contaminated soils and groundwater John P. Tharakan, A ssoc iateProfessor PhD University of California, San Die go Bi oprocess engineering protein sepa r ations biological hazardous waste treatment bio-environmental engineering Rob ert J. Lutz, Visiting Profe ssor PhD University of Penn sy lvani a Bi omedical engineering hemodynamics drug delivery pharmacokinetics Herbert M. Katz, Pro fessor Emeritus PhD University of Cincinnati Environmental engineering For further information and applications w ri te to M.S. Program Director. Graduate Studies Chemical Engineering Department Howard University Washington. DC 20059 Phone 202-806-6624 Fax 202-806-4635 Chemical Engineering Educat i on

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UIC The University of Illinois at Chicago Department of Chemical Engineering MS and PhD Graduate Program FACUL'IY John H. Kiefer, Professor and Head Ph D ., Cornell University, 1961 E-Mail : Kiefer @ UIC.EDU Kenneth Brezinsky Professor Ph D., City University of New York 1978 E-Mail: Kenbre z@UIC.E DU Andreas A. Linninger Assistant Professor Ph.D., Vienna University of Technology 1992 E-Mail: Linninge @ uic edu G Ali Mansoori Professor Ph.D., University of Oklahoma, 1969 E-Mail : Mansoori @ UIC.EDU Sohail Murad Professor Ph.D ., Cornell University, 1979 E-Mail: Murad @ UIC.EDU Ludwig C. Nitsche Associate Professor Ph.D ., Massachusetts Institute of Technology, 1989 E Mail: LCN @ UIC.EDU John Regalbuto Associate Professor Ph D., University of Notre Dame 1986 E-Mail: JRR @ UIC.EDU Satish C. Saxena Professor Emeritus Ph D., Calcutta University, 1956 E-Mail: Saxena @ UIC.EDU Stephen Szepe Associate Professor Ph D., Illinois In stitu t e of Technology 1966 E-Mail: SSzepe @ UIC.EDU Christos Tak oud is, Professor Ph.D. University of Minnesota, 1982 E-Mail: Takoudis @ UIC.EDU Raffi M. Turian Professor Ph.D ., University of Wisconsin 1964 E-Mail: Turian @ UIC.EDU Lewis E. Wedgewood Associate Professor Ph.D., University of Wisconsin 1988 E-Mail: Wedge @ uic .ed u RESEARCHAREAS Transport Ph e nomena: Transport properties of fluids, sl urry transport, a nd multiphase fluid flow. Fluid mechanics of polymers and other v i scoe lastic media Thermodynamics: Molecular s imulation and statistica l mechanics of liquid mixture s. Superficial fluid extraction/retrograde condensat i on, as ph a ltene characterization. Kinetic s and Reaction Engi n ee ring: Gas-solid r eact ion kinetics. Energy transfer proce sses, la ser diagnostic s, and combustion chemistry Environmental techn o l ogy, s urface chemistry and o ptimi zation Catalyst preparation a nd c har acterization, s upported metal s Chemical kinetics in automotive engine emissions. Biochemical E ngineering: Bioinstrumentation. Bio se parations. Biodegradable polymer s Nonaqueous enzymology. Optimization of mycobacterial fermentations. Materials : Microelectronic material s and processing heteroepitaxy in gro up IV materials, and in sit u s urface spectroscopies at interf aces. Combustion synt hesi s of ceramics and sy nthesis in s up ercritical fluids Product and Proce ss Development and de s ign co mputer-aided mode lin g and sim ulation pollution prevention For rrwre information, writ.e to Direct.or ofGraduat.e Studies Department of Chemical Engineering Fall 1999 University oflllinois at Chicago 810 S Clinton Chicago, IL 606077000 (3 12 ) 996-3424 Fax ( 312 ) 996-0808 URL : http ://www .uic.edu/dept&'clune/ 373

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Chemical Engineering at the University of Illinois at Urbana-Champaign The combination of distinguished faculty, outstanding facilities and a diversity of r ese arch intere sts results in exceptional opportunities for graduate education The chemical engineering department offers g raduat e programs leading to the M S and Ph.D. degree s Richard C. Alkire Electrochemical Engineering Richard D. Braatz Advanced Process Control Steve Granick Polymers and Biopolymers Nanorheology Surface Spectroscopies Vinay K. Gupta Interfacial Phenomena: Structure and Dynami cs in Thin Films Jonathan J. L. Higdon Fluid Mechanics and Transport Phenomena Mark J. Kushner Plasma Chemistry and Plasma Material Processing Deborah E. Leckband Biomole c ular Recognition Richard I. Masel Fundamental Studies of Catalytic Processes and Semi c onductor Growth Anthony J. McHugh Polymer Science and Engineering Daniel W. Pack Engineering of Advanced Drug Delivery Systems Nikolaos V. Sahinidis Optimization and Process Systems Engineering William R. Schowalter Mechanics of Complex Fluids Kenneth S. Schweizer Theory of Polymeric Materials, Colloidal Suspensions, and Complex Fluids Edmund G. Seebauer K. Dane Wittrup Charles F. Zukoski 374 Laser Studies of Semiconductor Growth Biochemical Engineering Colloid and Interfacial Science For information and application forms w rit e: Department of Chemical Engineering University of Illinoi s at Urbana-Champaign 114 Roger Adams Lab Box C-3 600 S Mathews Ave. Urbana Illinois 61801-3792 http://www uiuc ed u/ ~c hem eng A TRADITION OF EXCELLENCE Chemical Engineering Education

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GRADUATE STUDY IN CHEMICAL AND ENVIRONMENTAL ENGINEERING AT Illinois Institute of Technology THE UNIVERSITY Pri va t e, coe du ca ti o n a l a nd r esearc h uni ve r s it y 1 7 00 und e g radu a t e s tud e nt s 3 0 0 0 g radu a t e s tud e nt s Ca mpu s r ecog ni ze d as a n a r c hit ec tu ra l landmark Thr ee mil es fr o m d o wnt ow n C hi cago a nd o n e mil e wes t of L a k e Mi c hi ga n THE DEPARTMENT M e r ge r of c h e m ica l an d e n v i ro nm e nt a l e n g in ee r i n g d e p art ment s c r ea t e d s t a t e-ofth e-art, int e rdi s c iplin a r y r e s ea r c h a nd e du ca ti o n pro gra m s A ppro x im a t e l y 1 0 0 full-tim e and 110 p a rt tim e gra du a t e s tud e nt s M S ., P rofess i o n a l M as t e r a nd Ph D d eg r ee s in c hemi ca l a nd e n v ironm e nt a l e n g in ee rin g N ew foo d pro cess en g ine e rin g pro g ram N ew d o ubl e M as t e r 's d egree pro g ram in c h e mi ca l e n g in ee rin g a nd co mput e r sc i e n ce Fell ow s hip s a nd ass i s t a nt s hip s ava il a bl e APPL/CATIONS Graduate Admissions Coordinator Chemical and Environmental Engineering Department 11/inois Institute of Technology 10 W. 33rd Street Chicago IL 60616-3793 Phone : 312-567-3533 ; Fax: 312-567-8874 http :// www chee iit.edu / e-mail : chee @ charlie cns.iit edu F all 1 999 FA CUL TY AND RESEARCH AREAS Chairman: Hamid Arastoopour Associate Chair for Undergraduate A ffairs Fouad Teymour Associa te Chair for Graduate Affairs Salis h Parulekar Na d er A d e r ang i ; int e,facial ma ss t ra n sfe r rh eo l og i c al prop e rt i es P a ul R A nd e r s o n ; pr ec ipitati o n k in e ti cs ev aluati o n of o x i d e adso r b e nt s fo r w at e r a11d w a s t ew at e r tr e atm e nt H a mid Ara s too p o u r ; co mplllati o n a l multipha se fl ow, flu i di za t i o n mat e ri a l pr ocess in g p a rti cle t ec hn o l ogy fluid-parti cle fl ow B a rr y B e rn s tein ; co m p lll a ti o n a l fl uid m ec h a ni cs mat e rial pr o p e rti es, po l y m e r rh eo l ogy H Ted Cha n g; b i o l ogical p r ocesses h aza rd o u s was t e r e m e di a ti o n g r o und w at e r aq u if e r r e m e d i ati o 11 Al i Ci n ar ; c h e mi ca l a nd foo d pr ocess co ntr o l n o nlin ea r inplllo lllplll m od e lin g s ta ti s t i c al p r o ce ss m o n i t o ri n g St u art L. Coope r ; bi o m ed i c al b i o m a t e ri a l s, p o l y m e r sc i e n ce a nd e n g i 11 ee rin g S a i d S E l na s h a i e; pr ocess d esig n c h e mi c al and b ioc h e mi c al r e a c ti o n s and r e a c t o r d es i g 11 w a s t e m i n i mi za ti o 11 a n d e n v ir o nm e n ta l p r o c ess e s D i m i tri Gida s pow ; h yd r od y n a mi cs of fl uidi z ati o n u s in g kin e ti c th e or y, g a s-so lid tra n s p o rt as rin R. Kh ali li ; eva luati o n of adso r p ti o11 ca p acity of so lid a d so r b e nt s in w a s t e co mr o l, i ndu s tri a l w a s t e m a n age m e nt s trat eg i es H e nr y R. Lin de n ; foss il fue l t ec hn o l og i es, e n e r gy and r eso ur ce ec on o mi c s e n e r gy a nd e n v ir o n m e nt a l p o l i cy D e m e tri o s J Mo s c h a ndr ea s; amb i e nt and i n d oo r air p o ll u t i o n, s t atisti c al a n a l ys i s e n v ir o nm e mal imp ac t a ssess m e n t K e nn e th E No ll ; a ir r eso ur ces e n g in ee rin g, air p o l/ 111i o n m e t eo rolo gy, h aza r d o u s was t e tr ea tm e nt Kr i s hn a R P ag ill a; wa t e r and w a s t ew at e r e n g in ee r in g e n v ir o nm e ntal m i c rob i o l og y, so il r e m ed i a t io n s lud ge tr ea tm e nt S a ti s h P a rul eka r ; bi oc h e m i ca l e n g in ee r in g, c h e m i c al r eac tio n e n g in ee rin g Ja i P rak as h ; so lid s t a t e c h e mi s t ry, m a t e rial s sy nth es i s an d c har ac t e r i za ti o n f o r e n e r gy co n ve r s i o n a n d s t o ra ge appl i c a ti o n s J ay D Sc hi ebe r ; kin e ti c th eory, p o l y m e r r h eo l ogy pr e di c t i on s, t ra n sp o rt p h e n o m e n a n o 11N e w t o ni a 11 fl ui d 111 ec h a 11i cs J. R o b e rt S e l ma n ; appli e d e l ec tr oc h e mi s t ry a n d e l ec t r oc h e mi c a l e 11 g i n ee rin g batte 1 y and f u e l ce ll d e s i g n E u ge n e S S mo t k in ; FT IR s p ec tr osco p y of e l ec tr o d e s u,fa ces e l ec tr o c h e m i c al m a ss s p ec t r osco p y.f u e l ce ll s Fo u ad A T e y mour ; p o l y m e r r e a c ti o n e n g in ee r i n g, mat h e m at ic al m o d e lin g n o nlin e ar d y n a mi c s D avi d C. Ve n e ru s ; p o l y m er rh eo l og y and pr ocess in g tran s p o rt p h e n o m e n a i n po l y m e r i c sy stem s D ars h T. W a sa n ; thin liquid film s; int e ,fa c i al rh eo l ogy ;foam s, e mul s i on a n d d i sp e r s i o 11 e nvi r onm e n tal t ec h no l o g i e s Research Faculty and Lecturers J av ad A bba s i a n V M Ba l as u bra m a ni a m R i c h a rd B e i ss i n g er G u l nur B iro In a n e Bi r o Mi c h ae l Caraco t s i os E lli s F ie ld s T ed Kn ow lt o n W i lli a m F ra n ek H aro l d L inda hl R ohen L ycz k ow s k i A l e x Niko l ov A li O s ko ui e R ohe n P e t ers C h a rl es S i ze r A ll en Tuli s H wa-C h i W an g 3 75

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Graduate program for M S. and Ph.D. degrees in Chemical and Biochemical Engineering FACULTY Gary A Aurand North Carolina State U 1996 Supercritical Fluids / High pressure biochemical reactors Robert Linhardt Johns Hopkins 1979 Biopolymers and pharmaceutical applications V.G.J. Rodgers W ashington U 1989 Transport phenomena in bioseparations / Membrane separa t ions Audrey Butler U. of Iowa 1989 Chemical precipitation processes David Murhammer U. o f Houston 1 989 Insect cell culture / Bioreactor monitoring Alec B. Scranton Purdue U. l 990 Photopolymerization / Micro l ithography / Reversible emulsifiers / P o l ymerizati o n kinetics G r eg Carmichael U. of Kentucky 1979 Global change/ Supercomputing / Air pollution modeling Tonya L. Peeples Johns Hopkins 1994 Bioremediation / Extremophile physiology and biocatalysis John M. Wiencek Case Western Reserve 1989 Protein crystallization / Surfactant technol o gy Stephen K Hunter U. of Utah 1989 Bioartificial organs / Microencapsulation technologies David Rethwisch U. of Wisconsin 1985 Membrane science / Polymer science / Catalysis For information and application: THE UNIVERSITY O F I O WA Graduate Admissions Chemical and Biochemical Engineering 125 Chemistry Building Iowa City IA 52242-1219 l 800 553 IOWA ( l 800-553 4692 ) cheme n g @i caen uiowa edu www.engineering.uiowaedu/ ~ chemeng /

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IOWA STATE UNIVERSITY OF SCIENCE AND TECHNOLOGY m lffi e1n1c 1111 1111 1neer1ng For additional information Graduate Admissions Committee "' Department of Chemical Engineering f '..':;,:~;:.u,~~7:'" Telephone: 515-294-7643 f Fax: 515-294-3177 E-mail: chemengr@iastate.edu Richard C. Seagrave Ph.D Iowa State Iowa State Gordon R. Youngquist Ph D. Illinois Iowa State Carole A. Heath Ph D R P.I. !II Glenn L Schrnde<, Ph.D .. ,,,,. W1scons1n Robert C. Brown, Ph.D Michigan State Maurice A. Larson Ph D. Iowa State 1 Sur y a Mallapragada Ph.D. Purdue Derr;ck K. Ro!Hns, Ph.D Ohio State t ....... Kenneth R.Jolls, Ph D. Illinois Chris Baldwin, Ph.D. Cambridge

