Chemical engineering education

http://cee.che.ufl.edu/ ( Journal Site )
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Material Information

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

Subjects

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

Notes

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-

Record Information

Source Institution:
University of Florida
Rights Management:
All applicable rights reserved by the source institution and holding location.
Resource Identifier:
oclc - 01151209
lccn - 70013732
issn - 0009-2479
sobekcm - AA00000383_00170
Classification:
lcc - TP165 .C18
ddc - 660/.2/071
System ID:
AA00000383:00170

Full Text


























c
chemical engineering education














Joseph Reynolds
... of Manhattan College









Binous
-o




u Random Thoughts: Turning New Faculty Members Into Quick Starters (p. 51)
V1 Brent, Felder
C
M Incorporating Six Sigma Methodology Training into Chemical Engineering Education Ip. 53)
Dal
F- a An Internet-Based Distributed Laboratory for Interactive ChE Education (p. 24)
c< Guo, Kettler, AI-Dahhan
C The Chemical Engineering Behind How Pop Goes Flat: A Hands-On Experiment for Freshmen (p. 14)
.! n Hohn
>
S ._ The Devil's in the Delta (p. 19)
0 E Luyben
-r ^Implementation and Analysis of Hemodialysis in the Unit Operations Laboratory (p. 65)
o.- Madihally, Lewis
C- 0
2 i Future of Chemical Engineering: Integrating Biology Into the Undergraduate ChE Curriculum (p. 43'
LU Mosto. Savelski, Farrell. Hecht
S A Realistic Experimental Design and Statistical Analysis Project (p. 31)
E -c Muske, FMyers
- u Forced Convection HeatTransfer in Circular Pipes (p. 39)
Tosun




SPolytechnic University











aMg -teaching tips


This one-pagecolumn will present practical teaching tips in sufficientdetail thatChE educators can
adopt the tip.The focus should be on the teaching method, not content. With no tables orfigures
the column should be approximately 450 words. If graphics are included, the length needs to be
reduced.Tips that are too long will be edited to fit on one page. Please submit a Word file to Phil
Wankat , subject: CEE Teaching Tip.



TEACHING TIP: ELEVATOR TALKS

PHIL WANKAT
Purdue University West Lafayette, IN 47907


Both industry and ABET require that engineering gradu-
ates can communicate. Clearly the best way to achieve this
is to have frequent assignments throughout the curriculum
requiring writing and oral presentations. Unfortunately, oral
presentations tend to require a significant amount of class
time. An alternative oral presentation is the "elevator talk."
The scenario: a student steps into an elevator with someone
she needs to persuade or sell. For example, the student may
want to convince the person to hire her. She has from one to
two minutes to do this.


lassignedthe
topictothestu-
dents (askfor a
job),gavethem
the time (two
minutes), gave
them a copy of
the scoring ru-
bric (Table 1),
and told them
to prepare a
talk that they
will present
extemporane-
ously, without
visuals. There
was no written
assignment. In
class, assigned
the "boss" for
each person.
Students were


told to assume that they knew the boss well enough to talk
to. Presenters and bosses went to the front of the room and
stood in the elevator. Talks were timed for a strict two min-
utes. Since two minutes is actually fairly long, most students
finished early and had to do something-perhapsjust stand
there-for the remaining time. If they weren'tfinished attwo


minutes, the elevator door opened anyway and they had to
summarize very quickly.

The students saw the relevance of elevator talks and were
well prepared. Grading the talks with the scoring rubric was
straightforward and I was able to finish the grading while
the next pair walked to the front. Since it takes less than 30
secondstochangespeakers, 20two-minutetalkscan bedone
in a 50-minute period.

While not eliminating the need for more formal presen-


stations, eleva-
tor talks can
provide an
easy way to
include oral
communica-
tion in courses
that normally
would not
have time.
Grading all of
the talks with
the scoring ru-
bric and then
saving cop-
ies provides
evidence for
ABET that all
students have
been assessed
and can do
oral presenta-


tions, at least at the barely acceptable level.

REFERENCES
1. Mitchell, B.S., and VJ. Law, "Community-Based Presentations in the
Unit Ops Laboratory,"Chem. Eng. Ed., 39(2), 160 (2003)


SCopyright ChE Division of ASEE 2006


TABLE 1
Scoring Rubric for ElevatorTalks. Adapted from Mitchell and Law.!'
Attribute Not Barely Meets Exceeds
Acceptable Acceptable Expectations Expectations
Logical topic Disjointed; no Parts out of Organized by Superior;
order organization order guidelines enhancescom-
munication
Appropriate Far too long or Somewhat Appropriate
time use too short long or short length
Objective Not stated Poorly stated Clearly stated
Background & Neither stated Only one Both stated Both clearly
Significance stated stated
Conclusions None Present, but Logical & Logical& supe-
not logical clearly stated riorexplanation
Presentation Many Some No distractions Superior
mechanics* distractions distractions presentation
Response to Notresponsive Incomplete Clear and Complete
questions (if any) direct
Focus on person Not focused; Some focus; Focused with Totally
speaking to distracted, no some eye good eye focused; excel-
eye contact contact contact lenteyecontact
*voice, poise, mannerisms














Author Guidelines for the

LABORATORY

Feature

The laboratory experience in chemical engineering education has long been an integral part
of our curricula. CEE encourages the submission of manuscripts describing innovations in the
laboratory ranging from large-scale unitoperations experimentsto demonstrationsappropriate
for the classroom. The following guidelines are offered to assist authors in the preparation of
manuscripts that are informative to our readership. These are only suggestions, based on the
comments of previous reviewers; authors should use their own judgment in presenting their
experiences. A set of general guidelines and advice to the author can be found at ourWeb site:
.

c Manuscripts should describe the results of original and laboratory-tested ideas.
The ideas should be broadly applicable and described in sufficient detail to
allow and motivate others to adapt the ideas to their own curricula. It is noted
that the readership of CEE is largely faculty and instructors. Manuscripts must
contain an abstract and often include an Introduction, Laboratory Description,
Data Analysis, Summary of Experiences, Conclusions, and References.
An Introduction should establish the context of the laboratory experi-
ence (e.g., relation to curriculum, review of literature), state the learning
objectives, and describe the rationale and approach.
The Laboratory Description section should describe the experiment in
sufficient detail to allow the reader to judge the scope of effort required
to implement a similar experiment on his or her campus. Schematic dia-
grams or photos, cost information, and references to previous publica-
tions and Web sites, etc., are usually of benefit. Issues related to safety
should be addressed as well as any special operating procedures.
If appropriate, a Data Analysis section should be included that concisely
describes the method of data analysis. Recognizing that the audience
is primarily faculty, the description of the underlying theory should be
referenced or brief.The purpose of this section is to communicate to the
reader specific student-learning opportunities (e.g., treatment of reac-
tion-rate data in a temperature range that includes two mechanisms).
The purpose of the Summary of Experiences section is to convey the
results of laboratory or classroom testing. The section can enumerate,
for example, best practices, pitfalls, student survey results, or anecdotal
material.
A concise statement of the Conclusions (as opposed to a summary) of
your experiences should be the last section of the paper prior to listing
References.













EDITORIAL AND BUSINESS ADDRESS:
( Ih nr, all I. unimi i ml, Education
Department of Chemical Engineering
University of Florida Gainesville, FL 32611
PHONE and FAX : 352-392-0861
e-mail: cee@che.ufl.edu

EDITOR
Tim Anderson

ASSOCIATE EDITOR
Phillip C. Wankat

MANAGING EDITOR
Lynn Heasley

PROBLEM EDITOR
James O. Wilkes, U. Michigan

LEARNING IN INDUSTRY EDITOR
William J. Koros, Georgia Institute of Technology

EDITORIAL ASSISTANT
Nicholas Rosinia




-PUBLICATIONS BOARD

CHAIRMAN
John P. O'Connell
University of Virginia

PAST CHAIRMAN *
E. Dendy Sloan, Jr.
Colorado School of Mines

MEMBERS
Kristi Anseth
University of Colorado
Thomas F. Edgar
University of Texas atAustin
Richard M. Felder
North Carolina State University
H. Scott Fogler
University of Michigan
Carol K. Hall
North Carolina State University
Steve LeBlanc
University of Toledo
Ronald W. Rousseau
Georgia Institute of Technology
C. Stewart Slater
Rowan University
Donald R. Woods
McMaster University


Winter 2007


Chemical Engineering Education
Volume 41 Number 1 Winter 2007


> DEPARTMENT
2 Chemical Engineering at Polytechnic University
Edward N. Ziegler, Jovan Mijovic


> EDUCATOR
10 Joseph Reynolds of Manhattan College
Helen C. Hollein

> RANDOM THOUGHTS
51 Turning New Faculty Members Into Quick Starters
Rebecca Brent, Richard M. Felder

> CLASSROOM
14 The Chemical Engineering Behind How Pop Goes Flat: A Hands-On
Experiment for Freshmen
Keith L. Hohn
31 A Realistic Experimental Design and Statistical Analysis Project
Kenneth R. Muske, John A. Myers
39 Forced Convection Heat Transfer in Circular Pipes
Ismail Tosun
53 Incorporating Six Sigma l .I. ...I. I. Training into Chemical Engi-
neering Education
Lenore L. Dai

> CURRICULUM
43 Future of Chemical Engineering: Integrating Biology Into the Under-
graduate ChE Curriculum
Patricia Mosto, Mariano Savelski, Stephanie H. Farrell, Gregory B. Hecht

> LABORATORY
19 The Devil's in the Delta
William L. Luyben
24 An Internet-Based Distributed Laboratory for Interactive ChE Education
Jing Guo, David J. Kettler, Muthanna Al-Dahhan
65 Implementation and Analysis of Hemodialysis in the Unit Operations
Laboratory
Sundararajan V Madihally, Randy S. Lewis

> CLASS AND HOME PROBLEMS
59 Introducing Non-Newtonian Fluid Mechanics Computations With
Mathematica in the Undergraduate Curriculum
Housam Binous


57 Book Review


CHEMICAL ENGINEERING EDUCATION (ISSN 0009-2479) is published quarterly by the Chemical Engineering
Division, American Societyfor EngineeringEducation, and is edited at the University ofFlorida. Correspondence regarding
editorial matter, circulation, and changes of address should be sent to CEE, Chemical Engineering Department, University
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1










rj[ department
---- U s_____________________________________


Chemical Engineering at


Polytechnic University


EDWARD N. ZIEGLER
AND JOVAN MIJOVIC
T he Brooklyn Colle-
T giate and Polytechnic A
Institute was chartered
in 1854, when the city of .
Brooklyn's rapidly growing
population was 30,000 and
Brooklyn was separate from :
New York City. This was
roughly 30 years before the
completion of the Brooklyn
Bridge and prior to the Civil '
War. The stated purpose of the
first Polytechnic Board was to
establish "an educational insti-
tution in our midst,... to give 7 0
our sons an education as would i ".
qualify them in a far higher ':
degree, through an enlarged, "' i
liberal, and thorough training i
in a course of practical, scien-
tific, and classical studies, to
enter upon the active pursuits
and duties of life," and "that its .. !
location should be as central, -'
and as easily accessible as pos- i
sible by public conveyance, i
from all parts of the city ...."
In its earliest years, the college
drew students from the man-
sions and substantial homes of
the "Heights," the "Hill," the
"Eastern District," and other
parts of Brooklyn.
The Scientific Program lead-
ing to the Bachelor of Science
degree was established for
those bent in the direction A preserved picture of life
of science and engineering,
which in addition to theory included more than "200 laborato-
ry experiments, field trips, and exercises." Between 1885 and
1890 the "Scientific" course of study was ultimately divided


r ..:."


at Polytechnic's main campus at the beginning of last century.

into three areas of specialization: Engineering (Mechanical
and Civil), Electrical Engineering, and Chemistry. The latter
had offerings in applied and fundamental areas


@ Copyright ChE Division of ASEE 2007


Chemical Engineering Education










In 1898, Brooklyn became a part of New York
City. Like Brooklyn, Polytechnic's services and
influence have gone far beyond the borders of
the Borough, through the university's worldwide
contributions to science, engineering, and educa-
tion. Polytechnic's modem Brooklyn site is still
only two blocks from the Brooklyn Bridge, and
all three of the city's major subway systems have
stations within a few blocks of the Polytechnic,
maintaining the spirit of its original charter.
Chemical engineering at Polytechnic University
had its formal beginnings more than a century ago
when the Department of Chemistry became the
Department of Chemistry and Chemical Engineer-
ing at the Polytechnic Institute of Brooklyn, or
PIB. I.W. Fay was the first head of the combined
department in 1905, with only one chemical engi-
neer on the staff-John C. Olsen. In those days,
extensive use was made of eminent professionals
in local industries as "consulting professors."
In 1925, the chemical engineering program at Polytechnic
became one of the first engineering programs to receive
accreditation by a national professional society, when the
American Institute of Chemical Engineers (AIChE) listed it
among the first 15 accredited curricula in chemical engineer-
ing. In 1931, a separate Department of Chemical Engineering
was established, with Olsen as its first head. That same year
Olsen was elected president of the AIChE, which he helped
found (and for which he served as secretary for its first 23
years). Since then, more than 2,800 bachelor's, 1,000 master's,
and 350 doctoral degrees have been awarded in chemical
engineering at Poly.

THE OTHER YEARS
In 1932, then-28-year-old chemical engineer Donald F.
Othmer was hired into Olsen's department, after an impressive
five years of work at Eastman Kodak in Rochester, N.Y.
Kodak was the world's largest manufacturer of cellulose
acetate, a key ingredient in photographic film. A critical step
in creating cellulose acetate is concentrating the acetic acid
used in production. While in Kodak's employ, Othmer was
tapped to find ways to increase the acetic acid concentration
in various sources available to the company. Initially knowing
little about the subject, but always curious, Othmer designed
an experimental device to observe how acetic acid is distilled.
The apparatus he built became famous as the Othmer Still
and continues to be used to study the properties of mixtures
being distilled. The early version of the still was typical of
Other's hands-on, low-cost approach to science: He not only
conceptualized and designed the apparatus, but also learned
glass-blowing so that he could build it himself.
The Othmer Still allowed chemists and engineers to mea-


The Chemical Engineering Laboratory about 1919.

sure accurately for the first time concentrations in the vapor
and liquid phases in equilibrium.
Other also contributed greatly to the science of azeotropic
distillation, which introduces a third chemical during the
distillation process to improve the purity of the product and
reduce energy consumption. Thanks to Othmer, distillation
is now a science. His geometrical and mathematical instincts
were applied further to devise a figure in which the effects of
temperature on vapor pressure of various compounds could
be correlated as straight lines on a single sheet of paper, the
now-famous Othmer plot.
As a well-known chemical engineer, Othmer succeeded to
the chairmanship in 1937 and remained head of the depart-
ment until 1961, when he stepped down to devote more time
to teaching and research. He has authored hundreds of articles
and held numerous patents for chemical engineering applica-
tions. Around 1945 Raymond E. Kirk, head of the Depart-
ment of Chemistry, and Othmer, heading the Department of
Chemical Engineering, decided to embark on a project as
co-editors of an encyclopedia that would be a comprehensive
guide to industrial chemistry and chemical engineering. The
Kirk-Othmer Encyclopedia of Chemical Technology is now in
its 5th edition and comprises 27 volumes. It is the first place
chemists and chemical engineers turn when they are starting
a new project. It has everything from the commonplace to
the esoteric, from how to make batteries and beer to how
to reduce nitrobenzene. A set may be found in the library of
virtually every major university in the world.
When Othmer died in 1995 he bequeathed more than $175
million dollars to the Polytechnic, which remains as of today
the largest donation ever given to the university. Much of the
gift went to improving and expanding the university labora-


Winter 2007










tory and classroom facilities, with some to construction of a
new dorm and gymnasium. An interesting side note: If the
remaining professors had joined Othmer 30 years earlier in
the investment club he started at Poly-based on the advice
of a family friend named Warren Buffet-they all would've
been rich; but even sharing a fraction of the membership
fee of $25,000 would have been rather difficult for a faculty
member in those days.
Don Othmer supervised and inspired more than 60 doc-
toral students, many of whom went on to distinguished
careers in their own rights. He supervised research in the
fields of thermodynamic property estimation, distillative
and extractive separations, fluidized bed design, and energy
optimization. Having no biological children, he was quoted
as saying he regarded himself most fortunate to have been
blessed with so many brilliant "academic children" whom he
could recognize with almost-paternal pride. One of Othmer's
former students was Ju Chin Chu, who from 1950 to 1966
supervised fundamental distillation experiments on more
than 100 industrially important chemical mixtures. Chu,
in turn, must have passed along a high regard for research
and genes as well: His son, Steven Chu, won the Nobel
Prize in Physics in 1997.
Speaking of Nobel Prize winners, a corecipient of the 1995
Nobel Prize in Physics, Martin L. Perl, earned his chemical
engineering bachelor's at Poly in 1948 (followed by a Ph.D.
from Columbia). Perl was honored for the discovery of the tau
lepton, one of nature's most remarkable subatomic particles with
a mass 3,500 times that of the electron. In 1982, Perl's promise
had already been recognized closer to home: That year, he was
awarded the Wolf Prize for Physics for the Class of 1948.
In the '50s Othmer was able, through fund raising and
departmental equipment gifts from industrial colleagues, to
persuade Warren L. McCabe to come to Poly and become
administrative dean. A leading educator and consultant for-
merly at Cornell University, McCabe is, of course, famous
for the McCabe-Thiele diagrams of binary distillation, as
well as being coauthor of McCabe, Smith, and Harriott's Unit
Operations of Chemical Engineering.
Othmer already had a master craftsman of laboratory
equipment on staff, W. Fred Schurig (Poly '33, '35, and
'46) who constructed one of the finest teaching laboratories
in America-Poly's Unit Ops Laboratory. While at Poly and
after he retired, Schurig designed and built laboratories for
many schools throughout the Americas. Schurig became
known for his discipline and attention to detail, which he later
attributed to Othmer's influence.
Perhaps the most famous of Othmer's doctoral students,
Joseph J. Jacobs, also earned all three of his degrees at the
Polytechnic, receiving his Ph.D. in 1942. Jacobs developed a
system that could manufacture soap in 15 minutes compared
to the traditional process that required between three and


seven days. Jacobs was an assistant professor at Polytechnic
for a while and then headed west to San Francisco to take
a position assisting in the engineering of liquid fertilizers.
After doing consulting work for two years at Kaiser Alumi-
num and Chemical Company-at which he helped develop
caustic soda-Jacobs started his own business. In 1947, he
founded Jacobs Engineering Group Inc., an international
firm that Fortune magazine ranked No. 1 in 1999 as the
most admired engineering and construction company. In ad-
dition to authoring numerous articles on chemical engineer-
ing and economics, Jacobs made substantial contributions
to the study of social issues-including aging parents of
adult children-and authored two autobiographies. He was
recipient of the United Engineering Society's 1983 Herbert
Hoover Medal, which recognizes the civic and humanitar-
ian achievements of professional engineers. The university
also established the Joseph J. and Violet J. Jacobs Chair in
Chemical Engineering, and in 2002 opened the Joseph J. and
Violet J. Jacobs Building on campus, housing a full gymna-
sium and athletic center as well as state-of-the-art laboratories
and classrooms.
Another well-known doctoral student of Othmer, Ger-
hard Frohlich, earned his Ph.D. in chemical engineering
at Poly in 1957. He was the second member associated with
the Polytechnic to become president of AIChE, elected in
1999. Earlier he had been named corporate vice president
and general manager of Central Engineering at Hoffman-La
Roche, where for many years he engaged in the development,
design, and construction of chemical and pharmaceutical
facilities. In commenting on the importance of AIChE,
Frohlich said, "We must think globally, accept cradle-to-
grave stewardship of products, and strive for sustainable
development. Professional societies can lead the way by
facilitating dialogue among industry, government, academe,
and the public. By working together in new and more flex-
ible ways, using renewable resources, and learning from
advances in chemistry and biotechnology, we can make
products that enhance the quality of life and protect the
environment. If we commit to doing so, the new millennium
looks bright indeed."
Yet another of Othmer's students, Robert F. Benenati, had
a long and successful career as a professor who challenged stu-
dents to do more than they ever thought possible, particularly
in his design class. Warren Seider, a Poly graduate now at the
University of Pennsylvania, is in turn one of Benenati's former
students, and is coauthor of the major design text Product and
Process Design Principles, now in its 2nd edition.
In the '60s and '70s James J. Conti (Polytechnic '54, '56,
and '59) and Irving F. Miller were department heads through
a financial crisis, in which PIB merged with the NYU school
of engineering to form the Polytechnic Institute of New York,
with its main campus remaining at the Brooklyn site. In 1985,
the school was renamed Polytechnic University.
Chemical Engineering Education











Below, Don Othmer poses with a gold-plated
version of the invention he created in 1928,
the Othmer Still. Left, Othmer is seen with
Raymond Kirk, head of Poly's chemistry
department circa 1945 and co-editor of the
pair's comprehensive encyclopedia, now in
its 5th edition.


Rounding out the era, Leonard Stiel has carried the Othmer
tradition into the computer age; his work is cited widely in
the literature of thermodynamic and transport properties of
fluids and mixtures. Stiel officially retired a few years ago
but now as a research professor he's still very active at Poly
in education and as a consultant.

THE POLYMER CONNECTION
In the early part of the 20th century, many prominent chem-
ists dismissed the idea that molecules with molecular weights
in the thousands or millions could exist. Today, polymers are
everywhere, in everyday materials such as plastics, nylon, and
rubber. The year 1939 marked the introduction of a polymers
course in the chemical engineering department. That year,
chemical engineering professor Paul F. Bruins joined Poly
from the University of Iowa and offered the first graduate
course in polymer technology in the United States, paving the
way for what has become one of the most famous polymer
programs in the world. Bruins was affectionately called the
"walking encyclopedia" of plastics, and he wrote and edited
extensively. He was known to take his colleagues for a spin
in his small aircraft during the day and return in time to teach
his polymer course in the evening.
Much of today's widespread acceptance of polymers, their
chemistry, and their engineering is the result of work by the
Polymer Research Institute (PRI) of Polytechnic University.
Herman Mark, a pioneer in the study of giant molecules,
established the PRI in 1964. The institute brought together a
Winter 2007


* number of polymer researchers to create the first
academic facility in the United States devoted
to the study and teaching of polymer science.
Many scientists associated with the institute later
went on to establish polymer programs at other
universities and institutions, contributing significantly to the
development and growth of what has become a vital branch of
chemistry, engineering, and materials science. Under Mark's
leadership, the institute became the premier U.S. destination
for polymer chemistry, attracting students from all over the
world. But its effect wasn't limited to simply establishing
the importance of polymer chemistry and contributing
many of its fundamental discoveries-like colonists, PRI
alumni went on to found a number of polymer institutions
at other locations.
The American Chemical Society (ACS) recognized the
institute's pioneering efforts by designating it a National
Historic Chemical Landmark. Such designations recognize
important places, discoveries, and achievements in the his-
tory of chemistry. Other landmarks have included Joseph
Priestley's Pennsylvania home, penicillin, and the National
Institute of Standards and Technology. PRI holds a special
place in ACS Past President Eli M. Pearce's heart, as from
1982 to 1996 he served as its director. Pearce started at Poly-
technic in 1973, had a joint appointment in the Departments
of Chemistry and Chemical Engineering, and is currently a
university research professor. Pearce is confident about PRI's
future: "When you read the [National Research Council report
'Beyond the Molecular Frontier'], it's clear that the most ex-
citing developments in science and technology are occurring
at the interfaces. Over the years, considerable contributions
were made to the engineering side of polymerization research
and education."





































Two other Poly engineering faculty who have made long-
term contributions to the polymer-engineering field are Chang
Dae "Paul" Han, a former department head (1974-82), and
Jovan Mijovic, present department head. Han published
widely in polymer and chemical engineering journals, and
wrote two books: Rheology in Polymer Processing and
Multiphase Flow in Polymer Processing, both published by
Academic Press. Mijovic in the course of his illustrious career
has published widely in polymerjournals and supervised doz-
ens of doctoral students in the study of polymeric materials
properties and states, and more recently has been investigating
complex chemical and biosystem dynamics, nanotechnol-
ogy, and nano-materials. He has led the department into the
chemical and biological engineering era while continuing his
yeomanlike efforts as a dedicated, distinguished teacher and
researcher. He's committed to maintaining Poly's tradition
of excellence.

THE ENVIRONMENTAL SCIENCE AND
ENGINEERING CONNECTION
The Polytechnic has performed many research investiga-
tions concerned with the understanding of fluidized bed fun-
damentals. Fuidization is used widely in petroleum refining,
power generation, and in the chemical industry. Frederick
Zenz received his Ph.D. at Poly in 1961 and taught a graduate
course throughout the '60s entitled "Fuidization," eventually
writing and publishing the seminal work Fluidization and
Fluid Particle Systems with Othmer.
In the early portion of his career, Poly's Edward Ziegler
earned an international reputation for his research in fluidized


Acclaimed alumnus
.- _" Dr. Joseph Jacobs with a blueprint
-- for one of the many important
projects in which he was a partici-
pant. In addition to establishing a
Joseph J. and Violet J. Jacobs Chair
in Chemical Engineering, in 2002 the
university opened the Joseph J. and
Violet J. Jacobs Building on campus.
U It houses a full gymnasium and ath-
letic center as well as state-of-the-art
Sl laboratories and classrooms.

bed transport and reaction engineering
M E R modeling. His heat transfer model is
used in the design of fluidized bed coal
combustors. Ziegler, along with former
Poly professor Rutton Patel (now with
I ExxonMobil) supervised students in
Sthe fluid bed research area, and the two
AMAX -. often became members of each other's
guidance committees.
Later Ziegler's interests turned toward
environmental applications and specifi-
cally air pollution engineering control. He has co-edited the
5th Edition of the Pfafflin-Ziegler Encyclopedia of Envi-
ronmental Science and Engineering, published in January
2006, and authored a number of its articles. He started on the
encyclopedia's first edition some three decades ago, together
with his co-editor James Pfafflin- a former member of Poly's
Department of Civil Engineering. Over his career Ziegler has
taught more than 1,000 students in the undergraduate lab, and
more than 800 graduate students, mainly in his Chemical Re-
actor Design and Air Pollution Engineering Control courses.
He's been the thesis and project adviser to numerous master's
and doctoral students as well as advising undergrads.
Starting in 1986 Allan Myerson headed the department
and eventually became dean of the School of Chemical and
Materials Science. Myerson encouraged interdisciplinary
studies between the engineering and science departments. He
also was active in crystallization and nucleation research and
edited the Handbook of Industrial Crystallization.

A 'WORLD CLASS' UNIT OPERATIONS
LABORATORY, REVISITED
A major renovation of the chemical engineering lab took
place in 2001, when Walter P. Zurawsky's considerable
transport phenomena knowledge, research experience at
AT&T Labs, and equipment construction skills were put into
play. Professor Ziegler had been teaching the lab for many
years after his mentor Fred Schurig retired. With the help of
the Othmer gift to the school, Zurawsky and Ziegler planned
a student-friendly, state-of-the-art experimental teaching facil-
ity with new distillation columns, process control equipment, a
Chemical Engineering Education










controlled fermenter, and membrane separations experiments.
The new, highly automated distillation experiment is, by the
way, currently used to investigate the efficiency of concentrat-
ing acetic acid (shades of Donald Othmer?) using sieve trays
and packed columns. The senior CBE students perform 20
experiments in their final two semesters. Many of the scaled-
down versions of traditional chemical engineering operations
were retained and are still used to study classical theories and
industrial correlations, but with modern instrumentation. A
computation room was fitted with the latest PCs having Lab
View, Microsoft, and MatLab software to help store, transmit,
and analyze the data. The ASPEN Engineering Suite is avail-
able to all CBE students on their local network, primarily for
use in the senior design courses.

NEW PATH: CBE-PRESENT AND FUTURE
Over the past 40 years, chemical engineering curricula have
embraced an engineering science paradigm that spans from
molecular-level interactions and transformations to large-scale
systems. Indeed, it is an appreciation of, and a willingness
to work over, many decades of scale that is one of the distin-
guishing traits of the chemical engineering discipline. This
ability to adapt to work on many scales has allowed chemical
engineers to have productive interactions with a wide range of
other science and engineering disciplines, and will be essential
for the application of engineering principles to biologically
based processes. The rising need to convert advances in biol-
ogy into new processes and new industries makes it imperative
that we adopt biology as an enabling science.
Interest in integrating biology and chemical engineering,
or CBE, is growing nationwide. For example, the number
of biologically oriented presentations at the AIChE annual
meetings increased from less than 10% to close to 50% in
only four years. Many chemical engineering departments
across the country have changed names to reflect a growing
interest in, and overlap with, biology (examples include Johns
Hopkins, Cornell, the University of Pennsylvania, the Univer-
sity of Wisconsin-Madison, Northwestern, and RPI). Many
such departments have started to require a biology course as
part of their curriculum, but there are still very few that have
made a full commitment to developing a curriculum in which
biological systems and processes are fully integrated across
the curriculum, as we are doing.
Several years ago the engineering faculty within our de-
partment reviewed and revised the chemical engineering
curriculum to reflect what it felt was the emerging importance
of biology. The specific aim was to develop an exemplary
educational program (B.Sc.) in chemical and biological engi-
neering that builds on the traditional strengths and paradigms
of chemical engineering while embracing biology as a pillar
along with mathematics, chemistry, and physics. So substan-
tive are the changes that we, too, undertook a program name
change from chemical engineering to chemical and biological
Winter 2007


engineering. The CBE program was initiated with the fresh-
man class of 2003.
We firmly believe that chemical engineering principles can
and must be applied to biological systems and to the develop-
ment of new processes based on biology. The task we face
in implementing this new curriculum is substantial, but we
are eminently qualified and confident of the success of the
proposed program.
The courses for our new CBE program are shown in Table
1 (next page). The program has been approved by the faculty
of our department, by the faculty of Polytechnic University,
and by the State of New York. By careful choice of electives
and several course substitutions, CBE students can adjust their
schedules to satisfy medical school requirements if they have
an interest in pursuing medicine as a career.
The task we face is to meld, as seamlessly as possible, sys-
tems and processes of biological relevance into our engineer-
ing curriculum. We regard the systems-oriented, multiscale
approach to problems that is the hallmark of chemical engi-
neering as the primary strength we have to offer. We believe
it is essential that our students remain strong in engineering.
It is our further belief that by exposing our students to biology
and bio-processes in addition to more conventional chemical
processes, we will produce better, more versatile engineers.
As part of our new curriculum, we have introduced re-
quired courses in biology and biochemistry and are revising
virtually all of our engineering courses to include biological
applications and examples. Technical electives in the junior
and senior year provide opportunities for elective courses,
particularly new electives focusing on engineering in biology
such as System Biology, Protein Engineering, and Drug De-
livery. Although these new elective courses will be primarily
aimed at CBE students, they will be open to other engineering
and science students.
We are the only chemical and biological engineering pro-
gram in New York City and we have seen phenomenal growth
in our undergraduate enrollment over the past two years: from
41 undergraduates in 2004 to 110 in early 2006- a whopping
150% increase. The CBE program is acknowledged as the
most demanding major on campus. A GPA of 2.5 is required
to remain in the major (2.0 elsewhere) and the students'
response has been hugely enthusiastic. We have had the high-
est percentage of students on the Dean's List and named as
valedictorians in recent years.

UNIQUE ATTRIBUTES OF THE POLYTECHNIC
Polytechnic provides an important educational opportunity
for students who tend to be under represented in engineering.
Given our downtown Brooklyn location, our student popula-
tion has always included a large cross section of the population
of Brooklyn and the other boroughs of New York City. As
different ethnic groups have immigrated to the United States,











TABLE 1
Chemical and Biological Engineering Curriculum

Freshman Fall Freshman Spring
MA1014 Calculus I MA1114 Calculus II
CM1004 Gen. Chemistry for Engineers Intro to Cell & Molecular Biology
EN1014 Writing & Humanities I CBE1214 Intro to Chem & Bio Engineering
EG1004 Intro Engineering & Design EN1204 Writing & Humanities II
Sophomore Fall Sophomore Spring
MA2012 Linear Algebra I MA2112 Multi-variable Calculus A
MA2132 Ordinary Differential Equations MA2122 Multi-variable Calculus B
PH1004 Introductory Physics I PH2004 Introductory Physics II
CBE2124 Analysis of Chem & Bio Processes CS1114 Intro to Prog. & Problem Solving
CM2234 Industrial Organic Chemistry CM2514 Chemical & Biological Equilibria
Junior Fall Junior Spring
CM3314 Biochemistry I CBE3324 Chem & Bio Separations
CBE3103 Math Methods for Chem & Bio Eng. CBE3214 Chem & Bio Reactor Engineering
CBE3314 Physical Rate Processes Technical Elective
HI2104 Modern World History HU/SS Elective
CBE3622 Chem & Bio Eng. Thermodynamics
Senior Fall Senior Spring
CBE4113 Engineering Laboratory I CBE4123 Engineering Laboratory II
CBE4413 Process Dynamics & Control CBE4623 Chem & Bio Process Design II
CBE4613 Chem & Bio Process Design I CBE4713 Engineering Polymeric Materials
HU/SS Elective Engineering Elective
Technical Elective HU/SS Elective


Poly's student popu-
lation has changed,
always mirroring the
ethnic mix of the city.


In addition to the Annual Income < $20k $20k to $80k > $80k
ethnic diversity that Polytechnic 28.4% 51.6% 20%
is part of Polytechnic,
SUNY 13.0% 31.0% 56%
we are proud to note
that over the past de-
cade nearly 50% of the students who have graduated from and Albert Einstein Coll
our chemical engineering program are female. We fully few. Adding to the list, a
expect that this trend will continue with our new program in on the grounds of Bellev
chemical and biological engineering. Although there have Manhattan) was announce
been advances nationwide, women are still grossly under- York Times a few weeks
represented in engineering. River Science Park will
Polytechnic is a private university, but our role in the New The facility is being deve
York region is, de facto, one that would be expected of a Equities, Inc.-whose ct
public university. As shown in Table 2, we educate a much Sudarsky, is a Polytechn
greater percentage of students from lower-income households Board of Trustees of Pol
than the state university system does. Washington Monthly cal institutions and the n
ranked Polytechnic University second in the nation (out of graduates with avenues fo
245 national universities) in social mobility, ties for collaboration, an


Our location in New York
provides us with exceptional
opportunities. We are in a
region with many excellent
biomedical institutions in-
cluding Rockefeller Univer-
sity, Memorial Sloan-Ketter-
ing Cancer Institute, SUNY
Downstate Medical Center,
lege of Medicine, to mention a
new $700 million science park
ue (just across the East River in
ed on the front page of The New
ago. The focus of this new East
be the biotechnology industry.
loped by Alexandria Real Estate
[airman of the board, Dr. Jerry
lic alumnus and a member of the
ytechnic. These excellent medi-
ew science park will provide our
r continued education, opportuni-
d potential employment.
Chemical Engineering Education


TABLE 2
Student Family Incomes: Polytechnic and
the State University of New York
































'il CURRENT FACULTY
The explosive potential of CBE
has been recognized by the Poly-
technic trustees, our new president,
Zieer Jerry MacArthur Hultin, and the
Edward Ziegler members of the administration. These
Pivotal individuals have
made a major commit-
ment to our department's
continuing growth. Three
years ago, Jose M. Pinto
S joined our faculty from the
University of Sao Paulo
in Brazil. Pinto received
his Ph.D. from Carnegie-
Jovan Mijovic Mellon and is interested
in modeling and optimization of
chemical and biological processes
and systems biology. In fall 2004,
Stavroula Sofou joined the faculty.
S Sofou received her Ph.D. from Co-
l / lumbia University in New York City
SP and spent three years as a post-doc at
Jose Po the Memorial Sloan-Kettering Cancer
Research Center. Her principal
interest focuses on the use of
engineering principles for drug
delivery for cancer cure.
We announced two additional
faculty positions in fall 2006.
Stavroula Sofou Rasti Levicky, formerly of Co-
lumbia University, was named the Donald E Othmer Assistant
Professor of Chemical and Biological Engineering. Levicky
received his Ph.D. from the University of Minnesota and
has a strong interest in the field of biological polyelectrolyte
Winter 2007


systems, nanosized micro array biosen-
sors, and bio-diagnostics. Jin Ryoun Kim
is the Joseph J. and Violet J. Jacobs Assis-
tant Professor of Chemical and Biological
Engineering. He got his Ph.D. from the
University of Wisconsin at Madison. His
interest is in the area of protein en-
gineering and particularly those that
aggregate and cause Parkinson's and
Alzheimer's diseases.
Finally, we are very proud to an-
nounce that on Jan. 1, 2006, our
department was officially renamed
The Othmer-Jacobs Department of
Chemical and Biological Engineering,
in recognition of enormous contribu-
tions to our discipline made by these two
chemical engineering giants. Visit our
Web site: .

ACKNOWLEDGMENTS


Modern
buildings
on campus
include
Dibner
Library on
Metrotech
Commons,
far left, and
the Othmer
Dormitory,
left.


Rasti Levicky


For practical reasons, this article
mentions only a few of the people that Leonard Stiel
are part of the history of chemical
engineering at the Polytechnic.
We would like to acknowledge
those dedicated present and
former professors, students and
alumni, and their supporters,
without whom Polytech would
never have attained its success- ' ,
ful international reputation.
We thank our colleagues in the Walter Zurawsky
department for their help writing this article, and greatly
appreciate the efforts of Christopher Hayes. 7









rj[ =educator
---- U s_____________________________________


Joseph Reynolds


of Manhattan College


HELEN C. HOLLEIN
Manhattan College Riverdale, NY 10471

Joseph Reynolds earned a bachelor's degree in chemis-
try from Catholic University of America in 1957 and a
Ph.D. degree in chemical engineering from Rensselaer


Polytechnic Institute in 1964. He taught high school chemistry
and physics full time at LaSalle Academy in New York City
from 1957 to 1959, then taught college chemistry part time
for Catholic University (Troy extension) while pursuing his
doctoral degree at RPI. Joe excelled as a student and was
Copyright ChE Division of ASEE 2007
Chemical Engineering Education





























Joe, at right, posing with
Lou Theodore, his long-
time friend, collaborator
and fellow faculty member.


inducted into the Phi Beta Kappa, Tau Beta Pi, Sigma Xi, and
Phi Lambda Upsilon honor societies. His many accolades in-
clude listings in American Men and Women in Science, Who's
Who in Technology Today, Who's Who Among America's
Teachers, International Who's Who in Engineering, Who's
Who in the East, and Who's Who in Engineering.
Since 1964, Joe has been a member of the chemical en-
gineering faculty at Manhattan College, where he holds the
rank of professor of chemical engineering. It caused some
excitement among Joe's colleagues when Br. Thomas Scanlan
was appointed president of Manhattan College, because Br.
Thomas had been one of Joe's students in a freshman chemis-
try course that he taught in Troy. (Fortunately, we understand
that Br. Thomas earned an "A" in the course.)
Joe served as chairperson of the Department of Chemical
Engineering for seven years (1976 to 1983), and also was
called upon to serve as acting chair for brief stints totaling
another two and a half years while his successors were on
sabbatical leave. As part of his academic duties, Joe has
served for many years as moderator of the student chapter
of the American Institute of Chemical Engineers (AIChE),
and has been president of the college's Sigma Xi Chapter. He
has also served on a large number of college committees, but
says his favorite is the Board of Trustees' Facilities Planning
Committee because this membership ensures his invitation
to the President's Christmas Dinner (best wine selection and
food service, by far).
Since completing his doctoral research at RPI on "The Effect
of High Pressure on the Infrared Spectra of Solids," Joe has
collaborated for more than 30 years with Dr. Louis Theodore
at Manhattan College on various environmental research proj-
ects. Many of Joe's books and research publications include
Winter 2007


undergraduate students as coauthors. His current research
interests are in the air pollution control and hazardous waste
incineration areas. He has coauthored numerous text/reference
books, including Introduction to Hazardous Waste Incineration,
2nd Edition (2000), Accident and Emergency Management
(1989), and Handbook of Chemical and Environmental Engi-
neering Calculations (2002), all from Wiley-Interscience, New
York. He has developed computer software, which is available
commercially and currently used in the EPA's training program,
to simulate hazardous waste incinerator (HWI) performance.
His publications include problem and solution workbooks that
he uses in the courses that he teaches at the college, as well
as EPA training manuals for the HWI software. Joe has also
served as a consultant for several private companies and is
presently a consultant/expert witness for the Department of
Justice and the U.S. Environmental Protection Agency. He
has been active for most of his career in the Air and Waste
Management Association (AWMA), formerly the Air Pollu-
tion Control Association (APCA), where he presents papers
and chairs sessions at annual meetings as well as coordinating
associated continuing-education programs.

TEACHING TAKES PRECEDENCE
Manhattan College offers both B.S. and M.S. degrees in
chemical engineering, and Joe has always taught the under-
graduate courses by choice. He has taught the Engineering
Materials course and directed its associated laboratory for
his entire career at the college, and currently teaches Process
Calculations, Engineering Thermodynamics, Fluid Mechan-
ics, and Computer Aided Simulation and Design in Chemical
Engineering. During his tenure, he has taught nearly every
course that the department offers (or previously offered)
including Chemical Engineering Thermodynamics, Heat











Proudly posing
with students
at a poster
competition.


Transfer, Chemical Engineering
Laboratory I-II, Physical Metal-
lurgy, Physical Chemistry I-II,
Computer Methods in Chemical
Engineering, Computer Science
and Programming, and Fortran
Programming for Chemists.
In the classroom, Joe is very
much an "in your face" kind of
teacher. He teaches several of
the required sophomore courses
for chemical engineering ma-
jors, giving out grades from "A"
to "F," as deserved. The good
students stay, the others repeat
or change majors. The current seniors have created a bul-
letin board with pictures and the facts as they see it for the
chemical engineering faculty. Their advice for students of
Dr. Reynolds' classes includes: "Participate as much as pos-
sible. This will lessen your chance of being randomly called
on during class."
Joe's courses are well organized and fast paced. He sets high
standards, gives fair-but-tough tests, and assigns homework
due at every class. In the old days, he distributed the home-


work assignments for the entire semester
on day one, but when the Internet was
relatively new, he forced the students to use
it by sending out assignments via e-mail
only. The seniors advise, "check your e-
mail every day, at least twice a day. There
will always be something new in there."
This practice has the added advantage of
getting the students to read messages about
AIChE meetings and parties, which gets
them involved in departmental activities
from freshman year on.
Joe is one of the teachers who makes
effective use of the computer projector


and PowerPoint slides for each of his lecture courses: He
expects students to listen and respond during his presentation
instead of just madly copying information. His PowerPoint
presentations are available for all of his students through
the course Web sites on the Blackboard system. Many of
Joe's current and former students credit him as being a truly
outstanding teacher, a fact that is supported by his numer-
ous teaching awards and consistently excellent course and
teacher evaluations.


Joe's focus on excellent teaching must have set a good
example, because several of his former students also pursued
careers in academia. Among them are Dr. Ruben Carbonell
(B.E. 1969), now KoSa Professor of Chemical Engineering at
North Carolina State University; Dr. Sonia Kreidenweis (B.E.
1983), now professor of atmospheric science at Colorado State
University; Dr. John Blaho (B.E. 1983), now associate profes-
sor of microbiology at Mount Sinai School of Medicine; and
Dr. Marco Castaldi (B.S.ChE 1992), now assistant professor
of earth and environmental engineering at
Columbia University.
s much as
His former students turned academicians
will lessen
credit Joe in various ways for encouraging
being their graduate education and influencing
ed on their decision to pursue research and teach-
ing at the college level as a profession. Br.
Thomas participated as an undergraduate
in Joe's research at RPI, and credits this
n seniors to
early experience with giving him "an un-
ling to take derstanding of the way that research and
Oldss' class, scholarly activities reinforce teaching and
vice versa." Sonia Kreidenweis co-authored
her first publication with Drs. Reynolds
and Theodore in the Journal of the Air Pollution Control As-
sociation, based on her undergraduate research at Manhattan
College. She credits Joe as being "the first to suggest [that]
I apply to graduate school and go on for a Ph.D."-a degree
she subsequently completed at California Institute of Tech-
nology. Ruben Carbonell says that as an undergraduate, he
"looked up to Dr. Reynolds as a role model of an excellent
professor," which greatly influenced his decision to pursue a
career in college teaching.
Chemical Engineering Education


"Participate as
possible. This
your chance of
randomly calle
during class."


-Advice front
students plan
Reyn






























Top left, Joe and wife Barbara.
Top right, Barbara and daughter
Megan on a family trip to
Toledo, Spain-where both
Reynolds daughters got to prac-
tice their fluent Spanish. Right,
Joe and daughter Marybeth
undertaking a favorite family
activity-skiing-at Steamboat
Springs, Colorado.


OUTSIDE INTERESTS
All is not academics for this
overachiever, however. Joe's favor-
ite recreational activities include
skiing and jogging. He can be seen .
early mornings jogging around
his Bronx neighborhood near the
college. His equally active fam- 4
ily-wife Barbara and daughters
Megan and Marybeth-has accompanied him on the annual
Manhattan College ski trip every January since the girls were
infants. The foursome has also made the AWMA (APCA)
meetings in June an annual event. One of Barbara's favorite
activities is international travel, and the family has made
so many trips to Ireland that Megan and Marybeth recently
obtained dual citizenship.
Joe is as proud of his family's achievements as of his own.
Barbara has retired from Fordham Preparatory School in
the Bronx after 35 years of teaching. Megan and Marybeth
both earned baccalaureate degrees in chemical engineering
with honors from Manhattan College, so Joe is one of our
most enthusiastic alumnae parents. Megan recently received
a master's degree from Thunderbird, the Garvin School of
International Management in Phoenix. After working in Spain
for the pharmaceutical industry, she is currently working for
Merck in New Jersey. Marybeth completed her master's in
Winter 2007


Public Policy at Georgetown University and currently works
for Cancer Care in New York City. Both daughters are fluent
in Spanish and have studied other languages as well, i.e.,
Russian for Marybeth and Portuguese for Megan.

THE MOST REWARDING PART
Joe is well known for his quick smile and easygoing manner,
as well as for his endearingly annoying habit of correcting
everybody's grammar-often in midsentence. The seniors
say, "Use proper English. He will call you on it every day!"
This applies equally to his faculty colleagues.
Joe's story is unusual in that he is an outstanding teacher and
a respected researcher at a primarily undergraduate institution.
When he was honored with a Bonus et Fidelis Medal on his 25th
anniversary at Manhattan College, he was interviewed about his
experiences. Asked about the most rewarding part of his career,
his response was immediate: working with students. 7











ri]j1 classroom
---- U s_____________________________________


THE CHEMICAL ENGINEERING BEHIND

HOW POP GOES FLAT:

A Hands-On Experiment for Freshmen














KEITH L. HOHN
Kansas State University Manhattan, KS 66506-5102


One of the endemic problems specifically in chemical
engineering, as well as in the field of engineering in
general, is the low retention rate of undergraduate
students. This attrition is especially noticeable in the first two
years of undergraduate studies, as roughly 50% of freshmen
entering chemical engineering do not make it to their senior
year.11 While students have varying reasons for transferring
out of science and engineering fields, one of the most com-
mon is a loss of interest in science and engineering.[2] In most
chemical engineering departments, students do not take a core
chemical engineering course until their sophomore year, and
don't become immersed in chemical engineering until their
junior year. This means that underclassmen who switch ma-
jors due to a loss of interest in science and engineering do so
without a good understanding of chemical engineering.
To combat the retention problem, many chemical engineer-
ing departments require an introductory course in chemical
engineering during the first semester of the freshman year.


Typically these courses serve to introduce students to the
department and its procedures, and give a broad overview
of some applications in chemical engineering. From a brief
survey of course descriptions and syllabi found on the In-
ternet, it appears that many of these courses use field trips
to chemical plants and presentations by guest speakers to
give students more of a perspective on the discipline. While
these are excellent activities to which students in chemical
engineering can be exposed, one problem is that they are,

Keith Hohn is an associate professor of chemi-
cal engineering at Kansas State University.
He received his bachelor's degree from the
University of Kansas and his Ph.D. from
the University of Minnesota, both in chemi-
cal engineering. His research interests are
heterogeneous catalysis and its application
in hydrocarbon conversion and hydrogen
generation.