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Graduate Study and Research in Chemical Engineering at J ohos Hopkins The Johns Hopkins University's Department of Chemical Engineering e s tabli s hed in 1936 fe ature s a low student to faculty ratio that fosters a highly collaborative re s earch e x perience. The faculty are internationally known for their contributions in the traditional area s of chemical engineering re search, such as thermodynamics, fluid dynamics, and rheology, and at the forefront of emerging technologies, such as membrane-based separation processes recombinant DNA technology tissue engineering, and molecular/cellular biomedical engineering. Insect Cell Culture Recombinant DNA Technolog y Protein Folding and Aggregation M ic h ae l J B e t en b a u g h PhD Universi t y of D e l aware Equations of State Statistical Thermodynamics Solvent Replacement Marc D D o n o hu e P hD Univer s ity of Ca li fornia B erke l e y Biomaterials Synthe s i s Controlled/Targeted Drug Deliver y Tissue Engineering Ju s t i n S. H a n es PhD Massac hu se t t s In st itu te of T ec hn o l ogy Biomaterials and Nanocomposite Materials Macromolecular Transport Rheology of Soft Materials James L. H ar d e n Ph D Univer s ity of Cal i fornia Sa nt a B arbar a Nucleation Crystallization Flame Generation of Ceramic Powders J ose ph L. Ka t z P hD U ni ver s i t y of C hi cago Fluid Mechanics in Medical Applications Vascular and Cellular Biology Thrombosis, Inflammation Cancer Metastasis K o n sta n tino s Ko n s t anto p o ul o s, PhD Ri ce U ni vers i ty 37 8 Th e J o h n s H o pk i n s U n ivers it y d oes n o t d i scr im i n ate o n th e b as i s o f ra ce, co l o r sex. re l i g i o n sex u a l or i e ntat i o n n ati o n a l o r e th n i c o ri g i n a ge, d i sabi lit y or vc l e ran s ta t u s i n a n y s tud e nt p rog r a m o r ac ti v i t y admini s t e r e d by t h e U n i ve r s it y o r w ith r ega r d t o a d m i ss i o n o r e mpl oy m e nt De f e n se Depa nm e n t d isc rim i n a ti o n in ROT C p r og ram s o n th e b asis o f hom osex u a lit y co nfli c t s w ith th i s u ni vcrs i 1y pol icy. Th e uni vers it y i s co mm i n e d t o c n co u rng in g a c h n n ge i n th e De fe n se D e p a nm e n t po li cy Q u es t io n s regardi n g T i tl e V J T i t l e I X a nd Sectio n 504 s h o ul d be r e f erred t o Ycon n e M Th eodo r e A ffirm a t i ve A c t i o n O ffi ce r 2 0 5 Ga r l a n d H a ll (41 0 -5 1 6-8075). Surfactant/Supercritical Fluid Phase Behavior Computational Molecular Thermod y namics Polymer/Protein Thermod y namic s Mic h ael E. P a ul aitis P hD Univer s ity of Illinoi s Interfacial Phenomena Surfactant Transport Kinetic s Maragoni Effect s K athleen J. S t eb e, P h D The Cit y Uni ve r s it y of N ew York Phase Transition s and C ritical Phenomena Polymer Systems Far from Equilibrium ParticleTracking Microrheology D e n is Wir t z PhD S t a n ford Un i ver s i t y For furth e r in formatio n c onta c t : Jo h n s H opkin s U n iver s ity W h iti n g Schoo l of E n gineeri n g D epartme n t of C h emica l Engi n e er in g 3400 N C h a rl es Street B a l t im ore M D 21 2 1802681 410 516-5455 I c h e @ jhu edu h ttp :// ww w. jhu ed u/ ~chem e / C h emE.html OHNS HOPKINS C h e mi ca l E n g in e e rin g E du c ati on

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Durl a nd H a ll H o m e of Chemical Engineering KANSAS STATE UNIVERSITY M S. and Ph D. Programs Chemical Engineering with Interdisciplinary Areas of : Systems Engineering Environmental Engineering Complex Fluid Flows F i nancial A i d Available Up to $17,000 Per Year For More Information Write To Professor J H Edgar Durland Hall Kansas State University Manhattan KS 66506 o r v i s i t our web s i te a t http :// www engg ksu edu / CHEDEPT / Fall 1 999 Areas of Study and Research Biopolymers Biotechnology Controlled Drug Del iv ery Chemical Reaction Engineering Catalytic Hydrocarbon Conversion Coal and Biomass Conversion Multiphase Flow Hazardous Waste Treatment Environmental Pollution Control Intelligent Processing of Materials Process Systems Engineering and Artificial Intelligence Chemical Vapor Deposition of Electronic Materials 379

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University of Kentucky Department of Chemical & Matevials Engineering -J Enmonmenfal Engineering Biophannaceutical & Biocellular Enginee~ing 1 Materials Synthesis Advanc~d Separation & Supercritical Fluids Processing The Chem~ ca~ En~p,e~ r~~g Faculty: K fulderson ; Can;ieg1e-Mell <;i n /'U mv ~~ 1ty D [Bhattac~aryya ; \ Ill~ois In~tij;u~ o ~'U echnology F :perbyshire ; Im~enal Coll~g,e rlo ncion England E Grulke ; Ohio State Univers i ty Membranes & Polymers Aerosols C. Hamrin ; Northw~stem U Jti;v ersity D. Kalika ; Universi l}' of California, B~rkeley R Kermode ; Northwestern / University B Knutson ; Georgia Insti~ ~ of l'F chnol 9 gy A Ray ; Clarkson University ',J. T Schrodt ; University of lw uis le I;) Silverstein ; Vanderbilt [Q niversity t. Tsang ; University of T e xas W Ho ; University of Illinois ---For-more information: Web : http:/ ( WW"ft'. : engr.U:ky : edu/cme ---;._ :ii."-;~ ~ mail~ .dbf:o0ks@eilgr.uky.edu ""-. A'.dclress: Depa11J! ~ n t_!jt:_ ~b: ~J clil t :M_, a ~ l'ia1s _! ngtneerlng Director of Chemical Gnttuate Studies 177 Anderson Hall, V niv e rsitf of Kentucky Lexington,~ 40Sp6-0046 Phone: (60(,)257-8028 Fax : (606")'323-1929

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~ing Jtfafrn ~nibcrsit~ of Jctrolcum & 4ffi{incrals GRADUATE STUDIES IN CHEMICAL ENGINEERING at DHAHRAN, SAUDI ARABIA The Department of Chemical Engineering offers graduate programs leading to the degrees of Mast er of Science and Do ctor of Philos ophy in Chemical Engineering The Master's degre e requires s uccessful completion of 24 course credits and a thesis The Doctoral degr ee program requires successful completion of 30 co urse credits, a writ ten and o ral comprehensive examination, and the submis sion of an original dissertation. ( FIELDS OF RESEARCH [I Reaction Engineering and Catalysis [I Biochemical Engineering [I Thermod y nami cs and Phas e Equilibria [I Fluid and Thermal Sciences [I Proce ss Control [I Separation Pro cesses [I Materials and Polymer Engineering [ FINANCIAL AID ) Financial assistance is available in the form of graduate assista nt s hips consisting of a monthly stipend, accommoda tion, books medical care and air transportation. Fall 1999 ['-F A CUL_TY ________ ~) ABBAS Nureddin M. Stanford University ABU-SHARKH, Basel F. U. Wis co nsin-Madison ABUL-HAMA YEL Mohammed A ., Oklahoma State U. AL-ALI, H abib H ., Colorado School of Mines AL-AMER Adnan M.J., U. British Columbia AL-HARBI, Dulaihan K. Oklahoma State U. AL-NAAFA, Mohammed A., Colorado School of Mines AL-SALEH Muhammad A. Colorado School of Mines AL-ZAKRI, Abdullah S. Oklahoma State U. AMIN Mohammed B. Oklahoma State U. BEG Shafkat A. U. London BELTRAMINI Jorge N ., U. Litoral DEMIREL Yasar, U. Birmingham FATEHI, Ashrafhusein I. King Fahd U. Petroleum & Minerals HAMAD Esam Z. U. Illinois-Chicago HAMID S.Halim Ci ty U. London KAHRAMAN, Ram azan, Montana State U. LOUGHLIN Kevin F. U. New Brunswick MAADHAH, Ali G., Oklahoma Stat e U. SHAIKH Abdullah A., U Notre Dame SHALABI, Mazen A., Colorado S c hool of Mines SHARMA, R ajendra N. In dian In st. Tech. SIDRAK You sry L. Alexandria U. ZUGHBI, Habib D ., U. New South Wales Address Inquiri es R ega rdin g Admission to Dean College of Graduate Studies King Fahd University of Petroleum & Minerals Dhahran 31261 Kingdom of Saudi Arabia FAX: (96 6 ) (3) 860-2829 Email: dean-cg s@kf upm.edu .sa Add r ess Inquiri es R ega rdin g In formation Concerning the Chemical Engineering Pr ogra m to Chairman Department of Chemical Engineering King Fahd University of Petroleum & Minerals Dhahran 31261 Kingdom of Saudi Arabia FAX: (966) (3) 860 -4 234 Email: c-c he @kf upm. ed u. sa http : //www.kfupm.edu.sa/teaching/colleges/webche/index.htm 38 1

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C) C: ca I Cl) (.) Cl) E C: Cl) C) .c C: 0 w Graduate Studies M. Sc. and Ph. D. Biochemical engineering Catalysis Computer aided simulation and design Environmental engineering Polymer engineering Process modelling and control Rheology WE SHARE THE WORLD'S KNOWLEDGE esearc Abdellatif Ait-Kadi (Ph D Ecole Polytechnique de Montreal) aitkadi@gch ulaval.ca ( 418) 656 5222 rheology processing rheological modelling Mosto M. Bousmina (Ph D Ecole des Hauls Polymeres Strasbourg) bousmina@gch.ulaval.ca (418) 656-2769 rheology and modelling polymer blends and alloys polymer physics and engineering Alain Garnier (Ph.D. Ecole Polytechnique de Montreal) alain garnier@gch ulaval.ca (418) 656-3106 biotechnology animal cell culture v i ral vectors and vaccines production Suzanne Giasson (Ph.D. Universite Western Ontario and IFP Paris) sgiasson@gch ulaval ca (418) 656-3774 colloids : polymers surfactants interfacial phenomena surface forces Bernard Grandjean (Ph D Ecole Polytechnique de Montreal) grandjean@gch.ulaval.ca (418) 656-2859 catalytic membrane reactors neural network modelling industrial wastewater treatment Serge Kaliaguine (Dr Ing IGC Toulouse) kaliagui@gch.ulaval ca (418) 656-2708 zeolites and carbon blacks catalytic membranes industrial catalysis Rene Lacroix (Ph D Universite Laval) lacroix@gch ulaval ca (418) 656-3564 numerical simulation of polymer processing numerical simulation of cooling problem finite element method Fa"i~al Larachi (Ph.D. INPL Nancy) flarachi@gch ulaval.ca (418) 656-3566 multiphase reactors wet oxidation flow instrumentati on ~ Faculte DES SCl~NCES ET DE GENIE reas Anh LeDuy ( Ph.D. Universite Western On ta rio ) leduy @ gch ulaval.ca (418) 656-2634 biochemical and microbial processes b iokinetics Jean-Claude Methot ( Ph D Universite Laval ) methot @ gch ulaval ca Chairman of the department Denis Rodrigue ( Ph D Un iversite de Sherbrooke) drodrigu @ gch ulaval.ca (418) 656-2903 tra nsport phenomena rheology oriented foams Christian Roy ( Ph D. Universit e de Sherbrooke) croy @ gch.ulaval.ca (418) 656-7406 vacuum pyrolysis membranes in vapor phase engineering of industrial process Abdelhamid Sayari (Ph D Univers i te de Tunis / Lyon ) sayari@gch.ulaval.ca ( 418) 656-3563 heterogeneous catalysis zeolites and molecular sieves superacid catalysts Jules Thibault ( Ph D Un iversi te McMaster) jules.thibault @ gch ulaval ca ( 418) 656-2443 process identification and control bioreactor en gineering neural network modelling Additional information and Applications may be obtained from: Head of Graduate Program Mosto M Bousmina Department of Chemical Engineering Univers ite Laval Quebec (QC) Canada G1K 7P4 bousmina @gc h ulaval.ca www gch ulaval.ca tel. (418) 656-2769 telecop (41 8 ) 656-5993 ,,~ .. -.::.,i,,~-:..~' ..-. -~ ,., -~~---': -~ ~ ~(, I ---. =

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Synergistic, interdisciplinary research in .. Biochemical Engineering Catalytic Science & R eaction Engineering Environmental Engineering Int erfaciaJ Transport Mat eria l s Synthesis Characterization & Proce ss ing Microelectronics Proce ss ing Polymer Science & Engineering Proc ess Mod e lin g & Control Thermodynamjc P ropertjes Two-Phase Flow & Heat Transfer ... leading to M.S. and Ph.D degrees in chemical engineering and polymer science and engineering Highly attractive financial aid packages, which provide tuition and stipend, are available. Philip A. Blythe (Un i ve r s it y of Manche s ter) I fluid mechanic s heat transfer applied mathematics CJ) Hugo S. Caram (U niversity of Minnesota) I gas so lid and gas -liquid systems optical technique s reaction engineering Marvin Charles (Po l ytec hni c In stit ut e of Brooklyn) I bioproce ss de s ign cGMP R &D 1J.i Manoj K. Chaudhury (SUNY-Buffa l o) I adhesion thin fi lm s surface chemistry IX: John C. Chen (U niversity of Michigan ) I two-phase vapor-liquid flow fluidization radiative heat transfer environmental technology ,q: Mohamed S. El-Aasser (Mc GilJ University) I polymer colloids and films emulsion copolymerization polymer synt he sis and characterization n Christos Georgakis (University of Minnesota) I batch control model predictive control identification statistical process co ntrol IX: James T. Hsu (Nort h western U ni versity) I separation processes adsorption and cata l ysis in zeolites Andrew J. Klein (North Carolina State University) I emulsion pol yme rization colloidal and s urface effects in polymerization ..,. May ure sh Kothare (Ca li fornia Institute of T echno l ogy) I constrained control model predictive contro l optimizat i on industrial contro l fil William L. Luyben (U ni versity of D e l aware) I proces s de s ign and control distillation IX: Janice A. Phillips (U niversity of P ennsylvania) I biochemical engineering instrumentation/control of bioreactor s mammalian ce ll cu ltur e Maria M. Santore ( Prin ceto n Un i versity) I pol y mers adsorption proce sses and blend s tability c.. William E Schiesser ( Prin ceton University) I numerical algorithms and sof tware in chemical engineering ,q: Arup K. Sengupta (Univers it y of H ouston) I use of adsorbents ion exchange reactive polymer s, membranes in environmenta l pollution t Cesar A. Silebi (Le hi g h Univers it y) I se paration of colloidal particles electrophoresis mass transfer :::! Leslie H. Sperling ( Duk e University) I mechanical and morphological properties of polymers interpenetrating polymer networks -.J Fred P. Stein (U ni ve r si t y of Michigan) I thermodynamic properties of mixtures Harvey G. Stenger Jr. (Massac hu setts Institute of Technology) I reactor engineering U.: Israel E. Wachs (Stanford Unive r s it y) I materials c h aracterization surface chemistry heterogeneous catalys i s environmenta l cata l ysis Leonard A. Wenzel, Emeritus (U ni vers it y of Michigan) I th e rm o d yna mi cs cryoge ni cs a nd mixed-gas adsorption Living in B ethlehem, PA allows easy access to cultural and recreational opportunities in the New YorkPhil adelphia area Ad ditional information and appli catio n s ma y be obtained b y writing to: Dr. Maria M. Santore. Chairman Graduate Admissions Committee Department of Chemical Engineering Lehigh University 111 Research Drive lacocca Hall Bethlehem, PA 18015 FAX: (610) 758-5057 E-MAIL : mms2@lehigh.edu Fall 1999 383

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LOUISIANA STATE UNIVERSITY CHEMICAL ENGINEERING GRADUATE SCHOOL TH E CI T Y _________ Baton Rou ge i s the s tate capitol and home of th e major state institution for higher education LSU Situated in the Acadian region, B a ton Rouge blend s th e Old South and Cajun Culture s. Baton Roug e i s one of the nation 's bu s i es t port s and the city 's eco nomy re s t s heavily on th e chemical oil pla s tic s, and agricul tural indu s trie s. The great outdoors provide excellent recreational activities year-round especially fishing, hunting, a nd water sports The proximity of New Orlean s provide s for s uperb nightlife especially during Mardi Gras The city is also only two hours away from th e Mis s i ss ippi Gulf Coast, and four hours from either G ul f Shores or Houston TH E D E P A RTMENT ______ M S and Ph.D. Program s Approximately 60 Graduat e Student s Averag e research funding more than $2 million per year DEPARTMENTAL FACILITIES Departmental computing-with mor e than 80 PCs Exten s ive l aboratory facilitie s, especially in reaction and environmental engineering, tran s port phenomena and separations, po l ymer, textile and material s procesing bio c hemical engineering, thermodynamic s TO A PPL Y, CONT AC T DIRECTOR OF GRADUATE INSTRUCTION Gordon A. and M a ry Cain Department of Chemical Engineering Louisiana Stat e University 384 Baton Rou ge, LA 70803 Telephone : 1 (800) 256-2084 FAX : (225) 388 -14 76 e -mai l : gradcoo r @c h e l s u ed u F A C U LTY A. B. C ORRIP I O ( Ph D. L o ui s i a na Stat e University) Control, Simulation, Computer-Aided D esig n K. M. DOOL EY (Ph.D., University of Delaware ) H ete r oge n e ous Catalysis Hi g h Pr essu r e S e paration s G .L. G RI F FI N ( Ph D. Princeton Univer s ity) Electronic Mat e rials Surface Chemistry, CVD D P H A RRI S O N (Ph D ., University of T exas) Fluid-Solid R eactions Ha za rdous Waste Treatment M A.HENS O N ( Ph.D ., UC Santa B a rbar a) Nonlinear Pr ocess Control, Neural Networks M.A HJOR TS0 ( Ph.D. University of Houston ) Bi oc h e mi ca l R eac t io n Engineering, Appli ed M a th F C KN OPF (Ph.D., Purdue University) Supercriti c al Fluid Extraction, Ultrafast Kin e ti cs R. W PI KE (P h D ., Geor g i a Institute of T ec hn o log y) Fluid D y namics R eaction Engin ee rin g, Optimi z ation E J P ODL AHA ( Ph D ., Columbia University) Electrical Ph enomena, Allo y and Composite Mat eria l s G L. PRI CE ( Ph.D ., Rice University) H e t e ro ge n eo u s Catal ys i s, Zeolites M. R A DO S Z ( Ph D. University of Cracow ) Th er mod yna mi cs, P o l y m e r Ph ysica l Chemistry D D. REI BL E ( Ph D ., California In s titut e o f T ec hnolog y) Environmental Transport, Tran spo rt M ode lin g A.M S T E RL ING ( Ph.D ., University of Wa s hington ) Transport Ph enome na Combustion L. J. T HIBOD EAUX ( Ph.D ., Loui s iana State University) Chemodynamics H aza rd ous Waste Tran spo rt K.E. T HOMP S O N ( Ph.D ., University of Michigan ) Tran s port and R eac tion in P oro u s M ed i a K.T. V ALSA RAJ (Ph D ., V a nderbilt University) Environmental Transport, Separa ti ons D. M. WETZEL ( Ph D. University of D e laware ) Ha za rdous Wa ste Tr eat m e nt D ry in g F IN AN CIAL A ID _______ A ss i sta nt s hip s a t $ 16 ,800 $23,500, w ith waiver of out-of-state tuition Chem i cal Engi n eer in g Ed u cat i on

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Fall 1999 The University The spacious campus is situated on 1 200 acres overlooking the Penobscot and Stillwater Rivers Present enrollment of 12 ,000 offers the diversity of a large school, while preserving close personal co ntact between peers and faculty. The University s Maine Center for the Arts, the Hauck Auditorium and Pavil i on Theatre provide many cultural opportunites, in a ddition to those in the nearby city of Bangor. Les s than an hour away from campus are the beautiful Maine Coast and Acadia National park, alpine and cross-country ski resorts and northern wilderness areas of Baxter State Park and Mount Katahdin. Faculty and Research In t eres t s DO U G LAS BO US FI E W Ph.D. (U.C.Berkeley) Fluid Mechanics Rheology Coating Processe s, Particle Motion Modeling AL B E RT C O Ph.D (Wisconsin ) Polymeric Fluid Dynamics Rheology Transport Phenomena, Numerical Methods JO SE PH M G ENC O Ph.D ( Ohio State ) Process Engineering, Pulp and Paper Technology Wood Delignification AMY L GH ANEM Ph D. ( Cornell ) B iochemica l Engineer i ng Toxicology JOH N C. H ASS LER Ph D. ( Kan sas State ) Process Control, Numerical Methods In s trumentation and Real Time Computer Applications M ARQ U IT A K HILL P h.D (U.C. Davi s) Environmental Science Wa s te Management Technology Programs and Financia l Support J O H N J. H WALEK Ph.D. ( Illinoi s) Liquid Metal Natura l Convection, Electronics Coo l ing, Process Co n tro l Systems E RD OGAN KIRA N Ph.D. ( Princeton ) Polymer Physics & Chemistry, Supercritical Fluids, Thermal Analysis & Pyroly s i s, Pulp & Paper Science H EMANT P EN D SE Ph.D. ( Syracu se) Colloidal Phenomena Particul ate & Multiphase Proce sses Porous Media Modeling D OUGLAS M R U TH VEN Ph.D. Sc D. ( Cambridge) C ha i r Fundamentals of Adsorption and Adsorption Processes E D WA RD V. T HO M P S O N Ph D. ( Polytechnic l nstit u te of Brooklyn) Thermal & Mechanical Propertie s of Polymers Papermaking and Fiber Phy sics, Recycle Paper AD RI AAN VAN H E I N I NGEN Ph D. ( McGill ) Pulp and Paper Manufacture lndustrial fe ll owships u niversity fellowships, research assistantships and teaching assistantships are available. Various research programs s u ch as paper s u rface science and recycled fiber have industrial advisory boards. These boards provide s tudents contact with industry researcher s. Facilities include modem well equipped l aborabories and a pulp and paper pilot plant. Call Collector Write Doug Bousfield Department of Chemical Engineering 5737 J enness H all University of Maine Orono, Maine 04469-5737 (207) 581 2300 Obtain your graduate degree in en enjoyable setting! 385

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MANHATTAN 3 8 6 COLLEGE This well-established graduate program empha sizes the application of basic principles to the solution of process engineering problems T Financial aid is available including industrial fellowships in a one-year program involving participation of the following companies: ABB Lummus Global Inc. Air Products and Chemicals Inc. American Cyanamid Company Consolidated Edison Co. Foster Wheeler International Corp. Pfizer Central Research Texaco Global Gas & Power Tosco Refining Company For brochure and application form, write to Graduate Program Director Chemical Engineering Department Manhattan College Riverdale, NY 10471 chmldept@manhattan.edu Offering a Design-Oriented Master's Degree Program in Chemical Engineering ...... Ill Manhattan College is located in Riverdale, an attractive area in the northwest section of New York City. Ch e mi c al En g ine e ring Edu c ation

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UMBC University of M aryla n d B altimore C ounty EM PHASI S The Department of Chemical and Biochemi cal Engineering at UMBC offers graduate programs l eading to M S. and Ph.D. degrees i n C h emica l Engineering. Our research is heavily focused in biochemical biomedical and bioproces s engineering and covers a wide range of areas including fermentation, cell culture, down s tream proce ssi n g, drug delivery protein engineering, and bio-optic s. Uniq u e program s in the reg u latory-engineer ing interface of bioproce ss ing are offered as well. FA CILITIE S T h e De p artment offers state-of-the-art facilities for faculty and graduate st udent research. These modem facilit i es have been developed primari l y in the last s i x years and comprise 6 000 square feet of laboratory s pace in t h e Tec h no l ogy Researc h Center plus 7 000 square feet of departmental labora t ories in the new Engineering and Computer Science building LOCATION UMBC i s l ocated in the Baltimore-Washing ton corridor and within easy access to both metropolitan areas. A number of government research facilitie s s uch as NIH FDA USDA NSA a n d a large number of biotechnology companies are l ocated nearby and provide exce ll e n t opport uni ties for researc h interac tions. FOR FURTHER INFORMATION CONTACT: Graduate P rogram Coord i nator Departme n t of Chemical and Biochemical Engineering Unive r sity of Mary l a n d B a l ti m ore County 1000 Hilltop Circle Balti m o r e, Mary l a n d 2 1 250 Phone : (410) 455-3400 FAX: (410) 455-1049 Fall 1 999 Graduate Stud y in BIOCHEMICAL ENGINEERING For Engineering and Science Majors F A CULTY D F BR U L EY, Ph.D. Tennes see, P.E. Biodownstream processing and oxygen tran s port proces ses in the microcircu lation ; Proce ss simulation and control. D. D F RE Y, Ph.D. California-Berkeley Separation and transport proce sses in biotechnolo gy; protein purification ; chromatography. A GO ME ZPL A T A, Ph.D. Rens se la e r Heterogeneou s flow syste m s; Simultaneous ma ss transfer and chemical reaction s K. A. KAN G Ph.D California-Da v i s Chromatographic prote i n purification; Real-tim e lmmuno-optical bio se nsor ; Optic al imaging of DVT and cancer; Optical diagnosis of skin cancer M R. MA RT EN, Ph.D. Purdue Bioprocess engineering; Fermentation; Cell biology and protein sec retion. A. R M OREIRA Ph.D P e nns y l van ia rDNA fermentation; Regulator y i ss ues ; Scale-up; Downstream proces s ing G. F P AYNE, Ph.D. ** Mi c hi ga n Plant cell ti ss ue culture; Streptomyces biopro cessing; Adsorptive se paration; Toxic waste treatment G. RAO Ph.D .** Drexel Fluorescence-based se n sors and instrumentation ; Fermentation and cell culture. J .M RO SS, Ph D. Rice Cellular and biomedical engineering; Cell adhesion; Tis s ue engineering M. R. S IERK S, Ph.D. Iowa State Protein engineering; Site-directed mutagene s i s; Catalytic antibodies Emeritus ** Joint applintment with th e University of Mar y land Biot ec hn o lo gy In s titut e 387

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CHEMICAL ENGINEERING Degrees Offered M.S. and Ph.D. Advanced research in Aerosol Science Biochemical Engineering, Polymer Science and Engineering, Multiphase Flow and Mixing, Systems Modeling, Environmental Engineering Process Control, Thermophysical Properties, Physical Chemistry Nanoparticle Technology, Computational Engineering, Molecular Simulations, Membrane Science, and Separation Processes Faculty and Research Areas Raymond A. Adomaitis (UT) Systems modeling and simulation methodologies; semiconductor materials manufacturing Mikhail A. Anisimov (Moscow) Critical phenomena and phase transitions in fluids and fluid mixtures Timothy A. Barbari (Texas-Austin) Membrane science, polymer science, separation processes William E. Bentley (Colorado-Boulder) Biochemical engineering, metabolic engineering applications of molecular biolog y Richard V. Calabrese (Massachusetts) Multiphase flow, turbulence and mixing Kyu Yong Choi (Wisconsin) Polymer reaction engineering Sheryl H. Ehrman (UCLA) Aerosol science and engineering James W. Gentry (Texas-Austin) Aerosol science and engineering Sandra C. Greer (Chicago) Physical chemistry, polymer science Michael T. Harris (Tennessee) Nanoparticle technology Peter Kofinas (MIT) Pol y mer science and engineering Thomas J. McA voy (Princeton) Process control, neural network applications Athanassios Z. Panagiotopoulos (MIT) Computational engineering molecular s imulations Tracy R. Pulliam Holoman (Maryland) Biochemical engineering and bio-remediation Thomas M. Regan (Tulane) Teaching/learning pedagogy and delivery systems Jan V. Sengers (U. Amsterdam) Critical phenomena, thermophysical properties of fluids and fluid mixtures Nam Sun Wang (Caltech) Biochemical engineering William A. Weigand (UT) Biochemical engineering bioprocess control and optimization Evanghelos Zafiriou (Caltech) Process control, identification and optimi z ation 388 Location: The University of Maryland at College Park is located approximately 10 miles from the heart of the nation, Washington, D.C., and 25 miles from Baltimore. For Applications and Further Information. Write Graduate Admissions Officer Department of Chemical Engineering Room 2113 Building 090 University of Maryland College Park, MD 20742-2111 http://www.ench.umd.edu C h e mi c al En g in ee rin g Edu c a t i o n