Copyright ChE Division of ASEE 2007


Chemical Engineering Education










for the most part, passive activities. Students are generally
hearing someone tell them what chemical engineering is or
are seeing pieces of process or laboratory equipment. They
are not touching, designing, or building anything. Hands-on
activities are relatively rare, though some departments have
used them successfully. [37
There are numerous reasons why hands-on projects are not
incorporated into freshman chemical engineering courses
more often. First of all, freshmen do not generally have the
background to apply many chemical engineering principles.
Secondly, it is difficult to package a true chemical engineer-
ing application into something that freshman students can
manipulate since chemical engineering frequently deals with
very large and sometimes hazardous processes. Finally, many
interesting activities would require extensive laboratory and
calculational time (on the order of the laboratory experiments
taught in chemical engineering lab courses). The requirement
for a useful hands-on activity that could be incorporated
into a freshman course is one that is interesting, safe, easily
understood by students with limited chemical engineering
knowledge, fairly simple, and capable of being completed
in a reasonable amount of time. This paper details such an
experiment that in fall 2003 and fall 2004 was incorporated
into a freshman chemical engineering course at Kansas State
University (CHE 110, Current Topics in Chemical Engineer-
ing). This experiment has students study the often-encoun-
tered phenomenon of carbonated soft drinks that have lost
their fizz (here in Kansas, we call that flat pop). Students
design and carry out experiments to study one aspect of this
phenomenon. The efficacy of this exercise in teaching stu-
dents what chemical engineering is and in increasing student
enthusiasm for studying chemical engineering was measured
by a semester-end survey.

BACKGROUND
Freshman students are generally familiar with the phe-
nomenon of carbonated beverages going flat, and have some
intuitive understanding as to why it occurs. Most will know
that the loss of carbonation leads to a flat beverage, and some
will recognize that carbonation is simply the absorption of
CO2 into the liquid phase. What students will not be familiar
with are the chemical engineering principles behind how
pop goes flat and how chemical engineers use many of these
principles to design chemical processes.

There are numerous chemical engineering principles
involved in the loss of carbonation. This is truly a rich mass-
transfer problem. Loss of carbonation depends on two factors:
the gas-liquid equilibrium for CO2 and the rate at which mass
transfer of CO2 from the liquid to the gas phase occurs. The
gas-liquid equilibrium is represented by Henry's Law:[81

H= Pco2 (g)/ Cc (1) (1)


where Po2 (g) is the CO2 partial pressure in the gas phase,
Cco2 (1) is the concentration of CO2 in the liquid phase, and
H is the Henry's Law constant.
Given enough time, CO2 will leave the liquid solution and
enter the gas phase until the above equilibrium relationship is
fulfilled. Temperature plays an important role, as the Henry's
Law constant decreases with increasing temperature. For car-
bonated beverage bottles left closed for long periods of time,
equilibrium is the most important factor in how the carbonated
beverage goes flat. The volume of the head space is clearly
important here, as the partial pressure in the entire volume
must satisfy the equilibrium relationship. Large head space
volumes lead to a large loss of CO2 from the liquid.
Mass transfer kinetics can be important in such situations.
There really are two types of mass transfer occurring in this
system: mass transfer of CO2 from the liquid to the gas and
mass transfer of CO2 through the bottle to the outside atmo-
sphere. For the standard polymer used to construct carbonated
beverage bottles, polyethylene terephthalate, the rate of mass
transfer of CO2 through the bottle is small. This would not be
the case, for instance, if low-density polyethylene was used to
make the bottle. The rate of mass transfer from the liquid to
the gas becomes important in loss of carbonation if the bottle
is opened and closed often within a short period of time. In
this case, there is not enough time to reach equilibrium, so the
CO2 lost from the liquid phase is the amount that went into
the gas phase in the time between openings. Mass transfer of
CO2 into the gas phase can be represented by:'81
Nc = KG (P -P *) (2)

where:

Pco = HCc02 (3)
Nco2 is the flux of Co2', PC02 is the partial pressure of CO2
in the gas phase, KG is the gas-phase mass transfer coefficient
times the mass transfer area, PC2 is the partial pressure of
CO2 at the gas-liquid interface, and Cc02 is the concentration
of CO2 in the bulk liquid.

IMPLEMENTATION
This activity was incorporated in CHE 110 (Current Top-
ics in Chemical Engineering) for fall 2003 and 2004. This
is a one-hour introductory chemical engineering course that
freshmen and transfer students are required to take for a letter
grade. Four of the 16 contact hours were spent on the CO2
absorption activity. The remaining time was dedicated to
lectures on curriculum requirements, advising and enrollment,
how to seek internships and full-time positions, applications
of chemical engineering, and field trips to a dairy processing
facility and the chemical engineering laboratories.
Students were presented with the topic of carbonated
beverages going flat by having a number of students take
the "Pepsi challenge," in which they sampled two different


Winter 2007










beverages and determined which tasted better. To show why
carbonation is important, one of the beverages was flat while
the other was fresh. Brief discussion of what made the fresh
beverage better ensued. This was followed by a discussion of
why carbonated beverages go flat, which introduced the idea
of CO2 absorption and set up a discussion of mass transfer
and gas/liquid equilibrium.
Students were then shown two ways to quantify the mass
transfer of CO2 from carbonated beverages. The first method
was based on an article by Crossno.[91 Briefly, a balloon filled
with 50 ml of 1M NaOH was affixed to a flask containing
150 ml of a carbonated beverage. The beverage was stirred
and left for ~24 hours to drive the CO2 out of solution. CO2
was adsorbed into the sodium hydroxide solution to form so-
dium carbonate. Titration of that solution to the first colorless
phenolphthalein endpoint neutralized the excess sodium hy-
droxide and converted all of the sodium carbonate to sodium
bicarbonate. Continuation of the titration to the methyl orange
endpoint converted the sodium bicarbonate to water and CO2.
The amount of HC1 required to go from the phenolphthalein
endpoint to the methyl orange endpoint gave the amount of
CO2 in the carbonated beverage.
The second method was to replace the original bottle cap
with a cap in which a pressure gauge had been placed. This
cap allowed the pressure in the head space to be measured
as a function of time.
During demonstration of the two methods, laboratory
safety procedures were highlighted and a handout was given
on these procedures. Following the demonstrations, the
students were told to form groups (self-selected) of four or
five students. Each group was told that they were to identify
and select one research topic related to the mass transfer of
CO2 in carbonated beverages. Several topics were suggested
to them, although they were encouraged to brainstorm their
own project ideas. They were then instructed to identify what
experiments and measurements they needed to do in order to
address the research question. They were finally told that they
would be required to report their results in both a written and
an oral report. Final written reports were turned in the last day
of class. Oral reports were given during class time in front of
the whole class in the last two or three weeks of the class.
Performance on the project was a major factor in the
students' final grade. In the first year of implementation, an
overall letter grade was assigned for the reports, which was
given roughly equal weight with attendance. In the second
year of implementation, the project was assigned 200 points
out of a possible 500 points, with the remainder of the points
for attendance. Students were required to turn in several
reports during the semester to ensure that they were making
progress on the project. The reports and their point value are as
follows: firing memo (described in the following paragraph),
10 points; description of experimental objectives, 10 points;


detailed experimental plan, 20 points; preliminary results
report, 20 points; rough draft of final report, 10 points; final
written report, 100 points; oral report, 30 points.
The students were given little information on working in
teams the first year, and this led to a few problems (described
in the results section). To address this problem in 2004, each
team was asked to meet and discuss the team's expectations
for individual team members. They were also asked to lay
out what specific actions would be taken if students did not
meet those expectations, leading up to a possible ultimate
action of "firing" the individual. They were then required to
write a document (a "firing memo") detailing this discussion
and all team members had to sign it. In addition, students
were required to rate their peers in a number of areas, such
as attendance at team meetings, contribution to reports, and
attitude, and turn in their ratings with the final report. Students
consistently rated low by their peers received a deduction of
their project grade, with the severity of the deduction deter-
mined by how low their ratings were.

RESULTS
Because students were allowed to choose their own research
topics, topic selection varied. Topics included:
C Does the commercially available Fizzkeeper work?
C How does temperature affect CO2 absorption?
) Estimate the mass transfer coefficientfor CO, loss
from carbonated beverages.
C Estimate Henry's Law constantfor CO, in carbonated
beverages.
C Determine effect of different container materials
I .. i it ,.. glass, and PET) on carbonated bever-
ages going flat.
C Determine how different PET beverage containers
affected the loss of CO, over time.
C How does the ,,, i, of time the cap is left off a bottle
affect the rate at which the carbonated beverage goes
flat?

The experiments the students conducted and how they ana-
lyzed their data varied for the different projects. Most groups
addressed their research question empirically. For example,
several groups plotted CO2 concentration and/or gas pressure
vs. time for different conditions (i.e., different temperatures,
with and without a fizzkeeper). These groups did not use the
mass transfer equations described above.
Other groups relied on the mass transfer equations to ad-
dress quantitative questions, such as estimating the Henry's
Law constant or the mass transfer coefficient. The group that
estimated the Henry's Law constant measured concentration
of CO2 in the liquid phase and pressure in the gas phase for
several different samples, and attempted to fit these data with


Chemical Engineering Education










a single value of the Henry's Law constant. The group that
attempted to estimate a mass transfer coefficient measured the
gas pressure over time after the bottle had been opened and
closed (to start with atmospheric pressure). From the known
volume in the head space and the measured pressures, they
could calculate the change in moles of CO2 in the gas phase.
Next, the students solved Eq. (2) by separation of variables,
assuming that the concentration of the liquid (and therefore
Pco2 *) was a constant over time at the value they measured
after the mass transfer experiment. They then plotted their
experimental data using the resulting equation, and found
KQ from this plot. Essentially, they plotted the logarithm of
the partial pressure vs. time, which yielded a linear plot, the
slope of which was KG. This analysis assumed that all of the
mass transfer resistance was in the gas phase, which likely was
not the case. Making this assumption helped in the analysis,
however, since the students could readily measure the gas-
phase pressure over time.
The titration procedure was problematic for some students.
Sometimes students found that the balloon containing NaOH,
in which CO2 was absorbed, had been sucked into the flask
when they returned to the laboratory for titration. Sub-at-
mospheric pressures had apparently been created inside the
balloon due to loss of CO2 from the gas phase, causing the
balloon to shrink and eventually completely collapse. Stu-
dents also reported some problems with getting reproducible
results with the titration. These problems were likely due to
human error in most cases. There were fewer complaints in
the second year, possibly because a longer period of time
was given for completion of the project (nearly the entire
semester, as opposed to only six weeks) which allowed for
more repeat trials.
Student work showed promise, but analysis was often too
simplistic or relied on too few data points to draw a conclu-
sion. This provided a good opportunity, however, to present
important concepts such as estimating error and the need for
a good experimental design with replication. In the second

TABLE 1
Assessment Results for CO2 Absorption Activity
Aspect Assessed Fall 2003
Average response to: 'This session improved 4.07 (out of 5) 7
my understanding of what chemical engineering
is and what chemical engineers do."
Average response to: 'This session increased 3.64 (out of 5) 7
my enthusiasm for studying chemical engineer-
ing."
Number of students listing the CO, activity in N/A
response to the following: "Of all the activities
we did in class, which three did you find the
most useful?"
Number of students listing the CO, activity in N/A
response to the following: "Of all the activities
we did in class, which three did you enjoy the
most?"
Winter 2007


year, students were asked to lay out a detailed experimental
plan for the data they would take to address their research
question, and were given feedback on the appropriateness
of their plan. In addition, preliminary reports provided more
opportunity to give feedback on whether they were analyzing
their data properly. Their oral presentations showed a good
deal of sophistication, with all groups using PowerPoint pre-
sentations with imbedded graphics. It is obvious that they had
previously given PowerPoint presentations in high school, as
no time was spent teaching about the tool.

ASSESSMENT
Survey Results
A detailed survey was given to the students at the end of the
semester to evaluate both the course in general and individual
class activities. The results of this survey were used to assess
the effectiveness of the hands-on CO2 absorption experiment
in educating freshmen about chemical engineering and in-
creasing their enthusiasm for studying chemical engineering.
Table 1 summarizes student responses.
As seen in this table, students generally felt that the CO2
absorption activity improved their understanding of chemi-
cal engineering and increased their enthusiasm for studying
chemical engineering. In addition, the CO2 absorption activ-
ity was mentioned by 15 students (out of 36 students who
responded) as one of the three most useful activities in the
course (along with a field trip to a dairy processing facility and
a lecture on biotechnology), and by 17 students as one of the
three most enjoyable activities (along with the field trip to the
dairy processing facility and a tour of the chemical engineer-
ing laboratories). It is interesting, but perhaps not surprising,
that the most enjoyable activities had the students going out
to see applications of chemical engineering or engaging in a
hands-on activity rather than listening to a lecture.

QUALITATIVE EVIDENCE
Most students seemed to enjoy the exercise. The opportunity
to work with a "real world" engineering
problem energized a number of the students.
The students trying to evaluate the efficacy
Fall 2004 of the Fizzkeeper, for example, devoted
.23 (out of 10) a great deal of time (as well as a large
amount of sealant products) to attempting
to produce a bottle that would allow them
.05 (out of 10) to use the Fizzkeeper while simultaneously
measuring the pressure in the head space
of the bottle. It appeared that the students
15 (out of 36 with a more applied, rather than theoretical,
respondents)
mindset appreciated the activity.
Student comments on the end-of-semes-
17 (out of 36 ter surveys were mostly positive, and also
respondents) provide some insight into why students
enjoyed the activity. Comments reflected











the following positives about the activity:
1. Provided an opportunity for a hands-on/laboratory
activity

2. Allowed students to work in a group

3. Gave an idea as to what chemical engineers do

The opportunity for students to work in groups was particu-
larly well received. This was a great way for freshmen to get
to know their colleagues, make friends, and form study groups
for introductory science and engineering courses. Students
were forced to work in groups to decide what experiments
to run, to conduct those experiments, and to write the final
report on the project, leading to closer interactions than what
usually occur in a lecture course.
A few negative comments were noted. Comments in 2003
indicated that group dynamics were an issue. Some students
felt as if they had done all the work while other students had
done very little. To address these concerns, the next year more
time was spent discussing group work, and peer review of
group members was implemented. Another negative com-
ment, noted in both years, was that the project goals were not
well defined. This may, in part, be caused by the open-ended
nature of how the project was implemented. Student groups
were allowed to select their own projects with little input
from the instructor. Perhaps more input is needed when the
groups are selecting projects to ensure that the topic chosen
will yield good results and that the groups properly define
their objectives.

CONCLUSIONS
CO2 absorption in carbonated beverages can be used as a
hands-on activity in an introductory chemical engineering
course to educate students on chemical engineering. This


activity allows students to investigate a relatively familiar
phenomenon, a carbonated beverage going flat, using engi-
neering analysis. The CO2 absorption activity was successfully
implemented in a freshman introductory course at Kansas
State University. Students responded positively to its impact
on their understanding of and enthusiasm for studying chemi-
cal engineering. Most students also listed this activity as one
of the most fun and useful activities in the course. Student
comments indicated that they valued the hands-on nature of
the activity and enjoyed working in groups on a significant
"real world" engineering project.

REFERENCES
1. Unpublished data, based on comparison of enrollment of freshman
chemical engineering students in the fall with enrollment of junior
students in a class taught at the junior level two years later.
2. Seymour, E., "Revisiting the 'Problem Iceberg'- Science, Mathemat-
ics, and Engineering Students Still Chilled Out," Journal of College
Science Teaching 24, 392 (1995)
3. Hesketh, R.E, K. Jahan, T.R. Chandrupatla, R.A. Dusseau, C.S. Slater,
andJ.L. Schm alzel, | ii..i. ll..i I,,: 1I..... ..i 1 1 .1 .. . .. i..11.c
Freshman Clinic at Rowan University, "Proc. 1997Ann. Conf. ASEE,
Seattle (1997)
4. Marchese, A.J., R.P Hesketh, K. Jahan, T.R. Chandrupatla, R.A. Dus-
seau, C.S. Slater, and J.L. Schmalzel, "Design in the Rowan University
Freshman Clinic," Proc. 1997Ann. Conf. ofASEE, Seattle (1997)
5. Ramachandran, R.P, J.L. Schmalzel, and S. Mandayam, "Engineering
Principles of an Electric Toothbrush," Proc. 1999 Ann. Conf ASEE,
Charlotte (1999)
6. Farrell, S., R.P Hesketh, and M.J. Savelski, "A Respiration Experiment
To Introduce ChE Principles," Chem. Eng. Ed., 38(3), 182 (2004)
7. Moor, S.S., E.P Saliklis, S.R. Hummel, and Y.-C. Yu, "A Press RO
System. An Interdisciplinary Reverse Osmosis Project for First-Year
Engineering Students," Chem. Eng. Ed., 37(1), 38 (2003)
8. Henley, E.J., and J.D. Seader, Equilibrium-Stage Separation Operations
in Chemical Engineering, John Wiley & Sons, New York (1981)
9. Crossno, S.K., L.H. Kalbus, and G.E. Kalbus, "Determination of
Carbon Dioxide by Titration, "J. Chem. Ed., 73, 175 (1996) 7


Chemical Engineering Education











Mj =1 laboratory


THE DEVIL'S

IN THE DELTA













WILLIAM L. LUYBEN
Lehigh University Bethlehem, PA 18015


As I enter my 40th year of teaching, it seems appropri-
ate to remind teachers and students of a fundamental
error that occurs with surprising frequency. This error
is particularly evident in courses that cover a wide variety of
chemical engineering topics and pull together subjects sup-
posedly learned in previous courses. The senior design course
and a chemical engineering laboratory with a variety of experi-
ments fit this type of course. In teaching these courses I have
frequently encountered quite bright students who misuse the
deltas. Since the differences among the various deltas should
be obvious and not at all confusing, it is remarkable that errors
of this type crop up so frequently. But they do.
This paper will describe a particularly useful experiment
in the undergraduate Lehigh University chemical processing
laboratory that uses all three of the deltas and, therefore, helps
to cement in the minds of students the fundamental differences
among the three kinds.
Winter 2007


The title of this paper originates from the old expression
"The devil is in the details." (Some of you may also remember
Fip Wilson's famous portrayal of Miss Geraldene with her
expression, "The devil made me do it.")


William L. Luyben earned degrees in
chemical engineering from Penn State
(B.S., 1955) and Delaware (Ph.D., 1963).
His industrial experience includes four
years with Exxon, four years with DuPont,
and four decades of consulting with
chemical and petroleum companies. He
has taught at Lehigh University since 1967
and has participated in the development of
several innovative undergraduate courses.
He has authored 10 textbooks.


Copyright ChE Division of ASEE 2007










THE DEVIL DELTAS
A brief review might be useful to clarify the issues and
applications addressed in this discussion.
"In Minus Out" Delta
An "open" flow process has streams entering and streams
leaving. Mass, component, and energy balances can be applied
under either steady-state or dynamic conditions. For example,
a steady-state energy balance for a distillation column with a
single feed and two products is
AH=Q-W
The delta in this equation is
AH = Bh + DhD Fh
where the streams leaving the column are the distillate (with
flow rate D and specific enthalpy hD) and the bottoms (with
flow rate B and specific enthalpy hB), and the stream entering
the column is the feed (with flow rate F, and specific enthalpy
hF). Of course, appropriate and consistent units must be used
for flow rates and specific enthalpies. If the flow rates are in
moles per time, the specific enthalpies must be in energy units
per mole (e.g., Joule, kcal, Btu).
In a heat exchanger, streams are heated or cooled. Under
steady-state operations with no phase change, a stream enters
at temperature Tin and leaves at temperature Toot. If the mass
heat capacity cp is constant and the mass flow rate is FM, the
AH for the stream is
AH= FMc,(Tout T,)
If there is a phase change, for example if steam is entering
as a vapor with specific enthalpy Hn and leaving as liquid
condensate with specific enthalpy hont through a steam trap,
the AH for the steam is
AH = Fseam (ho.t Hn)
In fluid flow systems, the appropriate deltas are differences
in pressure, elevation, velocity, and density between the inlet
and the exit conditions.


"Driving Force" Delta
Transport processes occur because of differences in driv-
ing forces. In heat transfer, the difference is between hot and
cold temperatures. In mass transfer, the difference is between
large chemical potential and small chemical potential (partial
pressure, concentration, or activity). In momentum transfer,
the difference is between high pressure or velocity and low
pressure or velocity.
For example, consider a perfectly mixed vessel that is
surrounded by a jacket. The temperature of the liquid in the
vessel is Tv .ss Suppose the jacket is completely filled with
condensing steam at temperature Tteam. The driving force for
heat transfer is
AT = Tsteam Tvss
The heat-transfer rate Q that results from the driving force
AT is
Q = UAHAT = UAH (Tteam T,,,
where U is the overall heat-transfer coefficient and AH is the
heat-transfer area of the vessel wall. In this example, the jacket
temperature is the same at all positions in the jacket.
If the vessel is cooled or heated by a fluid flowing through
the jacket or through an internal or external coil in plug flow,
the temperature of this fluid changes with position. Therefore
the temperature driving force changes, and a log-mean tem-
perature difference must be used.
AT T AT,

AT T

where the two deltas are the temperature differences at the
inlet and outlet ends of the jacket or coil.
AT1 = Td T,
AT, = Tv, Tcout
Now the heat-transfer rate is


Steam In (Tco,)Top


SCooling
Water
(T-oo,) tti In
(To0)Bottom


Steam Trap


Condensate Out


Figure 1. Heated or cooled agitated vessel.


Cooling
Water
Out


Q = UAH (AT)LM


n, AT
ATIn
AT,


If a circulating cooling water system is used with a high
rate of circulation, the temperature in the jacket is essen-
tially constant at some temperature, T,. The heat-transfer
rate is

Q = UAHAT= UAH (T,,, T )

In this type of system, a cold makeup water stream at TCn
is added to the circulating loop, and water is removed at
the jacket temperature Tj. A circulating cooling water
system has superior dynamics compared to the once-
through system. The high circulation rate maintains a
high coolant-side film coefficient that does not change
Chemical Engineering Education










with the load on the system (the makeup water flow rate), so
time constants are less variable.
"Time" Delta
The variables in a dynamic process change with time, so we
can talk about changes in time, At, and changes in properties,
Ax, between their value at one point in time and their value at
a later point in time. For example, when the liquid in a vessel
is heated at startup, the temperature changes with time.
AT = T,, Tt

At any point in time the rate of change of temperature is
dT AT T12 -1
dt At t2 t1
if the time increment between t2 and t1 is small.

LABORATORY EXPERIMENT USING ALL
THREE DELTAS
Apparatus
The process consists of a stirred vessel, 1 m in diameter
containing 785 kg of water. The rpm's of the agitator can be
varied to see the effect on the inside film coefficient. A spiral
coil is wrapped around the outside of the vessel, making nine
wraps around the circumference. Figure 1 gives a sketch of the
apparatus. The tank is equipped with a 0.3 m, 6-blade impeller
with four baffles. The heat-transfer area is 3.14 m2.
The liquid in the vessel is initially at ambient temperature. It
is heated by introducing steam at the top of the coil. Conden-
sate leaves at the bottom through a steam trap. Temperatures
inside the vessel and at the inlet and outlet of the coil are
monitored by a data acquisition system.
When the temperature of the vessel reaches about 90 C, the
steam is shut off and cooling water is introduced. The water
enters at the bottom of the coil and leaves at the top.
Data and Analysis
Figure 2 shows typical temperature vs. time trajectories
for the batch heating and cooling. The temperature in the
coil during heating is shown as being constant at the steam
temperature. This is actually not the case because it takes
some time for the coil to become completely full of steam.
This complicates the analysis of the heating step because the
temperature profile along the coil is not known until it is full
of steam. We consider this later in this paper.
The analysis of the cooling step is much more straight-
forward, and our discussion for the purpose of illustrat-
ing the "devil deltas" will concentrate on this part of the
batch cycle.
The flow rate of cooling water is constant and can be mea-
sured by the old-fashioned "bucket and stop watch" method.
The inlet and outlet cooling water temperatures are measured,
as is the vessel temperature.
Winter 2007


At any point in time, there are two ways to estimate the
instantaneous heat-transfer rate. From the measurement of
the cooling water flow rate and inlet and outlet temperature,
the heat-transfer rate at that point in time is

QCW = FCWCp (TC.out Tc,, )
This is the "out minus in" delta. At time equal 30 minutes in
Figure 2, this "out-minus-in" delta is
ATot m = Tc,,ou Tc,, = 38 -15 = 23 C
The heat-transfer rate can also be estimated by the time rate
of change in vessel temperature. This uses the "time" delta.
At time equal tn, the instantaneous rate of heat transfer to the
fluid in the vessel is

S=Tvessel )(t= )- Tvessel (t=t_)
Qvessel(t=t,) = M lCp t

Since the heat-transfer rate varies with time, the slope of
the temperature vs. time curve varies during the batch cooling
step. Having two independent ways to estimate the rate of heat
transfer improves reliability of the estimated film coefficients.
Figure 2 shows this delta at 30 minutes is about 3.5 C per
minute (the slope of the vessel temperature line).
ATe,, = 3.5 C /minute
Using this value, the instantaneous heat-transfer rate is
calculated to be 192 kW. The heat-transfer rate from the flow
rate of cooling water (2 kg/sec) and the inlet and outlet cooling
water temperatures is very close to this number.
The temperature of the cooling water in the coil varies along
its length, so a log-mean temperature difference is used. This
is the "driving force" delta,
T AT -AT,
LM = AT
In --
AT,
42 T2


Figure 2. Temperature profiles and temperature deltas
during cooling.





























Figure 3. Using time delta for heating phase with
constant U and Tte.
where the two deltas are the temperature differences at the
inlet and outlet ends of the coil.
lATi_ T,_, T,
AT = Tv Tcout
The log-mean temperature difference at this point in time is


AT AT1 -AT2
LMa AT1

AT)


(70- 38)- (70-15) 42.5

n 70-38
70-15


With a heat-transfer area of 3.14 m2, the overall heat-transfer
coefficient is

U= 192 1.44kWm 2K
AHATL (3.14)(42.5)
The vessel inside film coefficient can then be calculated by
accounting for heat conduction through the vessel wall and
estimating the film coefficient inside the coil using the Dittus-
Boelter equation and an appropriate equivalent diameter.
Even with a constant agitator speed, there is some varia-
tion of the overall heat-transfer coefficient and the inside film
coefficient with time. This occurs because the varying vessel
temperature affects the viscosity of the water.
Approximate Analysis for Heating Step
If the temperature in the coil was constant during the heat-
ing period and the overall heat-transfer coefficient was also
constant with time, the analysis would be quite simple. It
would use "time" deltas in a way that may not be obvious. The
situation is analogous to the steady-state flow of fluid down the
length of a heated tube. In that situation, the appropriate driv-
ing force for calculating the heat-transfer rate is a log-mean
temperature difference using the temperature differentials at
the inlet and exit ends of the tube. The log-mean temperature
difference assumes a constant heat-transfer coefficient. The
independent variable is length.
22


In the batch heating situation, the independent vari-
able is time, but the heat-transfer equations are the same.
Therefore, total heat transfer can be calculated by the
change in vessel temperature from some point in time to
another point in time. The driving force can be calculated
using a log-mean temperature difference based on the
difference between the constant steam temperature and
the temperature of the vessel at the two points in time.
The similarity between length and time coordinates is
understood if you visualize a little particle of fluid flow-
ing down the tube in steady-state flow. It sees a constant
steam temperature and is heated as it flows along. This is
exactly the same as the batch heating of a vessel.
It should be emphasized that the analysis discussed
in this section makes two important assumptions. First,
the steam temperature is constant. Second, the overall
heat-transfer coefficient is constant.
Figure 3 shows how the vessel temperature changes during
heating. It starts at T when time is t and ends at T when time
is t2. The total amount of energy added during this period is
Energy = M .Cp (T2 T )

The average heat-transfer rate over this period is
= Energy Mss1 Cp (T2 T)
Q_


t2 t


t2 t


The instantaneous energy balance on the fluid in the vessel
is
dT
MvesselC Vssel = AHU Tstm Tesse )
dt
This linear ordinary differential equation can be integrated
to give


Tvessel(t) = Tsteam cle
The constant of integration c1 is evaluated at the initial condi-
tion where T = T1.

c = (T T ,a

The time dependent vessel temperature is


Tvessel(t) = Tsteam + 1 Tsteam ) e
Evaluating this equation at time equal t2 where T vi = T2
gives


T2 = T, T + ( T T, )e'


Rearranging gives


T-T
T2 steam
T etam
Zl steam


S-tl


Chemical Engineering Education










Taking the natural log of both side of this equation gives

In team t =- AHU (t
eam T1 .essel c
Rearranging and substituting the previously defined equation
for Q give


T T
In steam 2
Ts,,, 1T,


AHU(T T)
Mveselcp (T2 T )
(t2 t)


1n t T, T, ^ AHU(T
steam T, Q

Q =UAH ) UAH (team
In steam T2
team = UA (T)
Q= UAH(AT)L


-T)


T2 ) (TTseam T)

In steam T2
Steam 1


In our experimental apparatus, the temperature through the
entire coil is not equal to the steam temperature for about half
the heating period. In addition, the change in viscosity due to
changes in temperature results in variations in the heat-transfer
coefficient. So, the simple analysis described above can only
be applied for the period toward the end of the heating step.
During the initial part of the heating step when the tempera-
ture of the exit stream from the coil is not equal to the inlet


temperature, the full heat-transfer area is not being used for
steam condensation. Thus it is uncertain how to calculate an
internal heat-transfer coefficient. One approximate method
is to assume that the active heat-transfer area varies linearly
with time during this period.
Once the temperature of the exit stream from the coil be-
comes equal to the inlet temperature, either the approximate
method discussed in this section or a rigorous approach can
be applied. The rigorous method evaluates the inside film
coefficient at each point in time by getting the heat-transfer
rate from the rate of change of the vessel temperature, and
using the differential temperature driving force of Tteam minus
T and the full heat-transfer area.
For example, in Figure 2 at time equal 20 minutes, the
differential temperature driving force is 100 85 C and the
slope of the Tv si curve is about 1.3 C per minute.

CONCLUSION
This paper has attempted to provide a clear distinction
among the three deltas that are used in chemical engineering.
Although they are obvious to the experienced engineer, they
are often misapplied by young students.

ACKNOWLEDGMENT
Discussions of this experiment with Kemal Tuzla are grate-
fully acknowledged. 7


Winter 2007










Mr[ laboratory
---- U s_____________________________________


AN INTERNET-BASED

DISTRIBUTED LABORATORY

for Interactive ChE Education













JING Guo, DAVID J. KETTLER, MUTHANNA AL-DAHHAN
Washington University St. Louis, MO 63130
practical experimentation that processes real signals is Jing Guo received his B.S. degree in chemical engineering in 1997 and his
M.S. degree in 2000, both from Beijing University of Chemical Technology.
essential to helping students understand theory given He received his Ph.D. degree in chemical engineering from Washington
in textbooks and giving them skills to deal with real University in St. Louis in 2005, where he worked on the experimentation of
catalysis in multiphase reactors, including trickle bed reactor and packed
problems successfully. An indispensable part of the chemical bubble column. He also developed a modeling program to simulate the
engineering curriculum, the experimental class is designed multiphase reactions for applications ranging from bench-scale to com-
to train all students at the same time and in an effective way merci-scale.
for acquiring face-to-face interaction. This conventional ap- David J. Kettler was awarded double bachelor degrees in biomedical
proach, however, imposes difficulties on students with time and chemical engineering from Washington University in St. Louis in 2001.
During his study, he was also responsible for developing the Process
or distance constraints. Moreover, due to both safety and Control Laboratory's homepage and the Simulink Virtual Laboratory as an
security reasons, access to labs cannot be totally free and is interactive series of workshops.
restricted in time to ensure the presence of supervision person- Muthanna H. AI-Dahhan is an associate professor of chemical engineer-
nel. Interesting proposals have been made to use the Internet ing at Washington University in St. Louis and associate director of the
r v e p in in difr ty o Chemical Reaction Engineering Laboratory. He received his B.S. degree
for various educational purposes, including different types of in 1979 from the University of Baghdad in Iraq, M.S. degree in 1988 from
virtual laboratory Web sites,['] interactive simulations,[2] and Oregon State University, and Ph.D. degree from Washington University
access to real instruments and test benches through a remote in St. Louis in 1993. His research interests are in the fields of chemical
reaction engineering related to multiphase reactor systems, mass transfer,
connection.[35] In fact, some implementations of remote moni- and process engineering. He is author of more than 80 papers in the field
touring and control through the Internet have already reached of chemical engineering.


Copyright ChE Division ofASEE 2007


Chemical Engineering Education










the teaching laboratories of physics161 and electrical engineer-
ing.l1 For chemical engineering laboratories, this capability
is now available at University of Tennessee at Chattanooga,E81
University of Texas at Austin,[91 and MIT.1101
With appropriate planning, teachers and students can run
Web-connected experiments on a flexible schedule, which
provides educational facilities and opportunities for those
students whose schedules might be asynchronous.18 "1 An-
other advantage of such remotely accessible laboratories is
that teachers and students at another institution can have ac-
cess to laboratory facilities without incurring the full cost of
developing such resources. Rather than several universities
spending money on the same equipment for the same experi-
ments, cooperating universities may each carry out one unique
experiment and then form an experiment pool.12' 131 Using
such highly automated experiments for remote operations
can allow a drastic reduction in the amount of personnel time
required for those particular experiments. It is reported that
online laboratories hold promise of being up to two orders
of magnitude cheaper than conventional ones.1141 Having
access to tutorials, pictures, past data files, data processing
tools, and graphs tracking the dynamic process variables,
these Web pages provide students with sufficient resources
that can be viewed simultaneously by all class members.1101
Such expanded access allows the students and instructors to
spend less time communicating the operating procedure and
more time investigating the experimental results. Remote
learning has evolved into a new model of high quality aimed
at engaging students in a distinctive learning technology that
helps build a solid foundation.19, 5]
Advances in available computer software and interfacing
techniques enable remotely operated laboratory experiments
to be constructed at relatively low cost.1161 In this paper, we
report on the in-house development of remote control and
measurement methods for a chemical engineering labora-
tory on unit operations, which is offered to undergraduate
students at Washington University in St. Louis. A client-server

Remote Client HTTP Server
TCP/IP
Client Applcations Network Network Instrument Management
(Measurement Management Management (Board Drivers,
& Control Client Side Server Side Command Process)
User Interface)


Figure 1. Diagram of the client-server architecture
employed to implement the remote control measure
Winter 2007


architecture devoted to instrument management through the
Internet is built with Visual Basic and LabTECH program-
ming tools, providing a novel approach in comparison to the
Java and LabView software employed in other references.18
101 The architecture is described along with the specification
and design of a geographically distributed system based on
standard commercial components. Used for the required
undergraduate process control course, a tracer experiment
is restructured to illustrate the connection between physi-
cal instruments and the server-client Internet system. The
experimental data is archived for subsequent viewing and
analysis, and the responses of students to the online experi-
ment are assessed.

SYSTEM ARCHITECTURE
To achieve a standard component distribution system,
we adopted Internet technologies that allow portability and
independence through different client hardware/software
architectures. A standard portable language is instrumental
for independence of the application from the client system
on which it is executed. An Internet browser can now be con-
sidered a standard component of any computer installation.
Therefore, our approach will automatically work with any
widely available hardware/software environment.
The connection between the server and client program
is made by a TCP/IP Winsock socket located within both
programs, which functions much like a phone receiver/dialer
on each side of the Internet. The server and the clients are
connected on the same local area network (LAN) within the
laboratory or campus. Remote connections can even be set up
between the server and a single user working at home.
TCP/IP defines the physical interconnection, data transfer,
and message routing management. It is the typical protocol
suite adopted in the standard Internet.11 The server sends
measurement data to the client the same way the client sends
control commands to the server, by creating a string of num-
bers representing all the commands or measurements and
sending them through the TCP/IP socket. Like-
Lab Setup wise, once the client receives the measurement
string of numbers and the server receives the
control string of numbers, the string is parsed,
and each measurement or command within
the string is sent to its appropriate subroutine
within the client or server code.
S A block diagram of the proposed solution is
shown in Figure 1. The clients are hosted on
a user's personal computer while the server
runs on a laboratory computer and manages
an automatic control and measurement system
that embeds programmable instruments. Both
client and server computers run programs that
are logically split into two layers. One layer
e in both client and server sides deals with user
ient.
25


H a
II Cntrol

I-- -Measurement


Connect


Reply
Close
4j--


I-










[An] advantage of such remotely accessible laboratories is that teachers and
students at another institution can have access to laboratory facilities
without incurring the full cost of developing such resources.


interface and instrument management, while the other layer
deals with network intercommunication. The server is directly
connected to the instruments that measure physical quanti-
ties. In this work, the server computer, connected physically
to the instruments, makes available a set of remotely callable
procedures that perform all standard activities (address, read,
write, status poll, etc.). The client's command generator is-
sues commands according to the parameter set specified by
the user, and sends them via the TCP/IP client socket to the
server. The experimental results sent back by the server are
then handled and displayed in the client window. The sockets
of the client program and the server program are connected
by using the server computer's IP address on the Washington
University network. The same local port number must be
specified within both the client and server sockets. Socket con-
nections and the TCP/IP communication protocols transmit
the instrument control commands, parameters, and reports
between client and server.
Only one user group is allowed to connect at one time,
because physically only one experimental run can be done
on the reactor at a time. At the session's termination, the
socket connection is closed and the server can accept a new
connection on the same port to start a new session. If the
client/server connection is broken or remains idle more than
five minutes, the server application shuts down the system.
If the power shuts down, a system of safety interlocks in the
physical system prevents the system from running indefinitely.
To protect the server, several techniques can be used, e.g.,
access restriction based on user identification, firewalls, and
encryption. For simplicity and cost reasons, we adopted an
approach based on access restriction through user verifica-
tion of both the password and the IP address of the gateway
through which client connects to the server.
On the server site, the structure offers great flexibility.
Developed in Visual Basic, the programs require only the
addition of a very small number of statements necessary
for establishing and closing the interface-related functions
of corresponding network functions. When new instru-
ments are added to the instrument library, it is easy to add
a measurement or control variable with small modifications
to existing programs. The software related to any newly
connected equipment can be added to the system without
recompiling or modifying the application core. About two
or three lines added to the server and client programs will
add numbers representing the additional measurement or
control variables to the string sent through the TCP/IP
socket.


At the client site, because the whole core of the software
application (i.e., the components required to share, engage,
and release the resources) resides permanently on the server
computer, it is not necessary to install any special software
tool. Once a new client connection is accepted, the user lo-
cally runs the command necessary for selecting and driving an
instrument. As a consequence, the proposed structure makes
the application portable and safe for remote users.
The server is a Pentium-IV computer with a 1 GHz pro-
cessor, provided with two independent Universal Serial Bus
(USB) ports. The server runs on Windows 2000 Professional
and uses drivers from Data Translation to access the Data
Translation DT9804 interface board. The server connects
to the interface board using a USB cable, and the interface
board has analog input/output and digital input/output ports
for connection to the physical control hardware of the reactor
system. The overall system has been devised to assure reliable
communication between the client and the server, and between
the server and the physical resources available. A LabTECH
ControlPro 12.1 Runtime program receives data and sends
commands to the control hardware via the DT9804 interface
board. Once the control hardware and server are physically
connected to the DT9804 board and the board's drivers are
installed, LabTECH can be set up to control the hardware
by dragging and dropping control icon blocks from its menu
into its workspace.

BUILDING EXPERIMENTAL INSTRUMENTS
The lab setup icon shown in Figure 1 represents any real
instrument that requests automatic control and measure-
ment. The proposed server-client system structure can be
extended to fit a variety of requirements and serve different
experiments. As a test case performed on implementation of
the whole system, a tracer study experiment is carried out
remotely in real time over the Internet, using a tubular reac-
tor in the Chemical Engineering Laboratory at Washington
University. The purpose of the tracer test is to experimentally
determine the ideality of a real continuous flow reactor.

In an ideal plug flow reactor, the fluid flows through the
reactor with a pistonlike motion and no axial mixing. A real
tube reactor, however, cannot reach this ideal state. In the
experiment, a conductive tracer was injected into water just
before the reactor entrance and the conductivity of the solu-
tion mixture was measured at the reactor entrance and exit.
The mean residence time, tracer response curve variance,
dimensionless variance, and axial dispersion coefficient can
Chemical Engineering Education











then be calculated. Through data analysis, the tube reactor
was compared with an ideal plug reactor.
Figure 2 displays the physical hardware built for the tracer
study experiment. The students open the feed flow valve,
adjust the water flow rate by varying valve position, start
the tracer feed pump, adjust the tracer injection duration,
open the tracer injection valve, and then inject the tracer. Air
pressure (30-100 psi) is used as the driving force to control
the feed flow valve and the tracer injection valve. The feed
flow rate is measured by a turbine flow meter downstream,
and the measurement is sent to the client application. The
conductivity measurement will rise and then fall back to the


steady state value, at which point the students may close the
client application.
Table 1 lists all of the process variables used as signals in
the tracer experiment. Digital signals are either on or off when
equal to 1 or 0, respectively. Analog signals send (Output)
or receive (Input) signals within a defined range of values,
shown in the "Range" column in Table 1. The output signals
control the instrument setup, while the input signals are
variable measurements obtained at a specific condition. The
types of all variable signals are listed in the "Type" column.
The elements that launch and receive signals are listed in the
"Origin" and "Destination" column, respectively.


Water in Feed Flow Valve


Air in


..- Flow
------ -- Pneumatic line
------- Computer signal


KC1 Tank Pump


Figure 2. Overview of the physical experimental setup
and its connection to the Web.


NETWORKING CREATION FOR
ONLINE CONTROL
AND MEASUREMENT
The first application in the server computer is
the LabTECH Runtime program Traceexe.ltc.
It initiates the connection between the physical
laboratory setup and the server computer. This
connection channel receives measurement sig-
nals from the USB port on the interface card and
issues commands to control the setup operation.
All measurement variables are classified as analog
inputs in the Traceexe.ltc program. By specifying
the correct interface point, each analog input block
in Traceexe.ltc receives the proper signal from the
interface card.
The second application in the server computer,
ServerTracerStudy.exe, activates the server site
and enables it not only to transfer the remote cli-
ent signal to the physical setup, but also to receive
measurements from Traceexe.ltc by continuously
using the GetLT function. This function uses a


TABLE 1
Process Variables Used in the Tracer Experiment
Variable Range Units Type Origin Destination
Reactor Feed 0-1 Volts Digital Output "Client_TracerStudy.exe" Control Hardware
Valve
Tracer Feed Pump 0-1 Volts Digital Output "Client_TracerStudy.exe" Control Hardware
Inject Tracer 0-1 Volts Digital Output "Client_TracerStudy.exe" Control Hardware
Tracer Injection 1-3 sec Analog Output "Client_TracerStudy.exe" "Server_TracerStudy.exe"
Duration
Reactor Feed 0-100 % Analog Output "Client_TracerStudy.exe" Control Hardware
Valve Position
Run Time >0 sec Analog Input "Traceexe.ltc" "Client_TracerStudy.exe"
(Reactor) Influent >0 mS Analog Input Control Hardware "Client_TracerStudy.exe"
Conductivity
(Reactor) Effluent >0 mS Analog Input Control Hardware "Client_TracerStudy.exe"
Conductivity
(Reactor) Feed >0 1/min Analog Input Control Hardware "Client_TracerStudy.exe"
Flow Rate
Winter 2007












DATA
IRun Time 128.900 Isec

IFeed Flow Rate 0.17608 Ilpm


Influent Conductivity 1591.491 ImS


IEffluent Conductivity 155.389 ImS


1' I
Figure 3. User interface for the client application.

built-in LabTECH application called LT-Speedway to "grab"
the analog input data received by Traceexe.ltc. The program
ServerTracerStudy.exe takes four measurement variables it
receives from its GetLT function and combines them into
one string of text, called OutputString. Once the client
connects to the server computer using the client program
Client_TracerStudy, then Server_TracerStudy.exe sends
OutputString across the Internet once every 100 milliseconds
to the client program, using a timer within the server program
called Timer2.
These two applications must be running before a student
can access the experiment using the client program, Cli-
entTracerStudy The student downloads this program from an
Internet page and stores it on the remote computer. Once the
student double clicks on the related icon, the client program
opens up and connects to ServerTracerStudy on the server.
Every command the user manipulates sends text data from the
client TCP/IP socket across the Internet to the server TCP/IP
socket. The server program sends measurement data acquired
from the LabTECH Runtime program Traceexe.ltc back to the
client through TCP/IP socket and sends the control variable
commands acquired from the client to Traceexe.ltc, where it
is executed by that program on the control hardware.
The controlled variables, reactor feed "Valve Position" and
tracer "Injection Duration," are analog outputs in Traceexe.
Itc. Before injecting the tracer, the student sets the values
of analog outputs by using a scroll bar on the user interface
of the client program, Client TracerStudy.exe, as shown in
Figure 3. The student must also open the reactor "Feed How
Valve," turn on the "Tracer Feed Pump," and "Inject Tracer"
by pushing the respective buttons on the client user interface.
These are digital outputs in Traceexe.ltc. Whenever the stu-
dent pushes one of the buttons (digital) or slides one of the
scroll bars (analog) on the client user interface, the current
values of all the digital outputs are combined with the analog
outputs as a text string called InputString in the InputData
function in the client program. Then InputString is sent to the


CONTROLS
Feed Flow Valve
ON

|Feed Valve Position 501%

1:: r:::::: ac Eea:EiulmB::::::
ON


Infection Duration 21sec
INJECT TRACER
TRACER READY


IWater Flow Valve 0

Water Valve Position 50

Tracer Recirc. Pump [0

Iniect Tracer 0

Infection Duration 10


IWater Flow Rate 0.00549

Ilnfluent Conductivity 1592.376

IEffluent Conductivity |557.586

Client IP: INo one is connected


Check State I


Figure 4. Monitoring window for the server application.
Chemical Engineering Education


-.101A


server program through the client TCP/IP socket. The server
program picks up the InputString of text across the Internet
at its TCP/IP socket, separates all of the outputs, and places
them in their respective textboxes, as shown on the lefthand
side of the image in Figure 4. In the server application, the
function PutLT takes each of the values in the textboxes on
the lefthand side of the server monitoring window and sends
them to their respective input block in Traceexe.ltc. The input
blocks receive each signal in Traceexe.ltc and send them to
their corresponding Bit Number (digital) or Interface Point
(analog) on the DT9804 interface card.