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Come to Chemical Engineering at the University of Massachusetts Amherst Amherst is a small New England town in Wes tern I\ Iassachusetts. Set amid farmland and rolling hills, the area offers pleasant living conditions and extcnsiw recreational facilities, and urban pleasures are easily accessible. Fall 1999 See us 011 our Web paKl http://www.ecs.umass edu/d1e/ Faculty M.F. Malone (Massachusetts), Head S .R. Bh atia ( Princeton) W.C. Conner, Jr. (Johns H opkins) M.F. D oherty (Cambridge) J.M. D oug l as, Emeritus (Delaware) V H aensel Emeritus (Northwestern) R. L. La u re n ce (Northwestern) P.A. Monson (London) K.M Ng ( H ouston) S.C. R oberts (Cornell) M. Tsapatsis (Caltech) D G Vlac h os (Minnesota) J.J Watkins (Massachusetts) P R Westmoreland (MIT) H.H Winter (Stuttgart) Z. Q Z h e n g (Caltech) Current Areas of MS and PhD Research R obust process control Azeotropic, extractive and reactive distillation Crys t alliza t ion and d esign of solids process i ng Po l ymer processing and reactor engineering Ca t alyst a n d catalytic reactor deve l op m e n t Noncatalytic gas and gas solid kinetics : Comb u stion, PECV D and polymer pyrolysis Fluid mechanics and polymer rheology Statistical mec h anics and phase behavior App l ied ab initio computational chemistry B ioengi n eering and biomaterials Financial Support All st u dents are awarded full financial aid at a natio n al l y competitive rate. For application forms and further information on fellowships and assistantships, academic and research programs and student housing w rit e: Graduate Program Director Department of C h emical Engi n eering 159 Goessman n Laboratory, Box 33110 University of Massachusetts Amherst, MA O 1003-3110 The University of Mas sac husett s Amherst prohibit s di sc rimin a tion on the ba s is of race color, religion creed, sex, sexual orientation, age m ar it a l status, national origin, disability or handi ca p or ve teran s tatus in any aspect of th e admission or t r eatment of students or in emp l oyment. 389

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390 Chemical Engineering at MIT is located in Cambridge. just acms 1 the Charles Ril't'l".fi"()//1 /los/1111, a .few minutes by subway .fiom dm1tm1 llos/1111 and Harmrd Square The hemy co11ce11trati1111 1!f" coll1,ge 1 hospitals. research facilities and high technology i11dm11 : r prtll'ides a p11p11lace that de mwuls wul .ft II ds an 11111 11di11g mriety t!/" theaters, c1111certs restaurants. 11111se11111s. bo11kst11res. sporting e1e11ts. libraries. and recreati1111alfacilities. Research in ... Biochemical Engineering Biomedical Engineering Catalysis and Chemical Kinetics Colloid Science and Separations Energy Engineering Environmental Engineering Materials Polymers Process Systems Engineering Thermodynamics Statistical Mechanics and Molecular Simulation Transport Processes R.C. Armstrong, H ead P.I. Barton D. Blankschtein H. Brenner R.A.Brown R.E.Cohen C.K. Colton C.L. Cooney W.M.Deen K.K. Gleason With the largest chemical engineering research faculty in the country, the Department of Chemi cal Engineering at MIT offers programs of re search and teaching which span the breadth of c hemical engineering with unprecedented depth in fundamentals and applications. The D epart ment offers two levels of graduate programs lead ing to Master's and D octor's degrees I n addition graduate students may earn a Master's degree through the David H. Koch School of Chemical Engineering Practice a unique internship pro gram that stresses defining and solving industrial problems by applying chemical engineering fun damentals. Students in this program spend half a semester at each of two Practice School Station s, includin g domestic and international corporate sites, in addition to one or two semesters at MIT. W.H.Green G.C. Rutledge L.G. Griffith H.H. Sawin P.T. Hammond K.A. Smith T.A. Hatton Ge. Stephanopoulos J.B. Howard Gr. Stephanopoulos K.F. Jensen J.W. Tester P.E. Laibinis B.L. Trout R.S. Langer P.S. Virk D.A. Lauffenburger D.I.C. Wang G.J.McRae J.Y. Ying For more information, contact Chemical E n gineering Graduate Office, 66-366 Massachusetts Institute of Technology Cambridge MA 02139-4307 Phone (6 17 ) 253-4579; FAX (6 17 ) 253-9695; E-Mail info @c hemegrad.mit.edu WWW address http://web.mit.edu/af s/a thena/org/c/cheme/wwwfTitlepage html Chemical Engineering Education

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~hemical Engineering at The University of Michigan ~aculty 1. Ralph T. Yang Chair, Separations, adsorption, catalysis 2 Stac y G Bike Colloids, polymers, complex fluids 3. Ofe r Blum Bio-organometallic chemistry, drug design 4. Mark A. Bums Microfabricated analytical systems, biochemical separations 5. Bri c e Carnahan Numerical method~processsimulation 6. H. Scott Fogler F u sed reactions, colloids, gellation kinetics 7 John L. Gland Surface science 8. E rdogan Gulari Catalysis, electronic materials, combinational chemistry 9 Costas Kra v a ri s Nonlinear process co n trol, system ide n tification L O. Ron al d Larson Polymers, DNA, complex fluids, fluid mechanics ll. Jenni f er J Linderman Engineering approaches to cell b iology L2. Robe rt Lionberger Theory and compu t atio n of co m plex fluids L3. Susan Montgomery Undergraduate program advisor 1 4. Da vi d J Moone y Cellular and tissue engineering 1 5. Phillip E. Sa v age Reactions in supercritical water, "green" chemistry 16 Johannes Schwank Heterogeneous catalysis, surface science, gas sensors 17. Michael Solomon Light scattering and rheology of complex fluids 18. Lev i T Thompson, J r. Catalysis, electroca t alysis, ma t erials processing 19. Hen ry Y. Wang Pharmaceutical engineering, bioprocessing 20. James 0 Wilkes Numerical methods, polymer processing 21. Robert M Ziff Percolation catalysis, s t atistical thermodynamics 17 For More Information Contact: 1 2 3 4 5 6 7 8 9 10 11 12 ._;~ P" 1 ,. y ,, 13 14 15 16 18 19 20 21 Graduate Program Office, Departmen t of Chemical Engineering/ The University of Michigan/ Ann Arbor, MI 48109-2136 / 734 763-1148

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MICHIGAN STATE UNIVERSITY Graduate Study ID Chemical Engineering The Department of Chemical Engineering offers Graduat e Programs leading to M.S. a n d P h.D degrees in Chemical Engineering. Th e faculty co ndu c t fundamental and applied research in a variety of Chemical Engin ee ring dis ci plines. The Mi c hi gan Biot ec hnolo gy I n st itute the Composit e Materials and Stru c tur es Center, and the Crop and Food Biopro cess ing Cent e r p r ovide a forum fo r interdis c ipl i nary work in c urrent high t ec hnolog y areas. ( ASSISTANTSHIPS ) Ha l f-time grad u ate assistantships for incoming Master's ca n didates are expected to pay $ 1 5 690 per year p l us a t u ition and fee waiver of six cred i ts for Fa ll and Spring Semesters fo u r credits for Summer Semester. University paid hea l t h insura n ce i s a l so provided. T h eses are writte n o n t h e projec t covered by the research a ss istantship. ( ~ F_E_L L_O_W_S_H_I_PS _~) Avai l ab l e appointments pay up to $19,500 per year. FO R A DDITIO NAL I NFO RM AT IO N W RIT E Chairper s on Department of C hemical E ngineerin g 2527 E ngineering Building Michigan Stat e U niv e r s it y 392 Eas t Lan s in g, M ichi g an 48824 12 2 6 e-mai l : grad_rec@egr.msu.edu www: h ttp://www .eg r.ms u ed u /C h E/ MSU is a n Affirmati v e A c tion/Equal Opportunity /11 s tit111i o11 D .K. AN D E R S O N Prof esso r Em e ritu s Ph.D ., 1960 U niver s i ty of Wa sh in gto n K. A B E R G L UN D Ph.D ., 19 8 / Iowa State University Applied Spectroscopy, Forni and Biochemical E n g in eeri n g Crys t all i zatio n from Solution New Uses of Agricultural Cro p s D .M. BR IE DI S Ph D. 19 8 1 I owa Stat e University Bio c h e mi ca l and Fo o d Engineering, Bioadhe s ion Engineering P e dag ogy B. E D ALE, Chairperson Ph D 1 979 Purdu e University Bio c h e m i ca l Engineering Bi o r e m ed i a tion, Bi o ma ss Conversion L.T DR ZA L Ph D 19 74, Case W es t e rn Res e rv e University Surface and lnt erfac i a l Phenomena Adhesion Polymer Composite Mat e ri a l s Surface C har ac t er i z at ion Surface Modification of P o l y m e r s, P o l y mer Co mp os it e Pro ces s ing, Adhesive B o ndin g M C HAWLEY Ph D 1964 Mi c hi gan State University Kin e ti cs, Catalysis R eac ti o n s in Plasmas Pol y m er i za tion R eactio n s, Composite Pro cess in g Bi omass Conversion Reaction E n gineeri n g K J AYARAMAN Ph.D. 19 75, Prin ceton University P o l ymer Rheo l ogy Pro cess ing of Polymer Bl e nd s a nd Composites, Comp u tatio n al Method s C M LAST O S K IE Ph.D. 1994 Cornell Un i ve r s i ty Process D ynamics of Env ironm enta l System s, Adso rpti on in Porous Materials Statisti c al Themody n a mi cs and M o l ec ular Simulation C T LI RA Ph.D 1 986, Univers i ty of Illin ois at Urbana-Champaign Thermodynamics and Phase Equilibria of Complex Systems Adsorption Supercritical Fluid Studies D.J MILLE R Ph.D /9 82, University of Florida Kin et i cs and Catalysi s, Re actio n Engineering Catalytic Conver s i o n of Bi omass Ba s ed Mat eria l s R.J. M OR GAN Ph D 1968 Un i vers i ty of Man c hest er High P e rf o rmanc e Fibers P o lym e r M a tri ces, Fast Pro cess in g Composite M ater i a l s Reliabilit y a n d Durability R. NARAYAN Ph.D ., 19 75, University of B o mba y Polymer Bl en d s and Alloys Biodegradable Pla s tics B iofiber Composi t e s, Ext ru s i on P o l y m e ri za tion a nd R eactive Compounding, Biodegradation a nd Co mp os tin g Stud i e s R. Y O F OLI Ph.D. 1 994, Carnegie M e ll o n University Co ll oid a nd Lnt erfac i a l Science : Co ll oid Stability Adso rpti on of Pr o t eins R eceptor-L i gand Interactions at th e Liquid-Liquid I nter face Mi ce ll a r Solubi l ization C.A P ETTY Ph.D 1 97 0 University of Florida Fluid M ec hani cs, Turbulent Tr an s pon Phen ome n a Solid-Fluid a nd Liquid-Liquid Sep ara ti o n s, H y dro cyclo ne s A .B. SC RA NT O N Ph D 1990 Purdue University Polymer Science and E n g in ee rin g, Polymer Co mpl exat i o n a nd Network Formation A pp l i ca ti o n s o f NMR a nd Luminescence Spectroscopy Mo l ec ul a r M ode lin g Crosslinking Photopolymerization s B .W. WILKINSON Pr o fe sso r Em e ritu s Ph.D. 1 958 Ohio State U ni versit y R. M W ORD EN Ph.D 1986 University of T e nn essee Bio chemica l En g in eer in g, Microbial Transpon Pr ocesses Synthesis Ga s Fermentations Metabolic Engineering M icro bi a l Eco l ogy Chemical Engineering Education

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Chemical Engineering ~.: Michigan Technological University Add your name to the ranks of the prestigious engineering alumni from Michigan Tech. Combine a first-rate chemical engineering education with the beauti ful surroundings of the Keweenaw Penin s ula. Michigan Tech is a top-100 national university according to U.S. News & World Report MTU 's enrollment is approximately 6,300 with 640 graduate students. We have one of the largest chemical engineering programs in the nation with a vital and focused graduate program. Contact Department of Chemical Engineering Michigan Te c hnolo gical University 1400 Town se nd Drive Hought o n M1 49931-1295 906/487 -3 13 2 Fax: 906/487-3213 www.mtu edu Chemical Engineering Faculty Process and plant design Bru ce A. Barna ; Profe sso r PhD New Mexico State 1985 Demixing-polymerization polymer materials Gerard T Caneba ; A sso ciate Professor ; PhD California-Berkeley 1985 Process control, neural networks, fuzzy logic control Thomas B Co ; Associate Profe sso r ; PhD Massachusetts-Amherst, 1988 Chemical process safety Daniel A. Crowl ; Professor and D ow Chair in Chemical Process Safety; PhD Illinoi s 1 975 Excited state chemistry and transport processes Edward R Fisher ; Professor; PhD, Johns Hopkins, 1 965 Process control, energy systems Nam K. Kim ; As soc iate Profe ssor; PhD Montana State 1982 Polymers, composites Julia A King ; Assistant Profe sso r; PhD Wyoming, 1989 Chemical Process Systems Engineering David C. Miller; Assista nt Profe sso r PhD Ohio State U niv ers it y 1 998 Polymer rheology flow instabilities, complex fluids Faith A Morri so n; Associate Profes so r; PhD Massachusetts-Amher s t 1988 Catalysis, ceramic processing, reactor design Michael E. Mullin s ; Professor ; PhD Roche s ter 1983 Chemical process safety Anton J Pintar ; A ssoc iate Professor ; PhD, IIT 1968 Environmental thermodynamics Tony N. Ro gers; Associate Professor ; PhD, Michigan T ec h, 1994 Surface Science, catalysis Kirk H. Schulz ; A ssoc iate Profe ss or and Department Chair ; PhD Virginia Tech 1991 Environmental and biochemical engineering David R. Shonnard; A sso ciate Profe ssor PhD California-Davis 1991 Michigan Technol og i ca l University i s an equal opportunity e ducational institution/equal opportunity employer. Fall 19 99 393