LABORATORY EXPERIENCE
On the project Web site (),
eight groups of undergraduate students have participated in
the online operation test. After a class of introduction to the
distributed learning technology and two additional classes
on the theoretical aspects of the experiment, the instructor
demonstrated and monitored experiments using a classroom
computer connected to the Internet. When the students were
doing the measurements themselves in the computer lab one
floor above the laboratory, they were asked to provide their
inputs on the user-interface, analyze the experimental out-
comes, and answer questions posed by the instructor through
interactive dialog. Explanatory Web pages were provided to
answer most of their questions on the real instruments during
the lab session. As a result of this interactive tutoring mode,
students showed more interests in the online operation than
the local on-site operation.
During the lab session, students issued commands and pa-
rameters from the client window to the server via the TCP/IP
client socket. The experimental results were sent back by the
server and then handled and displayed in the client window.
The client program created a log containing measurements
of time, flow rates, influent conductivity, and effluent con-
ductivity. Once the client application is closed, students can
open this log to analyze the evolution of the collected tracer


iiiii TCP Seryer WamsiiijiTrcejSudylim













0.05
0.04 Inlet
a 3
0.03 -
o 3 Outlet
0.02

0.01 :

0
0 10 20 30 40 50 60 70 80
Time (s)

Figure 5. Typical tracer response curves shown in
the client side. Measurements are taken at the inlet and
outlet of the tubular reactor.

response. Typical tracer response curves at the inlet and outlet
with respect to time are shown in Figure 5. In an ideal plug
flow reactor, the tracer curves collected at the exit and entrance
would be identical as thin, spikelike peaks. This experiment,
however, found that dispersion and stagnancy have significant
effects on the tracer response curves. The best flow model
was determined to be a plug flow reactor with a dead zone to
account for the stagnancy, followed by a mixed flow reactor
to account for the axial dispersion. The reactor's nonideality
must be included in order to predict reactant conversion from
given feed rates and reactant compositions.
The experiment was conducted twice, once at a remote
client computer station that was Internet-linked to the server,
and once at the server computer station directly attached to
the setup elements. The typical experimental values obtained
from the online remote control and on-site local control, as
well as the relative error between these two values, are listed
in Table 2. Although there is a time delay between the client
and server due to the Web data transfer and the instrumenta-
tion synchronization, this delay penalty is negligible when
instruments take a long time to complete the measurement.[41
Hence, the insignificant relative error leads us to conclude that
the online control and on-site control give rise to the same

I TABLE 2


residence time measurement in the tubular reactor.
Student feedback is a key consideration for improvement
of the experiment. Surveys were filled out by the students
after each lab session to evaluate the beneficial features of the
remote learning experience and the fulfillment of educational
objectives. The responses contained encouraging comments
and constructive suggestions. In general, the proposed survey
recommendations were implemented before the next student
group was invited to evaluate the lab session. Students agreed
that lab sessions became improved with more user-friendly
options and tools added to the client window. One feature the
students liked most about operating experiments remotely was
that it allowed them to perform the process at any time from
a place that was convenient for them. The other appreciated
feature was that the remote operation helped the students get
used to a real world application that was either in a remote
control room or at a remote operation facility, especially when
hazards and safety concerns were present. Some students
showed intention to run the on-site physical experiments as
the complimentary reference check since their understand-
ing of the experimental flow scheme can be enhanced with
the actual devices in front of them. Actually, this intention
could be fulfilled by incorporating the live audio and video
streaming to the remote client window so students can listen
to the sounds of the device station and view it on the Internet
while they are operating. Such sophisticated user interface
will soon be added to the current system.

CONCLUSIONS
This paper describes an Internet-based client-server archi-
tecture specifically designed to allow flexible management
of remote instruments. The proposed solution is portable
using the employment of the TCP/IP protocol suite, and
also extensible because of the high level of abstraction in
system implementation. This approach offers a valuable
component to remote engineering instruction that cannot be
replaced by simulation software packages. Compared to the
traditional way of teaching, due to the absence of schedule
and physical constraints, this new approach reaches students
who otherwise would not have chance to take these courses
and allows a larger and more diversified audience to access
learning opportunities. A set
S of experiments based on the


Experimental Measurements of Residence Times
Valve Opening Actual Flow Local Control Remote Control Relative
Position (%) Rate (cm/sec) (sec) (sec) Error (%)
45 2.93 22.96 23.77 -3.53
55 3.86 18.32 19.02 -3.82
65 5.11 14.57 14.97 -2.75
75 6.02 11.90 12.19 -2.44
85 6.44 11.74 11.38 3.07
95 6.67 10.87 10.67 1.84
Winter 2007


proposed technique for the
control of remote instru-
mentation has been made
available to the students
of chemical engineering
laboratory courses held in
Washington University in
St. Louis. There is the op-
portunity to use this technol-
ogy to add other experimen-












tal demonstrations or assignments to one lecture. In order to
expand the scope of the experiments and to share costs and
software development time, we are planning collaboration on
this project with other universities.


REFERENCES

1. Ferrero, A., and V. Piuri, "A Simulation Tool for Virtual Laboratory
Experiments in a WWW Environment," IEEE Trans. Instrum. Meas.,
48,741 (1999)
2. Shin, D., E.S. Yoon, S.J. Park, and E.S. Lee, "AWeb-Based, Interactive
Virtual Laboratory System for Unit Operations and Process Systems
Engineering Education: Issues, Design, and Implementation, "Comput-
ers and Chem. Eng., 26, 319 (2002)
3. Benetazzo, L., M. Bertocco, E Ferraris, A. Ferrero, C. Offelli, M.
Parvis, and V. Piuri, "A Web-Based Distributed Virtual Educational
Laboratory, "IEEE Trans. Instrum. Meas., 49, 349 (2000)
4. Bertocco, M., F Ferraris, C. Offelli, and M. Parvis, "A Client-Server
Architecture for Distributed Measurement Systems," IEEE Trans.
Instrum. Meas., 47, 1143, (1998)
5. Arpaia, P, A. Baccigalupi, E Cennamo, and P Daponte, "A Measure-
ment Laboratory on Geographic Network for Remote Test Experi-
ments, "IEEE Trans. Instrum. Meas., 49, 992 (2000)
6. Enloe, C.L., WA. Pakula, G.A. Finney, and R.K. Haaland, "Teleopera-
tion in the Undergraduate Physics Laboratory--Teaching an Old Dog
New Tricks," IEEE Trans. Educ., 42, 174(1999)


7. Shen, H., Z. Xu, B. Dalager, V. Kristiansen, O. Strom, M.S. Shur, T.A.
Fjeldly, J.Q. Lu, and T. Ytterdal, "Conducting Laboratory Experiments
Over the Internet, "IEEE Trans. Educ., 42, 180 (1999)
8. Henry, J.,"Web-Based Laboratories: Technical and Pedagogical Con-
siderations, "AIChE Annual Meeting, Reno, NV (2001)
9. Rueda, L., and T.F Edgar, "Process Dynamics and Control Experiments
Carried Out Over the Internet, "AIChEAnnual Meeting, San Francisco
(2003)
10. Colton, C.K., "Heat Exchanger Experiment at MIT," International
Conference on Engineering Education, Valencia, Spain (2003)
11. Latchman, H.A., C. Salzmann, D. Gillet, and H. Bouzekri, "Informa-
tion Technology Enhanced Learning in Distance and Conventional
Education, "IEEE Trans. Educ., 42, 247 (1999)
12. Cameron, I.T., "An Interactive Web-Based Decision Support System
for Hazardous Industry Land-Use Planning," Computers and Chem.
Eng., 24, 1057 (2000)
13. Shin, D., E.S. Yoon, S.J. Park, and E.S. Lee, "Web-Based Interactive
Virtual Laboratory System for Unit Operations and Process Systems
Engineering Education," Computers and Chem. Eng., 24, 1381
(2000)
14. Aung, W, P Hicks, L. Scavarda, V. Roubicek, and C.H. Wei, "Engineer-
ing Education and Research: A Chronicle of Worldwide Innovations,"
Arlington, VA, USA: iEER (2001)
15. Hough, M., and T. Marlin, "Web-Based Interactive Learning Modules
for Process Control," Computers and Chem. Eng., 24, 1485 (2000)
16. Ferrero, A., S. Salicone, C. Bonora, and M. Parmigiani, "ReMLab: A
Java-Based Remote, Didactic Measurement Laboratory, "IEEE Trans.
Instrum. Meas., 52, 710 (2003) 1


Chemical Engineering Education











classroom
--- ^ K.___________________________-


A REALISTIC EXPERIMENTAL DESIGN

AND STATISTICAL ANALYSIS

PROJECT


KENNETH R. MUSKE AND JOHN A. MYERS
Villanova University Villanova, PA 19085-1681
The teaching of statistics can be one of the most chal-
lenging topics in the engineering curriculum. Students
often find the subject matter abstract and the plethora
of equations used in analysis rather confusing. For these
reasons, an applied approach that emphasizes and reinforces
how concepts presented in the statistics course can be used
in the practice of engineering has been proposed.1" An ex-
ample is the use of the senior laboratory course to reinforce
the concepts presented in the engineering statistics course.[2]
A stronger emphasis on case studies and realistic problems
of direct interest to engineering students is also suggested
to help motivate and create a more positive attitude toward
statistics] and engineering education in general.[4]
The statistical analysis project described in this article began
as a reactor simulation for a senior design course project. It
was later integrated into the professional development course,
and, after a curriculum revision, the Applied Statistics course,
over the last five years. The novel aspects of this project are
that the students are given a budget with which to perform


their experimental study, and the experimental results are
made available to the students one day after an experiment
is requested. Although a process simulation is generating
the experimental results, the intent is to mimic a realistic
experimental study where results are not available immedi-

Kenneth Muske is the Mr. and Mrs. Robert F. Moritz Sr. Chair of Systems
Engineering and professor of chemical engineering at Villanova University,
where he has taught since 1997. He received his B.S. and M.S. from
Northwestern (1977) and his Ph.D. from the University of Texas (1990), all
in chemical engineering. Prior to teaching at Villanova, he was a technical
staff member at Los Alamos National Laboratory and worked as a process
control consultant for Setpoint, Inc. His research and teaching interests
are in the areas of process modeling, control, and optimization.
John Myers is an emeritus professor of chemical engineering at Villanova
University, where he had taught from 1963 until his retirement in 1999.
He received his B.S. (1958), M.S. (1960), and Ph.D. (1964) in chemical
engineering from the University of Kansas. His teaching interests are in
the areas of process design, transport operations, and statistics. His
research interests are in the area of process design and operations.
He also served as a consultant to local industries. He currently spends
much of his time traveling.


Copyright ChE Division ofASEE 2007


Winter 2007










ately and there is an economic limit imposed on the amount
of information that can be obtained.

The pedagogical advantage of this approach is it requires
students to efficiently plan and adjust their experimental data
collection. A similar experimental design philosophy for a gas
chromatography experiment is described in Reference 5. It
also incorporates student data into the analysis exercise. The
integration of data sets collected by students into the teaching
of statistics as part of class projects and exercises has been
widely advocated. The benefits of this integration are the
incorporation of problem-based learning into the statistics
course,[6] and the recognition that experimental data sets
represent observations from a larger popula-
tion distribution, which may yield different
"answers" from a statistical analysis.71 An The appr
important goal of any engineering statis-
tics presentation is the appreciation that a article ..
single measurement does not represent the videe
"true" value.[8]
syn
The approach in this article also avoids that ca
the "video game" syndrome that can occur
in process simulation exercises. Although prOcess
simulation modules can be very useful exe
teaching and learning aids in chemical en-
gineering education, they can also impart
an exhaustive iteration approach to problem
solving and a lack of appreciation for the true time scale of
real engineering processes. The addition of a cost and the
delay of simulation results in this project are intended to
address this issue.


EXPERIMENTAL ANALYSIS PROJECT
OVERVIEW
In this project, the students determine the kinetic rate
constants of both the forward and reverse reaction for the
hydrolysis of ethylene to form ethanol.
CH, + H20 = C2,HOH
The hydrolysis is a vapor phase reaction that is catalyzed
by phosphoric acid supported on porous solid catalyst pellets.
The reaction rate for the hydrolysis can be expressed as
R (A) = k,PEP kP, (1)
in which R(A) is the rate of formation of ethanol (i, I 1 ti ,'i in i.
k is the forward reaction rate constant
(gmol/ fmin-bar2), k is the reverse reaction
'h in this rate constant (gmol/ -min-bar), and PE, Pw,
voids the PA are the partial pressures (bar) of ethylene,
water, and alcohol.
meThe students are told that they have a
me packed-bed tubular reactor available to
cur in carry out hydrolysis reaction experiments.
They must specify the molar flow rates of
ulation the feed components, the outlet reactor pres-
Ses. sure, and the average reactor temperature for
each experiment. The molar feed rates of the
reactants (steam and ethylene) and an inert
gas (methane) may be varied by adjusting
the corresponding flow controllers. Methane is supplied to
the reactor in order to dilute the reacting species and prevent
a runaway reaction. The average reactor temperature and
reactor outlet pressure can also be varied by adjusting the


Tubular Reactor
Length = 1 m
Diameter = 0.05 m
D Void Fraction =40% %


Ge Gw G


YA Yw YH


Safe Operating Temperature Range: 300-400 Deg C
Operating Temperature Limits: 250-450 Deg C
Safe Operating Pressure Range: 47.5-60.5 bar
Operating Outlet Pressure Limits: 34-68 bar

Reaction Specificationn

T Reactor average temperature (Deg C)
Po Reactor outlet pressure (bar)
G Ethylene molar feed rate (gmol/min)
G, Water molar feed rate (gmol/min)
Gm Methane molar feed rate (gmol/min)


,,1,- ,Molar Flow Operating Limits: 0*-20 gmole/min
EthLleneolar Flow Operating Limits: 0*-25 gmole/min
Methane Molar Flow Operating Limits: 0*-25 gmole/min
* Flow rates below 0.01 can not be accurately controlled


Reaction Result,

P Inlet Pressure (bar)
YA Alcohol (mole fraction)
Y Water (mole fraction)
YH Ethylene+Methane (molfrac)


Figure 1. Experimental reactor system.


Experimental Costs

$100,000 TotalBudget
$1000 Reaction Experiment
$200 Replicate Experiment
$2500 Expedite Results
$9500 Replacement Reactor


Chemical Engineering Education


roac
. a
o g
dro
n o
sim
Trci


---------










respective controllers. The reactor outlet
gas stream is sampled and analyzed for
alcohol fraction and hydrocarbon frac-
tion (ethylene plus methane). Since water
cannot be analyzed, it is determined by
difference.
The students are given a feasible reac-
tor temperature range of 300 to 400 C
and inlet pressure range of 45 to 65 bar.
Under these conditions, the reactor can
be safely operated. There is a potential, *
however, for the reactor to detonate due
to an exothermic, runaway reaction at
higher temperature or pressure. The initial
students are informed that temperatures
beyond 400 C and inlet pressures beyond
70 bar are dangerous and can very likely
result in detonation of the reactor. Operation of the reactor
with methane in the feed at the higher temperature and pres-
sure range is also recommended. The students must therefore
first determine safe operating conditions from initial experi-
mental trials as discussed in the sequel.

The project is carried out in two- or three-person groups.
Each student group is given a $100,000 budget to carry out
the experiments necessary to determine the reaction-rate
constants. Each experiment costs $1,000 for the initial run at
a given set of operating conditions and $200 for each replicate
run at the same conditions. The results from each experiment
are made available the day after they are requested. An ad-
ditional $2,500 cost is incurred in order to receive the results
on the same day for each expedited experiment and replicate
requested. Experiments can no longer be carried out when
there are insufficient funds to cover the cost. If the chosen
operating conditions cause the reactor to detonate, the students
are charged $9,500 for a replacement. The intent of this aspect
of the project is to illustrate that, as in an actual experimental
study, there are consequences to poor experimental design
choices. A schematic of the reaction system is presented in
Figure 1.

EXPERIMENTAL STUDY
The students are asked to determine the Arrhenius equation
parameters, activation energy, and pre-exponential factor for
the forward and reverse rate constants. They are also asked to
verify that the rate constants follow the Arrhenius equation

k = ko exp (-Ea / RT) (2)

over the feasible reactor temperature range where ko is the
pre-exponential factor, E is the activation energy, and T is
absolute temperature. Both ko and E can be determined by
obtaining each rate constant at two or more temperatures and
using the logarithmic transformation of Eq. (2)
Winter 2007


regression line through the origin
slope = kf













Figure 2. Example initial rate data regression.



Ink = Inko -E 1 (3)
RT

where In k is the y-intercept and -Ea/R is the slope of a linear
regression of In k as a function of 1/T. In order to determine
the forward and reverse rate constants students must carry
out two different types of experiments.
Irate data non-initial R ate ExperimentsPw
Thgure 2. Example initial rate method of measuring reaction rate constants







is used to detennine the forward reaction rate constant kf. This
Ink = Ink E- l (3)





wherique make is the followinintercept and assumption: 1) there of a liners so
little product fof edn k as a function of T. In order to determine
and,the forward and reversion of the cnstants is small ents must carry
out two different types of experim taken as constant. Using these
Initial Rate Experiments



The initial rate method assumptions with an idof measuring reaction rate constants
is used to determine the forward reaction rate constant kf. This
technique makes the following assumptions: 1) there is so
little product formed that the reverse reaction is negligible;
and, 2) the conversion of the reactants is small enough that
their concentrations may be taken as constant. Using these
initial rate method assumptions with an ideal tubular reactor
results in the following relationship for the outlet alcohol
mole fraction
yA = kfPEPWem (4)
where y, is the mole fraction of alcohol in the exit gas, kf is
the forward reaction rate constant, PE and P are the partial
pressures of the reactants, and em is the molar space time
defined as
m =V/F (5)
in which V is the void volume of the reactor and F is the molar
feed rate of gas entering the reactor.
Determination of the forward rate constant can be accom-
plished by noting that yA is directly proportional to the product
PEPw m in Eq. (4) where the proportionality constant is k,.
A plot of yA vs. PEPw m should be a straight line through the
origin with slope k,. When em increases beyond the value
where the initial rate method assumptions are valid, yA < k,
PE PW Om because the reverse reaction will begin to become
significant. Therefore, one would expect the data to begin to
deviate from a straight line when the initial rate method as-
sumptions are no longer valid, as illustrated in Figure 2.
33










A value for the forward rate constant can be determined
from the slope of a linear regression on the initial rate ex-
perimental data through the origin. The confidence interval
on the rate constant is obtained from the confidence interval
on the slope of the regression line.
Equilibrium Experiments
If the reactor is operated at low enough feed rates, the
reaction will reach equilibrium at the reactor outlet. The
equilibrium constant for the reaction can then be determined
from these experiments:

Kp YA kf (6)
KP = (6)
ePw YEYwPo kr
where P is the reactor outlet pressure. The reverse reaction
rate constant can be determined once the forward rate constant
and the equilibrium constant are known from Eq. (6).
Determination of the equilibrium constant can be accom-
plished by noting that yA is directly proportional to the product
YE yw Po in Eq. (6), where the proportionality constant is Kp. A
plot of yA vs. yE yw Po should be a straight line with slope Kp.
When m is below the value required for the reaction to reach
equilibrium, yA < Kp YE yw Po. Therefore, one would expect
the data to deviate from a straight line when the reaction is
not at equilibrium, as illustrated in Figure 3.
The equilibrium constant can be determined from the slope
of a linear regression on the equilibrium experimental data
through the origin. The confidence interval on the equilibrium
constant is obtained from the confidence interval on the slope
of the regression line. The reverse rate constant is calculated
from the ratio of the forward rate constant to the equilibrium
constant at a given temperature.

EXPERIMENTAL PROCEDURE
The students are instructed to select at least three tempera-
tures to study. At each temperature, they are encouraged to
perform exploratory experiments to determine the feed rate


range that will give measurable initial rates and the feed rate
range that results in equilibrium. Based on this information,
a series of initial rate experiments to determine the forward
rate constant and equilibrium experiments to determine the
equilibrium constant should be conducted at different feed
rates and compositions.
In order to carry out initial rate experiments, the reactor
must be operated with high feed rates that result in low outlet
alcohol concentration and low consumption of reactants. Al-
though short residence times are necessary for the assumptions
made by the initial rate method in Eq. (4) to be valid, the high
flow rates will also result in high inlet reactor pressures due to
pressure drop across the catalyst packed in the tube. Therefore,
students are encouraged to initially obtain an estimate of the
pressure drop at high flow rates. Class discussion is used to
suggest that this analysis may be safely carried out by oper-
ating the reactor without one of the reactants. The low feed
rates necessary for the equilibrium assumption in Eq. (6) to
be valid can be obtained without similar issues.
Class discussion is also used to point out possible sources
of variability in the reaction system study such as error in
laboratory analysis and experimental operating conditions.
Measuring instruments are often imprecise and/or inaccurate,
operating conditions cannot be set precisely as desired, and
factors that cannot be observed or controlled can affect the
behavior of any system under study. Therefore, any attempt
to duplicate or repeat a single set of experimental conditions
will usually produce different results. Sometimes the magni-
tude of this variation is small enough that useful conclusions
can be drawn from a single experiment. At other conditions,
however, an experiment must be repeated a number of times
to be confident that the average value is an acceptable repre-
sentation of the actual value.

EXPERIMENTAL DATA


The students


regression line through the origin
slope = Kp /


equilibrium data


* non-equilibrium data
*
*
*ii


*
** *
*
*
*


* *


obtain experimental data by e-mailing the
desired reaction conditions for each experi-
ment using a specified procedure outlined
in the project description handout. The
costs of the experiments are deducted
from the student group's budget as they
are performed. The results are made avail-
able by e-mail to each group member the
morning of the following day for normal
experiments and by that afternoon for ex-
pedited experiments. The results include a
summary of the experimental costs and the
remaining budget.
A separate e-mail account using the class
number as the e-mail address is created
each year for this project. Scripts were
developed to extract the operating condi-
tions from the e-mail message, pass this
Chemical Engineering Education


YEYwPo
Figure 3. Example equilibrium data regression.










information into the simulation and run it, create a report
containing the experimental results and budget information,
and then e-mail this report back to the student group. The
original intent was to automatically perform each of these
tasks without the intervention of the instructor. This approach,
however, was quickly abandoned. The ability of undergradu-
ate students to continuously find incorrect permutations to
the required e-mail format resulted in increasing complexity
to the data extraction script. Keeping in touch with each
group's progress and the experiments they requested was
also valuable. For these reasons, the project is administered
by manual execution of the scripts. The administration task
typically takes no more than 10 to 15 minutes each morning.
As the report deadline approaches, the time commitment does
increase slightly as a larger fraction of student groups request
experiments on a given day.

PROCESS SIMULATION
The reactor simulation is performed using the Octave
computational environment running under the Debian linux
operating system. Octave is a freely available mathematical
computation package with similar capability to MATLAB.
We note, however, that the Octave program files generated
to support this project will not run in MATLAB. Additional
information on Octave may be found at the Web site octave.org>.
The reactor is simulated using an isothermal, steady-state,
ideal plug flow reactor model. The forward and reverse rate
constant activation energy and pre-exponential factor values
are modified by the instructor each year. Literature values for
these parameters are not used in order to prevent the more
industrious student from obtaining the answer and reverse en-
gineering their analysis. The values are also changed each year
in order to prevent the less industrious student from getting
values out of a prior-year project report. We note that these
values are a function of the catalyst system used in the reactor
and would be expected to change with different catalysts.

Normally distributed random variation is added to the
specified values for reactor operating conditions. A standard
deviation of 7.5 x 10" mol/min is used for the variation added
to each of the requested molar flow rate values and 5 x 10'
bar is the standard deviation used for the variation added to
the requested outlet pressure. There is no variation added to
the requested average reactor temperature and the simulation
assumes a constant temperature at this value. The pressure
drop across the reactor is determined from the expression

P, = Po + oun (7)
where P is the inlet pressure (bar), Po is the specified outlet
pressure (bar), u is the inlet gas velocity (m/min), a = 1.25
x 104 and 3 = 1.25. These values provide a reasonable pres-
sure drop range for the molar flow rate limits. Slight changes
in these values have been made between years. Normally
Winter 2007


distributed random variation with a standard deviation on the
order of 2 x 10" is added to the ethanol mole fraction. The
standard deviation of the variation in the hydrocarbon mole
fraction is typically half that of the ethanol variation. Slight
changes in these values have been made between years. The
water mole fraction is determined by different checks made
to ensure that reported values are positive and consistent.
Determination of reactor detonation is made by comparing
the requested reactor average temperature and computed inlet


The students are informed that temperatures
beyond 400 C and inlet pressures beyond
70 bar are dangerous and can very likely result
in detonation of the reactor.... The students
must therefore first determine safe operating
conditions from initial experimental trials ....


pressure to a table of values. Temperatures below 375 C
or inlet pressures below 70 bar cannot result in detonation.
Temperatures above 400 C require inlet pressures above 69
bar for detonation, temperatures above 390 C require inlet
pressures above 72.5 bar, and so forth. These limits are chosen
to make detonation rather difficult unless one is either very
careless or intentionally wants to detonate the reactor. There
have been few unintentional reactor detonations in our experi-
ence with this project. There have been a number of groups,
however, who intentionally try to detonate the reactor with
their last experiment. Although this practice is not within the
scope of presenting a realistic experience to the students, it is
not actively discouraged because it does provide a source of
amusement and a final goal for some group members.

STATISTICAL ANALYSIS
For each temperature selected, the students are instructed
to plot the experimental outlet alcohol mole fraction as a
function of PE P, Om and yE y, Po to determine which data
points represent initial rate conditions and which data points
represent equilibrium conditions. Deviation from the lines
shown in Figures 2 and 3 by a given data point can be caused
by experimental variation and/or violation of the assumptions
made in the corresponding derivation. Although replicate
experimental runs can help quantify the experimental variabil-
ity, they do not provide the information necessary to exactly
determine the point at which the initial rate and equilibrium
assumptions are violated. This determination requires some
judgment by the students.

A linear regression analysis on the selected initial rate and
equilibrium data points is performed using a least squares
linear fit through the origin at each temperature studied. The
35











A number of

groups...

intentionally try

to detonate

the reactor

with their last

experiment.

Although this

practice is not

within the scope

of presenting

a realistic

experience to

the students, it

is not actively

discouraged

because it does

provide a source

of amusement

and a final goal

for some group

members.


forward rate constant and equilibrium constant are determined from the slope of the
respective lines. A 95% confidence interval on each of these values is determined
from the standard error of the slope. These calculations are typically performed by
the students using the EXCEL regression data analysis tool. The formulas may also be
found in a number of introductory statistics texts. An extensive summary of statistics
texts can be found in Reference 8 and is not replicated here.
A value for the reverse rate constant can be obtained from rearranging Eq. (6) to
yield k, = k /K The determination of a confidence interval, however, is more prob-
lematic. The reverse rate constant is the ratio of two independent t-distributed random
variables. The result is a Cauchy distributed random variable with an undefined vari-
ance.[9] The unbounded variance arises from the fact that there is a finite probability
that the equilibrium constant can be within an arbitrarily small neighborhood of zero.
Further discussion of this aspect of the project is presented in the section on discus-
sion topics.
A linear regression analysis based on Eq. (3) can be performed on both the forward
and reverse rate constants to determine the activation energy and the log of the pre-
exponential factor. This linear regression is also typically performed by students using
the EXCEL regression data analysis tool. The students are asked to explain any rate
constant values that they believe are inconsistent with the others and excluded from
the regression. The activation energy can be determined from the slope using the
relationship Ea = -mR, where m is the linear regression slope, and a 95% confidence
interval can be determined from the confidence interval of the slope by scaling with
the gas constant. The pre-exponential factor can be determined from the exponential
of the intercept.
The students are asked to determine an estimate of the error variance for the labora-
tory ethanol analysis from the variance of residuals for each initial rate constant and
equilibrium constant linear regression. The result is two error-variance estimates for
each temperature studied. They are asked to discuss any differences between the esti-
mated variances and whether the error in the alcohol analysis depends on the amount
present in the sample. A 95% confidence interval on the analysis error is determined
from the standard error computed from a pooled variance.

REPORTING REQUIREMENTS
Students report their results in a short group memo to the instructor. The memo
must contain a description of how the group arrived at their results, and enough detail
for someone to replicate their results. An appendix to the memo should contain all of
the data that was obtained. Plots of all the initial rate and equilibrium data with the
regression line and an indication of which points were used in the regression must be
included for each temperature selected. An Arrhenius plot for the forward and reverse
rate constants with the regression line and an indication of any rate constant values
that were not used in the regression must also be included.
Each group is scheduled for a 10-minute appointment with the instructor where
only the instructor and the group members are present. The students turn in the memo,
present their results, and answer any questions about their experimental plan and
statistical analysis. The intent of this oral presentation is to provide an opportunity
for the students to experience a technical interaction with a supervisor that many will
encounter early in their careers as practicing engineers.

DISCUSSION TOPICS
The project described in this article brings up a number of topics for discussion
concerning the application of the statistical analysis techniques presented in the Ap-


Chemical Engineering Education










plied Statistics course. The first topic typically brought up in
discussion is the method used to determine valid initial rate
and equilibrium experimental data. Although many student
groups use the "eyeball" method to perform this determina-
tion, a more rigorous approach is to perform the regression
with and without a given data point and look at the effect on
the slope, confidence interval, and correlation coefficient.
For points that are questionable, replicate experimental data
should be used to help determine whether the deviation is due
to experimental error alone.

A second topic for discussion is the basis for the linear
regressions used in this project. The students are reminded
that the regression equations given in their statistics text, and
carried out by EXCEL, assume that there is no error in the
independent variable. This assumption is clearly violated in
the rate and equilibrium constant regressions due to error
in the outlet composition measurements and the Arrhenius
expression regression due to error in the average reactor
temperature. Although an estimate of the magnitude of in-
dependent variable error can be obtained from the ethanol
analysis error variance, a formal treatment of linear regression
in this case is outside of the scope of the one-semester Applied
Statistics course. It is anticipated that student groups would
acknowledge that the regression assumption was violated.
Very few student groups, however, realize this point without
being prompted during the group oral presentation or class
discussion. A very valuable contribution from this aspect of
the project is to reinforce to the students that they must con-
sider the basis and limitations of a statistics formula before
they start performing any calculations.
Some student groups attempt to determine a reverse rate
constant confidence interval by dividing the maximum error
of the forward and equilibrium constants. A less suspect ap-
proach adopted by many student groups is to determine the
confidence interval by approximating the variance from the
forward rate and equilibrium constant variances as follows


S2 22 k
s2 kr 2 &kr 2
s- kf kf OK KP


1 kr s (8)
K2 kf KKp 8
P P


where the partial derivatives are obtained from the rear-
rangement of Eq. (6), and s2kf, and s2, are obtained from
the standard error of the slope from corresponding linear
regressions. This variance is used to compute the standard
error and a confidence interval is obtained from a t-distribu-
tion. A confidence interval for the pre-exponential factor is
obtained by most student groups from the exponential of
the 95% confidence interval of the intercept. Some groups
determine the variance of the pre-exponential factor from
that of the intercept from


2 =Oln(ko)2 2
Sko 0k In(ko


1 2
S 1 n(ko)
ko


and then compute the standard error and confidence interval
using this variance and a t-distribution. These approaches are
not correct. Confidence intervals on the reverse rate constant
and pre-exponential factor cannot be determined because the
parameter variance is undetermined. This aspect of the proj-
ect attempts to reinforce the concept presented early in the
statistics course that nonlinear transformations of normal or
t-distributed random variables no longer retain their original
distribution. Although it is fair to criticize the practice of
asking for values that cannot be computed by the students,
they may very well find themselves in this position later in
their careers and should have some experience in realizing
this point.
A further area of discussion on this topic is how one could
obtain a confidence interval for the reverse rate constant and
whether there is a more accurate method to determine its
value. The students are prompted to consider a revision of
the experimental plan that involves performing initial rate
experiments using ethanol as the feed. In this case, the reverse
rate constant can be determined directly from a single set of
experiments in the same manner as the forward rate constant.

STUDENT PERFORMANCE

The student groups are given about five weeks toward
the end of the semester to complete this project. They are
reminded in class during this period that it takes time to
obtain data and they should not wait for the last minute to
begin collecting data. Most student groups have successfully
determined forward and reverse rate constants for at least
three temperatures and have obtained reasonable values for
the activation energy and pre-exponential factor. Very few
groups have been unable to determine these values. The most
typical reasons are the group started their data collection too
late in the semester to obtain enough data and/or they were
very inefficient in their experimental plan and expended their
budget. Grading of the project in these cases is based on their
pattern of experimental data requests. Groups that started early
and appeared to have a plan but didn't quite get enough good
data are treated in a much more forgiving manner than groups
that waited for the last minute to request all of their data with
little or no planning.

Groups have been formed both by students' own selection
and by assignment of the instructor. There have been fewer
cases of incomplete or poorly executed projects with the
assigned groups, in our experience. Groups are instructed
not to discuss any aspect of the assignment with anyone out-
side of their group, including the exchange of experimental
data. Although it is difficult to enforce complete compliance
with this policy, analysis of requested experiments has not
revealed any obvious signs of copying experimental designs
between groups or the use of data that was not requested by
a group. We note that no two groups have ever obtained the


Winter 2007











same values for the Arrhenius parameters or used exactly the
same number of experiments in a given semester. We have not
performed this analysis between different semesters.

CONCLUSIONS

The experimental design and statistical analysis project
documented in this article has been developed to provide a
realistic experience to students. Based on comments contained
in course surveys, students have found the project to be in-
teresting and worthwhile. A number of students have made
positive comments on the realistic nature of the experience.
Although not incorporated into the scope of this project, ad-
ditional studies such as an analysis of variance to determine
the sources of variability in the experimental data-can be
included within the framework discussed in this article. This
project has also provided valuable documentation of the stu-
dents' ability to design, conduct, analyze, and interpret experi-
ments for Criterion 3b of the current ABET criteria.1101

ACKNOWLEDGMENTS

A curriculum revision grant to the Villanova University
Chemical Engineering Department from Air Products and
Chemical Co. that supported the development of this project is
gratefully acknowledged. We would also like to acknowledge
the helpful advice of Dr. John Eaton on the development of the
Octave simulation model software and the statistical analysis


discussions with Profs. Dorothy Skaf of Villanova University
and Babatunde Ogunnaike of the University of Delaware.


REFERENCES
1. Nelson, P, and T. Wallenius, "Improving the Undergraduate Statistical
Education of Engineers, "in G. Cobb, "Reconsidering Statistics Educa-
tion: A National Science Foundation Conference, "J. Stat. Educ., 1(1)
(1993)
2. Prudich, M., D. Ridgway, and V. Young, "Integration of Statistics
Throughout the Undergraduate Curriculum: Use of the Senior Chemi-
cal Engineering Unit Operations Laboratory as an End-of-Program
Statistics Assessment Course, "Proceedings of the 2003 ASEE Annual
Conference (2003)
3. Romero, R., A. Ferrer, C. Capilla, L. Zunica, S. Balasch, J. Serra, and R.
Alcover, "Teaching Statistics to Engineers: An Innovative Pedagogical
Experience," J. Stat. Educ., 3(1) (1995)
4. Mustoe, L., andA. Croft, "Motivating Engineering Students by Using
Modern Case Studies," Int. J. Eng. Educ., 15(6) (1999)
5. Ludlow, D., K. Schulz, and J. Erjavic, "Teaching Statistical Experi-
mental Design Using a Laboratory Experiment," J. Eng. Educ., 84(4)
(1995)
6. Mackisack, M., "What is the Use of Experiments Conducted by Sta-
tistics Students?"J. Stat. Ed., 1(2) (1994)
7. Vaughn, T., "Teaching Statistical Concepts with Student-Specific Data
Sets, "J. Stat. Ed., 11(1) (2003)
8. Fahidy, M., "An Undergraduate Course in Applied Probability and
Statistic," Chem. Eng. Ed., 36(2) (2002)
9. Evans, M., N. Hastings, and B. Peacock, Statistical Distributions, 3rd
Ed., Wiley, New York (2000)
10. ABET, Criteria for Accrediting Engineering Programs, Engineering
Accreditation Commission, (2004) 1


Chemical Engineering Education











classroom
--- ^ K.___________________________-


FORCED CONVECTION HEAT TRANSFER

IN CIRCULAR PIPES












ISMAIL TOSUN
Middle East Technical University Ankara, Turkey 06531


Forced convection inside circular pipes under fully
developed conditions is one of the main subjects
covered in both undergraduate- and graduate-level
heat transfer courses. Two types of boundary conditions are
usually considered, i.e., constant wall heat flux and constant
wall temperature. In engineering calculations, heat transfer
correlations are expressed in terms of the Nusselt number and
such expressions require the solution of the energy equation
given as
SOT k r OT 1
pCpv -- r-
Oz r r dr

in which the velocity distribution under laminar flow condi-
tions is given by

vz = 2(vz) 1- (2)

When the heat flux at the wall is constant, the temperature
gradient in the axial direction, 8T /8z, is constant. This makes


the solution of Eq. (1) rather simple since the left side is depen-
dent only on r. Integration of Eq. (1) twice yields the Nusselt
number equal to 48/11. This approach is presented in almost
all textbooks on heat transfer and/or transport phenomena.
In the case of constant wall temperature, however, the
solution of Eq. (1) requires advanced mathematical skills in
partial differential equations.1 As a result of this mathematical
complexity, the value of the Nusselt number is given as 3.66
in textbooks without presenting the analysis. Incropera and

Ismail Tosun received his B.S. and M.S.
degrees from the Middle East Technical
University, and a Ph.D. degree from the
University of Akron, all in chemical engineer-
ing. He is the author of the book Modelling
in Transport Phenomena-A Conceptual
Approach (Elsevier, 2002). His research
is directed to the unification of solid-liquid
separation processes using the multiphase
equations of change.

i ___________i__


Copyright ChE Division of ASEE 2007


Winter 2007










DeWitt,[2] for example, stated that:
". .. the solution may be obtained by an iterative proce-
dure, which involves making successive approximations to
the temperature profile. The resulting profile is not described
by a simple algebraic expression, but the resulting Nusselt
number may be shown as Nu = 3.66."
The method of Stodola and Vianello3, 4] is an approximate
technique used for a quick estimation of the first eigenvalue.
The purpose of this paper is to show students how to apply
this technique in the calculation of the Nusselt number for
forced convection in a circular pipe when the wall temperature
is constant. From my experience in teaching graduate-level
Transport Phenomena and Heat Transfer courses, the method
is well received by students.
MATHEMATICAL ANALYSIS
Consider the laminar flow of an incompressible New-
tonian fluid in a circular pipe of radius R under the action of
a pressure gradient. The fluid is at a uniform temperature of
T for z < 0. For z > 0, the wall temperature is kept constant
at T (T > T ) and we want to develop a correlation for heat
transfer in terms of the Nusselt number under thermally fully
developed conditions.
BULK TEMPERATURE GOVERNING EQUATION
As engineers, we are interested in the variation of the bulk
(or, mean) fluid temperature, Tb, rather than the local tempera-
ture, T. The bulk fluid temperature is defined by

fb fR vzTrdrdO
b 2O RO
f2 fR vz r drdO


1 R2(vzo f R vzTrdrd (3)

Since both v. and T are independent of 6, Eq. (3) simplifies
to
Tb =-- )fvzTrdr (4)
R "(vz
The governing equation for the bulk temperature can be
obtained by multiplying Eq. (1) by r dr and integrating from
r = 0 tor =R, i.e.,


pC R vz OTrdr
o 9 Oz


rR1 0f G T (T
k -- r- rdr
Or r Or r


Since v z v(z), the integral on the left side of Eq. (5) can be
rearranged, with the help of Eq. (3), as

pCP fv -rdr= pCPf vT) rdr
o z zOz
d R
= pCP vzTr dr
dzJo o(

= pCP O (6)
2 dz


On the other hand, the integral on the right side of Eq. (5)
takes the form
R OT 9OT r=R
kR -- r- T rdr = k r- (7)
Jor Or Or Or r = 0
The heat flux at the wall, qw, is defined by

qw = k (8)
Orr r= R
so that Eq. (7) becomes
p R 1 ) (T
k1 -- rdr Rq (9)
Jr r Orr )
Substitution of Eqs. (6) and (9) into Eq. (5) results in the
governing equation for the bulk temperature as
dTb 2 qw (10)
dz pCpR(vz)

THERMALLY FULLY DEVELOPED
CONDITIONS
The requirement for a thermally fully developed flow is
expressed as

0 T-TT j= 0 (11)
Oz Tw Tb
Note that the thermally fully developed condition also implies
that the local heat transfer coefficient, h, is a constant.
When the wall temperature, Tw, is constant, Eq. (11) re-
duces to

OT Tw T dTb
z T Tb) dz

Substitution of Eq. (10) into Eq. (12) results in

OT T 2q (13)
z T- T,) pCpR(vz)

NUSSELT NUMBER FOR CONSTANT WALL
TEMPERATURE
The Nusselt number is defined by

Nu = (14)
k
The heat flux at the wall is also expressed in terms of the
Newton's law of cooling as
q, = h(T Tb) (15)
so that the Nusselt number takes the form

Nu qw/(Tw -Tb) 2R (16)
k (16)


Chemical Engineering Education










Elimination of the term qw between Eqs. (13) and (16) leads
to
OT Nu(T -T)k (17)
Oz pCpR2(vz)
Substitution of Eqs. (2) and (17) into Eq. (1) yields

2Nu 1- R (T T) = -- [r (18)
e b ry r Or)
The boundary conditions associated with Eq. (18) are


atz =0

atr = 0

atr= R


T=To
OT
-0
TOr
T=Tw


In terms of the following dimensionless quantities
T-Tb T -T (20)
9=1- = (20)
Tw -T Tw -T
r
r (21)
R
the governing equation together with the boundary conditions
take the form


The first approximation to X1, I1(1), is given by

Sfbw(x) fl(x)yl (x)dx
X11 b 2-= (27)
fa w(x)[fl(x)]2dx
4. Repeat step (2) with a second trial function y,(x) defined


y2(x)= f(x)


(28)


5. Solve the resulting differential equation and express the
solution in the form
y(x)= Xf(x) (29)
The second approximation to 1, 1 (2), is given by
b
)(12) fbw(x)f2(x)y2(x)dx
1= (30)
f w(x)[f,(x)2 dx
6. Continue the process until the desired convergence is
obtained.
For the problem at hand, comparison of Eq. (22) with Eq.
(25) gives
y= x= p= X=Nu w=2(1- E2) (31)


1 d dO
2Nu(1- ) = --
( dd


at = 0

at= =l


dO
-=0
d0
9=0


It should be kept in mind that the dimensionless tempera-
ture, 6, is dependent on only the dimensionless radial coor-
dinate, , for the thermally fully developed condition. Eq.
(22) can be easily solved for Nu by the method of Stodola
and Vianello.

THE METHOD OF STODOLA AND VIANELLO
The method of Stodola and Vianello[3 4] is a successive ap-
proximation technique to estimate the lowest eigenvalue ?1
in the boundary value problem of the form


d dy
- p(x)\ x
dx dx


-Xw(x)y


with appropriate homogeneous boundary conditions at x = a
and x = b. The procedure is as follows:
1. Assume a trial function for y, (x) which satisfies the
boundary conditions x = a and x = b.
2. On the right side of Eq. (25), replace y(x) by y,(x).
3. Solve the resulting differential equation and express
the solution in the form


A reasonable first guess for 6 which satisfies the boundary
(22) conditions is

((23) 0) 1=- (32)
(23)Substitution of Eq. (32) into the leftside of Eq. (22) gives
Substitution of Eq. (32) into the left-side of Eq. (22) gives


d -2Nu(-2 +s) (33)

The solution of Eq. (33) using the boundary conditions given
by Eqs. (23) and (24) is


0 11- 182 9 2 j
36
fi(!


(34)


The first approximation to the Nusselt number is calculated
from Eq. (27) as


Nu(1) f1 (1- 2)2 f()d
fNu I(= -2)fl2 ()d
Jo (1- ()f (0)d


(35)


Substitution of f1 ( ) from Eq. (34) into Eq. (35) and evalu-
ation of the integrals gives
Nu(1 = 3.663 (36)
The trial function for the second approximation is
11- 18_ 2 + 94 26
0, (E = (37)
36


(26) Substitution of Eq. (37) into the left-side of Eq. (22) gives


y(x)= Xf,(x)


Winter 2007










NOMENCLATURE


d 1d Nu
d N(1- 293 + 272 -11+ 2(9) (38)
d d 18
The solution of Eq. (38) using the boundary conditions given by Eqs.
(23) and (24) is

= Nu( 2457 4400k2 + 29004 1200,6 + 275$8 3210 (3
28,800


Therefore, the second approximation to the Nusselt number is given
by


Nu2 = (1- 2)f2 ()02 () d
f I(1- 2)f22 () de
0


(40)


Substitution of f,(&) and 62(&) from Eqs. (39) and (37), respectively,
into Eq. (40) and evaluation of the integrals gives

Nu(2) = 3.657 (41)
which is equal to the exact value calculated by Graetz and Nusselt.

The solution of eigenvalue problems by the method of Stodola
and Vianello gives accurate results and convergence is very rapid.
Although the integrals seem formidable, they can be easily evaluated
using engineering calculation software such as MATHEMATICA or
MATHCAD. The method is easy to follow and students have no dif-
ficulty in understanding the presented material. The transformation
of the governing differential equation, Eq. (1), to the form to which
the method of Stodola and Vianello is applied, Eq. (18) or Eq. (22), is
also very helpful for students in grasping the concept of area averag-
ing and the difference between local and bulk temperatures, as well
as their functional dependence on coordinate directions.


IP Heat capacity, J kg-K
D Pipe diameter, m
k Thermal conductivity, W/m-K
Nu Nusselt number, dimensionless
qw Heat flux at the wall, W/m2
R Pipe radius, m
r Radial coordinate, m
T Temperature, K
Tb Bulk temperature, K
Tw Wall temperature, K
v Axial velocity, m/s
(vz) Axial average velocity, m/s
z Axial coordinate, m
Greek symbols
6 Dimensionless temperature
& Dimensionless radial coordinate
9 Density, kg m3

REFERENCES
1. Sellars, J.R., M. Tribus, and J.S. Klein, "Heat Transfer to
Laminar Flow in a Round Tube or Flat Conduit-The Graetz
Problem Extended, Trans. ASME, 78, 441 (1956)
2. Incropera, EP, and D.P DeWitt, Fundamentals of Heat and
Mass Transfer, 5th Ed., Wiley, New York (2002)
3. Bird, R.B., R.C. Armstrong, and 0. Hassager, Dynamics of
Polymeric Fluids, Volume 1: Fluid Dynamics, 2nd Ed., Wiley,
New York (1987)
4. Hildebrand, EB., Advanced Calculus for Applications, 2nd Ed.,
Prentice-Hall, Englewood Cliffs, NJ (1976) [


Chemical Engineering Education











curriculum
-0


Future of Chemical Engineering:

INTEGRATING BIOLOGY INTO THE

UNDERGRADUATE CHE CURRICULUM








PATRICIA MOST, MARIANO SAVELSKI, STEPHANIE H. FARRELL, AND GREGORY B. HECHT
Rowan University Glassboro, NJ 08028
C creating a working knowledge of biological principles Patricia Mosto has extensive environmental science experience. She has
in students and developing their ability to apply been actively involved with field and laboratory projects related to water
engineering principles to biological systems (and quality and pollution issues for the last 30 years. She has worked with the
Departments of Water and Power and Sanitation in Los Angeles for 10 years.
vice versa) is recognized nationwide as a goal for chemical In her 14 years at Rowan, she has supervised more than 50 independent
engineering programs.[15] The same can be said from a global undergraduate projects, taking many students to national and international
conferences. She is author of over 100 publications.
perspective.[6] There is currently a significant movement to
change chemical engineering department names to reflect Mariano Savelski has seven years of industrial experience in design and
in biofocused engineering. Bioengineering manufacturing. He has received a Lindback Foundation Award to continue
faculty expertiseinbio-focused engineering Bioeng ng his research in the area of industrial wastewater minimization, as well as
is very broad and inherently interdisciplinary. The need for a U.S. EPA Award to investigate zero water discharge cycles in manu-
bioengineers is on the rise. By 2010, there is projected to be facturing and chemical plants. He has been recognized as a rising star in
chemical engineering and participated as a panelist in the 2001 Galaxy of
a 31.4% increase in employment positions in bioengineering Stars at the ASEE meeting in Albuquerque. He has been actively involved
fields.[8' Moreover, most engineering jobs listed in the "Fast in undergraduate research through Rowan Engineering's clinic.
Company 25 Top Jobs" are bio-related.[9] To meet the needs of Gregory B. Hechthas extensive research experience in prokaryotic genet-
the global job market today's chemical engineering students ics and molecular biology. With Dr. Mosto, he has developed a new course
for chemical engineering students, Biological Systems and Applications. He
must receive a solid background in biology. The conventional is the creator and coordinator of the Rowan University Student Research
approach is to add a standard biology course, and many Symposium, an annual forum at which Rowan students from all of the SMET
schools do offer biology courses at the senior or graduate disciplines present the results of their independent research.
level.[10 11] The integration of biology in the undergraduate Stephanie H. Farrell received her B.S. in 1986 from the University of Penn-
chemical engineering curriculum, however-although dif- sylvania, her M.S. in 1992 from Stevens Institute of Technology, and her
Ph.D. in 1996 from NJIT. Prior to joining Rowan in 1998, she was a faculty
ficult in an already overloaded curriculum-provides a more member at Louisiana Tech University. Her research expertise is in the field
holistic and rewarding learning experience, of drug delivery and controlled release, and she is currently focusing efforts
on developing laboratory experiments related to membrane separations,
biochemical engineering, and biomedical systems for students.
Copyright ChE Division of ASEE 2007
Winter 2007 4.










Due to the interdisciplinary nature of the field, this holistic
way of teaching integrates both biology and engineering. The
biology provides knowledge and skills dealing with biological
concepts as the building blocks for engineering design and
process. It may also create a whole-system perspective neces-
sary for innovation and creativity. The engineering provides
access to existing technologies with an emphasis on the design
process itself. At Rowan University, we have developed such
an integrated, collaborative approach between engineering
and biology faculty to introduce chemical engineering stu-
dents to the application of engineering principles in biologi-
cal systems throughout their four-year curriculum. Through
specially designed courses and active learning modules that
can be easily adapted to any course, students are exposed to
the newest biological trends for chemical engineering. The
implementation of this philosophy exposes students to key
areas of collaboration between biologists and chemical en-
gineers at early stages in their undergraduate education, and
continues systematically during the upper years. This strategy
develops a cumulative knowledge of biological principles
in students, enabling faculty to build increasing detail and
technical content into problems and projects that address the
interface between biology and engineering. This application
allows students to work in interdisciplinary teams, think in
a more global fashion, create innovative ideas, and enhance
their entrepreneurship and communication skills.

Revisions to the chemical engineering curriculum at Rowan
University include: several laboratory modules and projects
at the freshman and sophomore levels; a novel, required
Biological Systems and Applications course designed to in-
troduce students to a variety of biological principles relevant
to chemical engineering1231; vertical integration of experi-
ments and applications of bio-related engineering analysis
in core engineering courses; collaborative research projects
involving biologists and chemical engineers in their junior
and senior years; team-taught senior chemical engineering
elective courses with strong biological components; and a
bioengineering concentration for those graduating with a
cadre of bio-related courses.

As the only four-year engineering college in Southern New
Jersey, Rowan Engineering is deeply committed to being a
major technological resource for the area, preparing students
for engineering careers in regionally important industries such
as biomedical, biotechnology, pharmaceutical, and food. The
abundance of such industry in New Jersey and nationwide
creates a steady demand for well prepared engineering gradu-
ates. Our collaborative approach to integrating biology and
chemical engineering helps prepare students for careers in
food, biotechnology, and pharmaceutical industries.

This paper will discuss the implementation, impact, and
benefits of our approach, with emphasis on the core courses
and junior- and senior-level engineering experiences. A de-
44


tailed description of the integration of biological principles
into the lower levels has been published previously."121

EXPERIENCES AT THE FRESHMAN LEVEL
Generally speaking, the Freshman Clinic sequence corre-
sponds to Introduction to Engineering courses in many other
universities, though in unique format. It consists of two parts.
In the fall semester we teach basic engineering skills (such
as problem solving and teamwork fundamentals) and ethics
that will be essential to students' success (or even survival) in
engineering school and in their future engineering careers. In
the spring semester students are exposed to an intense study
of engineering design through reverse engineering (or "dissec-
tion") and competitive assessment of consumer products.[13 14]
Comparable products are reverse engineered to gain under-
standing of the mechanisms by which they work.
In the Freshman Clinic we immediately establish a hands-
on, active-learning environment in which students are intro-
duced to a wide range of engineering principles applied to
both biomedical and biochemical systems.1" 15 18]
A strategy for introducing biological concepts throughout
a traditional engineering curriculum using examples, demon-
strations, and experiments has been presented by Maynard and
Razatos.[191 Their approach provides graduating engineers with
the skills to handle nontraditional problems and to address
emerging areas of research and development. We use a similar
approach in integrating biological concepts throughout our
core chemical engineering courses at Rowan. An important
feature of our implementation method is the emphasis on
vertical integration of bio-related course materials and labora-
tory experiments throughout core courses. Vertical integration
enhances educational quality by integrating concepts, skills,
models, and data throughout all levels of the curriculum,
building upon not only the work done in the previous labora-
tories of the same course but also those of previous courses.
Re-using experiments in freshman, core, and elective courses,
as well as in undergraduate research projects, makes efficient
use of laboratory equipment and space. This truly integrated
learning experience enhances student learning, concept reten-
tion, and motivation. 20 221
The Freshman Engineering Clinic biomedical engineer-
ing project mentioned previously in this paper is used here
as an example to illustrate the vertical integration of topics
throughout the curriculum. Through eight hands-on modules,
students in the freshman course are introduced to a variety
of multidisciplinary biomedical topics. Each topic is then
explored in greater depth in the appropriate core courses of
the chemical engineering curriculum. Table 1 shows the topi-
cal content of the eight hands-on modules taught during the
freshman year (first column), with the associated measure-
ments, calculations, and engineering principles (columns 2,3,
and 4). The engineering courses into which the experiments,
analysis, and concepts are integrated appear in the right-most
Chemical Engineering Education

























































column of the table. While the vertical integration of the
courses is multidisciplinary and involves other engineering
and science disciplines, this table shows only the information
that is directly related to the vertical integration into chemical
engineering courses.

EXPERIENCES AT THE SOPHOMORE LEVEL
To meet the anticipated growing demand for biology-liter-
ate engineers, faculty from biological sciences and chemical
engineering worked closely together to develop a lab-inten-
sive course open only to sophomore chemical engineering
majors. A detailed description of the Biological Systems and
Applications (BS&A) topical content and laboratory exercises
has been described previously, along with an assessment of
the effectiveness of the course.[23]
Concurrent with the Biological Systems and Applications
course, students take Sophomore Clinic I and II, a multi-
disciplinary engineering design and practice two-semester


course sequence providing them the necessary technical
communication tools. The students work in teams of three
to five for the entire semester. The lecture and laboratory
sessions are structured so that parallel activities support
the eventual completion of the project. In the semesterlong
project student teams design and create a microbial fuel cell
(MFC) that powers a Lego Mindstorms robot. The design of
microbial fuel cells provides an ideal application for many
concepts taught in the BS&A course.[23] In conjunction with
the design project, the first semester focuses on total quality
management and writing, and the second semester focuses
on public speaking.

EXPERIENCES AT THE JUNIOR LEVEL

As part of the clinic sequence at Rowan Engineering, stu-
dents participate in sponsored research projects during their
junior and senior years. Each semester, students work in
multidisciplinary teams as part of a two-credit course. Project


Winter 2007


TABLE 1
Biomedical Engineering Modules: Measurements, Calculations,
Engineering Principles, and Vertical Integration of Project Modules into Chemical Engineering Courses

Measurements Calculations Engineering Principles Vertical Integration
Respiration 0,, CO2 concentration Gas volumes Material balances Mass & Energy Balances
Air flow rate Moles of gas PVT relationships Biomedical Processes
Rate of gas consumption (elective)
and production
Metabolism Food intake Energy expenditure Material balances Mass & Energy Balances
Body surface area Energy balances Biomedical Processes
Stoichiometry
Correlations
Dimensional homogeniety
Pulmonary Lung volume PV work Mass transfer/separations Thermodynamics
System Air pressure Efficiency PV work Mass Energy Balances
Air flow rate Rate of heat transfer Efficiency Fluid Flow
Blood O0 % saturation Dissolved O0 Energy balance Separations
concentration Gas solubility/Henry's Biomedical Processes
Law
Resistance Poisieulle's
Law
Cardiovascular Heart rate Blood flow rate Mass balance in flow Fluid Mechanics
System Blood pressure system
Fluid flow Bernoulli
principle
Hydrostatics
Pumps-power and
efficiency
Work/Power Force Work Work Dynamics (ME, ECE)
Distance Power Energy Kinesiology (HS)
Recovery time Efficiency Power
Mechanics of For bone and cartilage: Stiffness Stress Materials Science
Materials Force (tension and Dampening Strain
compression) Forces
Deformation (tension Deformations
and compression)










funding is provided through either government or industrial
grants or sponsorships. Projects span a wide variety of emerg-
ing disciplines, depending on faculty expertise and availability
of funding. The number of projects that involve integration of
biology with chemical engineering has increased dramatically
during the seven years the Junior/Senior Clinic has existed.
Their preparation during the Biological Systems & Appli-
cation course allows students to tackle these bio-oriented
projects and succeed in their upper-class work.
At the conclusion of four semesters of Junior/Senior Clinic
activities, students are expected to:
Demonstrate expanded knowledge of the general prac-
tices and the profession of engineering /h. *, 1 immer-
sion in engineering projects of moderate complexity.
Demonstrate an ability to work effectively in a multidis-
ciplinary team.
Demonstrate acquisition of new technology skills.
Demonstrate understanding of business and entrepre-
neurial skills.
Demonstrate effective use of project and personnel
management techniques.
Integrate engineering professionalism and ethics in
their work as it relates to the context of engineering in
society.
Demonstrate improved communication skills including
written, oral, and multimedia.
Use information obtained from sources that cross geo-
political and language barriers.


PROJECT 1: BIOETHANOL GENERATION
Currently only 2% of U.S. energy needs are met by renew-
able resources. The National Renewable Resources Labora-
tory (NREL), however, projects that biomass resources can
eventually provide more than 50% of transportation fuel,
reducing dependence on foreign sources of energy, alleviating
air pollution problems, and increasing employment oppor-
tunities. Bioethanol is one biofuel that has been receiving a
great deal of attention in recent years. One factor suppressing
wider use of bioethanol is the costs associated with produc-
tion. In North America, most bioethanol is made from the
fermentation of corn. This process sets aside the stalks and
leaves of the corn plant referred to as corn stover. It has been
estimated that if the corn stover available from current crop
yields could be fermented efficiently, bioethanol production
in North America could be tripled."30 Because of its cellulose
and hemicellulose content, however, corn stover is more
difficult to ferment than corn itself and is considered to be a
waste product of corn farming. In particular, the preparation
of the fermentation feedstock and the subsequent increase
in ethanol concentrations can be toxic to the fermenting
microorganisms. The overall objective of this project is to
46


create and characterize new strains of the bacterium Esch-
erichia coli with the potential to sidestep these issues and, as
a result, produce greater yields of ethanol from corn stover.
For this project, teams of student researchers are assembled
as a cohort of two biology and two chemical engineering
majors, and each cohort works with a team of four professors
(two from biology and two from chemical engineering). The
student cohorts select a particular toxicological problem to
investigate over a two-year period. The sum of each cohort's
project is broken down into modules with specific objectives
that include extensive biological and engineering literature
search and review, isolation of novel toxin-resistant deriva-
tives of known ethanologenic microbes, quantification of the
toxicological properties of the new strains, pilot fermentation
studies to demonstrate the effectiveness of the new strains,
and presentations of their results at national microbiology
and chemical engineering conferences. This module ap-
proach and the cohort composition allows an emphasis on
multidisciplinary learning. The experiments conducted by
the students address applied microbiology, toxicology, fer-
mentation technology, engineering design, economics, and
professional communication. A conscientious effort is made to
ensure that all students in the cohort participate in all phases
of the experimental design and execution, including determin-
ing the effects of altering process variables (e.g., feedstock
composition), isolation, and characterization of the biological
catalyst with the desired properties, assessing the impact of
these activities on the process conditions of the downstream
operations and the overall economic feasibility of the system,
and disseminating the results at professional venues.

PROJECT 2. ASTAXANTHIN PRODUCTION
Haematococcus pluvials is one of the largest algal produc-
ers of astaxanthin, a carotenoid that is commonly used as a
feed supplement in the salmon farming industry to give the
salmon their pinkish hue. Astaxanthin is the ideal component
to color the salmon because it is a stable natural product and
is naturally retained by the fish's flesh. It has already been
established[241 that extreme light conditions yield a higher
production of astaxanthin in H. pluvials, however exact light-
to-dark time periods for optimum astaxanthin production are
unknown. The goal of this project was to determine the proper
lighting conditions for optimum astaxanthin production by
H. pluvialis so a pilot scale plant for large-scale production
could be constructed. Two students, one from biology and
one from chemical engineering, work over the course of a
year with two professors (one from biology and one from
chemical engineering). The students grow H. pluvialis in an
environmental chamber at different light/dark cycles (16/8,
20/4, 24/0) and constant temperature (26 C) to determine
the best light-to-dark ratio for maximum astaxanthin produc-
tion. Chlorophyll a, ash-dry biomass, and a cell count were
obtained daily for each of the growth conditions to establish
the optimum growth curves for H. pluvialis. Correlations
Chemical Engineering Education










between growth and astaxanthin production were studied,
and a continuous bioreactor for pilot scale production for
H. pluvials was designed, constructed, and tested. The 16/8
light-to-dark ratio was used, and it was possible to grow the
algae in one compartment and use gravity feed to a separate
compartment where the algae were stressed (e.g., longer
light cycle, carbon dioxide bubbled into reactor) to enhance
astaxanthin production. Several aspects of the reactor were
modified for use in Chilean salmon farms in a large-scale
algae production facility. This year's Junior/Senior Clinic
will complete the design of the reactor.

OTHER PROJECTS
The Junior and Senior Engineering Clinic projects described
above are just a few examples of collaborative, multidisci-
plinary projects that integrate biological and engineering prin-
ciples. Additional clinic projects have investigated problems
related to drug delivery, food preservation, pharmaceutical
separations, and artificial organs.
The clinic has proven to be a very effective vehicle for
development of educational experiments and course con-
tent. The biomedical, drug delivery, and food engineering
modules that are integrated throughout the curriculum were
developed via the clinic. In a typical project, students would
be responsible for collecting background material, building
the experimental apparatus, developing the experimental
procedure and methods of data analysis, writing a detailed
laboratory handout for students, and providing an instructor's
manual for a module on a given topic.

EXPERIENCES AT THE SENIOR LEVEL
Food Engineering Course
Rowan Engineering is committed to being a major techno-
logical resource for the area, preparing students for engineer-
ing careers in regionally important industries such as food
processing. The state has major manufacturing operations of
top companies such as The Campbell Soup Co., Coca Cola,
Anheuser-Busch, General Mills, and Kellogg's. The immedi-
ate Vineland area is the hub of Southern New Jersey's food
processing industry, home to about 30 companies employing
3,000 people and producing $700 million in shipments. The
abundance of food processing companies in New Jersey de-
mands a steady pipeline of well-prepared engineering gradu-
ates. Rowan Engineering students respond to the regional
emphasis on food processing with a tremendous interest in
the industry. In their senior exit interviews, an overwhelm-
ing number of graduating seniors strongly indicated a need
for more exposure to food-oriented projects and courses. To
respond to student demand and regional industrial needs,
chemical engineering faculty have secured support in recent
years for undergraduate clinic research projects. Food ex-
periments have been introduced to all engineering students
in the Freshman Engineering Clinic (a multidisciplinary,
Winter 2007


introductory course required of all freshmen) and a new
Food Engineering elective course was designed for chemical
engineering students.
This course provides students with the necessary background
in food science, food chemistry, unit operations relevant to
food industry (rarely taught in traditional chemical engineer-
ing curricula), and finally an approach to food preservation
designed and taught by biological science faculty.
Biomedical Engineering Course
The discipline of biomedical engineering has emerged from
informal collaborations between engineers, physicians, and
life scientists. While relatively new, it is the fastest-growing
engineering discipline at most universities.[20l Chemical engi-
neers play an important and expanding role in this burgeoning
field because core chemical engineering concepts are critical
to solving medical problems such as the design of artificial
organs and drug-delivery devices.
This course introduces students to applications of chemical
engineering fundamentals and biomedical systems. Students
analyze and design biomedical processes through the appli-
cation of advanced principles in mass transfer, heat transfer,
fluid flow and chemical reactions, pharmacokinetic models,
the circulatory system, transport across cell membranes, and
human and artificial organs. Several laboratory experiments
are conducted to explore the circulatory system, respiration,
metabolism, and cardiopulmonary dynamics.
It should be noted that many of the basic biomedical
concepts have been vertically integrated throughout the cur-
riculum, beginning with freshman biomedical modules re-
introduced in relevant core courses. The specific focus of this
course permits these topics and experiments to be explored in
greater depth with a more significant emphasis on the associ-
ated physiology and other biological concepts.
Drug Delivery Course
Controlled-release systems are designed to provide delivery
of a biologically active agent (e.g., a drug or pesticide) at a
predetermined rate for an extended period of time. Controlled
release offers several advantages over traditional methods of
formulation and administration such as: maintenance of ef-
fective concentrations for a sustained period, less total agent
required, cost effectiveness, convenience, and compliance.
This course on controlled-release systems introduces students
to chemical engineering fundamentals applied in controlled-
release systems. Basic principles of materials, mass transfer,
heat transfer, fluid flow, and chemical reactions are used to
analyze and design controlled-release systems. Applications to
pharmaceutical, agricultural, and food industries are explored,
with a primary focus on drug delivery systems. Several labo-
ratory experiments are conducted to explore drug stability,
membrane-based transdermal patches, controlled-release
tablets, erodible and dissolution-based systems, and osmotic
pumps.[26] Drug delivery topics represent another example of
47










vertical integration of experiments and examples throughout
the curriculum. Freshmen are first introduced to drug delivery
in the freshman year, and drug delivery examples are revis-
ited in core courses such as Transport Phenomena and Mass
Transfer. In the senior-level elective on controlled release,
students explore drug delivery systems in greater depth, with
more emphasis on topics such as distinguishing rate-control-
ling mechanisms and pharmacokinetic considerations.

IMPACT IN THE CURRICULUM
The combination of modules at the freshman and sopho-
more level, the Biological Systems and Applications course
specifically designed for chemical engineers, the research
projects as part of junior and senior clinics, the elective se-
nior courses in Food Engineering, Biomedical Engineering
and Drug Delivery, and the Concentration in Bioengeneering
all help prepare students for a future career in research and
industry. Located in Southern New Jersey, Rowan University,
through its Junior/Senior Clinic, has successfully completed
a wide range of projects generated and sponsored by local
industries and agencies. These include private companies
(e.g., Biothane, US Filter, Lockheed Martin, Johnson Matthey,
General Mills, ExxonMobil) and research foundations (e.g.,
Engineering Information Foundation, Water Environment
Research Foundation). These industrial partnerships benefit
both the faculty and the students. 27 Students are more likely
to obtain internships as a result of these experiences, and en-
gineering faculty with expertise that reflects this bio-intensive
regional interest strengthen their industry interactions and
receive research support. This research interest is reflected in
the types of clinic projects offered in the Junior/Senior Clinic


1998 1999 2000 2001 2002 2003 2004 2005 2006
Year

Figure 1. Number of bio-oriented abstracts and total abstracts submitted
by engineering students at Rowan University's STEM Symposium.


course, such as bioethanol production, astaxanthin production,
drug delivery, and food engineering. Working cooperatively
with local industry has also enabled students to obtain valu-
able entrepreneurship experience in supporting small- and
medium-size businesses. As part of clinic projects, students
may propose their own ideas and gain funding through the Na-
tional Collegiate Inventors and Innovators Alliance (NCIIA)
Venture Capital Fund. This fund is managed by a faculty
member and specifically earmarked for the development of
original inventions by multidisciplinary student teams within
the Junior and Senior Clinics.[28]

Students often cite a potential career in biochemical engi-
neering as a motivator for pursuing a chemical engineering
degree. This interest in the interplay between biology and
engineering is apparent in the demand by students for bio-
oriented research projects at the junior and senior levels. One
measure of student interest in bio-related projects is their
participation in Rowan University's student symposium in
the Science, Technology, Engineering, and Math (STEM)
Symposium. As shown in Figure 1, the percentage of bio-
related engineering projects that have been presented at the
symposium has increased dramatically. In 1998, only one
engineering abstract at the symposium had biology content.
By 2004, the number of posters with engineering students
pursuing biology-related projects was similar to the number
of nonbiology engineering posters. Importantly, Figure 1
demonstrates that 2004 was not a peak but the realization of
a new status quo, since subsequent years have had similar
numbers of bioengineering presentations. In many cases, the
lab component of the BS&A course has directly benefited
students working on research projects at Rowan University.
As the beginning cadre of students who
have been exposed to these innovations
in the curriculum progresses, we expect to
develop new engineering courses on mo-
lecular biotechnology or bioengineering
S ,,... that will be part of the new bioengineering
-i t concentration approved this year within
t %the College of Engineering.


Preparing students early in their college
career through a specially designed course
and bio-related modules during their
Freshman and Sophomore Clinics yields
excellent results on their bioengineering
clinic project and courses in their junior
and senior year. Additionally, students are
able to learn more material and applica-
tions in the time that is traditionally spent
in an introduction to biological principles.
Also, the Junior/Senior Clinics fostered a
strong research environment, evidenced
by the percentage of students pursuing
graduate degrees as shown in Figure 2.[29]
Chemical Engineering Education


22
20 O Biology Abstracts w/ Engineenng Students
8 Engineenng Abstracts
18
Engineenng Abstracts with Biology Conten
16
14
S12
S10 -
8
-n


6

4
2
0











The impact of the clinic model has been very positive in foster-
ing a spirit of inquiry and engaging students in cutting-edge
research as undergraduates.
As a final measure of impact on students, career paths of
chemical engineering graduates are considered. The AIChE
Placement Survey for Recent Graduates from domestic
institutions indicates that 22.5% of chemical engineering
graduates found work in biotechnology, pharmaceutical, and
food industries. A survey of Rowan Chemical Engineering
graduates reveals that more than 27% of chemical engineering
graduates found employment in these industries.

SUCCESSFUL IMPLEMENTATION
The implementation of these innovations into the curricu-
lum was relatively smooth, particularly considering that it has
required cooperation across not just separate departments but
also separate colleges within the university. We believe that
several factors were crucial to this success.
Foremost, the culture on the Rowan campus during the
implementation process was focused on de-emphasizing the
protection of "turf" by the academic departments and moving
towards interdisciplinary activity. Importantly, relations be-
tween the Departments of Chemical Engineering and Biologi-
cal Sciences were collegial at the start of the implementation,
as were the interactions between the deans of the College of
Engineering and the College of Liberal Arts and Sciences.
Moreover, both the engineering and the biology personnel
viewed the curricular development as a mutually beneficial
process. While the curricular development described here has
had an obvious benefit for the chemical en-
gineering department, it has also resulted in
dividends for the Department of Biological 45.00%
Sciences. No less than four biology faculty
have been involved in numerous collab- 40.00%
orative research projects, some of which
received external funding. Even better, the o 35.00%
addition of biology to the curriculum has (n
provided additional research opportunities 30.00%
for biology majors.


Incremental implementation was also im-
portant. Incorporation of biological content
and application into the curriculum required
resources from both departments, which to
some degree necessitated a stepwise ap-
proach. Initial steps involved the establish-
ment of biology projects in the Freshman
and Sophomore Clinics and the creation of
the sophomore Biological Systems & Ap-
plications course. Subsequent changes in
the curriculum at the junior and senior levels
would not have been successful without the
prior addition of both content and experien-
tial knowledge at the lower levels.
Winter 2007


The future of chemical engineering is in nano- and bio-
technology. This curriculum, with its integrative biological
components, is at the front of future education.

ACKNOWLEDGMENTS
Funding for the development and integration of the biomed-
ical and drug delivery modules was provided by grants from
the National Science Foundation, Division of Undergraduate
Education: DUE-CCLI 0088437 and DUE CCLI 0126902,
respectively. NSF REU EEC -( 1353744 provided additional
support for the development of drug delivery experiments.

REFERENCES
1.
American Institute of Chemical Engineers, 2001-2002 Initial Placement
of Chemical Engineering Graduates
2. Baum, R.M., "The Engineering Approach to Molecular Biology,"
Chem. and Eng. News, 76(13) (1998)
3. Breslow, R., "Into the Future," Chem. and Eng. News, 78(47) (2000)
4. Rawls, R.L., "Biochem Meets Engineering," Chem. and Eng. News,
77(35) (1999)
5. Westmoreland, PR., "Chemistry and Life Sciences in a New Vision of
Chemical Engineering," in Annual Meeting of the American Institute
of Chemical Engineers, Los Angeles (2000)
6. Oberholz, A., "Chemicals in 2010-Systems Solutions for the Cus-
tomer, CHISA Conference, 1492 (2004)
7. AIChE Annual Meeting, San Francisco (2003)
8. U.S. Department of Labor, Bureau of Labor Statistics, i ...i... ,1 ,,.1
Outlook: 2000- 2010, "Monthly Labor Review (2000)
9. < ii)l. I.- i. .. ... .... ..- i l1/bestjobs06.html>
10. Lauffenburger, D.A., "A Course in Cellular Bioengineering," Chem.
Eng. Ed., 23(4) (1989)
11. Oerther, D.B., "Introducing Molecular Biology to Environmental


2000 2001 2002 2003 2004 2005
Year

Figure 2. Percentage of students pursuing graduate degrees.28'


2 25.00%
0
. 20.00%

. 15.00%

| 10.00%
3
5.00%

0.00%












Engineers Through Development of a New Course,"( i..... i .Ed.,
36(4) (2002)
12. Hollar, K.A., S. Farrell, G. Hecht, and P Mosto, "Integrating Biology
and Chemical Engineering at the Lower Levels," Chem. Eng. Ed.,
38(2) (2004)
13. Farrell, S., "A Laboratory Project to Design and Implement a Process
for the Production of Beer, Proceedings of the American Society of
Engineering Education Conf. (1999)
14. Jahan, K., "WaterTreatment in Reverse," Proceedings of theAmerican
Society of Engineering Education Conference (1999)
15. Farrell, S., R.P Hesketh, and M.J. Savelski, "A Respiration Experiment
to Introduce Chemical Engineering Principles,"( ..... in i 38(3)
(2004)
16. Farrell, S., and R.P Hesketh, "An Introduction to Drug Delivery for
Chemical Engineers," Chem. Eng. Ed., 36(3) (2002)
17. Farrell, S., J.A. Newell, and M.J. Savelski, "Introducing Chemical
Engineering Students to Product Design through the Investigation of
Commercial Beer," Chem. Eng. Ed., 36(2) (2002)
18. Farrell, S., R.P Hesketh, J.A. Newell, and C.S. Slater, "Introducing
Freshmen to Reverse Process Engineering and Design through Inves-
tigation of the Brewing Process," I.J.E.E. 17(6) (2001)
19. Maynard, J., and A. Razatos, "The Evolution of Engineering: Incorpo-
rating Biology into Traditional Engineering Curriculum, "Proceedings
of the ASEE Annual Conference, Session 2313 (1999)
20. McDonald, D., A. Mahajan, and M.E. Walworth, NSF EHR 9751372
(1997)
21. McDonald, D., K. Schmaltz, M. Walworth, andA. Mahajan, "The De-
velopment of an Innovative Undergraduate Laboratory that Emphasizes
Vertical Integration in Multiple Engineering Curricula," Proceedings


of the ASEE Annual Conference, Session 2526 (1999)
22. Mahajan, A., M. Walworth, D. McDonald, and K. Schmaltz, "The
Integrated Systems Engineering Laboratory-An InnovativeApproach
to Vertical Integration using Modern Instrumentation, "Proceedings of
the ASEE Annual Conference, Session 2259 (1999)
23. Hecht, G.B., P Mosto, and C.S. Slater, "Effectiveness of an Applied
Microbiology Course Specifically Designed for Chemical Engineering
Majors, "Microbiology Education (2002)
24. Kobayaski, M., T. Kakizono, N. Nishio, and S. Nagai. "Effect of Light
Intensity and Light Quality onAstaxanthin Formation in a GreenAlage,
Haematococcus pluvialis, "J. Fermentation and Bioengineering, 74(1)
(1992)
25. "First Leadership Awards Made: Hopkins and UCSD get $30 Million
Total," The Whitaker Foundation, Biomedical Engineering News
(1998)
26. Farrell, S., R.P Hesketh, M.J. Savelski, and C.S. Slater, "Fundamentals,
Design and Applications of Drug Delivery Systems," ASEE Annual
Conference, Session 1313 (2003)
27. Dorland, D., and P. Mosto, 'The Engineering Clinics at Rowan Univer-
sity: A Unique Experience, "Proceeding of the International Congress
of Chemical and Processing Engineering (2006)
28. Marchese, A., J. Schmalzel, K.M. Weaver, "Creating an Entrepreneurial
Culture at a Startup Engineering Program, "Proceedings of the Ameri-
can Society of Engineering Education Conference (2004)
29. Sukumaran, B., K. Jahan, D. Dorland, J. Everett, J. Kadlowec, Z.
Gephardt, and S. Chin "Engineering Clinics: An Integration of Re-
search into the Undergraduate Engineering Curriculum, Council on
Undergraduate Research Quarterly, (3) (2006)
30. 1


Chemical Engineering Education











Random Thoughts...





TURNING NEW FACULTY MEMBERS


INTO QUICK STARTERS





REBECCA BRENT
Education Designs, Inc.
RICHARD M. FIELDER
North Carolina State University


If you're like most faculty members, you began your
academic career knowing very little about what you'd be
doing for a living. You knew about working on a research
project someone else had defined and gotten funded, but not
about starting and managing a research program, planning and
delivering courses, and dealing with the hundreds of technical
and management problems that always crop up in research
and teaching. No one told you much about those things after
you showed up either, so you had to figure it all out yourself
by trial-and-error.
This bizarre approach to career development has unfortu-
nate consequences. Roughly 95% of new faculty members
take an average of four to five years to meet or exceed their
institution's expectations for research and teaching.1, 2] The
remaining 5%, however-the ones Robert Boice1ll calls
"quick starters"-manage to do it in their first two years.
Considering the enormous investment institutions make in
each faculty member they hire, moving more of the new
ones into the quick starter category would clearly be good for
everyone the new faculty, their institutions, and the students
they will teach and mentor.
Converting new faculty members into quick starters is not
impossible-it's not even difficult. You just give them early
guidance on how to teach well, do good research, and balance
the competing demands of teaching, research, service, and
personal life, and supplement this orientation with one-on-one
mentoring by skilled senior colleagues.
A program containing those elements has been in place
since 2000 in the N.C. State University College of Engineer-
ing. We offer it as an example of what can be done-and in
our opinion, what should be done-to help new engineering
faculty make the transition to their new careers quickly and
successfully. In this column, we briefly outline the program
(Brent, et al.[3] provide more details) and summarize the les-
sons we have learned from our experience with it.
Winter 2007


THE NCSU NEW-FACULTY
SUPPORT PROGRAM
The centerpiece of the NCSU program is a four-day orien-
tation workshop held in mid-August. It covers grantsmanship,
recruiting and working with graduate students, designing
courses and getting them off to a good start, effective lecturing
and active learning, advising, time management, and dealing
with a variety of crises faculty members commonly encounter.
All presentations are highly interactive, and the presenters in-
clude some of the best teachers and researchers on the faculty
as well as key administrators and support staff. The workshop
was first given in 2000 to new engineering faculty, and since
2001 it has been given jointly to new faculty in the Colleges
of Engineering and Physical and Mathematical Sciences.


Richard M. Felder is Hoechst Celanese
Professor Emeritus of Chemical Engineering
at North Carolina State University. He is co-
author of Elementary Principles of Chemical
Processes (Wiley, 2005) and numerous
articles on chemical process engineering
and engineering and science education,
and regularly presents workshops on ef-
fective college teaching at campuses and
conferences around the world. Many of his
publications can be seen at edu/felder-public>.
SRebecca Brent is an education consultant
specializing in faculty development for ef-
ffective university teaching, classroom and
computer-based simulations in teacher
education, and K-12 staff development in
language arts and classroom management.
She codirects the ASEE National Effective
Teaching Institute and has published articles
on a variety of topics including writing in un-
dergraduate courses, cooperative learning,
Public school reform, and effective university
teaching.


Copyright ChE Division of ASEE 2007










The orientation workshop is followed by a series of hour-
long sessions during the academic year that reinforce work-
shop material and help maintain a sense of community among
the participants. Topics addressed include troubleshooting
teaching, dealing with funding agencies, and writing effective
proposals for CAREER Awards. (Workshop alumni have an
excellent record of landing them.) Another component of the
support program is mentoring. In 2000, all departments iden-
tified specific ways the department heads and senior faculty
would provide support to their new hires, and formal mentor-
ing programs have been initiated in several departments.[3]
The response of the new faculty has been overwhelmingly
positive. The participants to date have given the orienta-
tion workshop 99 overall ratings of "excellent," 12 "good,"
and no "average," "fair," or "poor" ratings. Past workshop
participants have given significantly higher ratings than
nonparticipants to their career orientations, and preliminary
assessments indicate that they have outperformed the non-
participants in terms of both funded research activity and
teaching evaluations. The program has maintained a high level
of administrative support and has become a strong selling
point for recruiting new faculty.

RECOMMENDATIONS
We have the following suggestions for schools planning
their own new-faculty support programs.
* Keep the program at the school/college level rather than
making it campus-wide.
Many universities have teaching centers that provide new
faculty orientation, but since the organizers have to address
faculty in all disciplines, they generally limit the program con-
tent to such things as campus resources and employee benefits.
As important as those topics may be, such programs don't do
much to convert new faculty into quick starters. When orien-
tation is designed specifically for faculty in engineering and
related disciplines, presenters can use research and teaching
examples that are clearly relevant to the participants-and
the greater the perceived relevance of presented material, the
greater its likely impact on the recipients.
* Get strong and visible support from the dean and depart-
ment heads.
If the director of a teaching center or the associate dean for
academics invites new faculty members to attend a four-day
workshop two weeks before the start of their first semester,
few are likely to show up, while if the dean and department
heads strongly encourage attendance and share positive evalu-
ations from past workshop participants, most new faculty
will attend.


* Provide guidance on both research and teaching and
discuss how to balance them.
Most new faculty are nervous about meeting expectations
for research productivity. Providing guidance on how to do
it is an excellent way to persuade them that the workshop is
worth their time. Presenters should also emphasize strate-
gies for making teaching efficient as well as effective and
for maintaining a balance of teaching, research, service, and
personal life consistent with the institution's expectations and
the faculty members' health and sanity.
* Keep the presentations practical and interactive.
A workshop that is mainly a parade of talking heads is
generally not worth the time it takes to prepare and present
it. If a designated presenter doesn't know how to design and
deliver an effective interactive presentation, someone else
who does should provide some coaching.
* Treat the participants well.
The new faculty should feel welcomed into the academic
community, and treating them well is one way to make that
happen. Hold the workshop in a convenient, comfortable
location and don't skimp on the budget for meals and breaks.
Provide useful resources in a well-organized notebook. Post
lists of good local restaurants, parks and playgrounds, cultural
attractions, and automobile repair shops. End the workshop
with a celebratory reception and invite all the department
heads and mentors to attend and interact with the participants.
Make sure mentoring in teaching and research is provided by
skilled and supportive colleagues who know something about
how to mentor.[4]
In summary, if the goal is to convert new faculty members
into quick starters-productive in research and effective in
teaching in their first two years-and the orientation that most
of us got (i.e., none) is all that's provided, there is a one-in-
twenty chance of succeeding. The strategies we've proposed
should improve the odds considerably.

REFERENCES
1. R. Boice, Advice for New Faculty Members, Needham Heights, MA:
Allyn & Bacon (2000)
2. R.M. Felder and R. Brent, "The New Faculty Member,"( ... I .
Education, 32(3), 206-207 (1998), public/Columns/Boice.html>
3. R. Brent, R.M. Felder, and S.A. Rajala, "Preparing New Faculty
Members to be Successful: A No-Brainer and Yet a Radical Concept,"
Proceedings of the 2006 Annual ASEE Conference, Washington,
DC: ASEE (2006), ASEEO6(NewFaculty).pdf>
4. R.M. Felder, 'Teaching Teachers to Teach: The Case for Mentoring,
Chem. Engr. Education, 27(3), 176-177 (1993), edulfelder-public/(-..... I, ...,,, ,, .... ,, > [


Chemical Engineering Education


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










classroom
--- ^ K.___________________________-


INCORPORATING SIX SIGMA

METHODOLOGY TRAINING

into Chemical Engineering Education


LENORE L. DAI
Texas Tech University Lubbock, TX 79409
Six Sigma is a buzz term in today's technology and
business worlds. In organizations like Motorola, GE,
DuPont, 3M, IBM, Dow Chemical, and PPG, Six
Sigma means a measure of quality that strives for perfection.El
Statistically, it means reducing the process variation so that
+six standard deviations lie between the mean and the nearest
specification limit. Under the Six Sigma control, the defect
probability is 3.4 per million.1, 2] Six Sigma methodology has
been successfully applied to manufacturing (especially chemi-
cal and related manufacturing), to research and development,
and to business and financial services.
Six Sigma methodology combines elements from several
quality movements with advanced statistical methodology. It
is a comprehensive tool combining business concepts with
technical and leadership skills, and thus it is suitable for pro-
fessionals at all levels: managers, engineers, and scientists.
Recently, there has been great interest in initiating Six Sigma
training in college education. This paper reports the success
of incorporating Six Sigma methodology into a traditional
chemical engineering course, Engineering Experimentation,
at Texas Tech University.


CHE 3343/4372, Engineering Experimentation, is a tradi-
tional undergraduate elective course in the chemical engineer-
ing curriculum at Texas Tech University. The original catalog
listing is "strategy in experimentation; planning efficient
experiments; analysis of data, interpretation, and presenta-
tion results." The course provided an excellent opportunity to
incorporate Six Sigma methodology training into traditional
engineering education. In practice, the instructor starts the
course with an introduction of the fundamentals of Six Sigma
methodology, emphasizing the D.M.A.I.C. process that refers


Copyright ChE Division of ASEE 2007


Winter 2007


Lenore L. Dai is an assistant professor
of chemical engineering at Texas Tech
University. She received her B.S. from
Beijing University of Chemical Technology
and her Ph.D. from the University of Illinois.
Her research fields of interest include
solid-stabilized emulsions, self-assembly
of solid particulates, dynamics of solid
particles at liquid-liquid interfaces, and
polymers and composites.










to Define (D), Measure (MI), Analyze (A), Improve (I), and
Control (C).E31 The course is then organized to discuss various
methodologies and tools in each process stage. For example,
moving range chart/individual chart and range chart/X-bar
chart are heavily emphasized to evaluate measurement sys-
tems in the process stage of Measure (M). The tools in the
process stage of Analyze (A) overlap with various classical
topics in Engineering Experimentation, including: design of
experiments (DOE) and analysis (focused on two-level full,
half, and highly fractionated factorial designs and analyses),
residual and model adequacy analyses, regression model, and
confidence levels. Apart from technical content, it is worth-
while to note that a small fraction of Six Sigma management
and business concepts are also addressed, mainly in the Define
stage. For example, we have discussed a S.M.A.R.T. goal
(refers to a goal that is specific, measurable, agreed upon,
realistic, and time bounded), thought map (a road map that
is composed of different paths of questions), Six Sigma team
development, and effective meeting management. A summary
of the different topics discussed in each stage of the course is
shown in Figure 1. As a more specific example, the instructor
included a request to write a S.M.A.R.T. goal for this course
in the first homework assignment. The students, working in
a group format, answer questions about the course includ-
ing: what is to be accomplished (S, specific), what level of
improvement is needed (M, measurable), what do we agree
upon as a team (A, agreed upon), whether the goal can be
accomplished by the given available resources (R, realistic),
and what the expected dates for major milestones are (T,
time bounded). The full D.M.A.I.C. process is then practiced
through a formal Catapult Project, discussed later, accounting
for 15% of the final grade.


Six Sigma D. M. A. I. C. Process

Six Sigma Tools Discussed in Ch E 334314372
[ Defin Six Sigma Concept, T I M E Problem Statement, S M A R T Goal,
Thought Map, Process Map, Six Sigma Team and Management, Creativit

Run Chart, Moving Range Chart/Individual Chart, Range Chart, Range
Mea ChartX-bar Chart, Common Cause/Special Cause Model, Measurement
System Evaluation, Factor Relationship Diagram, Dot-frequency Diagram
Engineering Experimentation Method
Analyze Full Factorial Design and Analysis, Half Factorial Design and Analysis,
Highly Fractioned Design and Analysis, Residual and Model Adequacy,
J Regression Models, Normal Probability Plot, Other Miscellaneous
Statistical Concepts
[Improve]
S Practice in the Catapult Project and some special homework assignment

Control



Figure 1. The Six Sigma D.M.A.I.C. process and
different tools discussed in CHE 3343/4372.


SPECIAL HOMEWORK ASSIGNMENTS
The homework assignments in CHE 3343/4372 include
the problems in the textbook Design and Analysis of Experi-
ments [4 and special problems generated by the instructor. For
example, the instructor provided raw data of several projects
in CHE 4232, Unit Operations Laboratory (permitted by the
class and the instructor Professor T. Wiesner), and requested
students perform new analyses using the tools learned in
CHE 3343/4372. Such assignments give students opportuni-
ties to work on practical problems related to other chemical
engineering subjects and, more importantly, allow them to
practice the Six Sigma methodology by solving practical
chemical engineering problems. In addition, the instructor
typically has several nontraditional homework assignments,
such as a card-drop exercise related to variation and creativity,
a paper airplane mini-project using a 22 full-factorial design to
study the influence of airplane weight and launching angle on
landing distance, and another card-drop exercise to conduct a
23 full-factorial design to study the influence of card weight,
surface area, and releasing height on target landing.
THE CATAPULT PROJECT
"Tell me, I'll forget; show me, I'll remember; involve me,
I will understand.""' 6] Without doubt, designing and practic-
ing are the heart of engineering majors. This is an important
element in CHE 3343/4372, Engineering Experimentation.
A formal Catapult Project assignment, which includes an
individual project report, a group presentation, and a group
competition, has been assigned for the last four successive
years and counts 15% toward the total grade. Catapults are
used by more than 200 companies as a training aid in Six
Sigma methodology training. A snapshot of the catapult used
in CHE 3343/4372 is shown in Figure 2. The project includes
four major elements. First, the students are assigned to
work in project teams (three to four students per team)
to investigate the performance of their catapults includ-
ing evaluating the measurement system and performing
factorial experiments to determine the major influencing
factorss. Second, each student works independently to
y analyze the collected raw experimental data and submit
a formal individual project report. Third, the project
team regathers and finalizes the developed model for
performance prediction and makes a formal project pre-
sentation to the entire class. Lastly, the team will use its
developed model for a project competition. During the
project competition, the instructor will place the target
at a random location within a defined target area and
each team needs to launch the ball within three minutes
with the goal of hitting the target. Figure 3a shows a
brief map of the setup in the project competition and
Figure 3b is a snapshot of a ball approaching the target
in a 2004 class competition.
The Catapult Project has given the students a unique
opportunity to practice the Six Sigma D.M.A.I.C.
Chemical Engineering Education




























Figure 2. A sample catapult.


process. In the Define stage, the students practice various
concepts taught in class such as defining a S.M.A.R.T. goal,
organizing a thought map, and managing a project team. Dur-
ing the stages of Measure and Analyze, the students evaluate
the measurement system and perform two-level full, half,
and/or highly fractionated factorial design experiments and
analyses to determine the major influencing factorss. In ad-
dition, they will develop a regression model41 quantitatively
relating the distance as a function of setting parameters such
as launching angle, type of ball, rubber band position, and stop
pin position. An example of a regression model developed
from a 23 full factorial design is:
Distance = P( + (1(parameter 1) + P2(parameter 2) +
(3(parameter 3) + (12 (parameter Ixparameter 2) +
P13 (parameter Ixparameter 3) + (23 (parameter 2x
parameter 3) + P123 (parameter Ixparameter 2x
parameter 3) + error (1)
where P( is the average response from the design and (3, (3 ,
and P(jk are calculated from the main effects of single pa-
rameters, two-way interactions, and three-way interactions,
respectively. Eq. (1) is the regression model that involves
all parameters and interactions in a 23 full-factorial design.
For practicality, the students have choices of including only
significant factors. The model adequacy will be evaluated
by various residue analyses. Finally, the students move to
the Improve and Control stage to optimize and apply the
developed regression model. For example, during the project
competition, each project team will measure the distance
where the instructor randomly locates the target (within the
target area) and use the model to decide the settings for dif-
ferent parameters. The accuracy and robustness of the model
will directly determine whether the ball can hit the target or
how close the ball is landing to the target.
It is worthwhile to note the Catapult Project also gives stu-
dents an opportunity to integrate business decision making to
Winter 2007


engineering practice, as each team is allowed a maximum of
45 shots with no deduction of scores during the entire project.
Upon completing the project, the students practice applying
Six Sigma methodology to solve a real-life problem as well
as obtaining the experience of improving the performance of
the catapult while maintaining a profitable business.

THE 'JMP IN' SOFTWARE TRAINING
Other than traditional classroom lectures, the course also
provides two or three training sections of the JMPIn statistical
software. The software is a statistical program that is widely
used in Six Sigma methodology training and at companies
such as Dow Chemical, Procter & Gamble, HP, and PPG.
The software allows students to solve complicated statistical
problems. For example, we have used the JMP In software
to generate a contour plot to view all the possible combina-
tions for desirable properties from the model developed in
the factorial design.

CREATIVITY
Another learning impact of CHE 3343/4372, Engineering
Experimentation, is on creativity. Most chemical engineering
education focuses on problem solving based on well-estab-
lished principles, placing less emphasis on creativity. Hueter
states that modern people's "creative abilities increase in ele-
mentary school up to eight years old and then steadily decrease
with further education, including college education."16 71 The
importance of creativity in engineering can be summarized
as follows: "Engineering is an art as well as a science, and
good engineering depends upon leaps of imagination as well
as painstaking care."1 8] Creativity is also heavily emphasized
in Six Sigma methodology.[9] The project, as well as a few


Figure 3. (a) A map illustrating the setup for the Catapult
Project competition; (b) a ball is approaching the target in
an actual competition in the class of 2004.


a. Launching
Spot











of the homework assignments (paper airplane competition,
card drop exercises, etc.), provide students opportunities not
only to practice the multidisciplinary methodology but also to
maximize their potential to be creative during the exercises.

EVALUATION
The course is among the most popular electives in the
chemical engineering curriculum at Texas Tech University.
In the spring semesters of 2003-2006, the enrollment was 16,
26, 13, and 14, respectively. The course has received excel-
lent student evaluation, with an average rating of 4.9/5.0,
5.0/5.0, 5.0/5.0, and 5.0/5.0 out of the 16 university-level
questionnaires [scores rank from 1 (poor) to 5 (excellent)]
on the instructor and course. Multiple students have said this
class was their "favorite class" and the "best experience in a
college course." Specific comments related to the Six Sigma
training and work experience include:
!./a ,, this class has given me confidence in my ability
to attack and solve problems at my new job this sum-
mer. "
"I think this class was one of the most beneficial
courses that I have taken."
"Really enjoyed this class being directly applicable to
my work today."
"I'm glad that the department decided to give this
course, with industry changing year to year. This class
will be extremely useful when we go to work!"
"Great course. It should be offered every year. It helped
me get my job."

SUMMARY
We have successfully incorporated Six Sigma methodol-
ogy training into a traditional chemical engineering course,
CHE 3343/4372, Engineering Experimentation, at Texas


Tech University. The course is structured along the Six Sigma
D.M.A.I.C. process and different technical and nontechnical
tools have been discussed in each stage of the process. Some
of the nontraditional aspects in this course include industrial
need, special homework assignments, the Catapult Project,
the JMP In statistical software training, and emphasis on
creativity. In addition, students have also obtained hands-on
experience to practice Six Sigma methodology and a unique
and integrative experience to practice engineering and busi-
ness concepts simultaneously.

ACKNOWLEDGMENTS
The author would like to thank Professor T. Wiesner for
his invaluable encouragement and discussion. In addition,
the author is grateful to the support from the Texas Tech Fac-
ulty Incentive Grant Award (2003) and the National Science
Foundation (CTS-0500323).