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Leadership and Innovation in CHEMICAL ENGINEERING AND MATERIALS SCIENCE at the UNIVERSITY OF MINNESOTA FACULTY Ruth e r fo rd A ri s ( Emeritu s) Theoretical studies of chemical reactors F r a nk S Bat es Thermod y namics and dynami cs of pol ymers and pol y mer mixtur es R o b e r t W. Ca rr Chemical kinetics, reaction engineering C. B arry Ca rt e r Electron microscopy of semiconductors and ce ramics solid-state reactions and growth of thin films Jam es R. C h e likow s k y Structural/electronic properti es of complex systems R o b e rt F. C ook M echa nical behavior of materials, microelectronic device fabrication and packa g ing E d w ard L. C u ss le r Mass transfer novel sepa r ation p r ocesses John S D a hl e r Nonequilibrium statistical mechani cs P r odr o mo s D a outidi s Nonlinear process control, pro cess anal ysis and design H. T e d Da v i s Colloid and interface science, statistical me c hani cs J e ffr ey J. Derb y Mat e rials processing, high performance co mputin g D Fe nn e ll Eva n s l nterfa c ial phenomena, surfactant microstructures Lorraine Falter Franci s Ceram i c processing electrical and mechanical properti es of ceramics A rnold G Fredrick s on Biochemical engineering microbial popu l ations C. Daniel Fri s bie Molecular materials and int e rfa ces, molecular electronics William W. Gerberich Fracture micromechanics inte fac i al defects Wei-Shou Hu Bio c hemical engineering Timoth y P. Lod ge Polymer structure and d y namics, pol y m e r characterization Christopher W. Maco s ko Polymer pro cess ing, rheolog y, polymer networks and blends Richard B. Mc C lurg The r mod y namics and kineti cs of phase c hanges A lon V. Mc C ormick Reaction engineering of mate r ials synthesis, spectroscopy molecular simulation Da v id C. Mor s e Statistical mechanics polymeric and co m p lex fluids Richard A. Oriani ( Emeritu s) Cor r osion, the r modynamics of solids, cold fusion C hri s topher Palm s tr ~ m Epitaxial growth pro cesses and heterostructure formation, properties of thin film Lann y D. Schmidt Su fa ce c hemistry, he t erogeneous catalysis, reaction engineering L. E S cri v en Fluid m ec hanics and rheolog y, transp or t r eact ion and stress phenomena materials pro cessing Da v id A Shore s H igh temperatur e co rrosion, fuel cells John M S ivertsen ( Emeritu s) Magnetic mi c roelectronic, and tribologi cal mate rials William H. S m y rl Electrochemical eng ineering, mod e lin g electrochemical syste ms microvisuali za tion of reactive surfaces F riedrich S ri e n c Bio c h e mical engineering, cell cycle and growth models, biopol y mers Rob e rt T Tranquillo Cell and tissue e ngin ee ring J e ffr ey D. V arner Math em atical modeling of cellular signaling and reaction n etwo rks, bioinformati cs and functional genomics Michael D. Ward Mol ecu lar materials crys tal growth, e/ectrochemistry John H. W e a ve r Su,faces, int e rfa ces, and nanostructur ed mat e rials Renat a M M W e ntzco v itch Electronic and structural properti es of condensed matter systems; first principl es mol ec ular dynamics For additional information. visit our web site at http://www.cems.umn.edu 394 Chemical Engineer i ng Educat i on

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Universit): of Missouri-Columbia Rake sh K. Baipai Ph.D. (!IT, Kanpur) Biochemical Engineering Ha zar dous Waste Paul C.H. Chan Ph.D (Ca/Tech) Reactor Analysis Fluid Mechanics Patricia A Darc y Ph.D ( Iowa) Protein Crystalli zat ion Biotechnology William A. Ta cobv Ph.D (Colorado) Photocatal ys is Transport Sung_gyu Lee Ph.D (Case Western) Process Engineering Pol yme rs Fuels Stephen .[. Lombardo Ph.D. (California -B erkeley) Ceramic Composites Transport Kinetics Sudarshan K. Loyalka Ph.D. (Stanford) Aerosol Me c hanics Kinetic Theory Richard H. Luecke Ph.D. ( Oklahoma) Pro cess Control Modeling Thomas R. Marrero Ph.D (Maryland) Coal Lo g Tran sport Conducting Pol y m e rs Da vid G. R etzloff Ph.D. ( Pittsburgh) Reactor Analysis Materials Truman S. Storvick Ph.D. (Purdue) Nuclear Waste Repro cess ing Thermodynamics Dabir S. Viswanath Ph D (Rochester) Applied Th ermodynamics Chemical Kin et i cs Hirotsug_u K Yasuda Ph.D. (SUNY, Syracuse) Pol y m ers Surfa ce Science The University is one of the most comprehensive institutions in the nation and is situated on a beautiful land grant campus halfway between St. Louis and Kansas City, at the foothills of the Ozark Mountains and the recreational Lake of the Ozarks. The Chemical Engineering Department offers M.S. and Ph.D. programs in a wide variety of research areas including surface science, nuclear waste, wastewater treatment, biodegradation, indoor air pollu tion, supercritical processes, plasma polymeri za tion, polymer processing coal transportation (hydraulic), fuels, chemical kinetics, protein crystallization, photocatal ys is ceramic composites, and pol y mer composites. For details contact: The Director of Graduate Studies Department of Chemical Engineering University of Missouri Columbia, MO 65211 Tel : (573) 882-3563 Fax: (573) 884-4940 E-mail: fudge@mi sso uri edu Website : chetigers.chemical. missouri.edu Fall 1 999 In centive scholarships available in the form of teaching/research assistantships and fellowships. 395

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MISSOURI'S TECHNOLOGICAL UNIVERSITY UNIVERSITY OF MISSOURI ROLLA Department of Chemical Engineering offering M.S. and Ph.D. Degrees N. L. BOOK (Ph.D., Colorado) Computer Aided Proce ss Design Bioconversion D. FORCINITI (Ph.D., North Carolina State) Bioseparations Thermodynamics Statistical Mechanics J. W. JOHNSON (Ph.D., Missouri) Electrode Reaction s Adsorption A. I. LIAPIS (Ph.D., ETH-Zurich) Transport Phenomena Adsorption/De sor ption Fundamentals and Processes Bioseparations Chromatographic Separation s Chemical Reaction Engineering Lyophiliz at ion D. K. LUDLOW (Ph.D., Ariwna State) Characterization of the Surfaces of Adsorbents and Catalysts Applications of Fractal Geometry to Surface Morphology D. B. MANLEY (Ph.D., Kansas) Th ermodynamics Vapor-Liquid Equilibrium Process Development N. C. MOROSOFF ( Ph.D. Brooklyn Polytech) Plasma Polymerization Membranes P. NEOGI (Ph.D., Carnegie-Mellon) Interfacial and Transport Phenomena G. K. PATTERSON (Ph.D., Missouri-Rolla) Mi xi n g Polymer Rheology Computational Fluid Dynamic s and Turbulent Transport X B REED, JR. (Ph.D., Minnesota) Fluid Mechanics Drop and Parti c le Mechanics Tran sport Phenomena Turbulence Structure Turbulence Modeling including Reactions S. L. ROSEN (Ph.D., Cornell) Polymerization Reactions Applied Rheology Polymeric Materials 0. C. SITTON (Ph.D., Missouri-Rolla) Bioengineering D. SOURLAS (Ph.D., UCLA) Process Control Optimization R. M. YBARRA (Ph.D., Purdue) Rheology of Polymer Solutions Chemical Reaction Kinetic s 396 Financial aid is obtainable in the form of Graduate and Research Assistantships and Industrial Fellowships Aid is also obtainable through the Materials Research Center. Contact Dr P. Neogi or Dr. D.D. Sour/as Graduate Coordinators Chemical Engineering Department University of Missouri Rolla Rolla Missouri 65409-1230 Telephone (573) 341-4417 Chemical Engineering Education

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University of Nebraska Graduate Studies in Chemical Engineering Jennifer Brand University of California San Diego Supercritical Fluid Processing; Natural Product Processing; Environmental Remediation L. Davis Clements University of Oklahoma Computer-Aided Process Design ; Process Synthesis; Fuels and Chemicals from Biomass James Eakman University of Minnesota Computer-Aided Process Engineering; Solids Properties & Processing; Reaction Engineering James Hendrix University of Nebraska Remediation of Mine Tailings Waste; Novel Analytical Chemistry; Non-Ideal Reactors Gustavo Larsen Yale University Heterogeneous Catalysis; Spectroscopic Characterization of Catalysts Lee Lauderback Purdue University Surface Analysis; Heterogeneous Catalysis Hossein Noureddini University of Nebraska Production of Chemicals from Agricultural Products ; Mathematical Modeling of Polymerization Kinetics Delmar Timm Iowa State University Polymer Composites; Step-Wise Polymerization Kinetics; Kinetic Analysis Using GPC Hendrik Viljoen University of Pretoria Plasma-Enhanced CVD; Detonation & Combustion; Ceramics For further information, write .................. Director of Graduate Studies Department of Chemical Engineering University of Nebraska Lincoln, NE 68588-0126 Also, please visit us at our web site at: http://www.unl.edu/chemengr/ Graduate admissions on-line applications and printable forms available at: http://www.unl.edu/gradstud/gradadmission.html

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398 UNIVERSITY OF NEVADA RENO Ph.D. and M.S. programs in Chemical Engineering Competiti v e fellowships and Enjoying the clear skies and moderate climate of Northern Nevada, UNR is conve ni ent to downtown and on l y 45 minutes from Lake Tahoe. assistantships are available Re s ear c h A rea s Biomaterials Fluidization Process Safety Process Design Polymer Engineering P rocess Control Fl u id Mechanics P rocess Simu l ation Molecular Simulation Separation Processes Pollution Prevention Phase Equilibria Reaction Engineering Risk Analysis F a c ult y Frank G Baglin (Washington State) C h ar l es J Coronella (Univ of Utah) Alan Fuchs (Tufts) Victor R. Vasquez (Univ. of Nevada, Reno) Wallace B Whiting, Chair (UC, Berkeley) For on-line application form s and information: www.unr.edu/chemengr chemengr@unr.edu (775) 784-4307[tel] (775) 784-4764 [fax] Chemical Engineering Univ. of Nevada Reno Reno NV 89557-0136 USA Chemi c al Engineering Ed u ca tion

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New Jersey Institute of Technology A Public Research University U ni v ersity Heights Newark New Jer s e y 07102-1982 The Department of Chemical Engineering Chemistry and Environmental Science offers excellent opportunities for interdisciplinary research and graduate studies particularly in the areas of hazardous waste treatment materials science engineering and biochemical processing Both master s and doctoral degrees are offered in a growing program that has national and international research ties Resources: 20 000 sq. ft. of modem laboratory and computing facilities particularly in environmental and materials research internationally respected faculty Support: approx $2 million in annual research support from state federal and industrial sponsors financial assistance programs Flexibility: part-time or full-time evening study interdisciplinary research diverse areas of specialization M.S and Ph.D degrees For program information contact Dr Dana Knox Graduate Recruiter Department of Chemical Engineering Chemistry and Environmental Science Phone: ( 9 73) 596-3599 Fax: (9 7 3) 596-8 4 36 E-mail knoxd@admin.njit edu Internet: http //www.njit edu For graduate admission informati o n w rite or call ( 9 7 3 ) 596-3 4 60 NJ[[ does not discrimi11a t e 0 11 the basis of sex sexual o r ie llf afio11 race handicap ve t e r ans status national or ethnic origin or age in the administration of student programs. Campus facilities are accessib l e to the disab l ed

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GRADUATE RESEARCH AT THE FRONTIER Faculty Harold M Anderson C Jeffrey Brinker Joseph L. Cecchi John G. Curro Abhaya K. Datye SangM Han David Kauffman Ronald E. Loehman Gabriel P Lopez Richard W Mead H Eric Nuttall Jonathan Phillips Timothy L. Ward Ebtisam S. Wilkins The University of New Mexico The future of chemical engineering is a bright one with rapidl y developing technologies and exciting new opportunities Pursue y our graduate degree in a stimulating student-centered intellectual environment anchored b y forward-looking research. We offer full tuition and competitive stipends The ChE faculty are leaders in exploring phenomena on the meso, micro, and nanoscales We offer graduate research projects in biotechnology and biomaterials ; catal y sis and interfacial phenomena ; environmental technologies and waste management ; microengineered materials and self-assembled nanostructures ; plasma processing and semiconductor fabrication ; polymer theo ry and modeling The department enjo y s e>..1ensive interactions and collaborations with New Mexico s federal laboratories : Los Alamos National Laboratory Sandia National Laboratories and the Air Force Research Laboratory as well as high technology industries both locally and nationall y Albuquerque is a unique combination of the v ery old and the highly contemporary the natural world and the manmade environment the frontier town and the cosmopolitan city a harmonious blend of diverse cultures and peoples Join us! Be part of this future Research Areas Plasma Processing Plasma Diagnostics Ceramics Sol-Gel Processing Self-assembled Nanostructures Semiconductor Manufacturing Technolog y Plasma Etching and Deposition Polymer Theory Computational Modeling Catal y sis Interfaces Advanced Materials Semiconductor Manufacturing Technolog y Plasma Etching and Deposition Plant Design Environmental Engineering Glass-Metal and Ceramic-Metal Bonding and Interfacial Reactions Chemical Sensors H y brid Materials Biotechnology Interfacial Phenomena Unit Operations Resource Extraction Environmental Science Waste Transport Management Colloid Science Materials Science Catalysis Plasma Ph y sics and Chemistry Aerosol Materials Synthesis Inorganic Membranes Biomedical Sensors and Waste Treatment For mor e information co nta c t : Timothy L. Ward G raduat e advisor C h e mical and N ucl e ar E ngin ee rin g 2 09 F arris E n g in ee rin g C e nt e r A lbuqu e rqu e, N M 8 71 3 1-13 4 1 505 277. 5431 Phon e 505 277 5433 F a x tl w ard @ unm .e du

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NEW MEXICO STATE UNIVERSITY Faculty and Research Area __ s __ ________ Paul K. Andersen, Associate Pro fessor, University of C alifornia, B erke l ey Transport Ph enomena, Electrochemistry Environmental Engineering Ron K. Bhada, Pro fessor, Associate Dean Univer sity of Michigan Environmental Engineering Joe L. Creed Assistant to the Pre si dent New Mexico State University Engineering De sig n Francisco R. Del Valle College Prof essor, Massachusetts Institute of Technolog y Food Engin ee ring Sarah W. Harcum, Assistant Profe ssor, University of Maryuland-College Park Biotechnolog y, Biochemical Engineering Environmental Engineering Richard L. Long, Profes s or Ri ce University Transport P henomena, Biom e dical Engineering, Separations Martha C. Mitchell, Assistant Professor Universi ty of Minnesota Advanced Materials, Stati stica l Mechanics, Molecular Modeling Stuart H. Munson-McGee, Profe ssor, Interim Head, Universi ty of D elaware Advanced Materials, Separations John T. Patton, Pro fessor Emeritus, Oklahoma State University David A. Rockstraw, Associate Pro fessor, University of Oklahoma Separations Environmental Engineering Kinetics Rudi V. Roubicek Professor Emeritus, Technical University of Prague Edward F. Thode, Profe ssor Emeritus Massachusetts In stitute of Technolog y D. Bruce Wilson, Professor Emeritus Prin ceton University LOCATION------~ Southern New Mexico For Application and Additional Information Internet http://chemeng nmsu .e du/ E-mail chemeng@nmsu.edu Fall 1 999 350 day s of s unshine a year PO Box 30001, MSC 3805 Department of Chemical Engineering New Mexico State University La s Cruces, NM 88003 New Mexico State University is an Equal Opportunity Affirmative Action Employer 401

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Go ahead, try one of our apples .. DeSimone Freeman Genzer Hall Khan Spontak, van Zanten Biochemical Engineering Carbonell Hall Haugh Kelly, Kilpatrick, Ollis Peretti van Zanten Electronic Materials Carbonell Fedkiw Genzer Khan Lamb Parsons Molecular Thermodynamics Genzer Gubbins Hall Kilpatrick Spontak Carbonell DeSimone Fedkiw Freeman Grant, Ollis Overcash Peretti ,: :~ ,; I .. I _. ,,. --.;:.Carbonell Desimone Genzer Grant Gubbins Khan Kilpatrick Lim Parsons Spontak vanZanten LI Roberts I ;,..: :_ ....,.~~ ... .... I :,:.. .,. -= 1il:~ ... ... '"" ___ .._ I I -,/1'_. L~ ,I .. ,, NSFS&T Center: Environmentally Responsible Solvent Processes Reaction Engineering Fedkiw Gubbins Kelly, Lamb Lim Ollis Roberts Ranked #1 Ranked #12 in US in Southeast NRG Report(1995) ,r Partnerships with Research Triangle Park North Carolina Biotechnology Center Microelectronics Center of North Carolina Kenan Center for the Utilization of CO 2 and let your graduate education bear fruit. Department of Chemical Engineering North Carolina State University Raleigh, North Carolina 27695-7905 Visit us at www.che.ncsu.edu or send your admission questions to Professor R.J. Spontak (Rich Spontak@ncsu.edu).