REFERENCES
1. Stamatis, D.H., Six Sigma and Beyond, CRC Press LLC (2002)
2. Statistical Six Sigma Definition, content/c010101a.asp>, (2006)
3. Rath & Strong's Six Sigma Pocket Guide, Rath & Strong Management
Consultants, Lexington (2002)
4. Montgomery, D.C., Design andAnalysis ofExperiments, 5th Ed., John
Wiley & Sons, Inc. (2001)
5. Eastlake, C.N., "Tell Me, I Will Forget; Show Me, I'll Remember;
Involve Me, I'll Understand (The Tangible Benefit of Labs in the
Undergraduate Curriculum), "Proceedings ASEE Annual Conference,
Washington, (1986)
6. Hueter, J.M. "Innovation and Creativity: A Critical Linkage, "Proceed-
ings ASEE Annual Conference, Washington, 1634 (1990)
7. Wankat, PC., and E S. Oreovicz, Teaching Engineering, McGraw-Hill
(1993)
8. Forman, S.C., The Civilized Engineer, St. Martin's Press, New York
(1987)
9. Pyzdek, T., The SixSigmaHandbook-A Complete Guide for Greenbelts,
Blackbelts, and Managers at All Levels, McGraw-Hill (2001) 1


Chemical Engineering Education











book review
--- ^ K.___________________________-


Process Dynamics and Control, 2nd Ed.
by Dale Seborg, Tom Edgar, and Duncan Mellichamp
Wiley (2003) $138.95


Reviewed by
Derrick K. Rollins, Sr.
Iowa State University of Science and Technology
First, I want to applaud the authors for making a substantial,
well-thought-out revision to their textbook. I have used the
book to teach my introductory process control course but had
not really read the additional material in the new chapters until
this review. I was very impressed with the depth and breadth
of the material. I am amazed that the authors were able to
eliminate so much material and yet not dilute the critical
topics that are important to a first course. I know that it was
a struggle to decide what to eliminate and what to keep, just
due to the fact that three personalities were involved. They
did an excellent job.
Since the authors did eliminate so much material, espe-
cially on digital control, I see the two versions being more
like Volume 1 and Volume 1.5 (not quite two volumes) and
working to complement each other in advanced courses in
process control. I see potentially three semester courses (at
least this is the way I would do it) from this text. The first
one is a general process control course for all undergraduate
chemical engineering students covering Chapters 1-9, 11-12,
and 15-16; a course in advanced methods covering Chapters
13-14, 18-21 (bringing in material from the first edition);
and an application toward plantwide control and plant design
covering Chapters 10, 22-24, and all the Appendices.
For those working in the process control field the book is
a good textbook as well as a good reference manual. Faculty
that are not, however, yet are teaching process control might
find the text intimidating and too complex. I asked a faculty
member in my department who fits this category and is cur-
rently using the text and that was his feeling. I kept this in mind
while reviewing the text and I could understand his feeling of
insecurity with it. One way the text could be improved is to
revisit the chapters I mentioned for an introductory course and
work to rewrite it in such a way that faculty in this category
could feel more comfortable with the material.
My comments on specific chapters are as follows. Chapter
1 needs more problems. I am disappointed that they took
the block diagram out of this chapter. I have used it to tell
students where we are going and why we need Chapters 2-7
and how each block represents certain chapters that we will
Winter 2007


tie back together in Chapter 11 (what used to be Chapter 10).
Chapter 2 is essentially the same as before just with some
new problems (I particularly like the additional application
on bioprocesses and the exercises). Chapter 3 is essentially
the same but the authors should have left Exercises 3.16 and
3.20 in this edition. These were two of my most popular
problems for homework. Chapter 4 also did not change much
but could be made shorter by giving a general method using
Section 4.3 material, which covers all cases. I like the addi-
tion of state-space formulation. Chapter 5 has been basically
untouched, which I applaud, but it does have more good
problems-something faculty always appreciate. Section
6.3.1 is a good addition to Chapter 6 and is explained well.
I have always appreciated this chapter and I am glad to see
it is even better. The problems are good, especially the ones
reflecting new material and bio-systems engineering. For
Chapter 7, I feel that all the emphasis on graphical methods
should be removed and replaced with regression. In illustrat-
ing regression techniques I think it is more important to show
how software packages would do this rather than to give the
mathematical equations on how they are done. Although they
give Matlab and Excel examples they do not show, step by
step, how this is exactly done. I think professors and students
would appreciate this detail.
Example 7.4 needs to be revised or removed. Who would
fit Models 3 and 4 to that response? In addition, a better ARX
or ARMAX model should give a better fit by the fact that
Model 1 fit so well.
Chapter 8 is basically the same but this chapter has always
needed, as it does now, more problems. Chapter 9 is done
well but needs more explanation of hardware and more
problems.
Other textbooks are much stronger in this material such as
Riggs (2001). I just skipped the material in Chapter 10 and
went straight to Chapter 11. It is good material but out of step
with how I do my course. It is important for the material on
plantwide control and design. I do not like the way the mate-
rial in the new Chapter 11 has combined Chapters 10 and 11
from the first edition. I like to keep stability analysis separate.
There are, however, plenty of good exercises in this chapter.
Chapter 12 is done well and has excellent problems. Chapters
13 and 14 are a good condensation of the three chapters on
frequency response from the first edition. This material needs
to remain but not be overemphasized, in my opinion. Chapter
15 is an excellent chapter with good problems.
For Chapter 16, the addition of Fuzzy Logic Control is an
excellent improvement but I couldn't find any exercises on
this topic. In Chapter 17 I am glad that they left the mate-
rial on filtering in this edition. I know that it was difficult to
remove much of the material on z-transforms and sample
data-control systems, but the first addition could supplement


@ Copyright ChE Division of ASEE 200;










these eliminations if necessary. It would help to actually have
an example for obtaining the poles and zeros. Also, what hap-
pened to COUz in Eq. 17-46? The Co is there but where is U ?
I appreciate the addition of Section 17.6 and I am glad they
did not go into a lot of detail [it would be hard to match the
material of Ogunnaike and Ray (1994) on the topic]. There
are a lot of good problems in the exercises.
I did not find many errors or typos in this edition, which is
commendable considering the amount of new material and re-
organization. In Chapter 18, however, "n!" on page 477 should
be "n." Also, on page 479, "hidden" is mistakenly printed as,
"hidd en." On page 492, just below Eq. 18-58, "4" should be
"w." I commend the authors for adding the SVD material and
updating this chapter. It may be the most important chapter
for the control design engineer in terms of theory.
I am glad that they shortened the material in Chapter 19
since optimization is a course in itself and only an overview
is critical to any process control course. Chapter 20 is a sub-
stantial and critical improvement over the first edition. All the
basic fundamentals and concepts of model predictive control
(MPC) appear to be present. At least it gives a good overview


and introduction on the subject. Although I have not taught
from this chapter yet, the exercises appear to be excellent.
The authors did an excellent job on Chapter 21. They did
it just right and the critical material is here in just the right
amount. These topics include the following: X bar chart, S
chart, Cusum, EWMA, Cpk, Six Sigma, and multivariate
MPC. They need, however, to point out which ones detect a
"mean shift" vs. a "variance shift." For example, there is no
statement in this regard for the X bar chart. I suggest that they
add the use of Minitab in this chapter as they did Mathlab and
Simulink for chapters exploiting their use. Finally, Chapters
22-24 appear to be done quite well and I look forward to using
them in future courses.
Overall, the authors' have made a timely and significant
improvement to this textbook by bringing it up to date
with current practices and needs, and enhancing its use as
a textbook in process control for undergraduate as well as
graduate students. I have used the earlier book since 1991,
and with the improvements they have made in the second
edition, this text will be useful in the courses I teach for
many years to come. 7


Chemical Engineering Education











M]!1n class and home problems


INTRODUCING NON-NEWTONIAN FLUID

MECHANICS COMPUTATIONS

With Mathematica in the Undergraduate Curriculum


HOUSAM BINOUS
National Institute of Applied Sciences and Technology
Anon-Newtonian fluid has a viscosity that changes with
the applied shear force. These fluids are characterized
by measuring or computing several theological prop-
erties, such as the viscosity and the first and second normal
stresses. Rheometers are used, under oscillatory shear flow
or extensional flow, to obtain experimental values of these
theological properties while kinetic theory calculations using
dumbbells allow the prediction of these theological properties.
For a Newtonian fluid (such as water), the viscosity is indepen-
dent of how fast you are stirring it. For a non-Newtonian fluid
the viscosity is dependent. It gets easier or harder to stir faster
for different types of non-Newtonian fluids. By adding corn
starch to water, one obtains a non-Newtonian fluid. Applying
agitation with a spoon makes the fluid behave like a solid.
Thus, the shear-thickening property of this non-Newtonian
fluid becomes apparent. When agitation is stopped and the
fluid is allowed to rest for a certain period of time, it recovers
its liquid-like behavior.
Non-Newtonian fluids display many peculiar phenomena
that can serve as the basis for multiple "fun" experiments
students can perform in the laboratory. These include dye
Winter 2007


*Tunis, Tunisia
swelling, rod climbing, and suspensions of particles behavior
while moving in non-Newtonian vs. Newtonian fluids. Stu-
dents can determine the terminal fall velocity and rotation
direction of a single settling particle as well as wall effects
and interaction between particles. Problems involving non-
Newtonian fluid flow are ubiquitous in modern industry, such
as in polymer processing plants. The study of body fluids such
as blood, which is non-Newtonian, has important applications
in biomedical engineering. In the present paper, we show
how one can use the mathematical software Mathematica to

Housam Binous is a full-time faculty member
at the National Institute of Applied Sciences
and Technology in Tunis. He earned a Dip-
lome d'ingenieur in biotechnology from the
Ecole des Mines de Paris and a Ph.D. in
chemical engineering from the University
of California at Davis. His research interests
include the application of computers in
chemical engineering.



Copyright ChE Division of ASEE 2007


The object of this column is to enhance our readers' collections of interesting and novel prob-
lems in chemical engineering. Problems that can be used to motivate the student by presenting
a particular principle in class, 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 elucidate difficult concepts.
Manuscripts should not exceed 14 double-spaced pages and should be accompanied by the origi-
nals of any figures or photographs. Please submit them to Professor James O. Wilkes (e-mail:
wilkes@umich.edu), Chemical Engineering Department, University of Michigan, Ann Arbor,
MI 48109-2136.










solve some simple non-Newtonian fluid problems. The most
relevant Mathematica commands'11 are inserted in the text
and can be found in any introductory book such as Math-
ematica, A System for Doing Mathematics by Computer by
Stephen Wolfram.[2] We start by reminding the reader of the
few simple constitutive equations for the power-law, Carreau,
and Bingham fluids. Then, we give the velocity profile for
the horizontal flow of power-law and Carreau fluids in a pipe
and an annulus. The velocity profile for the fall of a Bingham
liquid film is obtained in the next section. We also derive
volumetric flow rate expressions for pipe flow of Bingham
and power-law fluids. In the last part of the paper, we make a
model determination using previously found volumetric flow
rate expressions and representative data.

CONSTITUTIVE EQUATIONS FOR
NON-NEWTONIAN FLUIDS
For Newtonian fluids, the shear stress, T, is proportional to
the strain rate, T
S= rl (1)
where the viscosity, l, the proportionality factor, is constant.
The situation is different for non-Newtonian fluids, and the
viscosity is a function of the strain rate:
T =q 0 ) (2)
Different constitutive equations, giving rise to various models
of non-Newtonian fluids, have been proposed in order to ex-
press the viscosity as function of the strain rate. Inpower-law
fluids, the following relation is satisfied:

TI = r.-1 (3)
Dilatant fluids correspond to the case where the exponent
in Eq. (3) is positive (n > 1) while pseudo-plastic fluids are
obtained when n < 1. We see that viscosity decreases with
strain rate for n < 1, which is the case for pseudo-plastic
fluids, also called shear-thinning fluids. On the other hand,
dilatant fluids are shear-thickening. If n = 1, one recovers the
Newtonian fluid behavior.
The Carreau model describes fluids for which the viscosity
presents a plateau at low and high shear rates separated by a
shear-thinning region:
1I- i 1
S1 n2 (4)


where 0o is the zero-shear viscosity and 1_ is the infinite-
shear viscosity.
Finally, the Bingham model is defined as follows:


Atlow shear rates :


Athigh shear rates:


1 2
-(T:T)< T =0
2


1 2
-(T: T)> To,
2


T= tI'q+1 (6)


HORIZONTAL FLOW OF CARREAU AND
POWER-LAW FLUIDS IN A PIPE
Problem Statement
Find the velocity profiles for the laminar flow of power-
law and Carreau fluids in a pipe, shown in Figure 1. Use the
following values for the pressure difference AP, the exponent
n, the Newtonian fluid viscosity 1, the consistency index K,
the infinite-shear viscosity ] the zero-shear viscosity %,
the relaxation parameter X, the pipe length L, and radius R,
whose units appear under "Nomenclature" at the end of this
article:
AP =100; L = 50; and R = 0.02
Newtonian fluid: T = 8.9 X 104.
Dilatant fluid: n = 3.39 and K = 106.
Pseudo-plastic fluid: n = 0.4 and K = 5 X 103.
Carreau fluid: n= 0.5, X= 0.2, 0o= 1.72 X 103, and Tl= 0.
Solution
This problem is treated using Polymath, a numerical com-
putational package,[31 in Problem Solving in Chemical Engi-
neering with Numerical Methods by Cutlip and Shacham.[4]
The governing equation is the z-component of the equation
of motion in cylindrical coordinates:
Id _dvz P
d dv (7)
r dr dr L

Eq. (7) is subject to the following split boundary condi-
tions:


At r = 0:
At r= R:


z =0
v= 0


These kinds of mathematical problems often require the use of
a particular numerical approach called the shooting technique.
This method consists of guessing different values of v. at r = 0,
solving the differential equation, and checking that the no-
slip boundary condition at r = R is satisfied. An analytical
solution is possible for power-law fluids and details about
its derivation can be found in Fluid Mechanicsfor Chemical
Engineers by Wilkes:51]
AP Iln (R1+/n -r l/in
z (r)= 2 (10)

n

AP=P P2=100

R=0.02


Vx(r)

L=50
Figure 1. Flow of Carreau and power-law fluids
in a pipe.
Chemical Engineering Education










For the Carreau fluid, one must use a numerical approach
since no analytical solution is available.
For the power-law fluids, the following Mathematica com-
mands are used to find the velocity:
system[QJ = { D[r Tj[r],{r,1}] == AP/Lr,
D[v[r],{r,1}] == If[ Trz[r]0, -( T[r]/K )A(1/n),
(-T_[r]/K)A(1/n) ], Tr[10^-5] == 0, v[10^-5] == Q };
myODEsoln[Q_] := NDSolve[system[Q], { vz, TJ, {r,
10^-5, R}]
yend[Q_?NumericQ] := Flatten[(v,[r] / myODEsoln[t])
/. rR]
bc = FindRoot[yend[Q] == 0, {I, 0, 0.5} ][[1,2]];

The graphical capability of Mathematica allows the student
to plot the velocity profile without having to use different
software. Figure 2 shows the velocity profile for the New-
tonian, dilatant, Carreau, and pseudo-plastic cases using the
commands:


0.25
Newtonian

0.2


0.15 Carreau


0.1 Pseudo-plastic


0.05



0 0.005 0.01 0.015 0.02
r
Figure 2. Velocity profiles of dilatant, pseudo-plastic,
Carreau, and Newtonian fluids in a pipe.


AP=P, P2=100


soll=myODEsoln[bc]
pltl=Plot[v[r] /. soil, {r, 0.00001, R}, PlotStyle RGB-
Color[0, 0, 1]]

These profiles are obtained under equal volumetric flow
conditions. The velocity near the wall is higher for Carreau
and pseudo-plastic fluids than for Newtonian and dilatant
fluids. This results in higher heat transfer rates due to a higher
convection. The approach to solve split boundary problems
using Mathematica is more systematic than the one proposed
by Cutlip and Shacham[4] using Polymath, despite a steeper
initial learning curve for students. In fact, it automatically
finds the velocity at the center of the pipe by verifying the
no-slip boundary condition and using the Mathematica com-
mand FindRoot.

HORIZONTAL FLOW OF A CARREAU AND A
POWER-LAW FLUID IN AN ANNULUS
Problem Statement
Find the velocity profiles for the laminar flow of power-law
and Carreau fluids in an annulus, shown in Figure 3. Use the
following values, where R and R, are the inner and outer radii,
and all other symbols have already been defined:
AP= 100; L= 50; R,=0.02 and R =0.05
Newtonian fluid: T = 8.9 X 104.
Dilatant fluid: n = 1.2 and K = 4.7 X 104.
Pseudo-plastic fluid: n = 0.5 and K = 4.5 X 103.
Carreau fluid: n = 0.5, X = 0.2, 0o= 2.04 X 10 and T,= 0.
Solution
Cutlip and Shacham[4] have solved this example using
Polymath. The governing equation is again the z-component
of the equation of motion in cylindrical coordinates:

1 d dv A
!rdr -dr ) (11)
r dr dr L

Eq. (11) is subject to the following split boundary condi-
tions:


At r = R:
At r = R,


v =0
v =0


To solve this problem, we make use of the shooting technique
in a similar fashion as the previous example. This method
works by guessing different values of Tz at r = R solving the
differential equation, and checking that the no-slip boundary
condition at r = R, is satisfied. An analytical solution[41 is
available for the Newtonian fluid case:


vz(r)= ['PR2
4 4IL


r 2nR22- R ln(r /R2) (14)
ln(R, / R1)


There is no analytical solution for dilatant, pseudo-plastic, and
Carreau fluids, so one must resort to a numerical method.


Figure 3. Flow of Carreau and power-law fluids
in an annulus.
Winter 2007











For the power-law fluids, the following Mathematica com-
mand is used to find the velocity as a function of r:
system[Q] = { D[r T [r],{r,l}] == AP/L r,
D[v[r],{r,1}] == If[ T[r]>0, -(Tr[r]/K )A(l/n),
(-T_[r]/K)A(l/n)], T_[R1] == Q, z[R1] == 0 };
myODEsoln[Q_] := NDSolve[system[Q], {vz T), {r, R1,
R2}]
yend[Q_?NumericQ] := Flatten[(v[r] /. myODEsoln[Q])
/.r R2]
bc = FindRoot[yend[Q] == 0, {0, -2, 2} ][[1,2]];

One can plot the velocity profile, shown in Figure 4, for the
Newtonian, dilatant, Carreau, and pseudo-plastic cases using
the Mathematica commands:
soll=myODEsoln[bc]
pltl=Plot[vx[r] /. soil, {r, 0.00001, R}, PlotStyle RGB-
Color[0, 0, 1]]

These profiles are obtained under equal volumetric flow
conditions. The velocity profiles found for all four fluids are
not symmetric. In fact, they reach a maximum value close
to the radial position, given by r = 0.033, slightly less than
halfway from R and R2.

VERTICAL LAMINAR FLOW OF A BINGHAM
LIQUID FILM
Problem Statement
Find the velocity profile for the vertical laminar flow of a
Bingham fluid down the wall depicted in Figure 5. Values
of the gravitational acceleration, g, the density, p, the yield
stress, T0, the zero-shear viscosity, 10, the film thickness, b,
are given by:
g=9.81; p=950; T =5; 10 =0.15 and 8=0.005


Solution
Cutlip and Shacham 41 have presented a solution of this
example using Polymath. The governing equation is the
z-component of the equation of motion in rectangular co-
ordinates:

d-= pg (15)
dx
Eq. (15) is subject to the following split boundary condi-
tions:


At x= 0:


Tx =0


At x = 6: v = 0 (17)
We make the same treatment as the first two problems by
applying the shooting technique:
system[Q_] = {D[Tj[x],{x,l}] == Q g,
D[v[x],{x,l}] == If[Abs[T][x]] If[Tj[x] > To, (To-Tj[x] )/o -(To + Tj[x] ) / No ]]
J[O] == 0, v[O0] == Q };
myODEsoln[QJ := NDSolve[system[Q], {v TZ}, {x, 0,
6}]
yend[Q_?NumericQ] := Flatten[(v[r] /. myODEsoln[b])
/. r 6]
bc = FindRoot[yend[Q] == 0, {J, 0, 0.5} ][[1,2]];

For the Newtonian case, an analytical expression for the veloc-
ity, vz, as a function of position, x, can be easily derived:

v= 1- xI2 (18)


In Figure 6, we show the velocity profile for the Newtonian
and the Bingham fluids. This plot is obtained by using the
Mathematica commands:


0. / 'irrt.iu\

0.F P.tuiliii-llic t


0. 1
0.1


0.05



0.02 0.025 0.03 0.035 0.04 0.045 0.05
r
Figure 4. Velocity profiles of dilatant,
pseudo-plastic, Carreau, and Newtonian
fluids in an annulus.


Figure 5.
Vertical flow
of a Bingham
fluid in a
liquid film.


Bingham

0.2 Newtonian



0
0 0.001 0.002 0.003 0.004 0.005
x
Figure 6. Velocity profiles of Bingham and Newtonian
fluids in a liquid film.
Chemical Engineering Education










soll=myODEsoln[bc]
pltl=Plot[v[x] /. soil, {x, 0, 6}, PlotStyle RGBColor[0,
0, 1]]

A comparison of the velocity profile obtained using the ana-
lytical solution for the Newtonian fluid and the velocity profile
corresponding to the Bingham fluid shows that the latter is flat
near the surface of the liquid film. In fact, we have a nonzero
velocity gradient only when Txz> T. This behavior is typical
of Bingham fluids.


EXPRESSIONS OF VOLUMETRIC FLOW
RATES
Problem Statement
Derive expressions of volumetric flow rates for pipe flow of
Bingham and power-law fluids using symbolic computations
with Mathematica.
Solution
Power-law fluid case
First, we find the expression of the shear stress, T, as a func-
tion of the radial position, r:
sol3 = DSolve[D[r T [r],{r,l}] == AP/L r, T [r], r]
T[r] = soll[[l, 1, 2]]/.C[1] 0

We get the following result:
APr
Trz A- Pr (19)
2L
Then, we determine the velocity distribution using the sym-
bolic command, Dsolve,
sol4 = DSolve[D[vz[r],{r,1}] == -( -rz[r]/K )A(l/n), [r], r]

2 -1/"n nR ( )PR
v[r] = sol4[[1, 1, 2]]/. C[l] xL
l+n
Finally, the symbolic command, Integrate, is used,
Q = Integrate[2 Pi r v[r], {r, 0, R}]

TABLE 1
Volumetric Flow Rate vs. Pressure Gradient

AP/L (Pa/m) 105 X Q (m3/s)
10000 5.37
20000 26.4
30000 68.9
40000 129
50000 235
60000 336
70000 487
80000 713
90000 912
100000 1100
Winter 2007


and we get the following expression for the volumetric flow
rate,

2 n R RAP /n

Q=L (20)
1 +3n
Bingham fluid case
Just like the treatment above, we start by finding the ex-
pression of the shear stress, Trz, as a function of the radial
position, r:
soil = DSolve[D[r Tj[r],{r,l}] == AP/L r, Tr[r], r]
Tr[r] = soll[[l, 1, 2]]/.C[1] 0
We get the following result:
APr
Pr (19)
2L
In the first part of the derivation, we determine the velocity
distribution between r = (2T0L)/AP and r = R using boundary
condition vz(R) = 0 and the symbolic command, Dsolve:
sol2 = DSolve[D[v[r],{r,l}] == ( Tz[r]+T0)/qi, z[r],r]
vz[r] = sol2[[1, 1, 2]] /. C[l] i ((AP R2)/(4 q L))
(RT0)/qi

The symbolic command, Integrate, is used to obtain the ex-
pression of the volumetric flow rate between r = (2ToL)/AP
and r = R,
Q1 = Integrate[2 Pi r v[r], {r, -2 T0 L/AP, R}]

In the second part of the derivation, we determine the con-
stant velocity, v0, between r = 0 and r = (2T L)/AP using the
following symbolic command:
v = 1/4t (-AP/L) (r2-R^2) /4 + To /i (r-R) /. r 2 T0 AP

This is nothing more than expressing the continuity of the
velocity at r = (2T0L)/AP. In fact, we have written that vo=
Vz((2T0L)/AP) in the above Mathematica statement.
The symbolic command, Integrate, is used to obtain the
expression of the volumetric flow rate between r= 0 and r =
(2T0L)/AP,
Q2 = Integrate[2 Pi r v0, {r, 0, 2ToL/AP}]

and we get the following expression for the overall volumetric
flow rate,

7R4 AP 7R3T0 2Tr0L3
Q= p3 (21)
8vlL 3iq 3 AP3

NON-NEWTONIAN FLUID MODEL
DETERMINATION
Problem Statement
Wilkes5s] provides representative values of the volumetric
flow rate vs. the applied pressure gradient for horizontal flow
in a pipe. These values are reproduced in Table 1. The pipe
radius is equal to R = 0.01m. Use these representative values,










in conjunction with the analytical expression of the volumetric
flow rates determined in the previous section, to compute the
parameters of the constitutive equation.
Solution
First, we compute the following sum:
10
S= (Qep h 2 (22)

where Q rep and Qth are the representative value and analytical
expression of the volumetric flow rate. Then, we use the built-
in command of Mathematica, FindMinimum, to determine
the values of n and K for the power-law model, and to and
1] for the Bingham model that minimize the objective func-
tion, J. The approach used here is the least squares method.
For the power-law model, we find n = 0.437 and K = 6.708,
while for the Bingham model the result is to = 77.55 and q =
0.0326. The value of the sum given by Eq. (22) is 9.89X 106
for the Bingham model and 2.67X 107 for the power-law
model. Thus, we conclude that the power-law model fits the
representative data better.


CONCLUSIONS


We presented the solution of four non-Newtonian fluid
mechanics problems using Mathematica. The velocity profile
is obtained for the horizontal flow of power-law and Carreau
fluids in pipes and annuli, and for the vertical laminar flow
of a Bingham fluid. These problems have split boundary
conditions and were solved using the shooting techniques.
Analytical expressions of volumetric flow rates for pipe flow
of the Bingham and power-law fluids were derived using
Mathematica. The parameters of the constitutive equation
of non-Newtonian fluids were obtained from representative
data of flow rates measured under different applied pressure
gradients in a horizontal pipe. These problems are simple
enough to constitute an excellent introduction to the field
of non-Newtonian fluid mechanics. Students at the National
Institute of Applied Sciences in Tunis performed well de-
spite no previous knowledge of Mathematica. Mathematica


notebooks are available from author upon request or at the
information center[1]

NOMENCLATURE

g gravitational acceleration ( m/s2)
Q volumetric flow rate (m3/s)
L pipe length (m)
n power-law exponent
AP pressure difference (Pa)
R pipe radius (m)
R1,R2 annulus radii (m)
r radial position (m)
v velocity (m/s)
z axial position (m)
K power-law consistency index (N in1:
8 film thickness (m)
X relaxation parameter (s)
Y1 viscosity (kg in i:)
10 zero-shear viscosity (kg in i:
1r] infinite-shear viscosity (kg in i:)
p density (kg in i
T0 yield stress (kg/m-s)
Trz shear stress (kg/m s)

REFERENCES
1. results= 1;search_person_id= 1536>
2. Wolfram, S., Mathematica, A Systemfor Doing Mathematics by Com-
puter, Addison-Wesley, Redwood City, CA (1988)
3. 4. Cutlip, M.B., and M. Shacham, Problem Solving in Chemical Engi-
neering with Numerical Methods, Prentice Hall, Upper Saddle River,
NJ (1999)
5. Wilkes, J.O., Fluid Mechanicsfor Chemical Engineers, Prentice Hall,
Upper Saddle River, NJ (1999) 1


Chemical Engineering Education











M, laboratoryy


IMPLEMENTATION AND ANALYSIS


OF HEMODIALYSIS

in the Unit Operations Laboratory


SUNDARARAJAN V. MADIHALLY
Oklahoma State University Stillwater, OK 74078
RANDY S. LEWIS
Brigham Young University Provo, UT 84602
The recent boom in the biomedical/biochemical in-
dustry has necessitated the introduction of biological
components into the chemical engineering curriculum.
According to the U.S. Department of Labor, the job market for
biomedical engineers is projected to increase 31.4% through
2012.11] In 1990, less than 4,000 students were enrolled in
undergraduate biomedical/biochemical programs; in 2002
there were more than 10,000 students enrolled.[2] In the next
five years, it is estimated that two to three times more students
per year will take biomedical/biochemical courses.
To enhance biomedical/biochemical engineering oppor-
tunities in chemical engineering, experiments involving
enzymatic degradation of cellulose and dialysis of creatinine
were introduced at Oklahoma State University (OSU) in the
Unit Operations Laboratory (UOL). These projects enhance
the instruction students receive in optional Introduction to
Biomedical Engineering and Introduction to Bioprocess
Engineering courses. In the UOL, students work in teams of
Winter 2007


Sundararajan V. Madihally is an assistant
professor in the School of Chemical Engi-
neering at Oklahoma State University. He
received his B.E. in Chemical Engineering
from Bangalore University and his Ph.D.
in chemical engineering from Wayne State
University. He held a research fellow position
at Massachusetts General Hospital/Harvard
Medical School/Shriners Hospital for Chil-
dren. His research interests include tissue
regeneration and the development of thera-
pies for traumatic conditions.
Randy S. Lewis is a professor of chemical
engineering at Brigham Young University.
He received his B.S. and Ph.D. degrees in
chemical engineering from Brigham Young
University and Massachusetts Institute
of Technology, respectively. He recently
served as chair of the Career and Education
Operating Council of AIChE. His research
interests include biomaterial development
and the utilization of renewable resources
for the production of chemicals.


Copyright ChE Division ofASEE 2007










three participating in three five-week projects during each
semester. While assigning projects, bio-related ones are al-
located preferentially to students enrolled or committed to
biomedical and/or bioprocess courses.
The dialysis experiment demonstrates the fundamental
concepts of a hemodialysis device using creatinine as the
target agent for removal. Creatinine (\IW 113) is one of
several waste products produced in a human that must be
removed by the kidney. Although some dialysis experiments
have previously been demonstrated in the chemical engineer-
ing curriculum using salt solutions with short experimental
times,[3] the use of creatinine has several advantages. These
advantages include its larger relative size to other waste
products and its use, along with urea, as a marker for effec-
tive dialysis treatment. 4] The larger creatinine size leads to a
longer removal time in comparison to other waste products.
The waste product with the longest removal time is often
used in determining dialysis treatment time. Thus, the use of
creatinine leads to a more realistic dialysis experiment-even
with the drawback of longer dialysis time. This work presents
a dialysis model that demonstrates the assessment of model
assumptions. It will detail the dialysis project statement de-
livered to the student team, the experimental protocol, the
dialysis model, experimental results, and student feedback
and assessment. A benefit of incorporating the dialysis project
is that the student can integrate a number of concepts such
as material balances/modeling (i.e., blood and dialysate bal-
ances with assumptions), transport issues (i.e., evaluation of
transport coefficients), model validation of assumptions, and
solving differential equations (i.e., using Polymath) toward a
bioengineering project that allows the student to expand the
scope of his/her chemical engineering education.


PROJECT STATEMENT)
A biomedical engineering company makes many biomedical
devices, one of which is a hollow-fiber separatorfor dialysis
machines. Hospitals use dialysis to process the blood of
patients whose kidneys do not effectively remove toxins and
excess water from the blood. The machine has many features
that you will not need to use. We are interested in the hol-
low-fiber membrane separation unit that dialyzes the blood.
Please develop and validate an unsteady-state model for
predicting the temporal profile .. ', ioit. creatinine removal,
one of several toxic metabolites, from "blood" (represented
by water in this experiment). Using your model, determine
the effects on dialysis treatment time, blood recirculation flow
rate, and transmembrane pressure (AP) for removing 90%
of creatinine. Metabolites and electrolytes ,fi.A. t the osmotic
pressure, which affects the transport of water across the
membrane. This osmotic pressure effect must be included in
your model to determine the amount of water removed from
(or added to) the "blood" during the dialysis treatment.


As part of the model, you need to generate experimental
data from the hollow-fiber membrane separator to obtain an
overall transfer coefficient for creatinine and then you must
validate your model. The hollow-fiber membrane unit is simi-
lar to a shell-and-tube heat exchanger. Basically, blood flows
;ll,.. ,. 1 the inside of the hollow fibers (tubes), and dialysate
(composed of salts similar to normal blood concentrations)
flows ;,ii .i, il,.. shell-side. Unwanted toxins and other excess
metabolites and electrolytes in the blood difflt e ,Ir.. .. 1, the
fiber walls into the dialysate. The patient's blood is continu-
ously o1. il.air. wilhin hin hel body. The blood compartment
of the body can be assumed as a Continuous Stirred Tank
(CST) in which the partially purified blood coming from the
kidney dialysis unit is returned to the body.

EXPERIMENTAL PROTOCOL
The experiment consists of a hemodialysis unit connected
to a bucket of water containing creatinine (representing the
patient's blood), as shown in Figure 1. A schematic of the


Figure 1. Dialysis unit, dialyzer, and a continuously
stirred tank containing creatinine that represents the
patient's blood.


Chemical Engineering Education










experimental system is shown in Figure 2. Although hemo-
dialysis units are expensive, many dialysis centers regularly
replace their units on an annual or bi-annual basis. Since
there is often a cost for disposal of the units, the supplier of
hemodialysis units at a local dialysis center was contacted and
the supplier donated 10 units to OSU at no charge. It is likely
that such donations can be obtained from other hemodialysis
unit suppliers in the same fashion. Manometers were placed
at all inlets and outlets of the dialyzer to measure pressure
drops from one end of the dialyzer to the other end as well
as to measure transmembrane pressure differences. Three to
four liters of a solution (denoted "blood") containing up to
4.1 mM creatinine were used to simulate the patient's initial
blood concentration. The blood was continuously mixed using
a magnetic stirrer. The blood was pumped to the tube side of
the dialyzer at rates varying between 300-500 ml/min, con-
trolled by the dialysis unit, and blood volume changes were
monitored at regular intervals by weighing the bucket on an
electronic scale. Water (denoted "dialysate") was continuously
added at rates between 815-865 ml/min to the shell side of the
dialyzer and, upon exiting, emptied into a waste sink.
Experiments were conducted over a two-hour period. In the
open-loop experiment, the blood flowed such that the blood
entering the dialyzer from the bucket contained a constant
creatinine concentration and the blood exiting the dialyzer
was sent to a waste bucket. This experiment was performed to
determine the creatinine mass transfer parameter, Kc, neces-
sary to predict the creatinine concentration with time in the
closed-loop experiment. In the closed-loop experiment, the
blood continuously circulated such that the blood volume and
creatinine concentration decreased with time. The changing
creatinine concentration was used to compare model predic-
tions with experimental results. During the experiments, the
inlet and outlet pressures across the dialyzer and the volume
of the blood were recorded every five minutes (via measuring
the weight of the blood). Samples (0.3-0.5 mL) were collected
for analysis of the creatinine concentration.
To analyze the creatinine concentration, one part sample
was mixed with three parts of a solution containing a 10:1 ratio
of 0.14% picric acid and sodium hydroxide. Note that picric
acid is hazardous, highly explosive, and should only be used
under the careful guidance of an instructor. In this analysis,
creatinine reacts with alkaline picrate to form a reddish-yel-
low solution from which the absorbance can be detected in
a spectrophotometer at 490 nm.J51 The absorbances were
converted to concentrations via a linear calibration curve.
Spectrophotometers are a common component in many labo-
ratories and thus there is a possibility that arrangements could
be made to use existing spectrophotometers for the creatinine
analysis. Inexpensive spectrophotometers may be purchased,
however, for as little as $1,500. Other calorimetric methods
also exist for assaying creatinine, although the methods are
more expensive.[6]
Winter 2007


Figure 2. Schematic of Figure 1 showing the dialysis unit
and countercurrent flow in the dialyzer. The creatinine
concentration (C) parameters and volume (VcST) of the
continuously stirred tank used in Eqs. (2) and (3) and (7)
through (9) are shown.

DIALYSIS MODEL AND SOLUTION
To meet the objectives of the project statement, students
needed to develop a mathematical model for the process.
The blood in the bucket was modeled as a CST with a given
volume (VCST). During the closed-loop experiment, the CST
creatinine concentration (CT ) changes with time accord-
ing to:
dCCST QB out
-C (( B.out CST
dt VCST (C c
where QBout is the volumetric outlet flow rate of blood through
the dialyzer and C Bout is the "blood" creatinine concentration
exiting the dialyzer (and entering the CST). Since the CST
volume changes with time, the creatinine material balance
and the total mass balance (assuming constant density) were
combined to obtain Eq. (1). The total mass balance, assuming
constant density, is represented by:
dVCST Bout B in
S= QBout QBn (2)
dt
where QB."n is the volumetric inlet flow rate of blood through
the dialyzer. To solve Eqs. (1) and (2) to predict VCST and
Cs with time (as part of the project statement objective),
it is important to know how C B out and QB.out are related to










dialyzer inlet conditions. QB'" is constant and set by the
dialysis machine.
Material balances around the dialyzer identify the inter-
relationship between C Bt" and Q out, and demonstrate how
these parameters can be used in Eqs. (1) and (2) to predict
VCST and CST with time. Assuming countercurrent flow be-
tween the blood and dialysate, the material balances around
the dialyzer are:
QBn QBout = QDout QD,,n = a PAM (3)

dC' Kc
d = (CD CB) (4)
dA Q
dCD gAPP + K (
dA QD (C C (5)
Eq. (3) represents that total water loss from the blood side
into the dialysate side following a single pass, resulting from
the average transmembrane pressure difference (AP) between
the blood and dialysate. QB and QD are the blood-side and
dialysate-side volumetric flow rates. APis often constant and
can be approximated as AP = PB av_p avg where PB and PD are
the average pressures of blood and dialysate, respectively. The
convective transport coefficient for water across the dialyzer
membrane is represented by a, and AM is the total transport
area of the membrane. For the dialyzer
used in this study, AM= 1.5 m2 (CL T150L,
Terumo Medical Corporation, Tokyo, This wo
Japan). Eq. (4) is the material balance a dialysis
for creatinine in the blood side ( C) of
the dialyzer where Kc is the mass transfer demonstrates
coefficient of creatinine (units of length of model assi
per time) describing diffusive transport of
creatinine across the membrane relative detail the d
to convective flow. Eq. (5) is the material statement d
balance for creatinine in the dialysate side
(C') of the dialyzer. The differential student
membrane transport area with integration experiment
proceeding from the blood inlet to the
blood outlet is represented by dA.
The assumptions in the development of experime
Eqs. (3) to (5) include: 1) pseudo-steady and studt
state material balances, 2) plug flow, 3)
constant AP, and 4) the Staverman reflec- and as
tion coefficients (o) for all solutes have
a value of zero. Note that o has a value
ranging from 0, denoting solute flows unimpeded through the
membrane, to 1, in which solute is completely reflected by
the membrane and only diffusion occurs.[4] When o=0 for all
solutes, there is no osmotic driving force for water transport.
For this study, the small MW of creatinine (113 Da) relative
to the average pore size of the dialyzer (8,000-10,000 Da)
leads to oz0 for creatinine.[4] For analysis involving co-current
dialysate flow, the term QDout Q D"n in Eq. (3) is replaced with
QD in_ QDout, and the differential sign in Eq. (5) is negative.
68


The parameters a and Kc must be assessed to use the model.
To obtain a, the closed-loop experiment is performed in the
absence of solutes (or the presence of any solute as long as
o=0 for the solute) by measuring AP and the changing VCST.
Combining Eq. (3) with Eq. (2) suggests that a plot of VCST vs.
time yields a slope of -i, AP \ ,. Thus, the measurement of AP
with the known value of AM enables the calculation of a.
Kc can easily be obtained when aAP< aAPAM is very small compared to QB. n and QD.,n for Eq.
(3), such that QB.ou"' QB.n and QDout" QDn (i.e., QD and QB
are constant) according to Eq. (3). For these assumptions,
integration of Eqs. (4) and (5) results in CoB"= C s (1-E)
where E is


E 1- exp[-NT(1+ z)]
(1+ z)
E exp [NT(1- z)] -1
exp[N(1- z)] z


co-current flow

countercurrent flow


and NT and z are KcAM/QB," and QBn"/QDin, respectively.'[7 The
parameter Kc can be obtained from the open-ended experi-
ment with a known z by measuring CCsT (also equivalent to
CBIn) and CoB.ot, solving for E, solving for NT from either
Eq. (6) or (7), and then solving for Kc at
the given QB." and A The validity of the
resents assumptions can be assessed by comparing
aAP with K, and aAPAM with QB. and
del that QD,n The validity of assumptions should
assessment always be checked when applying models.
Thus, the dialysis project is an excellent
tool for allowing students to demonstrate
sis project the validation of assumptions.
ered to the Once values of a and Kc are known, VCST
m, the and C'w can be predicted with time for
fixed dialysate and blood inlet flow rates
protocol, (i.e., a given z value) by utilizing CB,' ut
model, CCST (-E) and QBout__ QB.n. AP\, in the
integration of Eqs. (1) and (2). Although
results, beyond the scope of this article, solving
feedback Eqs. (3) to (5) simultaneously [with Eq.
(3) in differential form] and then applying
ment. the solutions to Eqs. (1) and (2) allows a
more rigorous approach for predicting VCST
and CCs with time. The rigorous approach
eliminates the need for the assumptions that aAP is much
smaller than Kc, and QB and QD are constant as demonstrated
above. In many dialysis models, the assumption of negli-
gible aAP is always assumed.[47] The rigorous approach
is advantageous for students to use when the negligible
aAP assumption is not valid, providing an additional op-
portunity for students to compare the rigorous solution to
the simplified solution to understand the error associated
with assumptions.
Chemical Engineering Education


rk p
mo
the
imp
ialy,
eliv
tea,
ital
ysis
ntal
'ntJ
sess











3.98


3.96-


3.94
| ^ VCST=-0.001t +3.96
3.92


3.90

3.88


3.86
0 20 40 60 80 100
Minutes

Figure 3. Volume of the "blood" (VcST) as a function of time (t).
Creatinine was initially present at 4.1 mM with QB," = 500 ml/min.
The line represents the solution to Eqs. (2) and (7),
where the slope is used to evaluate K'.


In addition, the models can be further expanded to include mul-
tiple species and the utilization of species in which o # 0. Thus,
the dialysis project has great potential for many applications
involving model development, validation of assumptions, and
comparison with experimental results. Exposing students to
the various levels of model development helps them learn
how to simplify models using certain assumptions.
For example, blood contains proteins, salts, urea, and other
metabolites. The proteins are too large to transport through
the dialyzer (o = 1 and K for protein is negligible), such that
the proteins contribute to an osmotic pressure. If only proteins
(P) and creatinine (C) were present, Eqs. (3) to (5) would be
expanded to:


-dQB -dQD cxA RTCB
dA dA
dCpB CPB
dA QB
dCB Kc D
dA QB (Cc c)


dCD
dA


(8)

(9)


(10)

I1 ll


Kc +K' D
QD CDC


The RTC B term in Eq. (8) is the osmotic pressure contribu-
tion due to proteins. Eq. (9) is the protein material balance
on the blood side that demonstrates the protein concentration
can change as a result of water flow through the membrane
(note that protein is not in the dialysate, so a protein balance in
the dialysate is not needed). The solutions to these equations
Winter 2007


[combined with Eqs. (1) and (2)] can be solved to
provide VCST and CCsT predictions with time. The
value of RTCB is typically 28 mmHg, and dialysis
is often performed where AP is on the order of 200
mmHg.[4] Thus, K' is positive leading to a decreas-
ing QB along the length of the dialyzer. According
to Eqs. (8) and (9), the protein concentration will
increase due to the loss of water and the creatinine
concentration in the blood will decrease. The model
can be used to assess the degree to which increases
and decreases occur. Unlike the example given in
this article using creatinine alone where K' (or aAP)
was assumed negligible, K' is required to assess the
changes in protein concentration on the blood side
(as a result of water loss) according to Eq. (9). A
valuable exercise for students would be to derive
Eqs. (8) through (11) and show how the equations
can be solved with Eqs. (1) and (2) to predict time
profiles of VCST and C .sT

EXPERIMENTAL RESULTS
Figure 3 shows a plot of VCST VS. time for a closed-
loop experiment in which creatinine was initially


present at 4.1 mM and QB,' = 500 ml/min. With a negative
slope of one ml/min (i.e., 1 ml/min of water transports from
the blood to the dialysate) and A, = 1.5 m2 (CL T150L,
Terumo Medical Corporation, Tokyo, Japan), aAP is 6.7 X
105 cm/min (aAPAM = 1 ml/min). According to Eq. (3), QB.out
/ QB." = 0.998. Thus, QB is essentially constant such that the
assumption of aAPA << QB.'" is valid. Since QD was greater
than QB, the assumption of aAPA << QD,1 is also valid for
this particular experiment. Although AP was not measured
at QB." = 500 ml/min, AP z 26 mmHg was observed at QB. n
= 300 ml/min, leading to an approximation of a = 2.6 x 106
cm min' mmHg 1.
When evaluating Kc, the open-loop experiment was per-
formed at QB.n = 300 ml/min and QDn = 817 ml/min with
CS = 3.22 mM. The analytical measurements for this work
were sensitive enough to distinguish differences between
Cs and C" The measured value of C" was 2.03 +
0.03 mM, leading to C .." = 0.63 CcST and E = 0.37. For
countercurrent flow with z = 0.37, Eq. (7) yielded a value
of 0.5 for NT. Thus, Kc is 0.01 cm/min, which validates the
assumption that aAP << K,. This value of Kc is similar to
values observed for other hemodialyzers. 71
Once model parameters were obtained and the assump-
tions were validated, Eqs. (1) and (2) (with CB .." =(CST
(1-E) and QB.out = sQB .,. AP \ ,) were solved simultaneously
using Polymath[81 to predict VCST and CcST with time. The
predictions were compared to experimental results from a
closed-loop experiment in which 2.54 mM of creatinine was
initially present in 4 liters with QB.n' = 300 ml/min and QD n'
= 865 ml/min (z=0.347). From Eq. (7) u illi \ =1.5 m2 and
69











A benefit of incorporating the dialysis project is that the student can integrate a number of concepts
such as material balances/modeling (i.e., blood and dialysate balances with assumptions),
transport issues (i.e., evaluation of transport coefficients), model validation of assumptions,
and solving differential equations (i.e., using Polymath) toward a bioengineering project that allows
the student to expand the scope of his/her chemical engineering education.


Kc = 0.01 cm/min (NT=0.5), E=0.37. Figure 4 shows that
the model results for CoCST, with aAP ranging from 0 (con-
stant flow assumption) to 20 X 105 cm/min (representing a
3-fold increase in aAP from the experimental aAP value),
are the same. Increased water transport can occur via either
increasing AP or adding a constituent that contributes to the
osmotic pressure (where o # 0). The model predictions are
in general agreement with the experimental results although
there is a small discrepancy. The time to remove 90% of the
creatinine is 80 minutes. In all cases, varying aAP did not
affect the C ST profile (as expected with aAP << K,). After
100 minutes, however, the predicted VCST was 4000 ml, 3900
ml, and 3700 ml for aAP=0, aAP=6.7 X 105 cm/min, and
aAP=20 X 105 cm/min, respectively. As is evident, aAP is
critical for predicting water loss but does not affect predic-
tions. Figure 4 also shows predictions for aAP=0 with QB.
= 500 ml/min (E=0.24). As seen, the CcST profile does not
drastically change and the time to remove 90% of the creati-
nine only decreases to 76 minutes.

STUDENT FEEDBACK AND ASSESSMENT
Some of the comments from students included "this experi-
ment trained us with [nontraditional] equipment" and "I liked
seeing how close a model would actually fit experimental
data." There were several indirect assessments. Students
liked this project and explored more than they were asked
to do in the project statement. For example, they explained
the difference in various types of dialysis processes, pro-
vided statistics about each type, examined the relevance of
creatinine in clinical settings, explored the importance of
osmolarity, and developed an understanding for the need
of electrolytes in the dialysate. Whlil pi i. iing their find-
ings, they named their patient, talked about poor "Charlie"
needing to sit for two hours while the dialysis was taking
place, and worried about how creatinine generated in the
body during dialysis would affect the creatinine removal
process. To account for creatinine generation during dialy-
sis, a constant generation of creatinine could be introduced
into the experiment. It was also observed that as students
were told that they could present their results at the regional
and national American Institute of Chemical Engineers
(AIChE) student conferences, students were more willing
to spend extra time on the project. One student presented
his team's results at the 2004 Mid-America Regional
70


AIChE Conference and won second place.
One difficulty observed during the implementation of the
dialysis project was that students tended to focus on the
analysis (i.e., measurements), and focused less on the mod-
eling aspects. For instance, students spent ample time on
the creatinine analysis. One problem that was encountered,
however, was that students were not used to using micropi-
pettes and error in the calibration curve could be dominant
if proper volumes were not dispensed every time. Thus, it is
important to train students in using equipment that is not often
associated with traditional unit operations experiments. With
regards to modeling, the students did not always explore the
resources for model development. It would be beneficial for
the instructor to direct students toward resources containing
information about model development. The main point is
that students involved in nontraditional experiments should
have some training or guidance (such as identification of key
resources) to help them achieve their objectives.

CONCLUSIONS
Through the incorporation of creatinine dialysis, under-
graduates can integrate a number of concepts such as material
balances/modeling (i.e., blood and dialysate balances with


0.5


Experimental
- E=0.37, K'=0 to 20 x 10-5 cm/min
- E=0.24, K'=0 cm/min


90% removal
----.----. 90 rem ovY al ----- ---- -


0 20 40 60 80 100
Minutes

Figure 4. Creatinine concentration (initially 2.54 mM) in the
continuously stirred tank (CST originally at 4000 ml) as a
function of time for QB,'" = 300 ml/min and QDin = 865 ml/min.
The model is the solution to Eqs. (2) and (3) with CCB,-" = Ccsr
(1-E) and QB,ot = QBin- K'A, A is 1.5 m2.
Chemical Engineering Education












assumptions), transport issues (i.e., evaluation of Kc), model
validation (i.e., validating assumptions), and solving differen-
tial equations (i.e., using Polymath) towards a bioengineering
project that allows the student to expand the scope of his/her
chemical engineering education. The students enjoyed the
exposure to "nontraditional" experiments and this project
provided them an opportunity to connect bioengineering ex-
periments to material learned in the classroom. Deriving the
differential equations from the continuity equation requires the
student to draw on his/her math and engineering knowledge. It
is important for students to assess the validity of assumptions
when applying experimental results to model equations, and
this project allowed for such opportunities.

ACKNOWLEDGMENTS
The authors would like to thank the following students
in the School of Chemical Engineering at Oklahoma State
University who conducted the experiments: Paul Engel,
Kimberly Garrison, Kimberly Northy, and Jason Powell. In


addition, we thank the Stillwater Dialysis Center for helping
secure the dialysis machines and cartridges.

REFERENCES
1. (2004)
2. (2004)
3. Cavanagh, D.P, and L.H. Herbertson, "Effective Laboratory Exercises
for an Introduction to Biomedical Engineering Course," Proceedings
of the ASEE Annual Conference and Exposition, Salt Lake City, UT.
(2003)
4. Foumier, R.L., Basic Transport Phenomena in Biomedical Engineering,
Taylor and Francis, Philadelphia (1999)
5. Narayanan, S., and H.D. Appleton, "Creatinine: A Review, Clin. Chem.
26, 1119, (1980)
6. Bell, T., Z. Hou, Y. Luo, M. Drew, E. Chapoteau, B. Czech, A. Kumar,
"Detection of Creatinine by a Designed Receptor, "Science, 269(5224),
671, (1995)
7. Cooney, D.O., Biomedical Engineering Principles, Marcel Dekker,
New York (1976)
8. Cutlip, M.B., and M. Shacham, Problem Solving in Chemical Engineer-
ing with Numerical Methods, Prentice Hall PTR, Upper Saddle River,
NJ (1999) 1


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Winter 2007 1 Chemical Engineering Education Volume 41 Number 1 Winter 2007 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. Co r respondence regarding editorial matter, circulation, and changes of address should be sent to CEE, Chemical Engineering Department, University of Florida, Gainesville, FL 32611-6005. Copyright 2005 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 120 days of pu b lication. Write for information on subscription costs and for back copy costs and availability. POSTMA S TER: Send address changes to Chemical Engineering Education, Chemical Engineering Department., University of Florida, PUBLICATIONS BOARD EDITORIAL AND BUSINESS ADDRESS: Chemical Engineering Education Department of Chemical Engineering University of Florida Gainesville, FL 32611 PHONE and FAX : 352-392-0861 EDITOR Tim Anderson ASSOCIATE EDITOR Phillip C. Wankat MANAGING EDITOR Lynn Heasley PROBLEM EDITOR James O. Wilkes, U. Michigan LEARNING IN INDUSTRY EDITOR William J. Koros, Georgia Institute of Technology EDITORIAL ASSISTANT Nicholas Rosinia CHAIRMAN John P. OConnell University of Virginia PAST CHAIRMAN E. Dendy Sloan, Jr. Colorado School of Mines MEMBERS Kristi Anseth University of Colorado Thomas F. Edgar University of Texas at Austin Richard M. Felder North Carolina State University H. Scott Fogler University of Michigan Carol K. Hall North Carolina State University Steve LeBlanc University of Toledo Ronald W. Rousseau Georgia Institute of Technology C. Stewart Slater Rowan University Donald R. Woods McMaster University DEPARTMENT 2 Chemical Engineering at Polytechnic University Edward N. Ziegler, Jovan Mijovic EDUCATOR 10 Joseph Reynolds of Manhattan College Helen C. Hollein RANDOM THOUGHTS 51 Turning New Faculty Members Into Quick Starters Rebecca Brent, Richard M. Felder CLASSROOM 14 The Chemical Engineering Behind How Pop Goes Flat: A Hands-On Experiment for Freshmen Keith L. Hohn 31 A Realistic Experimental Design and Statistical Analysis Project Kenneth R. Muske, John A. Myers 39 Forced Convection Heat Transfer in Circular Pipes Ismail Tosun 53 Incorporating Six Sigma Methodology Training into Chemical Engi neering Education Lenore L. Dai CURRICULUM 43 Future of Chemical Engineering: Integrating Biology Into the Under graduate ChE Curriculum Patricia Mosto, Mariano Savelski, Stephanie H. Farrell, Gregory B. Hecht LABORATOR Y 19 The Devils in the Delta William L. Luyben 24 An Internet-Based Distributed Laboratory for Interactive ChE Education Jing Guo, David J. Kettler, Muthanna Al-Dahhan 65 Implementation and Analysis of Hemodialysis in the Unit Operations Laboratory Sundararajan V. Madihally, Randy S. Lewis CLASS AND HOME PROBLEMS 59 Introducing Non-Newtonian Fluid Mechanics Computations With Mathematica in the Undergraduate Curriculum Housam Binous 57 Book Review

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Chemical Engineering Education 2 T he Brooklyn Colle giate and Polytechnic Institute was chartered in 1854, when the city of Brooklyns rapidly growing population was 30,000 and Brooklyn was separate from New York City. This was roughly 30 years before the completion of the Brooklyn Bridge and prior to the Civil War. The stated purpose of the establish an educational insti tution in our midst, . to give our sons an education as would qualify them in a far higher degree, through an enlarged, liberal, and thorough training in a course of practical, scien enter upon the active pursuits and duties of life, and that its location should be as central, and as easily accessible as pos sible by public conveyance, from all parts of the city . . In its earliest years, the college drew students from the man sions and substantial homes of the Heights, the Hill, the Eastern District, and other parts of Brooklyn. ing to the Bachelor of Science degree was established for those bent in the direction of science and engineering, which in addition to theory included more than 200 laborato into three areas of specialization: Engineering (Mechanical and Civil), Electrical Engineering, and Chemistry. The latter had offerings in applied and fundamental areas Chemical Engineering at Polytechnic UniversityEDWARD N. ZIEGLER AND JOVAN MIJOVIC A preserved picture of life at Polytechnics main campus at the beginning of last century. Copyright ChE Division of ASEE 2007 ChE

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Winter 2007 3 In 1898, Brooklyn became a part of New York City. Like Brooklyn, Polytechnics services and the Borough, through the universitys worldwide contributions to science, engineering, and educa tion. Polytechnics modern Brooklyn site is still only two blocks from the Brooklyn Bridge, and all three of the citys major subway systems have stations within a few blocks of the Polytechnic, maintaining the spirit of its original charter. Chemical engineering at Polytechnic University had its formal beginnings more than a century ago when the Department of Chemistry became the Department of Chemistry and Chemical Engineer ing at the Polytechnic Institute of Brooklyn, or PIB. I.W. Fay department in 1905, with only one chemical engi neer on the staff John C. Olsen In those days, extensive use was made of eminent professionals in local industries as consulting professors. In 1925, the chemical engineering program at Polytechnic accreditation by a national professional society, when the American Institute of Chemical Engineers (AIChE) listed it ing. In 1931, a separate Department of Chemical Engineering Olsen was elected president of the AIChE, which he helped years). Since then, more than 2,800 bachelors, 1,000 masters, and 350 doctoral degrees have been awarded in chemical engineering at Poly. THE OTHMER YEARS In 1932, then-28-year-old chemical engineer Donald F. Othmer was hired into Olsens department, after an impressive in creating cellulose acetate is concentrating the acetic acid in various sources available to the company. Initially knowing little about the subject, but always curious, Othmer designed an experimental device to observe how acetic acid is distilled. The apparatus he built became famous as the Othmer Still and continues to be used to study the properties of mixtures being distilled. The early version of the still was typical of Othmers hands-on, low-cost approach to science: He not only conceptualized and designed the apparatus, but also learned glass-blowing so that he could build it himself. The Othmer Still allowed chemists and engineers to mea and liquid phases in equilibrium. Othmer also contributed greatly to the science of azeotropic distillation, which introduces a third chemical during the distillation process to improve the purity of the product and reduce energy consumption. Thanks to Othmer, distillation is now a science. His geometrical and mathematical instincts temperature on vapor pressure of various compounds could be correlated as straight lines on a single sheet of paper, the now-famous Othmer plot. As a well-known chemical engineer, Othmer succeeded to the chairmanship in 1937 and remained head of the depart ment until 1961, when he stepped down to devote more time to teaching and research. He has authored hundreds of articles and held numerous patents for chemical engineering applica tions. Around 1945 Raymond E. Kirk head of the Depart ment of Chemistry, and Othmer, heading the Department of Chemical Engineering, decided to embark on a project as co-editors of an encyclopedia that would be a comprehensive guide to industrial chemistry and chemical engineering. The Kirk-Othmer Encyclopedia of Chemical Technology is now in chemists and chemical engineers turn when they are starting a new project. It has everything from the commonplace to the esoteric, from how to make batteries and beer to how to reduce nitrobenzene. A set may be found in the library of virtually every major university in the world. When Othmer died in 1995 he bequeathed more than $175 million dollars to the Polytechnic, which remains as of today the largest donation ever given to the university. Much of the gift went to improving and expanding the university labora The Chemical Engineering Laboratory about 1919.

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Chemical Engineering Education 4 tory and classroom facilities, with some to construction of a new dorm and gymnasium. An interesting side note: If the remaining professors had joined Othmer 30 years earlier in the investment club he started at Polybased on the advice of a family friend named Warren Buffetthey all wouldve been rich; but even sharing a fraction of the membership member in those days. Don Othmer supervised and inspired more than 60 doc toral students, many of whom went on to distinguished careers in their own rights. He supervised research in the optimization. Having no biological children, he was quoted as saying he regarded himself most fortunate to have been blessed with so many brilliant academic children whom he could recognize with almost-paternal pride. One of Othmers former students was Ju Chin Chu, who from 1950 to 1966 supervised fundamental distillation experiments on more than 100 industrially important chemical mixtures. Chu, in turn, must have passed along a high regard for research and genes as well: His son, Steven Chu won the Nobel Prize in Physics in 1997. Speaking of Nobel Prize winners, a corecipient of the 1995 Nobel Prize in Physics, Martin L. Perl earned his chemical engineering bachelors at Poly in 1948 (followed by a Ph.D. from Columbia). Perl was honored for the discovery of the tau lepton, one of natures most remarkable subatomic particles with a mass 3,500 times that of the electron. In 1982, Perls promise had already been recognized closer to home: That year, he was awarded the Wolf Prize for Physics for the Class of 1948. In the 50s Othmer was able, through fund raising and departmental equipment gifts from industrial colleagues, to persuade Warren L. McCabe to come to Poly and become administrative dean. A leading educator and consultant for merly at Cornell University, McCabe is, of course, famous for the McCabe-Thiele diagrams of binary distillation, as well as being coauthor of McCabe, Smith, and Harriotts Unit Operations of Chemical Engineering Othmer already had a master craftsman of laboratory equipment on staff, W. Fred Schurig (Poly 5, and in AmericaPolys Unit Ops Laboratory. While at Poly and after he retired, Schurig designed and built laboratories for many schools throughout the Americas. Schurig became known for his discipline and attention to detail, which he later Perhaps the most famous of Othmers doctoral students, Joseph J. Jacobs also earned all three of his degrees at the Polytechnic, receiving his Ph.D. in 1942. Jacobs developed a system that could manufacture soap in 15 minutes compared to the traditional process that required between three and seven days. Jacobs was an assistant professor at Polytechnic for a while and then headed west to San Francisco to take a position assisting in the engineering of liquid fertilizers. num and Chemical Companyat which he helped develop caustic sodaJacobs started his own business. In 1947, he founded Jacobs Engineering Group Inc., an international Fortune magazine ranked No. 1 in 1999 as the most admired engineering and construction company. In ad dition to authoring numerous articles on chemical engineer ing and economics, Jacobs made substantial contributions to the study of social issuesincluding aging parents of adult childrenand authored two autobiographies. He was recipient of the United Engineering Societys 1983 Herbert Hoover Medal, which recognizes the civic and humanitar ian achievements of professional engineers. The university also established the Joseph J. and Violet J. Jacobs Chair in Chemical Engineering, and in 2002 opened the Joseph J. and Violet J. Jacobs Building on campus, housing a full gymna sium and athletic center as well as state-of-the-art laboratories and classrooms. Another well-known doctoral student of Othmer, Ger hard Frohlich earned his Ph.D. in chemical engineering at Poly in 1957. He was the second member associated with the Polytechnic to become president of AIChE, elected in 1999. Earlier he had been named corporate vice president and general manager of Central Engineering at Hoffman-La Roche, where for many years he engaged in the development, design, and construction of chemical and pharmaceutical facilities. In commenting on the importance of AIChE, Frohlich said, We must think globally, accept cradle-tograve stewardship of products, and strive for sustainable development. Professional societies can lead the way by facilitating dialogue among industry, government, academe, ible ways, using renewable resources, and learning from advances in chemistry and biotechnology, we can make products that enhance the quality of life and protect the environment. If we commit to doing so, the new millennium looks bright indeed. Yet another of Othmers students, Robert F. Benenati had a long and successful career as a professor who challenged stu dents to do more than they ever thought possible, particularly in his design class. Warren Seider a Poly graduate now at the University of Pennsylvania, is in turn one of Benenatis former students, and is coauthor of the major design text Product and Process Design Principles, now in its 2nd edition. In the s and s James J. Conti (Polytechnic , and 59) and Irving F. Miller were department heads through of engineering to form the Polytechnic Institute of New York, with its main campus remaining at the Brooklyn site. In 1985, the school was renamed Polytechnic University.

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Winter 2007 5 Below, Don Othmer poses with a gold-plated version of the invention he created in 1928, the Othmer Still. Left, Othmer is seen with Raymond Kirk, head of Polys chemistry department circa 1945 and co-editor of the pairs comprehensive encyclopedia, now in its 5th edition. Rounding out the era, Leonard Stiel has carried the Othmer tradition into the computer age; his work is cited widely in the literature of thermodynamic and transport properties of but now as a research professor hes still very active at Poly in education and as a consultant. THE POLYMER CONNECTION In the early part of the 20th century, many prominent chem ists dismissed the idea that molecules with molecular weights in the thousands or millions could exist. Today, polymers are everywhere, in everyday materials such as plastics, nylon, and rubber. The year 1939 marked the introduction of a polymers course in the chemical engineering department. That year, chemical engineering professor Paul F. Bruins joined Poly course in polymer technology in the United States, paving the way for what has become one of the most famous polymer programs in the world. Bruins was affectionately called the walking encyclopedia of plastics, and he wrote and edited extensively. He was known to take his colleagues for a spin in his small aircraft during the day and return in time to teach his polymer course in the evening. Much of todays widespread acceptance of polymers, their chemistry, and their engineering is the result of work by the Polymer Research Institute (PRI) of Polytechnic University. Herman Mark a pioneer in the study of giant molecules, established the PRI in 1964. The institute brought together a academic facility in the United States devoted to the study and teaching of polymer science. Many scientists associated with the institute later went on to establish polymer programs at other development and growth of what has become a vital branch of chemistry, engineering, and materials science. Under Marks leadership, the institute became the premier U.S. destination for polymer chemistry, attracting students from all over the world. But its effect wasnt limited to simply establishing the importance of polymer chemistry and contributing many of its fundamental discoverieslike colonists, PRI alumni went on to found a number of polymer institutions at other locations. The American Chemical Society (ACS) recognized the institutes pioneering efforts by designating it a National Historic Chemical Landmark. Such designations recognize important places, discoveries, and achievements in the his tory of chemistry. Other landmarks have included Joseph Priestleys Pennsylvania home, penicillin, and the National Institute of Standards and Technology. PRI holds a special place in ACS Past President Eli M. Pearce s heart, as from 1982 to 1996 he served as its director. Pearce started at Poly technic in 1973, had a joint appointment in the Departments of Chemistry and Chemical Engineering, and is currently a future: When you read the [National Research Council report Beyond the Molecular Frontier], its clear that the most ex citing developments in science and technology are occurring at the interfaces. Over the years, considerable contributions were made to the engineering side of polymerization research and education.

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Chemical Engineering Education 6 Two other Poly engineering faculty who have made longChang Dae Paul Han a former department head (1974-82), and Jovan Mijovic present department head. Han published widely in polymer and chemical engineering journals, and wrote two books: Rheology in Polymer Processing and Multiphase Flow in Polymer Processing, both published by Academic Press. Mijovic in the course of his illustrious career has published widely in polymer journals and supervised doz ens of doctoral students in the study of polymeric materials properties and states, and more recently has been investigating complex chemical and biosystem dynamics, nanotechnol ogy, and nano-materials. He has led the department into the chemical and biological engineering era while continuing his yeomanlike efforts as a dedicated, distinguished teacher and researcher. Hes committed to maintaining Polys tradition of excellence. THE ENVIRONMENTAL SCIENCE AND ENGINEERING CONNECTION The Polytechnic has performed many research investiga power generation, and in the chemical industry. Frederick Zenz received his Ph.D. at Poly in 1961 and taught a graduate course throughout the 60s entitled Fluidization, eventually writing and publishing the seminal work Fluidization and Fluid Particle Systems with Othmer. In the early portion of his career, Polys Edward Ziegler bed transport and reaction engineering modeling. His heat transfer model is combustors. Ziegler, along with former Poly professor Rutton Patel (now with ExxonMobil) supervised students in often became members of each others guidance committees. Later Zieglers interests turned toward cally air pollution engineering control. He has co-edited the 5th Edition of the ronmental Science and Engineering published in January 2006, and authored a number of its articles. He started on the with his co-editor a former member of Polys Department of Civil Engineering. Over his career Ziegler has taught more than 1,000 students in the undergraduate lab, and more than 800 graduate students, mainly in his Chemical Re actor Design and Air Pollution Engineering Control courses. Hes been the thesis and project adviser to numerous masters and doctoral students as well as advising undergrads. Starting in 1986 Allan Myerson headed the department and eventually became dean of the School of Chemical and Materials Science. Myerson encouraged interdisciplinary studies between the engineering and science departments. He also was active in crystallization and nucleation research and edited the Handbook of Industrial Crystallization A WORLD CLASS UNIT OPERATIONS LABORATORY, REVISITED A major renovation of the chemical engineering lab took place in 2001, when Walter P. Zurawsky s considerable transport phenomena knowledge, research experience at AT&T Labs, and equipment construction skills were put into play. Professor Ziegler had been teaching the lab for many years after his mentor Fred Schurig retired. With the help of the Othmer gift to the school, Zurawsky and Ziegler planned a student-friendly, state-of-the-art experimental teaching facil ity with new distillation columns, process control equipment, a Acclaimed alumnus Dr. Joseph Jacobs with a blueprint for one of the many important projects in which he was a partici pant. In addition to establishing a Joseph J. and Violet J. Jacobs Chair in Chemical Engineering, in 2002 the university opened the Joseph J. and Violet J. Jacobs Building on campus. It houses a full gymnasium and ath letic center as well as state-of-the-art laboratories and classrooms.

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Winter 2007 7 controlled fermenter, and membrane separations experiments. The new, highly automated distillation experiment is, by the ing acetic acid (shades of Donald Othmer?) using sieve trays and packed columns. The senior CBE students perform 20 down versions of traditional chemical engineering operations were retained and are still used to study classical theories and industrial correlations, but with modern instrumentation. A View, Microsoft, and MatLab software to help store, transmit, and analyze the data. The ASPEN Engineering Suite is avail able to all CBE students on their local network, primarily for use in the senior design courses. NEW PATH: CBEPRESENT AND FUTURE Over the past 40 years, chemical engineering curricula have embraced an engineering science paradigm that spans from molecular-level interactions and transformations to large-scale systems. Indeed, it is an appreciation of, and a willingness to work over, many decades of scale that is one of the distin guishing traits of the chemical engineering discipline. This ability to adapt to work on many scales has allowed chemical engineers to have productive interactions with a wide range of other science and engineering disciplines, and will be essential for the application of engineering principles to biologically based processes. The rising need to convert advances in biol ogy into new processes and new industries makes it imperative that we adopt biology as an enabling science. Interest in integrating biology and chemical engineering, or CBE, is growing nationwide. For example, the number of biologically oriented presentations at the AIChE annual meetings increased from less than 10% to close to 50% in only four years. Many chemical engineering departments interest in, and overlap with, biology (examples include Johns Hopkins, Cornell, the University of Pennsylvania, the Univer sity of Wisconsin-Madison, Northwestern, and RPI). Many such departments have started to require a biology course as part of their curriculum, but there are still very few that have made a full commitment to developing a curriculum in which biological systems and processes are fully integrated across the curriculum, as we are doing. Several years ago the engineering faculty within our de partment reviewed and revised the chemical engineering educational program (B.Sc.) in chemical and biological engi neering that builds on the traditional strengths and paradigms of chemical engineering while embracing biology as a pillar along with mathematics, chemistry, and physics. So substan tive are the changes that we, too, undertook a program name change from chemical engineering to chemical and biological engineering. The CBE program was initiated with the fresh man class of 2003. and must be applied to biological systems and to the develop ment of new processes based on biology. The task we face in implementing this new curriculum is substantial, but we proposed program. The courses for our new CBE program are shown in Table 1 (next page). The program has been approved by the faculty of our department, by the faculty of Polytechnic University, and by the State of New York. By careful choice of electives and several course substitutions, CBE students can adjust their schedules to satisfy medical school requirements if they have an interest in pursuing medicine as a career. The task we face is to meld, as seamlessly as possible, sys tems and processes of biological relevance into our engineer ing curriculum. We regard the systems-oriented, multiscale approach to problems that is the hallmark of chemical engi neering as the primary strength we have to offer. We believe it is essential that our students remain strong in engineering. It is our further belief that by exposing our students to biology and bio-processes in addition to more conventional chemical processes, we will produce better, more versatile engineers. As part of our new curriculum, we have introduced re quired courses in biology and biochemistry and are revising virtually all of our engineering courses to include biological applications and examples. Technical electives in the junior and senior year provide opportunities for elective courses, particularly new electives focusing on engineering in biology such as System Biology, Protein Engineering, and Drug De livery. Although these new elective courses will be primarily aimed at CBE students, they will be open to other engineering and science students. We are the only chemical and biological engineering pro gram in New York City and we have seen phenomenal growth in our undergraduate enrollment over the past two years: from 41 undergraduates in 2004 to 110 in early 2006a whopping 150% increase. The CBE program is acknowledged as the most demanding major on campus. A GPA of 2.5 is required to remain in the major (2.0 elsewhere) and the students response has been hugely enthusiastic. We have had the high est percentage of students on the Deans List and named as valedictorians in recent years. UNIQUE ATTRIBUTES OF THE POLYTECHNIC Polytechnic provides an important educational opportunity for students who tend to be under represented in engineering. Given our downtown Brooklyn location, our student popula tion has always included a large cross section of the population of Brooklyn and the other boroughs of New York City. As different ethnic groups have immigrated to the United States,

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Chemical Engineering Education 8 Polys student popu lation has changed, always mirroring the ethnic mix of the city. In addition to the ethnic diversity that is part of Polytechnic, we are proud to note that over the past de cade nearly 50% of the students who have graduated from our chemical engineering program are female. We fully expect that this trend will continue with our new program in chemical and biological engineering. Although there have been advances nationwide, women are still grossly under represented in engineering. Polytechnic is a private university, but our role in the New York region is, de facto, one that would be expected of a public university. As shown in Table 2, we educate a much greater percentage of students from lower-income households than the state university system does. Washington Monthly ranked Polytechnic University second in the nation (out of 245 national universities) in social mobility. Our location in New York provides us with exceptional opportunities. We are in a region with many excellent biomedical institutions in cluding Rockefeller Univer ing Cancer Institute, SUNY Downstate Medical Center, and Albert Einstein College of Medicine, to mention a few. Adding to the list, a new $700 million science park on the grounds of Bellevue (just across the East River in Manhattan) was announced on the front page of The New York Times a few weeks ago. The focus of this new East River Science Park will be the biotechnology industry. The facility is being developed by Alexandria Real Estate Equities, Inc.whose chairman of the board, Dr. Jerry Sudarsky is a Polytechnic alumnus and a member of the Board of Trustees of Polytechnic. These excellent medi cal institutions and the new science park will provide our graduates with avenues for continued education, opportuni ties for collaboration, and potential employment. TABLE 1 Chemical and Biological Engineering Curriculum Freshman Fall Freshman Spring MA1014 Calculus I MA1114 Calculus II CM1004 Gen. Chemistry for Engineers Intro to Cell & Molecular Biology EN1014 Writing & Humanities I CBE1214 Intro to Chem & Bio Engineering EG1004 Intro Engineering & Design EN1204 Writing & Humanities II Sophomore Fall Sophomore Spring MA2012 Linear Algebra I MA2112 Multi-variable Calculus A MA2132 Ordinary Differential Equations MA2122 Multi-variable Calculus B PH1004 Introductory Physics I PH2004 Introductory Physics II CBE2124 Analysis of Chem & Bio Processes CS1114 Intro to Prog. & Problem Solving CM2234 Industrial Organic Chemistry CM2514 Chemical & Biological Equilibria Junior Fall Junior Spring CM3314 Biochemistry I CBE3324 Chem & Bio Separations CBE3103 Math Methods for Chem & Bio Eng. CBE3214 Chem & Bio Reactor Engineering CBE3314 Physical Rate Processes Technical Elective HI2104 Modern World History HU/SS Elective CBE3622 Chem & Bio Eng. Thermodynamics Senior Fall Senior Spring CBE4113 Engineering Laboratory I CBE4123 Engineering Laboratory II CBE4413 Process Dynamics & Control CBE4623 Chem & Bio Process Design II CBE4613 Chem & Bio Process Design I CBE4713 Engineering Polymeric Materials HU/SS Elective Engineering Elective Technical Elective HU/SS Elective TABLE 2 Student Family Incomes: Polytechnic and the State University of New York Annual Income < $20k $20k to $80k > $80k Polytechnic 28.4% 51.6% 20% SUNY 13.0% 31.0% 56%

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Winter 2007 9 CURRENT FACULTY The explosive potential of CBE has been recognized by the Poly technic trustees, our new president, Jerry MacArthur Hultin and the members of the administration. These pivotal individuals have made a major commit ment to our departments continuing growth. Three years ago, Jose M. Pinto joined our faculty from the University of Sao Paulo in Brazil. Pinto received his Ph.D. from CarnegieMellon and is interested in modeling and optimization of chemical and biological processes and systems biology. In fall 2004, Stavroula Sofou joined the faculty. Sofou received her Ph.D. from Co lumbia University in New York City and spent three years as a post-doc at Research Center. Her principal interest focuses on the use of engineering principles for drug delivery for cancer cure. We announced two additional faculty positions in fall 2006. Rasti Levicky formerly of Co lumbia University, was named the Donald F. Othmer Assistant Professor of Chemical and Biological Engineering. Levicky received his Ph.D. from the University of Minnesota and systems, nanosized micro array biosen is the Joseph J. and Violet J. Jacobs Assis tant Professor of Chemical and Biological Engineering. He got his Ph.D. from the University of Wisconsin at Madison. His interest is in the area of protein en gineering and particularly those that aggregate and cause Parkinsons and Alzheimers diseases. Finally, we are very proud to an nounce that on Jan. 1, 2006, our The Othmer-Jacobs Department of Chemical and Biological Engineering, in recognition of enormous contribu tions to our discipline made by these two chemical engineering giants. Visit our Web site: .ACKNOWLEDGMENTS For practical reasons, this article mentions only a few of the people that are part of the history of chemical engineering at the Polytechnic. We would like to acknowledge those dedicated present and former professors, students and alumni, and their supporters, without whom Polytech would never have attained its success ful international reputation. We thank our colleagues in the department for their help writing this article, and greatly appreciate the efforts of Christopher Hayes Modern buildings on campus include Dibner Library on Metrotech Commons, far left, and the Othmer Dormitory, left. Edward Ziegler Jovan Mijovic Jose Pinto Stavroula Sofou Rasti Levicky Leonard Stiel Walter Zurawsky Jin Ryoun Kim

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Chemical Engineering Education 10 J oseph Reynolds earned a bachelors degree in chemis try from Catholic University of America in 1957 and a Ph.D. degree in chemical engineering from Rensselaer Polytechnic Institute in 1964. He taught high school chemistry and physics full time at LaSalle Academy in New York City from 1957 to 1959, then taught college chemistry part time for Catholic University (Troy extension) while pursuing his doctoral degree at RPI. Joe excelled as a student and was Joseph Reynolds of Manhattan College ChE HELEN C. HOLLEINManhattan College Riverdale, NY 10471 Copyright ChE Division of ASEE 2007

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Winter 2007 11 Phi Lambda Upsilon honor societies. His many accolades in clude listings in American Men and Women in Science, Whos Who in Technology Today, Whos Who Among Americas Teachers, International Whos Who in Engineering, Whos Who in the East, and Whos Who in Engineering. Since 1964, Joe has been a member of the chemical en gineering faculty at Manhattan College, where he holds the rank of professor of chemical engineering. It caused some excitement among Joes colleagues when Br. Thomas Scanlan was appointed president of Manhattan College, because Br. Thomas had been one of Joes students in a freshman chemis try course that he taught in Troy. (Fortunately, we understand that Br. Thomas earned an A in the course.) Joe served as chairperson of the Department of Chemical Engineering for seven years (1976 to 1983), and also was called upon to serve as acting chair for brief stints totaling another two and a half years while his successors were on sabbatical leave. As part of his academic duties, Joe has served for many years as moderator of the student chapter of the American Institute of Chemical Engineers (AIChE), has also served on a large number of college committees, but says his favorite is the Board of Trustees Facilities Planning Committee because this membership ensures his invitation to the Presidents Christmas Dinner (best wine selection and food service, by far). Since completing his doctoral research at RPI on The Effect of High Pressure on the Infrared Spectra of Solids, Joe has collaborated for more than 30 years with Dr. Louis Theodore at Manhattan College on various environmental research proj ects. Many of Joes books and research publications include undergraduate students as coauthors. His current research interests are in the air pollution control and hazardous waste incineration areas. He has coauthored numerous text/reference books, including Introduction to Hazardous Waste Incineration 2nd Edition (2000), Accident and Emergency Management (1989), and Handbook of Chemical and Environmental Engi neering Calculations (2002), all from Wiley-Interscience, New York. He has developed computer software, which is available commercially and currently used in the EPAs training program, to simulate hazardous waste incinerator (HWI) performance. His publications include problem and solution workbooks that he uses in the courses that he teaches at the college, as well as EPA training manuals for the HWI software. Joe has also served as a consultant for several private companies and is presently a consultant/expert witness for the Department of Justice and the U.S. Environmental Protection Agency. He has been active for most of his career in the Air and Waste Management Association (AWMA), formerly the Air Pollu tion Control Association (APCA), where he presents papers and chairs sessions at annual meetings as well as coordinating associated continuing-education programs.TEACHING TAKES PRECEDENCE Manhattan College offers both B.S. and M.S. degrees in chemical engineering, and Joe has always taught the under graduate courses by choice. He has taught the Engineering Materials course and directed its associated laboratory for his entire career at the college, and currently teaches Process Calculations, Engineering Thermodynamics, Fluid Mechan ics, and Computer Aided Simulation and Design in Chemical Engineering. During his tenure, he has taught nearly every course that the department offers (or previously offered) including Chemical Engineering Thermodynamics, Heat Joe, at right, posing with Lou Theodore, his long time friend, collaborator, and fellow faculty member.

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Chemical Engineering Education 12 Transfer, Chemical Engineering Laboratory I-II, Physical Metal lurgy, Physical Chemistry I-II, Computer Methods in Chemical Engineering, Computer Science and Programming, and Fortran Programming for Chemists. In the classroom, Joe is very much an in your face kind of teacher. He teaches several of the required sophomore courses for chemical engineering ma jors, giving out grades from A to F, as deserved. The good students stay, the others repeat or change majors. The current seniors have created a bul letin board with pictures and the facts as they see it for the chemical engineering faculty. Their advice for students of Dr. Reynolds classes includes: Participate as much as pos sible. This will lessen your chance of being randomly called on during class. Joes courses are well organized and fast paced. He sets high standards, gives fair-but-tough tests, and assigns homework due at every class. In the old days, he distributed the home work assignments for the entire semester on day one, but when the Internet was relatively new, he forced the students to use it by sending out assignments via e-mail only. The seniors advise, check your email every day, at least twice a day. There will always be something new in there. This practice has the added advantage of getting the students to read messages about AIChE meetings and parties, which gets them involved in departmental activities from freshman year on. Joe is one of the teachers who makes effective use of the computer projector and PowerPoint slides for each of his lecture courses: He expects students to listen and respond during his presentation instead of just madly copying information. His PowerPoint presentations are available for all of his students through the course Web sites on the Blackboard system. Many of Joes current and former students credit him as being a truly outstanding teacher, a fact that is supported by his numer ous teaching awards and consistently excellent course and teacher evaluations. Joes focus on excellent teaching must have set a good example, because several of his former students also pursued careers in academia. Among them are Dr. Ruben Carbonell 1983), now professor of atmospheric science at Colorado State University; Dr. John Blaho (B.E. 1983), now associate profes sor of microbiology at Mount Sinai School of Medicine; and Dr. Marco Castaldi (B.S.ChE 1992), now assistant professor of earth and environmental engineering at Columbia University. His former students turned academicians credit Joe in various ways for encouraging their decision to pursue research and teach ing at the college level as a profession. Br. Thomas participated as an undergraduate in Joes research at RPI, and credits this early experience with giving him an un derstanding of the way that research and scholarly activities reinforce teaching and vice versa. and Theodore in the Journal of the Air Pollution Control As sociation, based on her undergraduate research at Manhattan I apply to graduate school and go on for a Ph.D.a degree she subsequently completed at California Institute of Tech nology. Ruben Carbonell says that as an undergraduate, he looked up to Dr. Reynolds as a role model of an excellent career in college teaching. Proudly posing with students at a poster competition. Participate as much as possible. This will lessen your chance of being randomly called on during class. Advice from seniors to students planning to take Reynolds class.

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Winter 2007 13 OUTSIDE INTERESTS All is not academics for this overachiever, however. Joes favor ite recreational activities include skiing and jogging. He can be seen early mornings jogging around his Bronx neighborhood near the college. His equally active fam ilywife Barbara and daughters Megan and Marybethhas accompanied him on the annual Manhattan College ski trip every January since the girls were infants. The foursome has also made the AWMA (APCA) meetings in June an annual event. One of Barbaras favorite activities is international travel, and the family has made so many trips to Ireland that Megan and Marybeth recently obtained dual citizenship. Joe is as proud of his familys achievements as of his own. Barbara has retired from Fordham Preparatory School in the Bronx after 35 years of teaching. Megan and Marybeth both earned baccalaureate degrees in chemical engineering with honors from Manhattan College, so Joe is one of our most enthusiastic alumnae parents. Megan recently received a masters degree from Thunderbird, the Garvin School of International Management in Phoenix. After working in Spain for the pharmaceutical industry, she is currently working for Merck in New Jersey. Marybeth completed her masters in Public Policy at Georgetown University and currently works in Spanish and have studied other languages as well, i.e. Russian for Marybeth and Portuguese for Megan.THE MOST REWARDING PART Joe is well known for his quick smile and easygoing manner, as well as for his endearingly annoying habit of correcting everybodys grammaroften in midsentence. The seniors say, Use proper English. He will call you on it every day! This applies equally to his faculty colleagues. Joes story is unusual in that he is an outstanding teacher and a respected researcher at a primarily undergraduate institution. When he was honored with a Bonus et Fidelis Medal on his 25th anniversary at Manhattan College, he was interviewed about his experiences. Asked about the most rewarding part of his career, his response was immediate: working with students. Top left, Joe and wife Barbara. Top right, Barbara and daughter Megan on a family trip to Toledo, Spainwhere both Reynolds daughters got to prac tice their uent Spanish. Right, Joe and daughter Marybeth undertaking a favorite family activityskiingat Steamboat Springs, Colorado.

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Chemical Engineering Education 14 O general, is the low retention rate of undergraduate years of undergraduate studies, as roughly 50% of freshmen entering chemical engineering do not make it to their senior year. [1] While students have varying reasons for transferring mon is a loss of interest in science and engineering. [2] In most chemical engineering departments, students do not take a core chemical engineering course until their sophomore year, and dont become immersed in chemical engineering until their junior year. This means that underclassmen who switch ma jors due to a loss of interest in science and engineering do so without a good understanding of chemical engineering. To combat the retention problem, many chemical engineer ing departments require an introductory course in chemical Typically these courses serve to introduce students to the department and its procedures, and give a broad overview of some applications in chemical engineering. From a brief survey of course descriptions and syllabi found on the In to chemical plants and presentations by guest speakers to give students more of a perspective on the discipline. While these are excellent activities to which students in chemical engineering can be exposed, one problem is that they are, THE CHEMICAL ENGINEERING BEHIND HOW POP GOES FLAT : ChE KEITH L. HOHNKansas State University Manhattan, KS 66506-5102 Copyright ChE Division of ASEE 2007

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Winter 2007 15 for the most part, passive activities. Students are generally hearing someone tell them what chemical engineering is or are seeing pieces of process or laboratory equipment. They are not touching, designing, or building anything. Hands-on activities are relatively rare, though some departments have used them successfully. [3-7] There are numerous reasons why hands-on projects are not incorporated into freshman chemical engineering courses more often. First of all, freshmen do not generally have the background to apply many chemical engineering principles. ing application into something that freshman students can manipulate since chemical engineering frequently deals with very large and sometimes hazardous processes. Finally, many interesting activities would require extensive laboratory and calculational time (on the order of the laboratory experiments taught in chemical engineering lab courses). The requirement for a useful hands-on activity that could be incorporated into a freshman course is one that is interesting, safe, easily understood by students with limited chemical engineering knowledge, fairly simple, and capable of being completed in a reasonable amount of time. This paper details such an experiment that in fall 2003 and fall 2004 was incorporated University (CHE 110, Current Topics in Chemical Engineer ing). This experiment has students study the often-encoun tered phenomenon of carbonated soft drinks that have lost design and carry out experiments to study one aspect of this dents what chemical engineering is and in increasing student enthusiasm for studying chemical engineering was measured by a semester-end survey. BACKGROUND Freshman students are generally familiar with the phe intuitive understanding as to why it occurs. Most will know will recognize that carbonation is simply the absorption of CO 2 into the liquid phase. What students will not be familiar with are the chemical engineering principles behind how principles to design chemical processes. There are numerous chemical engineering principles involved in the loss of carbonation. This is truly a rich masstransfer problem. Loss of carbonation depends on two factors: the gas-liquid equilibrium for CO 2 and the rate at which mass transfer of CO 2 from the liquid to the gas phase occurs. The gas-liquid equilibrium is represented by Henrys Law: [8] HP gC l CO CO 2 2 1 () /( ) ( ) where Pg CO 2 () is the CO 2 partial pressure in the gas phase, C CO 2 1 () is the concentration of CO 2 in the liquid phase, and H is the Henrys Law constant. Given enough time, CO 2 will leave the liquid solution and enter the gas phase until the above equilibrium relationship is Law constant decreases with increasing temperature. For car bonated beverage bottles left closed for long periods of time, equilibrium is the most important factor in how the carbonated important here, as the partial pressure in the entire volume must satisfy the equilibrium relationship. Large head space volumes lead to a large loss of CO 2 from the liquid. Mass transfer kinetics can be important in such situations. There really are two types of mass transfer occurring in this system: mass transfer of CO 2 from the liquid to the gas and mass transfer of CO 2 through the bottle to the outside atmo sphere. For the standard polymer used to construct carbonated beverage bottles, polyethylene terephthalate, the rate of mass transfer of CO 2 through the bottle is small. This would not be the case, for instance, if low-density polyethylene was used to make the bottle. The rate of mass transfer from the liquid to the gas becomes important in loss of carbonation if the bottle is opened and closed often within a short period of time. In this case, there is not enough time to reach equilibrium, so the CO 2 lost from the liquid phase is the amount that went into the gas phase in the time between openings. Mass transfer of CO 2 into the gas phase can be represented by: [8] PP CO GC OC O 2 2 2 2 (* ) ( ) where: PH C CO CO 2 2 3 ( ) N CO 2 C CO 2 P CO 2 is the partial pressure of CO 2 G times the mass transfer area, P CO 2 is the partial pressure of CO 2 at the gas-liquid interface, and C CO 2 is the concentration of CO 2 in the bulk liquid. IMPLEMENTATION This activity was incorporated in CHE 110 (Current Top ics in Chemical Engineering) for fall 2003 and 2004. This is a one-hour introductory chemical engineering course that freshmen and transfer students are required to take for a letter grade. Four of the 16 contact hours were spent on the CO 2 absorption activity. The remaining time was dedicated to lectures on curriculum requirements, advising and enrollment, how to seek internships and full-time positions, applications facility and the chemical engineering laboratories. Students were presented with the topic of carbonated the Pepsi challenge, in which they sampled two different

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Chemical Engineering Education 16 beverages and determined which tasted better. To show why the other was fresh. Brief discussion of what made the fresh beverage better ensued. This was followed by a discussion of of CO 2 absorption and set up a discussion of mass transfer and gas/liquid equilibrium. Students were then shown two ways to quantify the mass transfer of CO 2 was based on an article by Crossno. [9] 150 ml of a carbonated beverage. The beverage was stirred and left for ~24 hours to drive the CO 2 out of solution. CO 2 was adsorbed into the sodium hydroxide solution to form so phenolphthalein endpoint neutralized the excess sodium hy droxide and converted all of the sodium carbonate to sodium bicarbonate. Continuation of the titration to the methyl orange endpoint converted the sodium bicarbonate to water and CO 2 The amount of HCl required to go from the phenolphthalein endpoint to the methyl orange endpoint gave the amount of CO 2 in the carbonated beverage. The second method was to replace the original bottle cap with a cap in which a pressure gauge had been placed. This cap allowed the pressure in the head space to be measured as a function of time. During demonstration of the two methods, laboratory safety procedures were highlighted and a handout was given on these procedures. Following the demonstrations, the students were told to form groups (self-selected) of four or and select one research topic related to the mass transfer of CO 2 in carbonated beverages. Several topics were suggested to them, although they were encouraged to brainstorm their own project ideas. They were then instructed to identify what experiments and measurements they needed to do in order to would be required to report their results in both a written and an oral report. Final written reports were turned in the last day of class. Oral reports were given during class time in front of the whole class in the last two or three weeks of the class. Performance on the project was a major factor in the overall letter grade was assigned for the reports, which was given roughly equal weight with attendance. In the second year of implementation, the project was assigned 200 points out of a possible 500 points, with the remainder of the points for attendance. Students were required to turn in several reports during the semester to ensure that they were making progress on the project. The reports and their point value are as 10 points; description of experimental objectives, 10 points; detailed experimental plan, 20 points; preliminary results written report, 100 points; oral report, 30 points. The students were given little information on working in in the results section). To address this problem in 2004, each team was asked to meet and discuss the teams expectations for individual team members. They were also asked to lay meet those expectations, leading up to a possible ultimate and all team members had to sign it. In addition, students were required to rate their peers in a number of areas, such as attendance at team meetings, contribution to reports, and consistently rated low by their peers received a deduction of their project grade, with the severity of the deduction deter mined by how low their ratings were. RESULTS Because students were allowed to choose their own research topics, topic selection varied. Topics included: Does the commercially available Fizzkeeper work? How does temperature affect CO 2 absorption? 2 loss from carbonated beverages. Estimate Henrys Law constant for CO 2 in carbonated beverages. Determine effect of different container materials (polyethylene, glass, and PET) on carbonated bever Determine how different PET beverage containers affected the loss of CO 2 over time. How does the length of time the cap is left off a bottle affect the rate at which the carbonated beverage goes The experiments the students conducted and how they ana lyzed their data varied for the different projects. Most groups addressed their research question empirically. For example, several groups plotted CO 2 concentration and/or gas pressure vs. time for different conditions ( i.e. different temperatures, mass transfer equations described above. Other groups relied on the mass transfer equations to ad dress quantitative questions, such as estimating the Henrys estimated the Henrys Law constant measured concentration of CO 2 in the liquid phase and pressure in the gas phase for

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Winter 2007 17 a single value of the Henrys Law constant. The group that gas pressure over time after the bottle had been opened and closed (to start with atmospheric pressure). From the known volume in the head space and the measured pressures, they could calculate the change in moles of CO 2 in the gas phase. Next, the students solved Eq. (2) by separation of variables, assuming that the concentration of the liquid (and therefore P CO 2 *) was a constant over time at the value they measured after the mass transfer experiment. They then plotted their experimental data using the resulting equation, and found G from this plot. Essentially, they plotted the logarithm of the partial pressure vs. time, which yielded a linear plot, the G This analysis assumed that all of the mass transfer resistance was in the gas phase, which likely was not the case. Making this assumption helped in the analysis, however, since the students could readily measure the gasphase pressure over time. The titration procedure was problematic for some students. Sometimes students found that the balloon containing NaOH, in which CO 2 when they returned to the laboratory for titration. Sub-at mospheric pressures had apparently been created inside the balloon due to loss of CO 2 from the gas phase, causing the balloon to shrink and eventually completely collapse. Stu dents also reported some problems with getting reproducible results with the titration. These problems were likely due to human error in most cases. There were fewer complaints in the second year, possibly because a longer period of time was given for completion of the project (nearly the entire semester, as opposed to only six weeks) which allowed for more repeat trials. Student work showed promise, but analysis was often too simplistic or relied on too few data points to draw a conclu sion. This provided a good opportunity, however, to present important concepts such as estimating error and the need for a good experimental design with replication. In the second year, students were asked to lay out a detailed experimental plan for the data they would take to address their research question, and were given feedback on the appropriateness of their plan. In addition, preliminary reports provided more opportunity to give feedback on whether they were analyzing their data properly. Their oral presentations showed a good deal of sophistication, with all groups using PowerPoint pre sentations with imbedded graphics. It is obvious that they had previously given PowerPoint presentations in high school, as no time was spent teaching about the tool. ASSESSMENT A detailed survey was given to the students at the end of the semester to evaluate both the course in general and individual class activities. The results of this survey were used to assess the effectiveness of the hands-on CO 2 absorption experiment in educating freshmen about chemical engineering and in creasing their enthusiasm for studying chemical engineering. Table 1 summarizes student responses. As seen in this table, students generally felt that the CO 2 absorption activity improved their understanding of chemi cal engineering and increased their enthusiasm for studying chemical engineering. In addition, the CO 2 absorption activ ity was mentioned by 15 students (out of 36 students who responded) as one of the three most useful activities in the a lecture on biotechnology), and by 17 students as one of the dairy processing facility and a tour of the chemical engineer ing laboratories). It is interesting, but perhaps not surprising, that the most enjoyable activities had the students going out to see applications of chemical engineering or engaging in a hands-on activity rather than listening to a lecture. QUALITATIVE EVIDENCE Most students seemed to enjoy the exercise. The opportunity to work with a real world engineering problem energized a number of the students. of the Fizzkeeper, for example, devoted a great deal of time (as well as a large amount of sealant products) to attempting to produce a bottle that would allow them to use the Fizzkeeper while simultaneously measuring the pressure in the head space of the bottle. It appeared that the students with a more applied, rather than theoretical, mindset appreciated the activity. Student comments on the end-of-semes ter surveys were mostly positive, and also provide some insight into why students T ABLE 1 Assessment Results for CO 2 Absorption Activity Aspect Assessed Fall 2003 Fall 2004 Average response to: This session improved my understanding of what chemical engineering is and what chemical engineers do. 4.07 (out of 5) 7.23 (out of 10) Average response to: This session increased my enthusiasm for studying chemical engineer ing. 3.64 (out of 5) 7.05 (out of 10) Number of students listing the CO 2 activity in response to the following: Of all the activities most useful? N/A 15 (out of 36 respondents) Number of students listing the CO 2 activity in response to the following: Of all the activities we did in class, which three did you enjoy the most? N/A 17 (out of 36 respondents)

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Chemical Engineering Education 18 the following positives about the activity: 1. Provided an opportunity for a hands-on/laboratory activity 2. Allowed students to work in a group 3. Gave an idea as to what chemical engineers do The opportunity for students to work in groups was particu larly well received. This was a great way for freshmen to get to know their colleagues, make friends, and form study groups for introductory science and engineering courses. Students were forced to work in groups to decide what experiments report on the project, leading to closer interactions than what usually occur in a lecture course. A few negative comments were noted. Comments in 2003 indicated that group dynamics were an issue. Some students felt as if they had done all the work while other students had done very little. To address these concerns, the next year more time was spent discussing group work, and peer review of group members was implemented. Another negative com ment, noted in both years, was that the project goals were not nature of how the project was implemented. Student groups were allowed to select their own projects with little input from the instructor. Perhaps more input is needed when the groups are selecting projects to ensure that the topic chosen their objectives. CONCLUSIONS CO 2 absorption in carbonated beverages can be used as a hands-on activity in an introductory chemical engineering course to educate students on chemical engineering. This activity allows students to investigate a relatively familiar neering analysis. The CO 2 absorption activity was successfully State University. Students responded positively to its impact on their understanding of and enthusiasm for studying chemi cal engineering. Most students also listed this activity as one of the most fun and useful activities in the course. Student comments indicated that they valued the hands-on nature of real world engineering project. REFERENCES 1. Unpublished data, based on comparison of enrollment of freshman chemical engineering students in the fall with enrollment of junior students in a class taught at the junior level two years later. 2. Seymour, E., Revisiting the Problem IcebergScience, Mathemat ics, and Engineering Students Still Chilled Out, Journal of College Science Teaching 24 392 (1995) and J.L. Schmalzel, Multidisciplinary Experimental Experiences in the Freshman Clinic at Rowan University, Proc. 1997 Ann. Conf. ASEE Seattle (1997) seau, C.S. Slater, and J.L. Schmalzel, Design in the Rowan University Freshman Clinic, Proc. 1997 Ann. Conf. of ASEE Seattle (1997) 5. Ramachandran, R.P., J.L. Schmalzel, and S. Mandayam, Engineering Principles of an Electric Toothbrush, Proc. 1999 Ann. Conf. ASEE Charlotte (1999) 6. Farrell, S., R.P. Hesketh, and M.J. Savelski, A Respiration Experiment To Introduce ChE Principles, Chem. Eng. Ed., 38 (3), 182 (2004) 7. Moor, S.S., E.P. Saliklis, S.R. Hummel, and Y.-C. Yu, A Press RO System. An Interdisciplinary Reverse Osmosis Project for First-Year Engineering Students, Chem. Eng. Ed., 37 (1), 38 (2003) 8. Henley, E.J., and J.D. Seader, Equilibrium-Stage Separation Operations in Chemical Engineering John Wiley & Sons, New York (1981) Carbon Dioxide by Titration, J. Chem. Ed., 73 175 (1996)

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Winter 2007 19 A s I enter my 40th year of teaching, it seems appropri ate to remind teachers and students of a fundamental error that occurs with surprising frequency. This error is particularly evident in courses that cover a wide variety of chemical engineering topics and pull together subjects sup posedly learned in previous courses. The senior design course and a chemical engineering laboratory with a variety of experi frequently encountered quite bright students who misuse the deltas. Since the differences among the various deltas should be obvious and not at all confusing, it is remarkable that errors of this type crop up so frequently. But they do. This paper will describe a particularly useful experiment in the undergraduate Lehigh University chemical processing laboratory that uses all three of the deltas and, therefore, helps to cement in the minds of students the fundamental differences among the three kinds. The title of this paper originates from the old expression The devil is in the details. (Some of you may also remember Flip Wilsons famous portrayal of Miss Geraldene with her expression, The devil made me do it.) ChE THE DEVILS IN THE DELTAWILLIAM L. LUYBENLehigh University Bethlehem, PA 18015 Copyright ChE Division of ASEE 2007

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Chemical Engineering Education 20 THE DEVIL DELTAS A brief review might be useful to clarify the issues and applications addressed in this discussion. leaving. Mass, component, and energy balances can be applied under either steady-state or dynamic conditions. For example, a steady-state energy balance for a distillation column with a single feed and two products is HQ W The delta in this equation is HB hD hF h BD F where the streams leaving the column are the distillate (with D ) and the bottoms (with B ), and the stream entering h F ). Of course, appropriate and consistent units must be used per mole ( e.g. Joule, kcal, Btu). In a heat exchanger, streams are heated or cooled. Under steady-state operations with no phase change, a stream enters at temperature T in and leaves at temperature T out If the mass heat capacity c p M the HF cT T MP out in () If there is a phase change, for example if steam is entering in and leaving as liquid out through a steam trap, HF hH steam out in () in pressure, elevation, velocity, and density between the inlet and the exit conditions. Transport processes occur because of differences in driv ing forces. In heat transfer, the difference is between hot and cold temperatures. In mass transfer, the difference is between large chemical potential and small chemical potential (partial pressure, concentration, or activity). In momentum transfer, the difference is between high pressure or velocity and low pressure or velocity. For example, consider a perfectly mixed vessel that is surrounded by a jacket. The temperature of the liquid in the vessel is T vessel condensing steam at temperature T steam The driving force for heat transfer is TT T steam ve sse l The heat-transfer rate Q that results from the driving force QU AT UA TT H H steam ve sse l ( ) H is the heat-transfer area of the vessel wall. In this example, the jacket temperature is the same at all positions in the jacket. the temperature driving force changes, and a log-mean tem perature difference must be used. T TT T T LM 12 1 2 ln where the two deltas are the temperature differences at the inlet and outlet ends of the jacket or coil. TT T TT T ve sse lC in ve sse lC out 1 2 Now the heat-transfer rate is QU AT UA TT T T H LM H 12 1 2 ln If a circulating cooling water system is used with a high rate of circulation, the temperature in the jacket is essen tially constant at some temperature, T J The heat-transfer rate is QU AT UA TT H H ve sse lJ In this type of system, a cold makeup water stream at T Cin is added to the circulating loop, and water is removed at the jacket temperature T J A circulating cooling water system has superior dynamics compared to the oncethrough system. The high circulation rate maintains a Steam In Cooling Water Out Cooling Water In Condensate Out Steam Trap T vessel Figure 1 ( T coil ) Top ( T coil ) Bottom Figure 1. Heated or cooled agitated vessel.