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A nn e li se E. Barr o n Ph D ., Berk e l ey, 1995 Bi ose parati ons, biopol y m e r eng in ee rin g Li nd a J. Bro a db e lt Ph.D ., Delawar e, 1994 R eac ti on e n g ineering kin e ti cs mod e lin g pol ymer r eso ur ce r ecove r y Wes l ey R. Bur g hardt Ph.D ., Stanford 1990 P olyme r science, rh eo lo gy Bu ck l ey C ri s t Jr Ph D ., Duk e, 1 966 P o l y m e r science, thermod y nami cs, mechanics Jo s hua S Dranoff Ph D ., Princeton 1960 Ch e mical r e a c tion engineering, c hromat og raphi c separations Ki mberl y A. G r ay Ph D John s H o pkin s, 198 8 Catalys i s, treatm e nt technolo g i es, environmenta l c h e mistry H a rold H. K u ng Ph D. o rth westem 1974 Kin e ti cs, het e r oge n eo us catal ys i s W illi a m M. M ill e r Ph D ., Berkel ey, 1 987 Ce ll c ultur e for biot ec hn o l ogy and medicine Lyle F. M o c kro s Ph D ., B e rk e l ey, 1 962 B iomed i ca l e n g in eer ing, fluid m ec hani cs in biologi c al syste m s Mo ni ca Ol ve r a d e l a C ru z Ph D ., Cambridge, 1 984 Statisti c al m ec h anics in pol y m e r sys t e ms Juli o M Ottin o Ph D ., Minnesota, 1 979 Fluid me c hani cs, c haos mixin g in mat e ri a l s pro ce ssin g E. Te rr y Papout sa ki s Ph.D ., Purdu e, 1980 Biot ec hnolo gy of animal and mi crobia l ce ll s Bru ce E. Rittmann Ph.D. Stan ford, 1 979 In sit u bi o r e m e di a ti on, biofilms G r ego r y R ys kin Ph D ., Caltech 1 983 Fluid m ec hani cs, co mputational m e thod s, pol y meri c liquid s Lonnie D S hea Ph D ., Mi c higan 1 997 Ti ss u e e n gineering, ge n e therap y R a ndall Q. S nurr Ph D ., Berk e l ey, 1 994 Adsorpt i on and diffusion in p o r o us media mole c ular m o d e ling Me lod y A Swa rt z Ph D ., M.I.T ., 199 8 Bi omed i ca l transport ph e n omena J o hn M Tork e l s on Ph D. Minne so ta 1983 P oly m e r science, membranes Fa/1 1 999 U ID.Versaw Formfbrmati,onwulapplieationtothe gradua/E~wriJe Dir ector of Graduat e Admissions Departm e nt of Chemical Engineering M c Cormi ck School of Engineering a nd Applied Scien ce Northwestern Univer s it y E va n s t o n Illinoi s 60208-3120 Ph one: (847) 49 1 -7398 or (800) 8 48-5135 (U. S. on l y) E-mail: admissions-c h e m eng@nw u.edu or v i sit our website at www chem-eng.nwu.edu 403

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404 Chemical Engineering at FACULTY J. F. Brennecke H -C. Chang D A. Hill J. C. KantwD. T. Leighton, Jr. E. J. Maginn M. J. McCready P.J. McGinn A.E. Miller A.E Ostafin R. A. Schmitz M A. Stadtherr W. C. Strieder A.Varma E. E. Wolf RESEARCH AREAS Biological Photonic Devices Catalysis and Reaction Engineering Combustion Synthesis Environmentally Conscious Process De sign Enzyme Encapsulation Gas Liquid Flows Inorganic Membranes Molecular Modeling Nonlinear Dynamics Parallel Computing Physiological Dynamics Polymer and Suspension Rheology Process Dynamics and Control Statistical Mechanics Superconducting Materials Supercritical Fluids Thermodynamics and Separations The University of Notre Dame offers a program of graduate study leading to a Master of Science or Doctor of Philosophy degree in Chemical Engi neering. The requirements for a master's degree are normally com pleted in sixteen to twenty-four months. The doctoral program re quires about four years of full-time study beyond the bachelor's degree. We accept applications from students whose undergraduate degrees are in areas of science or engineering other than chemical engineering. Firtancially attractive fellowships and assistantships, which include a full-tuition waiver, are available to stu dents pursuing either degree. For further information!/ write or call Dr. David A. Hill Department of Chemical Engineering University of Notre Dame Notre Dame Indiana 46556 Phone : 1-800 -528-9487 E mail : chegdept.l@nd.edu www site: http://www nd.edu/-che g dept/ Chemica l Enginee rin g Education

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FACULTY [] Bha v ik Bak s hi Mass. I nst Tech. Proc ess Systems Engineering [] Robert S. Brodke y, Wisconsin Image P rocessing and Analysis Fluid Mechanic s [] J e ffr ey J C halm e r s, Cornell Bioengineering Ce ll C ul ture, lmmunomagnetic Cell Separation [] K e nn e th R. C ox I llinois-Urbana Statistical Mechanic s Molecular Thermodynamic s, Applied Computat i ona l Chemistry [] Jam es F Da v i s, Northwestern Knowledge-Ba se d Systems Decision Support, Data Interpretation [] LiangS hih Fan West Virginia Fluidization, Multiphase Flow Particulate Rea ctio n Engineering Particle Technology [] M artin Feinber g, Prin ce ton Complex Chemical Systems [] Morton H. Friedman Mich i gan Biomedical Engineering Hydrodynamic Effects in Vascular Disea se [] Kurt W Ko e llin g, Princeton Rheology of Complex Fluids Polymer Proce ssing Biocompatible Polymers [] Is amu Ku s ak a, Caltech Nucleation [] L. Jame s Le e, Minnesota Compo s ite and Polymer Processing, Polymer Characterization, Micro-Fabrication [] U mit S. Ozkan Iowa Stat e Heterogeneous Catalysis [] Jame s F. Rathman Oklahoma Colloids Interfaces, Molecular Se l f-Assembly [] David L. Tomasko Illinois-Urbana Excellent f acilities and a unique combinat i on of r esearch p r o j ects at t h e front i e r s of science a n d techno l ogy O utsta n ding faculty and student population who are dedicated and professional. Fina n cial support ranging from $14,5 0 0 to $ 1 9, 0 0 0 annually plus tu i tion C lose working r elationships between gra d uate stu d e nt s a nd facu l ty. Attractive campus mi n utes away fro m downtow n C o l u mb us For complete information w r ite, ca ll o r catch us on th e web at http : // www.c h e e n g.o hi o s t a t e.e du or write S up e r cr iti ca l F l uid Thermody n amics, Separations Materia l s Processing [] Shang-Tian Yan g, Purdue Professor Shang-Tian Yang Department of Chemical Engineering The Ohio State Uni v er s ity 140 West 19th Avenue Biotechnology Fermen t ation Cell Culture Tis s ue Engineering [] Jacque s L. Zakin New York Drag R educt i o n Rh eo l ogy M i crostructures of Surfactant So l ution s C olumbu s, Ohio 43210-1180 Ph o n e : (614) 292-6591 Fax: (6 1 4) 292-3769 Em ai l a ddr ess: c h e-gra d @c h e e n g.o h io s t a t e e du The O hio State Unive r sity is an equal opportunity/affirmative action institution. Fall 1 999 405

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406 Ohio University Chemical Engineering For More Information Co ntact : Graduate Programs The Department of Chemical Engineering offers pro gra m s l eadi n g to both the M.S. and Ph.D. degrees The department is l ocated in the Stocker Engineering Ce nt e r which r ecent l y (1994) underwent expansio n and n ow co ntain s some of the fi n es t state-of-the-art eq uipment avai labl e. The department's act i v iti es are e nh a nc ed by th e Stocker endowment, which was made possible by the generosity of Dr. C. Paul and Beth K. Stocker and which has n ow grown to over $14 million. The interest o n thi s e nd owme nt is used to he l p support research efforts in such ways as providing competitive graduate fe ll ows hip s and assoc i ateships, matching eq uipm ent fund s, and seed money for n ew project areas Research A rea s Multiph ase Flow a nd Assoc i ated Corrosion Coal Conversion Technology and Desulfurization Aeroso l Science and Technology Proce ss Contro l Separations Energy a nd Environmental Engineeri n g Thin Film Material s Chemical Reaction Engineering Wastewater Treatment Bioreactor Analysis Downstream Processing of Proteins Biom ed i ca l Engineering Financial Aid Financial s upp ort includes teaching and gra nt related associa t eships and fe ll owships ranging from $10 000 to $15 000 per twelve month s. In addition, st ud e nt s are granted a full tuition scho lar ship for both the regular and summer academic t e rm s. Stocker Fellowships are avai l a bl e to especia ll y well-qua li fied s tudents. The Facult y Ca l vin H. Baloun, P.E ., Emeritus ( Ph.D. Cincinnati, 19 62) W. J Ru sse ll Chen (Ph .D Syracuse 1974) Nicholas Dinos, Emeritus (Ph.D., Lehigh, 1967) Dou g l as J Goetz (Ph.D., Cornell, 1 995) Madan Gopal ( Ph.D. Ohio 1994) Tingyue G u ( Ph.D Purdue 1990) Daniel A. Gulino (Ph.D., lllinois 1 983) W. Paul J epson (Ph D., H e ri ot-Watt, 19 80) Michael E. Prudi c h Chair (Ph.D., West Virginia, 1979) Darin Ridgway P .E. (Ph.D., Florida State 1 990) Kendre e J Sampson ( Ph D Purdue, 1981) Ben J Stuart ( Ph D. Rut gers, 1 995) Valerie L. Young (Ph.D., Virginia Tech., 1 992) Director of Grad u ate Studie s Department of Chemical E n gineering 172 Stocker Center Ohio University, Athens OH 45701-2979 E-mail: c hedept @ bobcat.ent ohio u .e du Visit o u r website at : http : //www .ent.ohio u edu / che Ohio University is an affirmative ac ti on institution Chemi ca l Eng in eer in g Education

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Tlie University ef Okfalioma Graduate Studies in Chemical Engineering and Materials Science f/oue,eUue,~(Ut,~ ue,tk~aueu: &~ &~ 'P~ C ha i rman Graduate Program C ommitt ee S c ho o l of Chemi c a l En g i n ee rin g an d M at e rials S cie n ce Th e U n i versi ty of Okl a homa J OO E. Bo y d Room T-335 No rman O K 73 019-06 2 8 Phone : ( 405) 32 5-5811 Fax: ( 405) 32 5 5813 EMail: c lt eg ra d@)p u.edu F or mor e detailed informa t ion v isit o ur World W id e W eb s ite at: http: // www.ou edu/ ce mslnewsitelindex.html Th"o ;,m ;"'''"=; 1111 an Equal Opportunity Inst itutio n TM Faculty and Research Interests M i g u e l J. B aga j ew i cz Associate Professor process plant simu lation and data reconciliation design of heat / mass-exchange networks for waste minimization applications mathematical background, algorithm development and process design applica tions of optimization theory high temperature fuel-gas cleaning r eac tors modeling of fluid-solid diffusion-reaction problems Bill y L Cry n es Professor modeling of hydrocarbon pyrolysis surface effects during pyrolysis of hydrocarbons Brian P. Grad y, Assistant Professor e multiphase and block copolymers ion-containing polymers x-ray, neutron and light scattering biodegradable and bioabsorbable polymers orientation and orientation mechanisms in polymers Ro g er G. Ha rri s on J r. Associate Professor e production of proteins and peptides using recombinant DNA technology separation and purification of biochemicals enzyme reactors protein engineering drug delivery systems applications of biotechnology to waste treatment Je ffre y H Ha rwell Conoco/DuPont Professor tertiary oil recovery unconventional low energy separation processes m ass transfer dynamics of multicomponent mass transfer processes surface phenomena adsorption kinetics Lloy d L Lee C. M. Sliepcevich Professor thermodynamics molecular transport theory statistical mechanics structured liquids Monte Carlo and molecular dynamics studies confor mal solution theory natural gas properties polar fluids, ionic solutions, and molten salts surface adsorption turbulent flow La n c e L. L obb a n Associate Professor and Director catalytic reaction rate mechanisms and modeling partial oxidation of hydrocarbons e fuel cells Richard G. M allinson Associate Professor chemical reaction engineering polymerization synthetic and alternative fuels Ma thias U N oller t Assistant Professor biomedical enginee r ing cellular metabolism and transport fluid transport and mechanics E d ga r A O Re ar, II I Professor catalysis surface chemistry and physics kinetics blood trauma associated with medical devices biorheology organic chemistry coal technology Dimitr i o s V. P a p ava s s iliou Assistant Professor e modeling of transport processes novel computational methods applied to turbulent trasport of mass and heat r eac t ive flows, and flows in porous media integrated process simulations transport phenomena in biological systems small scale transport Daniel E Res a sco Associate P rofesso re heterogeneous catalysis, reaction engineering and kinetics design of catalysts for pollutant abatement transpo r t and adsorption in porous materials physical chemistry of surfaces characterization of ceramic supports M eli s sa M Rieger Assistant Professo r electrochemical pheno m ena and electrochemical engineering alternative ene r gy sources material systems and electroche m ical processes in mic r oelectronic processing optoelectronic integration into silicon electronics electroche m ica l behavior of po l ymeric m a t eria l s p hotochemical etching of silicon carbide porous silicon lu m inescence John F Sc a mehorn Asahi Glass Chai r e s u rface and co ll oid science tertiary oil recovery detergency m e m b r a n e separa tions adsorption pollution control poly m e r s pla s tics deinking Robert L Shamb a ugh Professor e polymerization chemistry polymer processing technology fiber spinning texturing and extrusion was t ewater enginee r ing physicochemical treatment ozonation gas-liquid reactions