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Winter 2007 21 time constants are less variable. The variables in a dynamic process change with time, so we a later point in time. For example, when the liquid in a vessel is heated at startup, the temperature changes with time. TT T tt 2 1 At any point in time the rate of change of temperature is dT dt T t TT tt t t () 2 1 21 if the time increment between t 2 and t 1 is small.LABORATORY EXPERIMENT USING ALL THREE DELTAS The process consists of a stirred vessel, 1 m in diameter containing 785 kg of water. The rpms of the agitator can be coil is wrapped around the outside of the vessel, making nine wraps around the circumference. Figure 1 gives a sketch of the apparatus. The tank is equipped with a 0.3 m, 6-blade impeller 2 The liquid in the vessel is initially at ambient temperature. It is heated by introducing steam at the top of the coil. Conden sate leaves at the bottom through a steam trap. Temperatures inside the vessel and at the inlet and outlet of the coil are monitored by a data acquisition system. When the temperature of the vessel reaches about 90 C, the steam is shut off and cooling water is introduced. The water enters at the bottom of the coil and leaves at the top. Figure 2 shows typical temperature vs. time trajectories for the batch heating and cooling. The temperature in the coil during heating is shown as being constant at the steam temperature. This is actually not the case because it takes some time for the coil to become completely full of steam. This complicates the analysis of the heating step because the of steam. We consider this later in this paper. The analysis of the cooling step is much more straightforward, and our discussion for the purpose of illustrat ing the devil deltas will concentrate on this part of the batch cycle. sured by the old-fashioned bucket and stop watch method. The inlet and outlet cooling water temperatures are measured, as is the vessel temperature. At any point in time, there are two ways to estimate the instantaneous heat-transfer rate. From the measurement of the heat-transfer rate at that point in time is QF cT T CW CW PC out Ci n ,, This is the out minus in delta. At time equal 30 minutes in Figure 2, this out-minus-in delta is TT T C out in C out Ci n ,, 38 15 23 The heat-transfer rate can also be estimated by the time rate of change in vessel temperature. This uses the time delta. At time equal t n the instantaneous rate of heat transfer to the QM c TT ve sse lt t ve sse lp ve sse l tt ve s n n s se l tt nn n tt 1 1 Since the heat-transfer rate varies with time, the slope of the temperature vs. time curve varies during the batch cooling step. Having two independent ways to estimate the rate of heat Figure 2 shows this delta at 30 minutes is about 3.5 C per minute (the slope of the vessel temperature line). TC tim e 35 ./ minut e Using this value, the instantaneous heat-transfer rate is rate of cooling water (2 kg/sec) and the inlet and outlet cooling water temperatures is very close to this number. The temperature of the cooling water in the coil varies along its length, so a log-mean temperature difference is used. This is the driving force delta, T TT T T LM 12 1 2 ln 0 10 20 30 40 50 60 10 20 30 40 50 60 70 80 90 100 110 Figure 2 Temp (C) Time (min) T vessel T Cout T Cin T 1 T 2 T vessel T steam Figure 2. Temperature proles and temperature deltas during cooling.

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Chemical Engineering Education 22 where the two deltas are the temperature differences at the inlet and outlet ends of the coil. TT T TT T ve sse lC in ve sse lC out 1 2 The log-mean temperature difference at this point in time is T TT T T LM 12 1 2 70 38 70 ln 15 70 38 70 15 42 5 ln .C With a heat-transfer area of 3.14 m 2 the overall heat-transfer U Q AT kW HL M 192 31 44 25 14 4 21 .. accounting for heat conduction through the vessel wall and Boelter equation and an appropriate equivalent diameter. Even with a constant agitator speed, there is some varia temperature affects the viscosity of the water. If the temperature in the coil was constant during the heatconstant with time, the analysis would be quite simple. It would use time deltas in a way that may not be obvious. The length of a heated tube. In that situation, the appropriate driv ing force for calculating the heat-transfer rate is a log-mean temperature difference using the temperature differentials at the inlet and exit ends of the tube. The log-mean temperature independent variable is length. In the batch heating situation, the independent vari able is time, but the heat-transfer equations are the same. Therefore, total heat transfer can be calculated by the change in vessel temperature from some point in time to another point in time. The driving force can be calculated using a log-mean temperature difference based on the difference between the constant steam temperature and the temperature of the vessel at the two points in time. The similarity between length and time coordinates is exactly the same as the batch heating of a vessel. It should be emphasized that the analysis discussed in this section makes two important assumptions. First, the steam temperature is constant. Second, the overall Figure 3 shows how the vessel temperature changes during heating. It starts at T 1 when time is t 1 and ends at T 2 when time is t 2 The total amount of energy added during this period is Ener gy Mc TT ve sse lP 21 The average heat-transfer rate over this period is Q Ener gy tt Mc TT tt ve sse lP 21 21 21 is Mc dT dt AU TT ve sse lP ve sse l Hs t eam ve sse l This linear ordinary differential equation can be integrated to give TT ce ve sse lt steam AU Mc h ve sse lP () 1 t The constant of integration c 1 is evaluated at the initial condi tion where T vessel = T 1 cT Te steam AU Mc t h ve sse lP 11 1 The time dependent vessel temperature is TT TT e ve sse lt steam steam AU Mc H ve sse lP () 1 tt 1 Evaluating this equation at time equal t 2 where T vessel = T 2 gives TT TT e steam steam AU Mc H ve sse lP 2 1 () tt 12 Rearranging gives TT TT e steam steam AU Mc H ve sse lP 2 1 tt 21 0 10 20 30 40 50 60 10 20 30 40 50 60 70 80 90 100 110 Figure 3 Temp (C) Time (min) T vessel T 1 T 2 T steam t = t 1 t = t 2 T 1 T 2 Figure 3. Using time delta for heating phase with constant U and T steam

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Winter 2007 23 Taking the natural log of both side of this equation gives ln TT TT AU Mc steam steam H ve sse lP 2 1 tt 21 for Q give ln TT TT AU TT M steam steam H ve 2 1 21 s sse lP cT T tt 21 21 ln TT TT AU TT steam steam H 2 1 12 Q QU A TT TT T H steam steam 12 2 ln T UA TT TT T H steam steam s 1 2 1 ln t t eam steam H LM T TT QU AT 2 1 In our experimental apparatus, the temperature through the entire coil is not equal to the steam temperature for about half the heating period. In addition, the change in viscosity due to changes in temperature results in variations in the heat-transfer be applied for the period toward the end of the heating step. During the initial part of the heating step when the tempera ture of the exit stream from the coil is not equal to the inlet temperature, the full heat-transfer area is not being used for steam condensation. Thus it is uncertain how to calculate an is to assume that the active heat-transfer area varies linearly with time during this period. Once the temperature of the exit stream from the coil be comes equal to the inlet temperature, either the approximate method discussed in this section or a rigorous approach can rate from the rate of change of the vessel temperature, and using the differential temperature driving force of T steam minus T vessel and the full heat-transfer area. For example, in Figure 2 at time equal 20 minutes, the differential temperature driving force is 100 85 C and the slope of the T vessel curve is about 1.3 C per minute.CONCLUSION This paper has attempted to provide a clear distinction among the three deltas that are used in chemical engineering. Although they are obvious to the experienced engineer, they are often misapplied by young students.ACKNOWLEDGMENT fully acknowledged.

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Chemical Engineering Education 24 P ractical experimentation that processes real signals is essential to helping students understand theory given in textbooks and giving them skills to deal with real problems successfully. An indispensable part of the chemical engineering curriculum, the experimental class is designed to train all students at the same time and in an effective way for acquiring face-to-face interaction. This conventional ap or distance constraints. Moreover, due to both safety and security reasons, access to labs cannot be totally free and is restricted in time to ensure the presence of supervision person nel. Interesting proposals have been made to use the Internet for various educational purposes, including different types of virtual laboratory Web sites, [1] interactive simulations, [2] and access to real instruments and test benches through a remote connection. [3-5] In fact, some implementations of remote moni toring and control through the Internet have already reached AN INTERNET -BASED DISTRIBUTED LABORATORY JING GUO, DAVID J. KETTLER, MUTHANNA AL-DAHHANWashington University St. Louis, MO 63130 ChE Copyright ChE Division of ASEE 2007

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Winter 2007 25 the teaching laboratories of physics [6] and electrical engineer ing. [7] For chemical engineering laboratories, this capability is now available at University of Tennessee at Chattanooga, [8] University of Texas at Austin, [9] and MIT. [10] With appropriate planning, teachers and students can run provides educational facilities and opportunities for those students whose schedules might be asynchronous. [8, 11] An other advantage of such remotely accessible laboratories is that teachers and students at another institution can have ac cess to laboratory facilities without incurring the full cost of developing such resources. Rather than several universities spending money on the same equipment for the same experi ments, cooperating universities may each carry out one unique experiment and then form an experiment pool. [12, 13] Using such highly automated experiments for remote operations can allow a drastic reduction in the amount of personnel time required for those particular experiments. It is reported that online laboratories hold promise of being up to two orders of magnitude cheaper than conventional ones. [14] Having tools, and graphs tracking the dynamic process variables, that can be viewed simultaneously by all class members. [10] Such expanded access allows the students and instructors to spend less time communicating the operating procedure and more time investigating the experimental results. Remote learning has evolved into a new model of high quality aimed at engaging students in a distinctive learning technology that helps build a solid foundation. [9, 15] Advances in available computer software and interfacing techniques enable remotely operated laboratory experiments to be constructed at relatively low cost. [16] In this paper, we report on the in-house development of remote control and measurement methods for a chemical engineering labora tory on unit operations, which is offered to undergraduate students at Washington University in St. Louis. A client-server architecture devoted to instrument management through the Internet is built with Visual Basic and LabTECH program ming tools, providing a novel approach in comparison to the Java and LabView software employed in other references. [810] and design of a geographically distributed system based on standard commercial components. Used for the required undergraduate process control course, a tracer experiment is restructured to illustrate the connection between physi cal instruments and the server-client Internet system. The experimental data is archived for subsequent viewing and analysis, and the responses of students to the online experi ment are assessed. SYSTEM ARCHITECTURE To achieve a standard component distribution system, we adopted Internet technologies that allow portability and independence through different client hardware/software architectures. A standard portable language is instrumental for independence of the application from the client system on which it is executed. An Internet browser can now be con sidered a standard component of any computer installation. Therefore, our approach will automatically work with any widely available hardware/software environment. The connection between the server and client program is made by a TCP/IP Winsock socket located within both programs, which functions much like a phone receiver/dialer on each side of the Internet. The server and the clients are connected on the same local area network (LAN) within the laboratory or campus. Remote connections can even be set up between the server and a single user working at home. and message routing management. It is the typical protocol suite adopted in the standard Internet. [1] The server sends measurement data to the client the same way the client sends control commands to the server, by creating a string of num bers representing all the commands or measurements and sending them through the TCP/IP socket. Like wise, once the client receives the measurement string of numbers and the server receives the control string of numbers, the string is parsed, and each measurement or command within the string is sent to its appropriate subroutine within the client or server code. A block diagram of the proposed solution is shown in Figure 1. The clients are hosted on a users personal computer while the server runs on a laboratory computer and manages an automatic control and measurement system that embeds programmable instruments. Both client and server computers run programs that are logically split into two layers. One layer in both client and server sides deals with user 1 Client Applications (Measurement & Control, User Interface) Remote Client Network Management Client Side Network Management Server Side Instrument Management (Board Drivers, Command Process) Server HTTP TCP/IP Connect Request Reply Close Lab Setup Control Measurement Client Applications (Measurement & Control, User Interface) Remote Client Network Management Client Side Network Management Server Side Instrument Management (Board Drivers, Command Process) Server HTTP TCP/IP Connect Request Reply Close Lab Setup Control Measurement Figure 1 Figure 1 Diagram of the client-server architecture employed to implement the remote control measurement.

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Chemical Engineering Education 26 interface and instrument management, while the other layer deals with network intercommunication. The server is directly connected to the instruments that measure physical quanti ties. In this work, the server computer, connected physically to the instruments, makes available a set of remotely callable procedures that perform all standard activities (address, read, write, status poll, etc.). The clients command generator is the user, and sends them via the TCP/IP client socket to the server. The experimental results sent back by the server are then handled and displayed in the client window. The sockets of the client program and the server program are connected by using the server computers IP address on the Washington University network. The same local port number must be nections and the TCP/IP communication protocols transmit the instrument control commands, parameters, and reports between client and server. Only one user group is allowed to connect at one time, because physically only one experimental run can be done on the reactor at a time. At the sessions termination, the socket connection is closed and the server can accept a new connection on the same port to start a new session. If the client/server connection is broken or remains idle more than If the power shuts down, a system of safety interlocks in the To protect the server, several techniques can be used, e.g. encryption. For simplicity and cost reasons, we adopted an tion of both the password and the IP address of the gateway through which client connects to the server. Developed in Visual Basic, the programs require only the addition of a very small number of statements necessary for establishing and closing the interface-related functions of corresponding network functions. When new instru ments are added to the instrument library, it is easy to add to existing programs. The software related to any newly connected equipment can be added to the system without recompiling or modifying the application core. About two or three lines added to the server and client programs will add numbers representing the additional measurement or control variables to the string sent through the TCP/IP socket. At the client site, because the whole core of the software application ( i.e. the components required to share, engage, and release the resources) resides permanently on the server computer, it is not necessary to install any special software tool. Once a new client connection is accepted, the user lo cally runs the command necessary for selecting and driving an instrument. As a consequence, the proposed structure makes the application portable and safe for remote users. The server is a Pentium-IV computer with a 1 GHz pro cessor, provided with two independent Universal Serial Bus (USB) ports. The server runs on Windows 2000 Professional and uses drivers from Data Translation to access the Data Translation DT9804 interface board. The server connects to the interface board using a USB cable, and the interface board has analog input/output and digital input/output ports for connection to the physical control hardware of the reactor system. The overall system has been devised to assure reliable communication between the client and the server, and between the server and the physical resources available. A LabTECH ControlPro 12.1 Runtime program receives data and sends commands to the control hardware via the DT9804 interface board. Once the control hardware and server are physically connected to the DT9804 board and the boards drivers are installed, LabTECH can be set up to control the hardware by dragging and dropping control icon blocks from its menu into its workspace. BUILDING EXPERIMENTAL INSTRUMENTS The lab setup icon shown in Figure 1 represents any real instrument that requests automatic control and measure ment. The proposed server-client system structure can be experiments. As a test case performed on implementation of the whole system, a tracer study experiment is carried out remotely in real time over the Internet, using a tubular reac tor in the Chemical Engineering Laboratory at Washington University. The purpose of the tracer test is to experimentally reactor with a pistonlike motion and no axial mixing. A real tube reactor, however, cannot reach this ideal state. In the experiment, a conductive tracer was injected into water just before the reactor entrance and the conductivity of the solu tion mixture was measured at the reactor entrance and exit. The mean residence time, tracer response curve variance, [An] advantage of such remotely accessible laboratories is that teachers and students at another institution can have access to laboratory facilities without incurring the full cost of developing such resources.

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Winter 2007 27 then be calculated. Through data analysis, the tube reactor was compared with an ideal plug reactor. Figure 2 displays the physical hardware built for the tracer the tracer feed pump, adjust the tracer injection duration, open the tracer injection valve, and then inject the tracer. Air pressure (30-100 psi) is used as the driving force to control and the measurement is sent to the client application. The conductivity measurement will rise and then fall back to the steady state value, at which point the students may close the client application. Table 1 lists all of the process variables used as signals in the tracer experiment. Digital signals are either on or off when equal to 1 or 0, respectively. Analog signals send (Output) shown in the Range column in Table 1. The output signals control the instrument setup, while the input signals are types of all variable signals are listed in the Type column. The elements that launch and receive signals are listed in the Origin and Destination column, respectively. NETWORKING CREATION FOR ONLINE CONTROL AND MEASUREMENT the LabTECH Runtime program Traceexe.ltc. It initiates the connection between the physical laboratory setup and the server computer. This connection channel receives measurement sig nals from the USB port on the interface card and issues commands to control the setup operation. inputs in the Traceexe.ltc program. By specifying the correct interface point, each analog input block in Traceexe.ltc receives the proper signal from the interface card. The second application in the server computer, Server_TracerStudy.exe, activates the server site and enables it not only to transfer the remote cli ent signal to the physical setup, but also to receive measurements from Traceexe.ltc by continuously using the GetLT function. This function uses a T ABLE 1 Process Variables Used in the Tracer Experiment Variable Range Units Type Origin Destination Reactor Feed Valve 0-1 Volts Digital Output Client_TracerStudy.exe Control Hardware Tracer Feed Pump 0-1 Volts Digital Output Client_TracerStudy.exe Control Hardware Inject Tracer 0-1 Volts Digital Output Client_TracerStudy.exe Control Hardware Tracer Injection Duration 1-3 sec Analog Output Client_TracerStudy.exe Server_TracerStudy.exe Reactor Feed Valve Position 0-100 % Analog Output Client_TracerStudy.exe Control Hardware Run Time >0 sec Analog Input Traceexe.ltc Client_TracerStudy.exe Conductivity >0 mS Analog Input Control Hardware Client_TracerStudy.exe Conductivity >0 mS Analog Input Control Hardware Client_TracerStudy.exe (Reactor) Feed Flow Rate >0 l/min Analog Input Control Hardware Client_TracerStudy.exe 1 Tubular Reactor DT9804 Interface Card Controller ClientServer TCP/IPUSB Water in Air in Probe Probe Pump KCl Tank Flow Pneumatic line Computer signal Feed Flow Valve Tracer Injection Valve Tubular Reactor DT9804 Interface Card Controller ClientServer TCP/IPUSB Water in Air in Probe Probe Pump KCl Tank Flow Pneumatic line Computer signal Feed Flow Valve Tracer Injection Valve Figure 2 Figure 2 Overview of the physical experimental setup and its connection to the Web.

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Chemical Engineering Education 28 built-in LabTECH application called LT-Speedway to grab the analog input data received by Traceexe.ltc. The program Server_TracerStudy.exe takes four measurement variables it receives from its GetLT function and combines them into one string of text, called OutputString. Once the client connects to the server computer using the client program Client_TracerStudy, then Server_TracerStudy.exe sends OutputString across the Internet once every 100 milliseconds to the client program, using a timer within the server program called Timer2. These two applications must be running before a student can access the experiment using the client program, Cli ent_TracerStudy. The student downloads this program from an Internet page and stores it on the remote computer. Once the student double clicks on the related icon, the client program opens up and connects to Server_TracerStudy on the server. Every command the user manipulates sends text data from the client TCP/IP socket across the Internet to the server TCP/IP socket. The server program sends measurement data acquired from the LabTECH Runtime program Traceexe.ltc back to the client through TCP/IP socket and sends the control variable commands acquired from the client to Traceexe.ltc, where it is executed by that program on the control hardware. The controlled variables, reactor feed Valve Position and tracer Injection Duration, are analog outputs in Traceexe. ltc. Before injecting the tracer, the student sets the values of analog outputs by using a scroll bar on the user interface of the client program, Client_TracerStudy.exe, as shown in Figure 3. The student must also open the reactor Feed Flow Valve, turn on the Tracer Feed Pump, and Inject Tracer by pushing the respective buttons on the client user interface. These are digital outputs in Traceexe.ltc. Whenever the stu dent pushes one of the buttons (digital) or slides one of the scroll bars (analog) on the client user interface, the current values of all the digital outputs are combined with the analog outputs as a text string called InputString in the InputData function in the client program. Then InputString is sent to the server program through the client TCP/IP socket. The server program picks up the InputString of text across the Internet at its TCP/IP socket, separates all of the outputs, and places them in their respective textboxes, as shown on the lefthand side of the image in Figure 4. In the server application, the function PutLT takes each of the values in the textboxes on the lefthand side of the server monitoring window and sends them to their respective input block in Traceexe.ltc. The input blocks receive each signal in Traceexe.ltc and send them to their corresponding Bit Number (digital) or Interface Point (analog) on the DT9804 interface card. LABORATORY EXPERIENCE On the project Web site (), eight groups of undergraduate students have participated in the online operation test. After a class of introduction to the distributed learning technology and two additional classes on the theoretical aspects of the experiment, the instructor demonstrated and monitored experiments using a classroom computer connected to the Internet. When the students were doing the measurements themselves in the computer lab one inputs on the user-interface, analyze the experimental out comes, and answer questions posed by the instructor through interactive dialog. Explanatory Web pages were provided to answer most of their questions on the real instruments during the lab session. As a result of this interactive tutoring mode, students showed more interests in the online operation than the local on-site operation. During the lab session, students issued commands and pa rameters from the client window to the server via the TCP/IP client socket. The experimental results were sent back by the server and then handled and displayed in the client window. The client program created a log containing measurements ductivity. Once the client application is closed, students can open this log to analyze the evolution of the collected tracer 1 Figure 3 Figure 3 User interface for the client application. 1 Figure 4 Figure 4 Monitoring window for the server application.

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Winter 2007 29 response. Typical tracer response curves at the inlet and outlet with respect to time are shown in Figure 5. In an ideal plug would be identical as thin, spikelike peaks. This experiment, to account for the axial dispersion. The reactors nonideality must be included in order to predict reactant conversion from given feed rates and reactant compositions. The experiment was conducted twice, once at a remote client computer station that was Internet-linked to the server, and once at the server computer station directly attached to the setup elements. The typical experimental values obtained from the online remote control and on-site local control, as well as the relative error between these two values, are listed in Table 2. Although there is a time delay between the client and server due to the Web data transfer and the instrumenta tion synchronization, this delay penalty is negligible when instruments take a long time to complete the measurement. [4] the online control and on-site control give rise to the same residence time measurement in the tubular reactor. Student feedback is a key consideration for improvement objectives. The responses contained encouraging comments and constructive suggestions. In general, the proposed survey recommendations were implemented before the next student group was invited to evaluate the lab session. Students agreed that lab sessions became improved with more user-friendly options and tools added to the client window. One feature the students liked most about operating experiments remotely was that it allowed them to perform the process at any time from a place that was convenient for them. The other appreciated feature was that the remote operation helped the students get used to a real world application that was either in a remote control room or at a remote operation facility, especially when hazards and safety concerns were present. Some students showed intention to run the on-site physical experiments as the complimentary reference check since their understand the actual devices in front of them. Actually, this intention streaming to the remote client window so students can listen to the sounds of the device station and view it on the Internet while they are operating. Such sophisticated user interface will soon be added to the current system. CONCLUSIONS This paper describes an Internet-based client-server archi of remote instruments. The proposed solution is portable using the employment of the TCP/IP protocol suite, and also extensible because of the high level of abstraction in system implementation. This approach offers a valuable component to remote engineering instruction that cannot be replaced by simulation software packages. Compared to the traditional way of teaching, due to the absence of schedule and physical constraints, this new approach reaches students who otherwise would not have chance to take these courses learning opportunities. A set of experiments based on the proposed technique for the control of remote instru mentation has been made available to the students of chemical engineering laboratory courses held in Washington University in St. Louis. There is the op portunity to use this technol ogy to add other experimen T ABLE 2 Experimental Measurements of Residence Times Valve Opening Position (%) Actual Flow Rate (cm/sec) Local Control (sec) Remote Control (sec) Relative Error (%) 45 2.93 22.96 23.77 -3.53 55 3.86 18.32 19.02 -3.82 65 5.11 14.57 14.97 -2.75 75 6.02 11.90 12.19 -2.44 85 6.44 11.74 11.38 3.07 95 6.67 10.87 10.67 1.84 Figure 5. Typical tracer response curves shown in the client side. Measurements are taken at the inlet and outlet of the tubular reactor. 1 0.05 0.04 0.03 0.02 0.01 Inlet Outlet 0 0 Time (s) E curve 103050607080 2040 0.05 0.04 0.03 0.02 0.01 Inlet Outlet 0 0 Time (s) E curve 103050607080 0.05 0.04 0.03 0.02 0.01 Inlet Outlet 0 0 Time (s) E curve 103050607080 2040 Figure 5

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Chemical Engineering Education 30 tal demonstrations or assignments to one lecture. In order to expand the scope of the experiments and to share costs and software development time, we are planning collaboration on this project with other universities. REFERENCES 1. Ferrero, A., and V. Piuri, A Simulation Tool for Virtual Laboratory Experiments in a WWW Environment, IEEE Trans. Instrum. Meas. 48 741 (1999) 2. Shin, D., E.S. Yoon, S.J. Park, and E.S. Lee, A Web-Based, Interactive Virtual Laboratory System for Unit Operations and Process Systems Engineering Education: Issues, Design, and Implementation, Comput ers and Chem. Eng. 26 319 (2002) 3. Benetazzo, L., M. Bertocco, F. Ferraris, A. Ferrero, C. Offelli, M. Parvis, and V. Piuri, A Web-Based Distributed Virtual Educational Laboratory, IEEE Trans. Instrum. Meas. 49 349 (2000) 4. Bertocco, M., F. Ferraris, C. Offelli, and M. Parvis, A ClientServer Architecture for Distributed Measurement Systems, IEEE Trans. Instrum. Meas. 47 1143, (1998) 5. Arpaia, P., A. Baccigalupi, F. Cennamo, and P. Daponte, A Measure ment Laboratory on Geographic Network for Remote Test Experi ments, IEEE Trans. Instrum. Meas. 49 992 (2000) tion in the Undergraduate Physics LaboratoryTeaching an Old Dog New Tricks, IEEE Trans. Educ. 42 174 (1999) Fjeldly, J.Q. Lu, and T. Ytterdal, Conducting Laboratory Experiments Over the Internet, IEEE Trans. Educ. 42 180 (1999) 8. Henry, J.,Web-Based Laboratories: Technical and Pedagogical Con siderations, AIChE Annual Meeting, Reno, NV (2001) 9. Rueda, L., and T.F. Edgar, Process Dynamics and Control Experiments Carried Out Over the Internet, AIChE Annual Meeting, San Francisco (2003) Conference on Engineering Education, Valencia, Spain (2003) 11. Latchman, H.A., C. Salzmann, D. Gillet, and H. Bouzekri, Informa tion Technology Enhanced Learning in Distance and Conventional Eduction, IEEE Trans. Educ. 42 247 (1999) 12. Cameron, I.T., An Interactive Web-Based Decision Support System for Hazardous Industry Land-Use Planning, Computers and Chem. Eng. 24 1057 (2000) 13. Shin, D., E.S. Yoon, S.J. Park, and E.S. Lee, Web-Based Interactive Virtual Laboratory System for Unit Operations and Process Systems Engineering Education, Computers and Chem. Eng. 24 1381 (2000) 14. Aung, W., P. Hicks, L. Scavarda, V. Roubicek, and C.H. Wei, Engineer ing Education and Research: A Chronicle of Worldwide Innovations, Arlington, VA, USA: iEER (2001) 15. Hough, M., and T. Marlin, Web-Based Interactive Learning Modules for Process Control, Computers and Chem. Eng., 24 1485 (2000) 16. Ferrero, A., S. Salicone, C. Bonora, and M. Parmigiani, ReMLab: A Java-Based Remote, Didactic Measurement Laboratory, IEEE Trans. Instrum. Meas. 52 710 (2003)

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Winter 2007 31 T he teaching of statistics can be one of the most chal lenging topics in the engineering curriculum. Students of equations used in analysis rather confusing. For these reasons, an applied approach that emphasizes and reinforces how concepts presented in the statistics course can be used in the practice of engineering has been proposed. [1] An ex ample is the use of the senior laboratory course to reinforce the concepts presented in the engineering statistics course. [2] A stronger emphasis on case studies and realistic problems of direct interest to engineering students is also suggested to help motivate and create a more positive attitude toward statistics [3] and engineering education in general. [4] The statistical analysis project described in this article began as a reactor simulation for a senior design course project. It was later integrated into the professional development course, and, after a curriculum revision, the Applied Statistics course, that the students are given a budget with which to perform A REALISTIC EXPERIMENTAL DESIGN AND STATISTICAL ANALYSIS PROJECTKENNETH R. MUSKE AND JOHN A. MYERSVillanova University Villanova, PA 19085-1681 ChE Copyright ChE Division of ASEE 2007 their experimental study, and the experimental results are made available to the students one day after an experiment is requested. Although a process simulation is generating the experimental results, the intent is to mimic a realistic experimental study where results are not available immedi

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Chemical Engineering Education 32 ately and there is an economic limit imposed on the amount of information that can be obtained. The pedagogical advantage of this approach is it requires collection. A similar experimental design philosophy for a gas chromatography experiment is described in Reference 5. It also incorporates student data into the analysis exercise. The integration of data sets collected by students into the teaching of statistics as part of class projects and exercises has been incorporation of problem-based learning into the statistics course, [6] and the recognition that experimental data sets represent observations from a larger popula tion distribution, which may yield different answers from a statistical analysis. [7] An important goal of any engineering statis tics presentation is the appreciation that a single measurement does not represent the true value. [8] The approach in this article also avoids the video game syndrome that can occur in process simulation exercises. Although simulation modules can be very useful teaching and learning aids in chemical en gineering education, they can also impart an exhaustive iteration approach to problem solving and a lack of appreciation for the true time scale of real engineering processes. The addition of a cost and the delay of simulation results in this project are intended to address this issue. EXPERIMENTAL ANALYSIS PROJECT OVERVIEW In this project, the students determine the kinetic rate constants of both the forward and reverse reaction for the hydrolysis of ethylene to form ethanol. CH HO CH OH 22 22 5 The hydrolysis is a vapor phase reaction that is catalyzed by phosphoric acid supported on porous solid catalyst pellets. The reaction rate for the hydrolysis can be expressed as RA kP Pk P fE Wr A () 1 in which R(A) is the rate of formation of ethanol (gmol/ l min), k f is the forward reaction rate constant (gmol/ minbar 2 ), k r is the reverse reaction rate constant (gmol/ minbar), and P E P W P A are the partial pressures (bar) of ethylene, water, and alcohol. The students are told that they have a packed-bed tubular reactor available to carry out hydrolysis reaction experiments. the feed components, the outlet reactor pres sure, and the average reactor temperature for each experiment. The molar feed rates of the reactants (steam and ethylene) and an inert gas (methane) may be varied by adjusting the reactor in order to dilute the reacting species and prevent a runaway reaction. The average reactor temperature and reactor outlet pressure can also be varied by adjusting the P i P o G e G w G m ,, G e G m P o G w P i Y w Y A Y H Y H Y A Y w , Safe Operating Pressure Range: 47.5-60.5 bar Operating Temperature Limits: 250-450 Deg C Safe Operating Temperature Range: 300-400 Deg C Operating Outlet Pressure Limits: 34-68 bar Etylene Molar Flow Operating Limits: 0*-20 gmole/min Steam Molar Flow Operating Limits: 0*-25 gmole/min Methane Molar Flow Operating Limits: 0*-25 gmole/min Flow rates below 0.01 can not be accurately controlled T $100,000 $1000 $200 $2500 Ethylene molar feed rate (gmol/min) Water molar feed rate (gmol/min) Methane molar feed rate (gmol/min) Reaction Specifications Experimental Costs Total Budget Reaction Experiment Replicate Experiment Expedite Results Replacement Reactor $9500 Reactor average temperature (Deg C) Reactor outlet pressure (bar) Ethylene+Methane (mol frac) Inlet Pressure (bar) Alcohol (mole fraction) Water (mole fraction) Reaction Results Tubular Reactor Length = 1 m Diameter = 0.05 m Void Fraction = 40 % Figure 1. Experimental reactor system. The approach in this article . avoids the video game syndrome that can occur in process simulation exercises. Ethylene

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Winter 2007 33 respective controllers. The reactor outlet gas stream is sampled and analyzed for alcohol fraction and hydrocarbon frac tion (ethylene plus methane). Since water cannot be analyzed, it is determined by difference. The students are given a feasible reac tor temperature range of 300 to 400 C and inlet pressure range of 45 to 65 bar. Under these conditions, the reactor can be safely operated. There is a potential, however, for the reactor to detonate due to an exothermic, runaway reaction at higher temperature or pressure. The students are informed that temperatures beyond 400 C and inlet pressures beyond 70 bar are dangerous and can very likely result in detonation of the reactor. Operation of the reactor with methane in the feed at the higher temperature and pres sure range is also recommended. The students must therefore mental trials as discussed in the sequel. The project is carried out in twoor three-person groups. Each student group is given a $100,000 budget to carry out the experiments necessary to determine the reaction-rate constants. Each experiment costs $1,000 for the initial run at a given set of operating conditions and $200 for each replicate run at the same conditions. The results from each experiment are made available the day after they are requested. An ad ditional $2,500 cost is incurred in order to receive the results on the same day for each expedited experiment and replicate requested. Experiments can no longer be carried out when operating conditions cause the reactor to detonate, the students are charged $9,500 for a replacement. The intent of this aspect of the project is to illustrate that, as in an actual experimental study, there are consequences to poor experimental design choices. A schematic of the reaction system is presented in Figure 1. EXPERIMENTAL STUDY The students are asked to determine the Arrhenius equation parameters, activation energy, and pre-exponential factor for the forward and reverse rate constants. They are also asked to verify that the rate constants follow the Arrhenius equation kk ER T o a ex p/ () 2 over the feasible reactor temperature range where k o is the pre-exponential factor, E a is the activation energy, and T is absolute temperature. Both k o and E a can be determined by obtaining each rate constant at two or more temperatures and using the logarithmic transformation of Eq. (2) ln ln () kk E RT o a 1 3 where ln k o a /R is the slope of a linear regression of ln k as a function of 1/T. In order to determine the forward and reverse rate constants students must carry out two different types of experiments. The initial rate method of measuring reaction rate constants is used to determine the forward reaction rate constant k f This technique makes the following assumptions: 1) there is so little product formed that the reverse reaction is negligible; and, 2) the conversion of the reactants is small enough that their concentrations may be taken as constant. Using these initial rate method assumptions with an ideal tubular reactor results in the following relationship for the outlet alcohol mole fraction yk PP Af EW m () 4 where y A is the mole fraction of alcohol in the exit gas, k f is the forward reaction rate constant, P E and P W are the partial m is the molar space time m VF / ( ) 5 in which V is the void volume of the reactor and F is the molar feed rate of gas entering the reactor. Determination of the forward rate constant can be accom plished by noting that y A is directly proportional to the product P E P W m in Eq. (4) where the proportionality constant is k f A plot of y A vs. P E P W m should be a straight line through the origin with slope k f m increases beyond the value where the initial rate method assumptions are valid, y A < k f P E P W m because the reverse reaction will begin to become deviate from a straight line when the initial rate method as sumptions are no longer valid, as illustrated in Figure 2. Y P ** * * * * * * * * * * regression line through the origin initial r ate data non initial r ate data k slope = Figure 2. Example initial rate data regression. yk PP Af EW m () 4 yk PP Af EW m () 4 yk PP Af EW m () 4

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Chemical Engineering Education 34 A value for the forward rate constant can be determined from the slope of a linear regression on the initial rate ex on the slope of the regression line. If the reactor is operated at low enough feed rates, the reaction will reach equilibrium at the reactor outlet. The equilibrium constant for the reaction can then be determined from these experiments: P PP y yy P k k P A ew A EW o f r () 6 where P o is the reactor outlet pressure. The reverse reaction rate constant can be determined once the forward rate constant and the equilibrium constant are known from Eq. (6). Determination of the equilibrium constant can be accom plished by noting that y A is directly proportional to the product y E y W P o P A plot of y A vs. y E y W P o P m is below the value required for the reaction to reach equilibrium, y A P y E y W P o Therefore, one would expect the data to deviate from a straight line when the reaction is not at equilibrium, as illustrated in Figure 3. The equilibrium constant can be determined from the slope of a linear regression on the equilibrium experimental data of the regression line. The reverse rate constant is calculated from the ratio of the forward rate constant to the equilibrium constant at a given temperature. EXPERIMENTAL PROCEDURE The students are instructed to select at least three tempera tures to study. At each temperature, they are encouraged to perform exploratory experiments to determine the feed rate range that will give measurable initial rates and the feed rate range that results in equilibrium. Based on this information, a series of initial rate experiments to determine the forward rate constant and equilibrium experiments to determine the equilibrium constant should be conducted at different feed rates and compositions. In order to carry out initial rate experiments, the reactor must be operated with high feed rates that result in low outlet alcohol concentration and low consumption of reactants. Al though short residence times are necessary for the assumptions made by the initial rate method in Eq. (4) to be valid, the high pressure drop across the catalyst packed in the tube. Therefore, students are encouraged to initially obtain an estimate of the suggest that this analysis may be safely carried out by oper ating the reactor without one of the reactants. The low feed rates necessary for the equilibrium assumption in Eq. (6) to be valid can be obtained without similar issues. Class discussion is also used to point out possible sources of variability in the reaction system study such as error in laboratory analysis and experimental operating conditions. Measuring instruments are often imprecise and/or inaccurate, operating conditions cannot be set precisely as desired, and factors that cannot be observed or controlled can affect the behavior of any system under study. Therefore, any attempt to duplicate or repeat a single set of experimental conditions will usually produce different results. Sometimes the magni tude of this variation is small enough that useful conclusions can be drawn from a single experiment. At other conditions, however, an experiment must be repeated a number of times sentation of the actual value. EXPERIMENTAL DATA The students obtain experimental data by e-mailing the desired reaction conditions for each experi in the project description handout. The costs of the experiments are deducted from the student groups budget as they are performed. The results are made avail able by e-mail to each group member the morning of the following day for normal experiments and by that afternoon for ex pedited experiments. The results include a summary of the experimental costs and the remaining budget. A separate e-mail account using the class number as the e-mail address is created each year for this project. Scripts were developed to extract the operating condi tions from the e-mail message, pass this * * * * * * * * * * * * * * * ** * * * * * regression line through the origin equilibrium data Y slope = P Figure 3. Example equilibrium data regression. P PP y yy P k k P A ew A EW o f r () 6 yk PP Af EW m () 4 P PP y yy P k k P A ew A EW o f r () 6

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Winter 2007 35 information into the simulation and run it, create a report containing the experimental results and budget information, and then e-mail this report back to the student group. The original intent was to automatically perform each of these tasks without the intervention of the instructor. This approach, however, was quickly abandoned. The ability of undergradu the required e-mail format resulted in increasing complexity groups progress and the experiments they requested was also valuable. For these reasons, the project is administered by manual execution of the scripts. The administration task typically takes no more than 10 to 15 minutes each morning. As the report deadline approaches, the time commitment does increase slightly as a larger fraction of student groups request experiments on a given day. PROCESS SIMULATION The reactor simulation is performed using the Octave computational environment running under the Debian linux operating system. Octave is a freely available mathematical computation package with similar capability to MATLAB. to support this project will not run in MATLAB. Additional information on Octave may be found at the Web site . The reactor is simulated using an isothermal, steady-state, constant activation energy and pre-exponential factor values these parameters are not used in order to prevent the more industrious student from obtaining the answer and reverse en gineering their analysis. The values are also changed each year in order to prevent the less industrious student from getting values out of a prior-year project report. We note that these values are a function of the catalyst system used in the reactor and would be expected to change with different catalysts. Normally distributed random variation is added to the deviation of 7.5 10 mol/min is used for the variation added bar is the standard deviation used for the variation added to the requested outlet pressure. There is no variation added to the requested average reactor temperature and the simulation assumes a constant temperature at this value. The pressure drop across the reactor is determined from the expression PP u io () 7 where P i is the inlet pressure (bar), P o 10 in these values have been made between years. Normally distributed random variation with a standard deviation on the order of 2 10 is added to the ethanol mole fraction. The standard deviation of the variation in the hydrocarbon mole fraction is typically half that of the ethanol variation. Slight changes in these values have been made between years. The water mole fraction is determined by different checks made to ensure that reported values are positive and consistent. Determination of reactor detonation is made by comparing the requested reactor average temperature and computed inlet pressure to a table of values. Temperatures below 375 C or inlet pressures below 70 bar cannot result in detonation. Temperatures above 400 C require inlet pressures above 69 bar for detonation, temperatures above 390 C require inlet pressures above 72.5 bar, and so forth. These limits are chosen careless or intentionally wants to detonate the reactor. There have been few unintentional reactor detonations in our experi ence with this project. There have been a number of groups, however, who intentionally try to detonate the reactor with their last experiment. Although this practice is not within the scope of presenting a realistic experience to the students, it is not actively discouraged because it does provide a source of STATISTICAL ANALYSIS For each temperature selected, the students are instructed to plot the experimental outlet alcohol mole fraction as a function of P E P W m and y E y W P o to determine which data points represent initial rate conditions and which data points represent equilibrium conditions. Deviation from the lines shown in Figures 2 and 3 by a given data point can be caused by experimental variation and/or violation of the assumptions made in the corresponding derivation. Although replicate experimental runs can help quantify the experimental variabil ity, they do not provide the information necessary to exactly determine the point at which the initial rate and equilibrium assumptions are violated. This determination requires some judgment by the students. A linear regression analysis on the selected initial rate and equilibrium data points is performed using a least squares The students are informed that temperatures beyond 400 C and inlet pressures beyond 70 bar are dangerous and can very likely result in detonation of the reactor. . The students conditions from initial experimental trials . .