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Oklahoma State University "Where People Are Important" Faculty Gary L. Foutch (Ph.D., University of Missouri-Rolla) K.A.M. Gasem (Ph.D., Oklahoma State University) Karen A. High (Ph.D., Pennsylvania State University) Martin S. High (Ph.D. Pennsylvania State University) A.J. Johannes (Ph.D. University of Kentucky) OSU's School of Chemical Engineering offers programs leading to M.S. and Ph.D. degrees. Qualified students receive financial assistance at nationally competitive levels. Randy Lewis (Ph.D., Massachusetts Institute of Technology) R. Russell Rhinehart (Ph.D., North Carolina State University) Robert L. Robinson, Jr. (Ph.D. Oklahoma State University) D. Alan Tree (Ph.D., University of Illinois) Research Areas Jan Wagner (Ph.D., University of Kansas) James R. Whiteley (Ph.D., Ohio State University) Visit our w e b pa ge at Adsorption Air Pollution Artificial Intelligence Biochemical Processes Corrosion Design Environmental Engineering Fluid Flow Gas Processing Hazardous Wastes Ion Exchange Kinetics Mass Transfer Modeling Phase Equilibria Polymers Process Control Process Simulation Thermodynamics For more information contact Dr. Robert L. Robinson http://www cheng.okstate.edu School of Chemical Engineering Oklahoma State University Stillwater OK 74078 RROBINS@OKWA Y.OKSTATE.EDU 408 C h emical Engineering Educat i on

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OREGON STATE Chemical Engineering M.S. and Ph.D. Fall 19 99 Programs Our programs reflect not only tradi tional chemical engineering fields but also technologies important to the Northwest's industries, such as elec tronic material processing, forest products, food science, and ocean products. Oregon State is located only a short drive from the Pacific O cean, white water rivers, hiking I skiing and climb ing in the Cas cade Mountains. FACULTY C. Chang Semiconductor Materials Device Physics A H. Hassan High Pressure Transport Pro cesses, Pharma ce uticals G. N. Jovanovic Fine Particle Processing, Transport Phenomena S. Kimura Reaction Engineering, High-Temperature Materials M. D. Koretsky Electronic Materials Processing K. L. Levien Process Optimi za tion and Control J. McGuire Protein Adsorption, Biofilm Development C. McConica Gas Solid Kinetics, Semiconductor Processing W. E. Rochefort Rh eological, Thermal, and Molecular Characteri zat ion of Pol y mers, Polymer Processing Biomaterials G. L. Rorr er Biochemical R eaction Engineering Competitive research and teaching assistantships are available. For further information, write: Chemical Engineering Department Oregon State University 103 Gleeson Hall Corvallis, Oregon 97331-2702 Visit u s on the web at www/che/orst/edu or e-mail u s at mail @c he.orst.edu 409

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410 University of Pennsylvania Chemical Engineering Pennsylvania's chemical engineer ing program is designed to b e fle x ible while emphasi z ing th e fundamental nature of chemical and ph y sical processes. Students may focus their studies in an y of th e research areas of th e d e partment. The full resources of this Iv y League university including the Wharton School of Business and one of this country's foremost medi c al centers, ar e a v ailabl e to students in the program The cultural advantages historical assets and recreational facilities of a great city are within walking distance of the University For additional information write: Dir ec tor o f Grad u a t e A d m ission s D e p a rtm ent o f Ch e m ica l E n g in eeri n g 3 1 1A To wne Buildin g U ni ve r s it y of P en n sy l van i a Phil a d e lphi a, P e n nsy l v ani a 191046 3 93 Eric T. Bod er Biotechnology Stuart W. Churchill Combus t ion, incineration Czac hr a l ski crystall i z ation, rate processes Russell J. Composto P o l y m eric materia l s science, su r face and i n terface studies Scott L. Diamond Endothe li a l ce ll mechano b i ology, drug and gene del i very bio i ranspo r t phenomena Dennis Discher Ce ll and molecular mechanics, biomembrane and bipolymer mesostructures and Junctions William C. Forsman P o l y m er science a n d e n ginee r ing, graphite intercalation Eduardo D. Glandt Classica l and statistical thermodynamics, random media Keith J. Gooch Tissue engineering and gene therapy Raymond J. Gorte H eterogeneous catalysis supported meta l s z eolites David J. Graves B ioc h emica l and biomedical engi n ee r ing biotechnology Daniel A. Hammer Ce ll ular b i oengineering, biointe r facia l phenome n a, adhesion Alan L. Myers Adsorption of gases and l iquids molecu l ar simula t ion Daniel D. Perlmutter Chemical reactor design, gas so l id reactions, gel ki n etics John A. Quinn M e mb rane trans p ort, b i oc h em i ca l /biomedica l eng i neering Warren D. Seider P rocess ana l ysis, simu l a t ion, design and control Talid R. Sinno T r ansport and reaction, statistical mec h anical modeling Lyle H. Ungar Ar t ificia l intelligence in p r ocess control, neural netwo r ks John M. Vohs Surface science, catalysis, electro ni c materia l s processing Karen I. Winey P o l ymer mo r phology, processing, and pro p erty inte rr elationships Chemi c al Engineering Education

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PENN STATE Individuals with a B.S. degree in chemistry or other related areas are encouraged to apply. For more information contact: Chairperson Graduate Admissions Cornrruttee Department of Chemical Engineering The Pe n nsylvania State University 158 Fenske Laboratory University Park PA 16802-4400 HTTP://GIBBS. CHE!PSU.EDU Fall 1 999 Chemical Engineering Aziz Ben-Jebria (Univ. of Paris )-Respiratory Transport, Inhalation Toxicology Ali Borhan (Stanford)-Fluid Dynamics, Transport Phenomena Alfred Carlson (Wisconsin)-Biotechnology, Bioseparations Lance Collins (Penn)-Turbulent Flow Combustion Wayne R. Curtis (Purdue)-Plant Biotechnology Ronald P. Danner (Lehigh)-Applied Thermodynamics, Adsorption Phenomen a Thomas E. Daubert (Penn State)-Applied Thermodynamics J. Larry Duda ( D elaware)Pol ymers, Diffusion, Tribology, Fluid Mechanics, Rheology David A. Edwards (Illinois Institut e ofTech.)-Transport Phenomena Dru g Delivery Kristen Fichthorn ( Michigan)-Statistical Mechanics Surface Science, Catalysis Costas D. Maranas ( Princeton)---Computational Chemistry, Design and Control Optimization Theory Themis Matsoukas (Michigan)-Aerosol Processes, Colloidal Particl es, Ceramic Powders John R McWhirter ( P enn State)--Gas-Liquid Mass Transfer, Microencapsulation R Nagarajan (SUNY at Buffal o )--Colloid and Polymer Science Joseph M. Perez (Penn State)-Tribology Lubrication Jonathan Phillips (Wisconsin) -H eterogeneo u s Catalysis, Surface Science John M. Tarbell (Delaware)---Cardiovascular Fluid Mechanics a nd Mass Transfer Turbulent Reacting Flows James S. Ultman (Delaware)-Physiological Transport Processes Environmental Health M Albert Vannice (Stanford)-Heterogeneous Catalysis Darrell Velegol (Carnegie Mellon)-Colloidal Systems Colloidal Particle Interaction s James S. Vrentas ( D elaware)-Tra n sport Phenomena, Applied Mathematics, Polymer Science Penn State is an affirmative action equal opportunity university. 411

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DEGREE PROGRAMS W h at 1 s PhD and MS i n Chem i cal Eng i neer i ng MS i n Petroleum Engineer i ng chemical eng1neer1ng For a more detailed answer and information abou t fellowsh i ps and applications wr i te or ca ll the Graduate Coordinator Department of Chemical and Petroleum Engineering 1249 Benedum Hall University of Pittsburgh Pittsburgh PA 15261 Phone: 412-624-9630 at Pitt? or visit us at our website http://www.engrng.pitt.edu/~chewww/ A short answer: applied enzymology biochemical engineering biotechnology chemistry of fossil fuels colloidal suspensions flow through porous media heterogeneous catalysis kinetics materials simulation microemulsions molecular thermodynamics organometallic chemistry particle technology petroleum engineering phase equilibria polymers process control process design protein engineering reaction engineering solids processing supercritical fluids FACULTY _________ Mohammad M Ataai Anna C Bal azs Eric J. Beckman Harve y S. Borovetz Shiao-Hung Chiang James T. Cobb, Jr Julie L. d ltri Robert M. Enick Joint appointment Dan Farcasiu Badie I. Mor si William Federspiel Robert Parker James G. Goodwin Jr. John F. Patzer Gerald D. Holder Alan J. Ru sse ll J Karl Johnson George E. Klinzing Vladmir Ko valc huk J. Thomas Lindt Joseph McCarthy Jerome S Schultz John W Tierney William R. Wagner Irving Wender University of Pittsburgh 412 surface chemistry transport phenomena .I ~, Chemical Engineering Education

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I};)@ !lili) !J @&JO & @@ !J@ @@ f? !J@@ @r?&J@J(Jj]&Jzl@ &j(l(Jj]@J/J@@ at Polytechnic University Build Your Bridge to a Better Future FACULTY Fall 19 99 N .P. Balsara microstructured pol y mer materials, scattering of light, X-ra ys and neutrons phase transitions, diffusion T K. Kwei pol y mer-pol y mer miscibility pha se relationships in pol y mers J. Mijovic dielectric properties of reactive polymers, in-situ real time monitorin g of processes, structural relaxation in g lass y polymers A.S. Mye r son crystallization, mass transfer E.M. Pearce pol y mer synthesis and degradation L. I. Stiel thermod y namics, properties of polar fluids E.N. Ziegler kinetics and reactor design, air pollution co ntrol W.P. Zurawsk y plasma polymerization, polymer adhesion Come to New York City's Polytechnic University, where a dynamic research-oriented faculty carries on a tradition of excellence and innovation in chemical engineering. For more information con ta ct Profe ssor K. Le von Department of Chemical Engineering Chemistry, and Materials S cie nc e Pol ytec hnic University Six MetroTech C e nter Brookl y n NY 11201 Phon e ( 718 ) 26 0 -333 9 413

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Graduate Studies in Chemical Purdue acuity L.F. Albright Emeritus R P Andres O.A. Basaran G.E Blau J.M Caruthers K.C Chao Emeritus D S. Corti W.N Delgass R.E Eckert E.I. Franses R.A. Greenkorn R E Hannemann R N Houze D.P. Kessler H S Lackritz J.H Lee J. Lauterbach J.F. Pekny N.A. Peppas D Ramkrishna G V Reklaitis E.M. Sevick-Muraca J.L. Sinclair R.G. Squires G.T. Tsao V Venkatasubramanian N.H.L. Wang P C Wankat esearch Areas Applied Mathematics Artificial Intelligence Biochemical Engineering Biomedical Engineering Catalysis and Reaction Engineering Colloids and lnterfacial Engineering Process Dynamics and Control Environmental Science Fluid Mechanics Fluid Particle Systems Materials and Microelectronics Processing Parallel Computing and Combinatorics Polymer Science and Engineering Separation Processes Surface Science and Engineering Thermodynamics and Statistical Mechanics Transport Phenomena ng1neer1n niversity ... ,.:.:-,. ., -, .,; inancial Assistance Fellowships Research Assistantships Teaching Assistantships egrees Offered Master of Science Doctor of Philosophy or More Information Graduate Studies Purdue University 1283 Chemical Engineering Bldg West Lafayette Indiana 47907-1283 Phone: (765) 494-4057 Web Address : http: //www. che purdue edu Purdue i s an equal access/equal opportunity university

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m THE UNIVERSITY ~ OF QUEENSLAND AC Fall 1999 Graduate study from a different perspective. Graduate st udy in the Department of Chemical Engineering at The University of Que ensland, Australia, offers an opportunity to broaden your socia l and cult ral perspectives while you are furthering oor career development. Situated in the vibrant Asia-Pacific region, the department ha s six research groups offenng exciting areas for grad uate st udy Adsorption and Engineering Science Bioprocess Engineering Computer Aided Proce ss Engineering Environmental Engineering Pla s tic s and Material Rheolo gy and Proces si ng Particle s and Fluid s. Join our 22 faculty and 140 Australian and international gra duate s tudents doing funaamental and applied re searc h in areas s uch as 'Adsorption Animal & Insect Cell Produ cts ,Environmental y_s tem V rmen ation Pro esses Fluidisation and Particle Mechanics Granulation H ybr idoma Technology Mi11eral Processing N merical Analysis Parti a} e Technolo y Pol ym er Processi11g Powder Pro cessing Pn c s Economics To obtain more information or a cop) of our postgraduate prospectus, please contact: Mr Ray .Johnson, Administrative Officer, Department of Chemical Engineering, The University of Queensland, St Lucia 4072 Queensland, email: info @, cheque.uq.edu.au Phone: +61 7 3365 4202 or fax: +61 7 3365 4199 or, isit our World Wide Weh page at http://,nrn.cheque uq.cdu.au 415

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Chemical Engineering at Rensselaer Polytechnic Institute The Chemical Engineering Department at R e nsselaer has long been recogni z ed for its exc e llence in teaching and research. !ts graduate programs lead to research-based M.S. and Ph.D. degrees and to a c ourse-based M.E. degree. Programs are also offered in c ooperation with the S c hool of Management and Technolog y which lead to an M.E. in Chemical Engineering and to an MBA or the M.S in Management. Owing to funding, consulting, and previous faculty experience, the department maintains close ties with industry. Department web site: http://www.eng.rpi.edu/dept/chem-eng/ Located in Troy New York Rensselaer is a private school with an enro llm ent of some 6000 students. Situated on the Hudson River, just north of New York 's capital city of Albany, it is a three-hour drive from New York City Boston and Montreal. The Adirondack Mountains of New York the Green Mountains of Vermont, and the Berkshires of Massachusetts are readily accessible. Saratoga with its battlefield, racetrack and Performing Arts Center (New York City Ballet, Philadelphia Orchestra and jazz festival) is nearby 416 Application materials and information from: Graduate Service s Rensselaer Polytechnic Institute Troy NY 12180-3590 Telephone: 518-276-6789 e-mail : grad-admissions @ rpi.edu http://www rpi edu/dept/grad-services/ Faculty and Research Interests Michael M. Abbott, abbotm2@rpi.edu Associate Department Chair Thermodynamics; equations of state; phase equilibria Elmar R. Altwicker, altwie@rpi.edu Spouted-bed combustion; incineration; trace-pollutant kinetics Georges Belfort, belfog@rpi.edu Membrane separatio ns ; adsorption ; biocatalysi s; MRI, interfacial phenomena B. Wayne Bequette, bequeb@rpi.edu Process modeling, control, design and optimization Henry R. Bungay m, bungah@rpi.edu Wastewater treatment; biochemical engineering Timothy S. Cale, calet@rpi.edu Semiconductor materials processing; transport and reaction analyses Steven M. Cramer, crames@rpi.edu Displacement, membrane, and preparative chromatogra phy; environmental research Jonathan S. Dordick, dordick@rpi.edu Department Chair Biochemical engineering; biocatalysis, polymer science, bioseparation s Arthur Fontijn, fontia@rpi.edu Combustion; high -te mperature kinetics; gas-phase reactions Shekhar Garde, gardes@rpi.edu Macromolecular self-assemb ly computer simu lation s, statistica l thermodynamics of liquids, hydration phenomena William N. Gill, gillw@rpi.edu Microelectronics; reverse osmosis; crystal growth; ceramic composites Howard Littman, Iittmh@rpi.edu Fluid/particle systems; fluidization, spouting pneumatic transport Charles Muckenfuss, Professor Emeritus E. Bruce Nauman, nauman@rpi .e du Polymer blend s; nonlinear diffusion; devolatilization; polymer structure and properties; plastics recycling Joel L. Plawsky, plawsky@rpi.edu Electronic and photonic materials; interfacial phenom ena; transport phenomena Hendrick C. Van Ness, In stit ute Profe ssor Emeritus Peter C. Wayner, Jr., wayner@rpi.edu Heat transfer; interfacial phenomena; porous materials Ch e mi c al Engin ee rin g Edu c ation

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Graduate Study in Chemical Engineering at Rice Th.e University Privately endowed coeducational school University 2600 undergraduate students 1300 graduate students Quiet and beautiful 300-acre tree-shaded campus 3 miles from downtown Houston Archit.ecturally uniform and aesthetic campus TheDepartn,em M ChE., M.S ., and Ph D. degrees Approximately 75 graduate students ( predominantly Ph.D. ) Stipends and tuition waivers for full-time students Special fellowships with high stipends for outstanding candidates Large metropolitan and cultural center Petrochemical capital of the world Industrial collaboration and job opportunities World renowned research and treatment medical center Professional sports Close to recreational areas Low cost of living SendApplicationscmd Inquiries to Chair Graduate Oimmittee Department of Chemical Engineering MS-362 Rice University 6100 S. Main St. Roust.on, TX 77005-1892 Additinnnl informntion is auailnbk ekctronicaJJy through ou r W o rl a Wid W e bhomepag e/,ocatedat http :// riceinfo rice.edu/-dek/CENG/index.html Fall 19 99 Applied Mathematics Bio c hemic al Engineering B iomedical Engineering Equilibrium Thermodynamic Properties Fluid Mechanics Interfaci al Phenomena Kinetics and Catalysis Polymer Science Proce ss Contr ol Reaction Engineering Rheolo gy Statistical Mechanics Tissue Engineering Tran sport in Porou s Media Transport Proc esses Transport Prop erties Faculty William W. Akers ( Michigan, 1950) Constantine D. Armeniades (Case Western R ese rve 1969) Walter Chapman ( Cornell 1988 ) Sam H. Davis, Jr. ( MIT, 1957 ) Derek C. Dyson ( London, 1966) Jacqueline Goveas ( Princeton, 1996) J. David Hellums ( Michigan 1961 ) Joe W. Hightower ( Johns Hopkins 1963) George J. Hirasaki ( Rice 1967 ) Riki Kobayashi ( Michigan, 1951 ) Larry V. McIntire ( Prin ceto n 1970 ) Antonios G. Mikos ( Purdue, 1988) Clarence A. Miller ( Minnesota 1969) Matteo Pasquali ( Minnesota, 1999) Mark A. Robert ( Swiss Fed Inst of T ec h ., 1980) Ka-Yiu San ( CalTech 1984 ) Kyriacos Zygourakis ( Minnesota 1981 ) --* Emeritus --417

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Department of Chemical Engineering University of Rochester Graduate Study and Research leading to M.S. and Ph.D. degrees Fellowships to $20,000 plus full tuition S. H. CHEN Ph D 1981 Minnesota Polymer S c ience and Eng in ee ri ng Organic Materials for Optics and Photonics D ev ic e Science E. H. CHIMOWITZ Ph.D. 19 82 Co nn ec ti c ut C r it i cal Phenomena Statistical M ec hanics of Fluids Computer Aided Design R.H HEIST Ph.D 1 972, Purdue Nucleation Ae r osols Ultrafine Particles S A. JENEKHE, Ph.D. 1985, Minnesota Polymer Scien ce and Engineering Materials Chemistry Optoelec troni c and Photoni c Materials and D evices J JORNE Ph.D. 1972, Ca li fornia ( Berkeley ) Electrochemical Engineering Microelectroni cs Processing Theoretical Biolo gy R.H. NOTTER Ph.D. 1969 Washington (Sea ttle ) M.D. 1980 Ro c h es ter Biomedical Engineering Lung Surfactant Molecular Bioph ysics H.J PALMER Ph.D. 1 971, Washington (Seattle) lnt erfacial Ph enomena Phase Transf e r R eac ti ons Mass Transf e r Bioengineering S V SOTIRCHOS Ph D. 19 82 H o u s ton Reaction E n gi n eering Transport and R eaction in Porous Media Proc ess ing of Cerami c Materials and Composites J. H. D. WU Ph.D. 19 87, M.I.T. Bio chemical Engineering ermentation Bi ocata l ysis B o n e Marrow Tissue Engineering Gen e tic and Prot ein Engineering 418 For further information and application write Graduate Admissions Department of Chemical Engineering University of Rochester Rochester New York 14627 Phone: (716) 275 4042 Fax: (716 ) 273-1348 e-mail: gradadm@che.rochester.edu Chemical Engineering Education

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THE STATE UNIVERSITY OF NEW JERSEY RUTGERS Graduate Program in Chemical & Biochemical Engineering Research Areas Biotechnology Chemical Engineering Science Environmental E n gineering Pharma ce uti cal Engineering Polymers Faculty Helen M. Buettner Associate Profe sso r ; Ph D ., University of P ennsylvania 1987 Applied neurobiolog y ce ll motility ce ll -s ubstrate interactions crys talli z atio11 of pharmaceuticals Yee C. C hiew Profe ssor; University of P e nn sy l vania 1984 sr. Alkis Constantinides, Profe sso r and Chair; D applied numeri c al analysis, artificial int ? Pi C structu r es of fluids a11d particle s y stems int erfac ial phe n ome 11 a 1eeri11g optimiza ti o11 and co ntrol of fe rm e 11tation pro cesses, : ::::7:::: :::~ : ~ ~7J~t l ~~ : t1!~r2 ,~ ~:i:: :~:::::::: : :,I:::, :::::, :::= .~v .;: .. t ~ Prof ;sso r; ; ~~:b:, ~~w : ~1\ ~~s ~ ~;~ 1 f ; plr:{hfi~~ ;;; ;j~~:;, : t\fl{} ~;} t d~ idenvironme'.,1; ii l 1t!tte ngineeri11g, t11rbu/e11t transport Cessor Ph D f fl~~ot ) J9 ~5 ~iJr~ '. g .,~. a '.'. 'i tlgr m(ifif i~~$ .. : : .. .. : .. y .. ',. p:,~,~ll1i s11spe 11si o11s; nonlinear { #~;::~ ~i,;: ~qi::;fy;l ".) dit 4);::z;:;,;t::;~:, .. ,,,;,,. ,,,~,,,,,,. }~ ,; ~/ : ffi,pws ~: (!Mi fl kri t a;,i lt~/ large d y namical Marianthi G. I a/y-sii h,1~ r&c1iu1.teJhne?tf/!i ;' a ut o mat ed kinetic i::a:1,~:~tj~~t nt Profe sso r ; Pt ; o : : D~~ e David S. Koss .:.::: \ biodegradable polymers in medicine c ardio vq,k uiar materials Fernando Muzzio, Asso d\~ ;e Profe ss .. Balaji Narasimhan, Ass imaging co ntroll ed d Brian A. Newman, Pro~ physics t:;r, ,1 'rf' ';;:~~:;:}~~f "(ljl:~::::.:::::::,:::,,,, \ ; ~rsity j \:l ~/bciit n1( J! eng in eef!ft, ;;, i fu?Bl~\fd~i911ii[ P(g Henrik Pedersen Profes so r ; Ph D Carlos B. Rosas Visiting Profes so r and pharmaceuti c als and biologicals ve bi r tfur&, 1J131:g;teuti~al En/geer\_~~ Pf6gfan1; MJ Ml~!&%s In s titut e of Technology, 1968 Fine c h emica ls Jerry I. Scheinbeim, Professor; Ph.D University of materials.ferroelectric pie z oelectric, p y roele c tri c, diel ec tr( 7;: e' '.~ /ectr oac ti ve propenies relationships in pol y m eric of polymers Shaw S Wang Profe sso r; Ph.D. Rutger s Unive r sity, 1 970 Kin ~i(l 'fi;id themwd y i1a ;;;/ cs of food process engineeri n g, a nd stud i es of biochemical and biological processes. Martin L. Yarmush, Visiting Profe ssor; Ph .D., Rockefeller University, 1979 ; M.D. Yale University 1984 Applied immunology, artificial orga n s, bioseparations, protein e n gineering, biotechnolog y FELLOWSHIPS TRAINEESHIPS, AND ASSISTANTSHIPS A VAi/ABLE For further information contact: Graduat e Pro gra m Dep a rtment of Ch emica l a nd Biochemic a l Engineering Rut gers, The State University of New Jer sey 98 Br ett R oad Pi scataway, NJ 08854 8058 Ph one (732) 445-4950 Fax ( 732 ) 445-2421 Email : cbemai l @sol. rut ge r s.e du http ://so l.rut ge r s.ed u/ Fall 1 999 4 1 9

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The National University of Singapore Department of Chemical and Environmental Engineering Found e d I 905 Singapore's strategic location has long been es teemed as the gateway to Asia. Situated in the heart of Asia just above the equator, the rich and diverse cultu r al background of this small tropical island has never failed to amaze its audience with different perspectives. The National University of Singapore is the landmark of pride in Singapore. Located on th e scenic Kent Rid ge hills the camp u s overlooks the western coast of Singapore and off-shore petro l eum refineries and petrochemical industries. The Department of Chemical and Environmental Engineering takes pride in being the sole institution responsible for the training of professional chemi cal and environmental engineers with a strong back ground in process engineering in Singapore the world's third largest petroleum refining centre. With a current strength of more than 40 faculty members and supported by m ore than 70 technical and re search staff, the Departm ent strives to provide stu dents and staff with the state-of-the-art research facilities and a conducive environment for creative and dynamic research. Financial assistance is available to qualified ap plicants in the form of tuition fee research scholar ship and research studentship. Contact Us At: 420 The National University of Singapore Department of Chemical and Environmental Engineering 10 Kent Rid ge Crescent Singapore 117576 Tel: (65) 874-2186 Fax : (65) 779-1936 E-mail: chehead@nus.edu.sg http :/ /www.eng.nu s.ed u .sg /ChemEn g / Research Areas Separation & Purification I Ad sorption Separation Liquid Chromatography Liquid Membrane Memb rane Separation Technology Materials & Devices P olymers C rystals C atalytic Material s Ultr a Thin Films S ensors, Electrochemical Device s Chemical Engineering Fundamentals I Tran sport Phenomena Proce ss Control, Modeling and Optimization R eaction Engineering Thermodynamics Environmental Science & Engineering A erosol Technology Environmental Chemistry Rem ediation and Decontamination Biolo gical Treatment Acade1nk Prognuns Undergraduate Level Bachelor of Engineering ( Chemical ) Bachelor of Engineering (Environmental) Postgraduate Level Coursework-based Postgraduate Diploma (Environmental Engineering) Master of Science (Chemical Engineering) Master of Science (Environmental Engineering) Ma s ter of Science ( Safety Health & Environmental Technology ) Research-based Master of Engineering Doctor of Philosophy Chemical Engineering Edu c ation

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The University of South Carolina Graduate Studies in CHEMICAL ENGINEERING The Department of Chemical Engineering at the University of South Carolina is booming! External re s earch funding is at an all time high-exceeding $4 000,000 per year-and the department i s still growing with a charter to increase its faculty size by at least one more faculty member. As a result thi s progressive department, with its young (average age < 40) and dynamic faculty, is al220 000 square foot John E Swearingen Engineering Center, w here the faculty teach a nd conduct research in state of -the-art facilities. In addition, programs are offered that lead to both MS and PhD degrees; and PhD candidates are offered full tuition waiver and highl y com petitive, twelve-month stipends ranging from $1,575 to $1,975 per month. So come to one of the fastest growing areas in the country, enjoy the beautiful weather and the ideal location (1.5 hrs to the beach 2 hrs to the mountains), an d be part of the explosion in Chemi ca l Engineering at the University of South Carolina ready recognized as one of the top teaching and research programs in the Southeast. Chernical e n gi n eeri n g occ u pies over o n e-t hird of the new and innovative Stipend Levels $18,900 to $23,700/yr Tuition Waiver Stipends Fall 1999 Faculty M.D Amiridis, Wisconsin P B. Balbuena, Texas F.A. Gadala-Maria Stanford J.H. Gibbons Pittsburgh K.A Kosanovich, Notre Dame M A. Matthews, Texas A&M T. Papathanasiou, McGill Re se arch Areas Adsorption Technology Batterie s and Fuel Cell s Colloids and Interfaces Composite Materials Corrosion Engineering Crossflow Filtration H.J Ploehn, Princeton B.N Popov, Illinois J A. Ritter SUNY Buffalo T.G. Stanford, Michigan V Van Brunt Tennessee J.W. Van Zee, Texas A&M J.W. Weidner, NC State R.E. White, Berkeley C T Williams, Purdue Heterogeneou s Cataly s i s Numerical Methods Phase Equilibria Pollution Prevention Process Control Process Design Rheology Separations Sol-Gel Processing Solvent Extraction Surface Science Surface Spectroscopy Supercritical Fluids Waste Management Waste P