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Chemical Engineering Education 36 forward rate constant and equilibrium constant are determined from the slope of the from the standard error of the slope. These calculations are typically performed by found in a number of introductory statistics texts. An extensive summary of statistics texts can be found in Reference 8 and is not replicated here. A value for the reverse rate constant can be obtained from rearranging Eq. (6) to yield k r = k f P lematic. The reverse rate constant is the ratio of two independent t-distributed random ance. [9] that the equilibrium constant can be within an arbitrarily small neighborhood of zero. Further discussion of this aspect of the project is presented in the section on discus sion topics. A linear regression analysis based on Eq. (3) can be performed on both the forward and reverse rate constants to determine the activation energy and the log of the preexponential factor. This linear regression is also typically performed by students using constant values that they believe are inconsistent with the others and excluded from the regression. The activation energy can be determined from the slope using the relationship E a the gas constant. The pre-exponential factor can be determined from the exponential of the intercept. The students are asked to determine an estimate of the error variance for the labora tory ethanol analysis from the variance of residuals for each initial rate constant and equilibrium constant linear regression. The result is two error-variance estimates for each temperature studied. They are asked to discuss any differences between the esti mated variances and whether the error in the alcohol analysis depends on the amount from the standard error computed from a pooled variance. REPORTING REQUIREMENTS Students report their results in a short group memo to the instructor. The memo must contain a description of how the group arrived at their results, and enough detail for someone to replicate their results. An appendix to the memo should contain all of the data that was obtained. Plots of all the initial rate and equilibrium data with the regression line and an indication of which points were used in the regression must be included for each temperature selected. An Arrhenius plot for the forward and reverse rate constants with the regression line and an indication of any rate constant values that were not used in the regression must also be included. Each group is scheduled for a 10-minute appointment with the instructor where only the instructor and the group members are present. The students turn in the memo, present their results, and answer any questions about their experimental plan and statistical analysis. The intent of this oral presentation is to provide an opportunity for the students to experience a technical interaction with a supervisor that many will encounter early in their careers as practicing engineers. DISCUSSION T OPICS The project described in this article brings up a number of topics for discussion concerning the application of the statistical analysis techniques presented in the Ap A number of groups . intentionally try to detonate the reactor with their last experiment. Although this practice is not within the scope of presenting a realistic experience to the students, it is not actively discouraged because it does provide a source of amusement for some group members.

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Winter 2007 37 discussion is the method used to determine valid initial rate and equilibrium experimental data. Although many student groups use the eyeball method to perform this determina tion, a more rigorous approach is to perform the regression with and without a given data point and look at the effect on For points that are questionable, replicate experimental data should be used to help determine whether the deviation is due to experimental error alone. A second topic for discussion is the basis for the linear regressions used in this project. The students are reminded that the regression equations given in their statistics text, and independent variable. This assumption is clearly violated in the rate and equilibrium constant regressions due to error in the outlet composition measurements and the Arrhenius expression regression due to error in the average reactor temperature. Although an estimate of the magnitude of in dependent variable error can be obtained from the ethanol analysis error variance, a formal treatment of linear regression in this case is outside of the scope of the one-semester Applied Statistics course. It is anticipated that student groups would acknowledge that the regression assumption was violated. Very few student groups, however, realize this point without being prompted during the group oral presentation or class discussion. A very valuable contribution from this aspect of the project is to reinforce to the students that they must con sider the basis and limitations of a statistics formula before they start performing any calculations. Some student groups attempt to determine a reverse rate of the forward and equilibrium constants. A less suspect ap proach adopted by many student groups is to determine the forward rate and equilibrium constant variances as follows s k k s k s s k k r f k r P P k r P r f P f 2 2 2 2 2 2 2 2 1 4 4 2 8 s P () where the partial derivatives are obtained from the rear rangement of Eq. (6), and s 2 kf and s 2 are obtained from the standard error of the slope from corresponding linear regressions. This variance is used to compute the standard obtained by most student groups from the exponential of determine the variance of the pre-exponential factor from that of the intercept from s k k s k s k o o k k o o o 2 2 2 0 2 2 1 9 ln () ln ln using this variance and a t-distribution. These approaches are and pre-exponential factor cannot be determined because the parameter variance is undetermined. This aspect of the proj ect attempts to reinforce the concept presented early in the statistics course that nonlinear transformations of normal or t-distributed random variables no longer retain their original distribution. Although it is fair to criticize the practice of asking for values that cannot be computed by the students, their careers and should have some experience in realizing this point. A further area of discussion on this topic is how one could whether there is a more accurate method to determine its value. The students are prompted to consider a revision of the experimental plan that involves performing initial rate experiments using ethanol as the feed. In this case, the reverse rate constant can be determined directly from a single set of experiments in the same manner as the forward rate constant. STUDENT PERFORMANCE the end of the semester to complete this project. They are reminded in class during this period that it takes time to obtain data and they should not wait for the last minute to begin collecting data. Most student groups have successfully determined forward and reverse rate constants for at least three temperatures and have obtained reasonable values for the activation energy and pre-exponential factor. Very few groups have been unable to determine these values. The most typical reasons are the group started their data collection too late in the semester to obtain enough data and/or they were budget. Grading of the project in these cases is based on their pattern of experimental data requests. Groups that started early and appeared to have a plan but didnt quite get enough good data are treated in a much more forgiving manner than groups that waited for the last minute to request all of their data with little or no planning. Groups have been formed both by students own selection and by assignment of the instructor. There have been fewer cases of incomplete or poorly executed projects with the assigned groups, in our experience. Groups are instructed not to discuss any aspect of the assignment with anyone out side of their group, including the exchange of experimental with this policy, analysis of requested experiments has not revealed any obvious signs of copying experimental designs between groups or the use of data that was not requested by a group. We note that no two groups have ever obtained the

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Chemical Engineering Education 38 same values for the Arrhenius parameters or used e xactly the same number of experiments in a given semester. We have not performed this analysis between different semesters. CONCLUSIONS The experimental design and statistical analysis project documented in this article has been developed to provide a realistic experience to students. Based on comments contained in course surveys, students have found the project to be in teresting and worthwhile. A number of students have made positive comments on the realistic nature of the experience. Although not incorporated into the scope of this project, ad ditional studiessuch as an analysis of variance to determine the sources of variability in the experimental datacan be included within the framework discussed in this article. This project has also provided valuable documentation of the stu dents ability to design, conduct, analyze, and interpret experi ments for Criterion 3b of the current ABET criteria. [10] ACKNOWLEDGMENTS A curriculum revision grant to the Villanova University Chemical Engineering Department from Air Products and Chemical Co. that supported the development of this project is gratefully acknowledged. We would also like to acknowledge the helpful advice of Dr. John Eaton on the development of the Octave simulation model software and the statistical analysis discussions with Profs. Dorothy Skaf of Villanova University and Babatunde Ogunnaike of the University of Delaware. REFERENCES 1. Nelson, P., and T. Wallenius, Improving the Undergraduate Statistical Education of Engineers, in G. Cobb, Reconsidering Statistics Educa tion: A National Science Foundation Conference, J. Stat. Educ., 1 (1) (1993) 2. Prudich, M., D. Ridgway, and V. Young, Integration of Statistics Throughout the Undergraduate Curriculum: Use of the Senior Chemi cal Engineering Unit Operations Laboratory as an End-of-Program Statistics Assessment Course, Proceedings of the 2003 ASEE Annual Conference (2003) 3. Romero, R., A. Ferrer, C. Capilla, L. Zunica, S. Balasch, J. Serra, and R. Alcover, Teaching Statistics to Engineers: An Innovative Pedagogical Experience, J. Stat. Educ. 3 (1) (1995) 4. Mustoe, L., and A. Croft, Motivating Engineering Students by Using Modern Case Studies, Int. J. Eng. Educ. 15 (6) (1999) mental Design Using a Laboratory Experiment, J. Eng. Educ. 84 (4) (1995) 6. Mackisack, M., What is the Use of Experiments Conducted by Sta tistics Students? J. Stat. Ed., 1 (2) (1994) Sets, J. Stat. Ed. 11 (1) (2003) 8. Fahidy, M., An Undergraduate Course in Applied Probability and Statistic, Chem. Eng. Ed. 36 (2) (2002) 9. Evans, M., N. Hastings, and B. Peacock, Statistical Distributions 3rd Ed., Wiley, New York (2000) 10. ABET, Criteria for Accrediting Engineering Programs, Engineering Accreditation Commission, (2004)

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Winter 2007 39 F orced convection inside circular pipes under fully developed conditions is one of the main subjects covered in both undergraduateand graduate-level heat transfer courses. Two types of boundary conditions are usually considered, i.e. wall temperature. In engineering calculations, heat transfer correlations are expressed in terms of the Nusselt number and such expressions require the solution of the energy equation given as Cv T z k rr r T r P z () 1 tions is given by vv r R zz 21 2 2 () the solution of Eq. (1) rather simple since the left side is depen dent only on r. Integration of Eq. (1) twice yields the Nusselt number equal to 48/11. This approach is presented in almost all textbooks on heat transfer and/or transport phenomena. In the case of constant wall temperature, however, the solution of Eq. (1) requires advanced mathematical skills in partial differential equations. [1] As a result of this mathematical complexity, the value of the Nusselt number is given as 3.66 in textbooks without presenting the analysis. Incropera and FORCED CONVECTION HEAT TRANSFER IN CIRCULAR PIPESISMAIL TOSUN Middle East Technical University Ankara, Turkey 06531 Copyright ChE Division of ASEE 2007 ChE

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Chemical Engineering Education 40 DeWitt, [2] for example, stated that: . . the solution may be obtained by an iterative proce dure, which involves making successive approximations to by a simple algebraic expression, but the resulting Nusselt number may be shown as Nu = 3.66. The method of Stodola and Vianello [3, 4] is an approximate The purpose of this paper is to show students how to apply this technique in the calculation of the Nusselt number for forced convection in a circular pipe when the wall temperature is constant. From my experience in teaching graduate-level Transport Phenomena and Heat Transfer courses, the method is well received by students. MATHEMATICAL ANALYSIS Consider the laminar flow of an incompressible New T o for z < 0. For z > 0, the wall temperature is kept constant at T w (T w > T o ) and we want to develop a correlation for heat transfer in terms of the Nusselt number under thermally fully developed conditions. B UL K T EMPERATURE G OVERNING E QUATION As engineers, we are interested in the variation of the bulk b rather than the local tempera T vT rd rd vr dr d Rv vT r b z R z R z z 0 0 2 0 0 2 2 1 d dr d R () 3 0 0 2 Since both v z to T Rv vT rd r b z z R 2 4 2 0 () The governing equation for the bulk temperature can be obtained by multiplying Eq. (1) by r dr and integrating from r = 0 to r = R, i.e ., Cv T z rd rk rr r T r rd r P z R R 1 0 0 () 5 Since v z z (z), the integral on the left side of Eq. (5) can be rearranged, with the help of Eq. (3), as Cv T z rd rC vT z rd r C d dz P z R P z R P 0 0 v vT rd r C Rv d z R P z 0 2 2 T T dz b () 6 On the other hand, the integral on the right side of Eq. (5) takes the form k rr r T r rd rk r T r R 1 0 rR r0 7 () w qk T r rR w () 8 so that Eq. (7) becomes k rr r T r rd rR q w R 1 9 0 () Substitution of Eqs. (6) and (9) into Eq. (5) results in the governing equation for the bulk temperature as dT dz q CR v b w P z 2 10 () THERMALLY FULLY DEVELOPED CONDITIONS expressed as z TT TT b wb 0 1 1 () Note that the thermally fully developed condition also implies When the wall temperature, T w is constant, Eq. (11) re duces to T z TT TT dT dz w wb b () 12 Substitution of Eq. (10) into Eq. (12) results in T z TT TT q CR v w wb w P z 2 13 () NUSSELT NUMBER FOR CONSTANT W ALL TEMPERATURE Nu hD k () 14 Newtons law of cooling as qh TT ww b () 15 so that the Nusselt number takes the form Nu qT TR k ww b / () 2 16

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Winter 2007 41 Elimination of the term q w between Eqs. (13) and (16) leads to T z Nu TT k CR v w P z 2 17 () Substitution of Eqs. (2) and (17) into Eq. (1) yields 21 2 2 Nu r R TT R rr r w T T r () 18 The boundary conditions associated with Eq. (18) are at z T T at r T r at rR TT o w 0 0 0 19 () In terms of the following dimensionless quantities 1 2 0 21 TT TT TT TT r R b wb w wb () () the governing equation together with the boundary conditions take the form 21 1 22 0 2 Nu d d d d at d () d at 0 2 3 1 0 24 () () It should be kept in mind that the dimensionless tempera (22) can be easily solved for Nu by the method of Stodola and Vianello. THE METHOD OF STODOLA AND VIANELLO The method of Stodola and Vianello [3, 4] is a successive ap 1 in the boundary value problem of the form d dx px dy dx wx y () () 25 with appropriate homogeneous boundary conditions at x = a and x = b. The procedure is as follows: 1. Assume a trial function for y 1 boundary conditions x = a and x = b. 2. On the right side of Eq. (25), replace y(x) by y 1 (x). 3. Solve the resulting differential equation and express the solution in the form yx fx () () () 1 26 1 1 (1) is given by 1 1 11 1 2 () () () () () () ( wx fx yx dx wx fx dx a b a b 2 27 ) 4. Repeat step (2) with a second trial function y 2 by yx fx 21 28 () () () 5. Solve the resulting differential equation and express the solution in the form yx fx () () () 2 29 1 1 (2) is given by 1 2 22 2 2 () () () () () () ( wx fx yx dx wx fx dx a b a b 3 30 ) 6. Continue the process until the desired convergence is obtained. For the problem at hand, comparison of Eq. (22) with Eq. (25) gives yxp Nu w 21 31 2 () () conditions is 1 2 1 3 2 () () Substitution of Eq. (32) into the left-side of Eq. (22) gives d d d d Nu 22 33 35 () The solution of Eq. (33) using the boundary conditions given by Eqs. (23) and (24) is Nu f 11 18 92 36 24 6 1 () () 34 from Eq. (27) as Nu fd fd () () () () () ( 1 22 1 0 1 2 1 2 0 1 1 1 3 35 ) Substitution of f 1 ation of the integrals gives Nu () ( ) 1 3 663 36 The trial function for the second approximation is 2 24 6 11 18 92 36 37 () () Substitution of Eq. (37) into the left-side of Eq. (22) gives

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Chemical Engineering Education 42 d d d d Nu 18 11 29 27 11 35 ( 7 79 23 8 )( ) The solution of Eq. (38) using the boundary conditions given by Eqs. (23) and (24) is Nu 2457 4400 2900 1200 275 32 28 2 4 6 8 10 ,, () 800 2 f () 39 Therefore, the second approximation to the Nusselt number is given by Nu fd fd () () () () 2 2 22 0 1 2 2 2 1 1 0 0 1 40 () Substitution of f 2 2 into Eq. (40) and evaluation of the integrals gives Nu 2 3 657 41 ( ) which is equal to the exact value calculated by Graetz and Nusselt. The solution of eigenvalue problems by the method of Stodola and Vianello gives accurate results and convergence is very rapid. Although the integrals seem formidable, they can be easily evaluated using engineering calculation software such as MATHEMATICA or MATHCAD. The method is easy to follow and students have no dif of the governing differential equation, Eq. (1), to the form to which the method of Stodola and Vianello is applied, Eq. (18) or Eq. (22), is also very helpful for students in grasping the concept of area averag ing and the difference between local and bulk temperatures, as well as their functional dependence on coordinate directions. NOMENCLATURE C P D Pipe diameter, m Nu Nusselt number, dimensionless q w 2 R Pipe radius, m r Radial coordinate, m T b T w v z Axial velocity, m/s v z Axial average velocity, m/s z Axial coordinate, m Greek symbols 3 REFERENCES Laminar Flow in a Round Tube or Flat ConduitThe Graetz Problem Extended, Trans. ASME 78 441 (1956) 2. Incropera, F.P., and D.P. DeWitt, Fundamentals of Heat and Mass Transfer 5th Ed., Wiley, New York (2002) 3. Bird, R.B., R.C. Armstrong, and O. Hassager, Dynamics of Polymeric Fluids, Volume 1: Fluid Dynamics 2nd Ed., Wiley, New York (1987) 4. Hildebrand, F.B., Advanced Calculus for Applications 2nd Ed., Prentice-Hall, Englewood Cliffs, NJ (1976)

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Winter 2007 43 C reating a working knowledge of biological principles in students and developing their ability to apply engineering principles to biological systems (and vice versa) is recognized nationwide as a goal for chemical engineering programs. [1-5] The same can be said from a global perspective. [6] faculty expertise in bio-focused engineering. [7] Bioengineering is very broad and inherently interdisciplinary. The need for bioengineers is on the rise. By 2010, there is projected to be a 31.4% increase in employment positions in bioengineering [8] Moreover, most engineering jobs listed in the Fast Company 25 Top Jobs are bio-related. [9] To meet the needs of the global job market todays chemical engineering students must receive a solid background in biology. The conventional approach is to add a standard biology course, and many schools do offer biology courses at the senior or graduate level. [10, 11] The integration of biology in the undergraduate chemical engineering curriculum, howeveralthough dif holistic and rewarding learning experience. INTEGRATING BIOLOGY INTO THE UNDERGRADUATE CHE CURRICULUMPATRICIA MOSTO, MARIANO SAVELSKI, STEPHANIE H. FARRELL, AND GREGORY B. HECHTRowan University Glassboro, NJ 08028 Copyright ChE Division of ASEE 2007 ChE

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Chemical Engineering Education 44 way of teaching integrates both biology and engineering. The biology provides knowledge and skills dealing with biological concepts as the building blocks for engineering design and process. It may also create a whole-system perspective neces sary for innovation and creativity. The engineering provides access to existing technologies with an emphasis on the design process itself. At Rowan University, we have developed such an integrated, collaborative approach between engineering and biology faculty to introduce chemical engineering stu dents to the application of engineering principles in biologi cal systems throughout their four-year curriculum. Through specially designed courses and active learning modules that can be easily adapted to any course, students are exposed to the newest biological trends for chemical engineering. The implementation of this philosophy exposes students to key areas of collaboration between biologists and chemical en gineers at early stages in their undergraduate education, and continues systematically during the upper years. This strategy develops a cumulative knowledge of biological principles in students, enabling faculty to build increasing detail and technical content into problems and projects that address the interface between biology and engineering. This application allows students to work in interdisciplinary teams, think in a more global fashion, create innovative ideas, and enhance their entrepreneurship and communication skills. Revisions to the chemical engineering curriculum at Rowan University include: several laboratory modules and projects at the freshman and sophomore levels; a novel, required Biological Systems and Applications course designed to in troduce students to a variety of biological principles relevant to chemical engineering [23] ; vertical integration of experi ments and applications of bio-related engineering analysis in core engineering courses; collaborative research projects involving biologists and chemical engineers in their junior and senior years; team-taught senior chemical engineering elective courses with strong biological components; and a bioengineering concentration for those graduating with a cadre of bio-related courses. As the only four-year engineering college in Southern New Jersey, Rowan Engineering is deeply committed to being a major technological resource for the area, preparing students for engineering careers in regionally important industries such as biomedical, biotechnology, pharmaceutical, and food. The abundance of such industry in New Jersey and nationwide creates a steady demand for well prepared engineering gradu ates. Our collaborative approach to integrating biology and chemical engineering helps prepare students for careers in food, biotechnology, and pharmaceutical industries. This paper will discuss the implementation, impact, and and juniorand senior-level engineering experiences. A de tailed description of the integration of biological principles into the lower levels has been published previously. [12] EXPERIENCES AT THE FRESHMAN LEVEL Generally speaking, the Freshman Clinic sequence corre sponds to Introduction to Engineering courses in many other universities, though in unique format. It consists of two parts. In the fall semester we teach basic engineering skills (such as problem solving and teamwork fundamentals) and ethics that will be essential to students success (or even survival) in engineering school and in their future engineering careers. In the spring semester students are exposed to an intense study of engineering design through reverse engineering (or dissec tion) and competitive assessment of consumer products. [13, 14] Comparable products are reverse engineered to gain under standing of the mechanisms by which they work. In the Freshman Clinic we immediately establish a handson, active-learning environment in which students are intro duced to a wide range of engineering principles applied to both biomedical and biochemical systems. [11, 15-18] A strategy for introducing biological concepts throughout a traditional engineering curriculum using examples, demon strations, and experiments has been presented by Maynard and Razatos. [19] Their approach provides graduating engineers with the skills to handle nontraditional problems and to address emerging areas of research and development. We use a similar approach in integrating biological concepts throughout our core chemical engineering courses at Rowan. An important feature of our implementation method is the emphasis on vertical integration of bio-related course materials and labora tory experiments throughout core courses. Vertical integration enhances educational quality by integrating concepts, skills, models, and data throughout all levels of the curriculum, building upon not only the work done in the previous labora tories of the same course but also those of previous courses. Re-using experiments in freshman, core, and elective courses, use of laboratory equipment and space. This truly integrated learning experience enhances student learning, concept reten tion, and motivation. [20-22] The Freshman Engineering Clinic biomedical engineer ing project mentioned previously in this paper is used here as an example to illustrate the vertical integration of topics throughout the curriculum. Through eight hands-on modules, students in the freshman course are introduced to a variety of multidisciplinary biomedical topics. Each topic is then explored in greater depth in the appropriate core courses of the chemical engineering curriculum. Table 1 shows the topi cal content of the eight hands-on modules taught during the ments, calculations, and engineering principles (columns 2, 3, and 4). The engineering courses into which the experiments, analysis, and concepts are integrated appear in the right-most

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Winter 2007 45 column of the table. While the vertical integration of the courses is multidisciplinary and involves other engineering and science disciplines, this table shows only the information that is directly related to the vertical integration into chemical engineering courses. EXPERIENCES AT THE SOPHOMORE LEVEL To meet the anticipated growing demand for biology-liter ate engineers, faculty from biological sciences and chemical engineering worked closely together to develop a lab-inten sive course open only to sophomore chemical engineering majors. A detailed description of the Biological Systems and Applications (BS&A) topical content and laboratory exercises has been described previously, along with an assessment of the effectiveness of the course. [23] Concurrent with the Biological Systems and Applications course, students take Sophomore Clinic I and II, a multi disciplinary engineering design and practice two-semester course sequence providing them the necessary technical communication tools. The students work in teams of three sessions are structured so that parallel activities support the eventual completion of the project. In the semesterlong project student teams design and create a microbial fuel cell (MFC) that powers a Lego Mindstorms robot. The design of microbial fuel cells provides an ideal application for many concepts taught in the BS&A course. [23] In conjunction with management and writing, and the second semester focuses on public speaking. EXPERIENCES AT THE JUNIOR LEVEL As part of the clinic sequence at Rowan Engineering, stu dents participate in sponsored research projects during their junior and senior years. Each semester, students work in multidisciplinary teams as part of a two-credit course. Project T ABLE 1 Biomedical Engineering Modules: Measurements, Calculations, Engineering Principles, and Vertical Integration of Project Modules into Chemical Engineering Courses Measurements Calculations Engineering Principles Vertical Integration Respiration O 2 CO 2 concentration Gas volumes Moles of gas Rate of gas consumption and production Material balances PVT relationships Mass & Energy Balances Biomedical Processes (elective) Metabolism Food intake Energy expenditure Body surface area Material balances Energy balances Stoichiometry Correlations Dimensional homogeniety Mass & Energy Balances Biomedical Processes Pulmonary System Lung volume Air pressure Blood O 2 % saturation PV work Rate of heat transfer Dissolved O 2 concentration Mass transfer/separations PV work Energy balance Gas solubility/Henrys Law Resistance/Poisieulles Law Thermodynamics Mass Energy Balances Fluid Flow Separations Biomedical Processes Cardiovascular System Heart rate Blood pressure system principle Hydrostatics Pumpspower and Fluid Mechanics Work/Power Force Distance Recovery time Work Power Work Energy Power Dynamics (ME, ECE) Mechanics of Materials For bone and cartilage: Force (tension and compression) Deformation (tension and compression) Stiffness Dampening Stress Strain Forces Deformations Materials Science

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Chemical Engineering Education 46 funding is provided through either government or industrial grants or sponsorships. Projects span a wide variety of emerg ing disciplines, depending on faculty expertise and availability of funding. The number of projects that involve integration of biology with chemical engineering has increased dramatically during the seven years the Junior/Senior Clinic has existed. Their preparation during the Biological Systems & Appli cation course allows students to tackle these bio-oriented projects and succeed in their upper-class work. At the conclusion of four semesters of Junior/Senior Clinic activities, students are expected to: Demonstrate expanded knowledge of the general prac tices and the profession of engineering through immer sion in engineering projects of moderate complexity. Demonstrate an ability to work effectively in a multidis ciplinary team. Demonstrate acquisition of new technology skills. Demonstrate understanding of business and entrepre neurial skills. Demonstrate effective use of project and personnel management techniques. Integrate engineering professionalism and ethics in their work as it relates to the context of engineering in society. Demonstrate improved communication skills including written, oral, and multimedia. Use information obtained from sources that cross geo political and language barriers. PROJECT 1: BIOETHANOL GENERATION Currently only 2% of U.S. energy needs are met by renew able resources. The National Renewable Resources Labora tory (NREL), however, projects that biomass resources can eventually provide more than 50% of transportation fuel, reducing dependence on foreign sources of energy, alleviating air pollution problems, and increasing employment oppor tunities. Bioethanol is one biofuel that has been receiving a great deal of attention in recent years. One factor suppressing wider use of bioethanol is the costs associated with produc tion. In North America, most bioethanol is made from the fermentation of corn. This process sets aside the stalks and leaves of the corn plant referred to as corn stover. It has been estimated that if the corn stover available from current crop in North America could be tripled. [30] Because of its cellulose and hemicellulose content, however, corn stover is more waste product of corn farming. In particular, the preparation of the fermentation feedstock and the subsequent increase in ethanol concentrations can be toxic to the fermenting microorganisms. The overall objective of this project is to create and characterize new strains of the bacterium Esch erichia coli with the potential to sidestep these issues and, as a result, produce greater yields of ethanol from corn stover. For this project, teams of student researchers are assembled as a cohort of two biology and two chemical engineering majors, and each cohort works with a team of four professors (two from biology and two from chemical engineering). The student cohorts select a particular toxicological problem to investigate over a two-year period. The sum of each cohorts that include extensive biological and engineering literature search and review, isolation of novel toxin-resistant deriva toxicological properties of the new strains, pilot fermentation studies to demonstrate the effectiveness of the new strains, and presentations of their results at national microbiology and chemical engineering conferences. This module ap proach and the cohort composition allows an emphasis on multidisciplinary learning. The experiments conducted by the students address applied microbiology, toxicology, fer mentation technology, engineering design, economics, and professional communication. A conscientious effort is made to ensure that all students in the cohort participate in all phases of the experimental design and execution, including determin ing the effects of altering process variables ( e.g. feedstock composition), isolation, and characterization of the biological catalyst with the desired properties, assessing the impact of these activities on the process conditions of the downstream operations and the overall economic feasibility of the system, and disseminating the results at professional venues. PROJECT 2. ASTAXANTHIN PRODUCTION Haematococcus pluvials is one of the largest algal produc ers of astaxanthin, a carotenoid that is commonly used as a feed supplement in the salmon farming industry to give the salmon their pinkish hue. Astaxanthin is the ideal component to color the salmon because it is a stable natural product and established [24] that extreme light conditions yield a higher production of astaxanthin in H. pluvials however exact lightto-dark time periods for optimum astaxanthin production are unknown. The goal of this project was to determine the proper lighting conditions for optimum astaxanthin production by H. pluvialis so a pilot scale plant for large-scale production could be constructed. Two students, one from biology and one from chemical engineering, work over the course of a year with two professors (one from biology and one from chemical engineering). The students grow H. pluvialis in an environmental chamber at different light/dark cycles (16/8, 20/4, 24/0) and constant temperature (26 C) to determine the best light-to-dark ratio for maximum astaxanthin produc tion. Chlorophyll a, ash-dry biomass, and a cell count were obtained daily for each of the growth conditions to establish the optimum growth curves for H. pluvialis Correlations

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Winter 2007 47 between growth and astaxanthin production were studied, and a continuous bioreactor for pilot scale production for H. pluvials was designed, constructed, and tested. The 16/8 light-to-dark ratio was used, and it was possible to grow the algae in one compartment and use gravity feed to a separate compartment where the algae were stressed ( e.g. longer light cycle, carbon dioxide bubbled into reactor) to enhance astaxanthin production. Several aspects of the reactor were algae production facility. This years Junior/Senior Clinic will complete the design of the reactor. OTHER PROJECTS The Junior and Senior Engineering Clinic projects described above are just a few examples of collaborative, multidisci plinary projects that integrate biological and engineering prin ciples. Additional clinic projects have investigated problems related to drug delivery, food preservation, pharmaceutical The clinic has proven to be a very effective vehicle for development of educational experiments and course con tent. The biomedical, drug delivery, and food engineering modules that are integrated throughout the curriculum were developed via the clinic. In a typical project, students would be responsible for collecting background material, building the experimental apparatus, developing the experimental procedure and methods of data analysis, writing a detailed laboratory handout for students, and providing an instructors manual for a module on a given topic. EXPERIENCES AT THE SENIOR LEVEL Rowan Engineering is committed to being a major techno logical resource for the area, preparing students for engineer ing careers in regionally important industries such as food processing. The state has major manufacturing operations of top companies such as The Campbell Soup Co., Coca Cola, ate Vineland area is the hub of Southern New Jerseys food processing industry, home to about 30 companies employing 3,000 people and producing $700 million in shipments. The abundance of food processing companies in New Jersey de mands a steady pipeline of well-prepared engineering gradu ates. Rowan Engineering students respond to the regional emphasis on food processing with a tremendous interest in the industry. In their senior exit interviews, an overwhelm ing number of graduating seniors strongly indicated a need for more exposure to food-oriented projects and courses. To respond to student demand and regional industrial needs, chemical engineering faculty have secured support in recent years for undergraduate clinic research projects. Food ex periments have been introduced to all engineering students in the Freshman Engineering Clinic (a multidisciplinary, introductory course required of all freshmen) and a new Food Engineering elective course was designed for chemical engineering students. This course provides students with the necessary background in food science, food chemistry, unit operations relevant to food industry (rarely taught in traditional chemical engineer designed and taught by biological science faculty. The discipline of biomedical engineering has emerged from informal collaborations between engineers, physicians, and life scientists. While relatively new, it is the fastest-growing engineering discipline at most universities. [20] Chemical engi neers play an important and expanding role in this burgeoning organs and drug-delivery devices. This course introduces students to applications of chemical engineering fundamentals and biomedical systems. Students analyze and design biomedical processes through the appli cation of advanced principles in mass transfer, heat transfer, the circulatory system, transport across cell membranes, and are conducted to explore the circulatory system, respiration, metabolism, and cardiopulmonary dynamics. It should be noted that many of the basic biomedical concepts have been vertically integrated throughout the cur riculum, beginning with freshman biomedical modules recourse permits these topics and experiments to be explored in ated physiology and other biological concepts. Controlled-release systems are designed to provide delivery of a biologically active agent ( e.g. a drug or pesticide) at a predetermined rate for an extended period of time. Controlled release offers several advantages over traditional methods of formulation and administration such as: maintenance of ef fective concentrations for a sustained period, less total agent required, cost effectiveness, convenience, and compliance. This course on controlled-release systems introduces students to chemical engineering fundamentals applied in controlledrelease systems. Basic principles of materials, mass transfer, analyze and design controlled-release systems. Applications to pharmaceutical, agricultural, and food industries are explored, with a primary focus on drug delivery systems. Several labo ratory experiments are conducted to explore drug stability, membrane-based transdermal patches, controlled-release tablets, erodible and dissolution-based systems, and osmotic pumps. [26] Drug delivery topics represent another example of

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Chemical Engineering Education 48 vertical integration of experiments and examples throughout in the freshman year, and drug delivery examples are revis ited in core courses such as Transport Phenomena and Mass Transfer. In the senior-level elective on controlled release, students explore drug delivery systems in greater depth, with more emphasis on topics such as distinguishing rate-control ling mechanisms and pharmacokinetic considerations. IMPACT IN THE CURRICULUM The combination of modules at the freshman and sopho more level, the Biological Systems and Applications course projects as part of junior and senior clinics, the elective se nior courses in Food Engineering, Biomedical Engineering and Drug Delivery, and the Concentration in Bioengeneering all help prepare students for a future career in research and industry. Located in Southern New Jersey, Rowan University, through its Junior/Senior Clinic, has successfully completed a wide range of projects generated and sponsored by local industries and agencies. These include private companies (e.g., Biothane, US Filter, Lockheed Martin, Johnson Matthey, General Mills, ExxonMobil) and research foundations ( e.g., Engineering Information Foundation, Water Environment both the faculty and the students. [27] Students are more likely to obtain internships as a result of these experiences, and en regional interest strengthen their industry interactions and the types of clinic projects offered in the Junior/Senior Clinic course, such as bioethanol production, astaxanthin production, drug delivery, and food engineering. Working cooperatively with local industry has also enabled students to obtain valu able entrepreneurship experience in supporting smalland medium-size businesses. As part of clinic projects, students may propose their own ideas and gain funding through the Na tional Collegiate Inventors and Innovators Alliance (NCIIA) Venture Capital Fund. This fund is managed by a faculty original inventions by multidisciplinary student teams within the Junior and Senior Clinics. [28] Students often cite a potential career in biochemical engi neering as a motivator for pursuing a chemical engineering degree. This interest in the interplay between biology and engineering is apparent in the demand by students for biooriented research projects at the junior and senior levels. One measure of student interest in bio-related projects is their participation in Rowan Universitys student symposium in the Science, Technology, Engineering, and Math (STEM) Symposium. As shown in Figure 1, the percentage of biorelated engineering projects that have been presented at the symposium has increased dramatically. In 1998, only one engineering abstract at the symposium had biology content. By 2004, the number of posters with engineering students pursuing biology-related projects was similar to the number of nonbiology engineering posters. Importantly, Figure 1 demonstrates that 2004 was not a peak but the realization of a new status quo, since subsequent years have had similar numbers of bioengineering presentations. In many cases, the students working on research projects at Rowan University. As the beginning cadre of students who have been exposed to these innovations in the curriculum progresses, we expect to develop new engineering courses on mo lecular biotechnology or bioengineering that will be part of the new bioengineering concentration approved this year within the College of Engineering. Preparing students early in their college career through a specially designed course and bio-related modules during their Freshman and Sophomore Clinics yields excellent results on their bioengineering clinic project and courses in their junior and senior year. Additionally, students are able to learn more material and applica tions in the time that is traditionally spent in an introduction to biological principles. Also, the Junior/Senior Clinics fostered a strong research environment, evidenced by the percentage of students pursuing graduate degrees as shown in Figure 2. [29] 1 0 2 4 6 8 1 0 1 2 1 4 1 6 1 8 2 0 2 2 1 9 9 8 1 9 9 9 2 0 0 0 2 0 0 1 2 0 0 2 2 0 0 3 2 0 0 4 2 0 0 5 2 0 0 6 Y e a r N u m b e r o f A b s t r a c t s B i o l o g y A b s t r a c t s w / E n g i n e e r i n g S t u d e n t s E n g i n e e r i n g A b s t r a c t s E n g i n e e r i n g A b s t r a c t s w i t h B i o l o g y C o n t e n t Figure 1 Number of bio-oriented abstracts and total abstracts submitted by engineering students at Rowan Universitys STEM Symposium.

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Winter 2007 49 The impact of the clinic model has been very positive in foster ing a spirit of inquiry and engaging students in cutting-edge research as undergraduates. chemical engineering graduates are considered. The AIChE Placement Survey for Recent Graduates from domestic institutions indicates that 22.5% of chemical engineering graduates found work in biotechnology, pharmaceutical, and food industries. A survey of Rowan Chemical Engineering graduates reveals that more than 27% of chemical engineering graduates found employment in these industries. SUCCESSFUL IMPLEMENTATION The implementation of these innovations into the curricu lum was relatively smooth, particularly considering that it has required cooperation across not just separate departments but also separate colleges within the university. We believe that several factors were crucial to this success. Foremost, the culture on the Rowan campus during the implementation process was focused on de-emphasizing the protection of turf by the academic departments and moving towards interdisciplinary activity. Importantly, relations be tween the Departments of Chemical Engineering and Biologi cal Sciences were collegial at the start of the implementation, as were the interactions between the deans of the College of Engineering and the College of Liberal Arts and Sciences. Moreover, both the engineering and the biology personnel process. While the curricular development described here has gineering department, it has also resulted in dividends for the Department of Biological Sciences. No less than four biology faculty have been involved in numerous collab orative research projects, some of which received external funding. Even better, the addition of biology to the curriculum has provided additional research opportunities for biology majors. Incremental implementation was also im portant. Incorporation of biological content and application into the curriculum required resources from both departments, which to some degree necessitated a stepwise ap proach. Initial steps involved the establish ment of biology projects in the Freshman and Sophomore Clinics and the creation of the sophomore Biological Systems & Ap plications course. Subsequent changes in the curriculum at the junior and senior levels would not have been successful without the prior addition of both content and experien tial knowledge at the lower levels. The future of chemical engineering is in nanoand bio technology. This curriculum, with its integrative biological components, is at the front of future education. ACKNOWLEDGMENTS Funding for the development and integration of the biomed ical and drug delivery modules was provided by grants from the National Science Foundation, Division of Undergraduate Education: DUE-CCLI 0088437 and DUE CCLI 0126902, respectively. NSF REU EEC #0353744 provided additional support for the development of drug delivery experiments. REFERENCES 1. American Institute of Chemical Engineers, 2001-2002 Initial Placement of Chemical Engineering Graduates 2. Baum, R.M., The Engineering Approach to Molecular Biology, Chem. and Eng. News 76 (13) (1998) 3. Breslow, R., Into the Future, Chem. and Eng. News 78 (47) (2000) 4. Rawls, R.L., Biochem Meets Engineering, Chem. and Eng. News 77 (35) (1999) 5. Westmoreland, P.R., Chemistry and Life Sciences in a New Vision of Chemical Engineering, in Annual Meeting of the American Institute of Chemical Engineers, Los Angeles (2000) 6. Oberholz, A., Chemicals in 2010Systems Solutions for the Cus tomer, CHISA Conference, 1492 (2004) 7. AIChE Annual Meeting, San Francisco (2003) 8. U.S. Department of Labor, Bureau of Labor Statistics, Employment Outlook: 20002010, Monthly Labor Review (2000) 9. 10. Lauffenburger, D.A., A Course in Cellular Bioengineering, Chem. Eng. Ed. 23 (4) (1989) 11. Oerther, D.B., Introducing Molecular Biology to Environmental 1 0 0 0 % 5 0 0 % 1 0 0 0 % 1 5 0 0 % 2 0 0 0 % 2 5 0 0 % 3 0 0 0 % 3 5 0 0 % 4 0 0 0 % 4 5 0 0 % 2 0 0 0 2 0 0 1 2 0 0 2 2 0 0 3 2 0 0 4 2 0 0 5 Y e a r S t u d e n t s P u r s u i n g G r a d u a t e S t u d i e s P e r c e n t M a l e P e r c e n t F e m a l e P e r c e n t T o t a l Figure 2 Percentage of students pursuing graduate degrees. [28]

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Chemical Engineering Education 50 Engineers Through Development of a New Course, Chem. Eng. Ed. 36 (4) (2002) and Chemical Engineering at the Lower Levels, Chem. Eng. Ed. 38 (2) (2004) 13. Farrell, S., A Laboratory Project to Design and Implement a Process for the Production of Beer, Proceedings of the American Society of Engineering Education Conf. (1999) Society of Engineering Education Conference (1999) 15. Farrell, S., R.P. Hesketh, and M.J. Savelski, A Respiration Experiment to Introduce Chemical Engineering Principles, Chem. Eng. Ed. 38 (3) (2004) 16. Farrell, S., and R.P. Hesketh, An Introduction to Drug Delivery for Chemical Engineers, Chem. Eng. Ed. 36 (3) (2002) 17. Farrell, S., J.A. Newell, and M.J. Savelski, Introducing Chemical Engineering Students to Product Design through the Investigation of Commercial Beer, Chem. Eng. Ed. 36 (2) (2002) 18. Farrell, S., R.P. Hesketh, J.A. Newell, and C.S. Slater, Introducing Freshmen to Reverse Process Engineering and Design through Inves tigation of the Brewing Process, I.J.E.E. 17 (6) (2001) 19. Maynard, J., and A. Razatos, The Evolution of Engineering: Incorpo rating Biology into Traditional Engineering Curriculum, Proceedings of the ASEE Annual Conference, Session 2313 (1999) 20. McDonald, D., A. Mahajan, and M.E. Walworth, NSF EHR 9751372 (1997) velopment of an Innovative Undergraduate Laboratory that Emphasizes Vertical Integration in Multiple Engineering Curricula, Proceedings of the ASEE Annual Conference, Session 2526 (1999) Integrated Systems Engineering LaboratoryAn Innovative Approach to Vertical Integration using Modern Instrumentation, Proceedings of the ASEE Annual Conference, Session 2259 (1999) 23. Hecht, G.B., P. Mosto, and C.S. Slater, Effectiveness of an Applied Majors, Microbiology Education ( 2002) Intensity and Light Quality on Astaxanthin Formation in a Green Alage, Haematococcus pluvialis, J. Fermentation and Bioengineering 74 (1) (1992) 25. First Leadership Awards Made: Hopkins and UCSD get $30 Million Total, The Whitaker Foundation, Biomedical Engineering News (1998) 26. Farrell, S., R.P. Hesketh, M.J. Savelski, and C.S. Slater, Fundamentals, Design and Applications of Drug Delivery Systems, ASEE Annual Conference, Session 1313 (2003) 27. Dorland, D., and P. Mosto, The Engineering Clinics at Rowan Univer sity: A Unique Experience, Proceeding of the International Congress of Chemical and Processing Engineering (2006) Culture at a Startup Engineering Program, Proceedings of the Ameri can Society of Engineering Education Conference (2004) Gephardt, and S. Chin Engineering Clinics: An Integration of Re search into the Undergraduate Engineering Curriculum, Council on Undergraduate Research Quarterly, (3) (2006) 30.

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Winter 2007 51 I f youre like most faculty members, you began your academic career knowing very little about what youd be doing for a living. You knew about working on a research about starting and managing a research program, planning and delivering courses, and dealing with the hundreds of technical and management problems that always crop up in research and teaching. No one told you much about those things after by trial-and-error. This bizarre approach to career development has unfortu nate consequences. Roughly 95% of new faculty members institutions expectations for research and teaching. [1, 2] The remaining 5%, howeve r the ones Robert Boice [1] calls Considering the enormous investment institutions make in each faculty member they hire, moving more of the new ones into the quick starter category would clearly be good for everyonethe new faculty, their institutions, and the students they will teach and mentor. Converting new faculty members into quick starters is not guidance on how to teach well, do good research, and balance the competing demands of teaching, research, service, and personal life, and supplement this orientation with one-on-one mentoring by skilled senior colleagues. A program containing those elements has been in place since 2000 in the N.C. State University College of Engineer ing. We offer it as an example of what can be doneand in our opinion, what should be doneto help new engineering faculty make the transition to their new careers quickly and (Brent, et al. [3] provide more details) and summarize the les sons we have learned from our experience with it.THE NCSU NEW -F ACULTY SUPPORT PROGRAM The centerpiece of the NCSU program is a four-day orien tation workshop held in mid-August. It covers grantsmanship, recruiting and working with graduate students, designing courses and getting them off to a good start, effective lecturing and active learning, advising, time management, and dealing with a variety of crises faculty members commonly encounter. All presentations are highly interactive, and the presenters in clude some of the best teachers and researchers on the faculty as well as key administrators and support staff. The workshop 2001 it has been given jointly to new faculty in the Colleges of Engineering and Physical and Mathematical Sciences. TURNING NEW FACULTY MEMBERS INTO QUICK STARTERSREBECCA BRENT Education Designs, Inc.RICHARD M. FELDER North Carolina State University Random Thoughts . Copyright ChE Division of ASEE 2007

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Chemical Engineering Education 52 The orientation workshop is followed by a series of hourlong sessions during the academic year that reinforce work shop material and help maintain a sense of community among the participants. Topics addressed include troubleshooting teaching, dealing with funding agencies, and writing effective proposals for CAREER Awards. (Workshop alumni have an excellent record of landing them.) Another component of the support program is mentoring. In 2000, all departments iden would provide support to their new hires, and formal mentor ing programs have been initiated in several departments. [3] The response of the new faculty has been overwhelmingly positive. The participants to date have given the orienta tion workshop 99 overall ratings of excellent, 12 good, and no average, fair, or poor ratings. Past workshop nonparticipants to their career orientations, and preliminary assessments indicate that they have outperformed the nonparticipants in terms of both funded research activity and teaching evaluations. The program has maintained a high level of administrative support and has become a strong selling point for recruiting new faculty.RECOMMENDATIONS We have the following suggestions for schools planning their own new-faculty support programs. Keep the program at the school/college level rather than making it campus-wide. Many universities have teaching centers that provide new faculty orientation, but since the organizers have to address faculty in all disciplines, they generally limit the program con As important as those topics may be, such programs dont do much to convert new faculty into quick starters. When orien related disciplines, presenters can use research and teaching examples that are clearly relevant to the participantsand the greater the perceived relevance of presented material, the greater its likely impact on the recipients. Get strong and visible support from the dean and depart ment heads. If the director of a teaching center or the associate dean for academics invites new faculty members to attend a four-day few are likely to show up, while if the dean and department heads strongly encourage attendance and share positive evalu ations from past workshop participants, most new faculty will attend. Provide guidance on both research and teaching and discuss how to balance them. Most new faculty are nervous about meeting expectations for research productivity. Providing guidance on how to do it is an excellent way to persuade them that the workshop is worth their time. Presenters should also emphasize strate for maintaining a balance of teaching, research, service, and personal life consistent with the institutions expectations and the faculty members health and sanity. Keep the presentations practical and interactive. A workshop that is mainly a parade of talking heads is generally not worth the time it takes to prepare and present it. If a designated presenter doesnt know how to design and deliver an effective interactive presentation, someone else who does should provide some coaching. Treat the participants well. The new faculty should feel welcomed into the academic community, and treating them well is one way to make that happen. Hold the workshop in a convenient, comfortable location and dont skimp on the budget for meals and breaks. Provide useful resources in a well-organized notebook. Post lists of good local restaurants, parks and playgrounds, cultural attractions, and automobile repair shops. End the workshop with a celebratory reception and invite all the department heads and mentors to attend and interact with the participants. Make sure mentoring in teaching and research is provided by skilled and supportive colleagues who know something about how to mentor. [4] In summary, if the goal is to convert new faculty members into quick startersproductive in research and effective in of us got ( i.e. none) is all thats provided, there is a one-intwenty chance of succeeding. The strategies weve proposed should improve the odds considerably.REFERENCES 1. R. Boice, Advice for New Faculty Members Needham Heights, MA: Allyn & Bacon (2000) 2. R.M. Felder and R. Brent, The New Faculty Member, Chem. Engr. Education 32 (3), 206207 (1998), 3. R. Brent, R.M. Felder, and S.A. Rajala, Preparing New Faculty Members to be Successful: A No-Brainer and Yet a Radical Concept, Proceedings of the 200 6 Annual ASEE Conference Washington, DC: ASEE (2006), 4. R.M. Felder, Teaching Teachers to Teach: The Case for Mentoring, Chem. Engr. Education 27 (3), 176 (1993), All of the Random Thoughts columns are now available on the World Wide Web at

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Winter 2007 53 S ix Sigma is a buzz term in todays technology and business worlds. In organizations like Motorola, GE, DuPont, 3M, IBM, Dow Chemical, and PPG, Six Sigma means a measure of quality that strives for perfection. [1] Statistically, it means reducing the process variation so that six standard deviations lie between the mean and the nearest probability is 3.4 per million. [1, 2] Six Sigma methodology has been successfully applied to manufacturing (especially chemi cal and related manufacturing), to research and development, Six Sigma methodology combines elements from several quality movements with advanced statistical methodology. It is a comprehensive tool combining business concepts with technical and leadership skills, and thus it is suitable for pro fessionals at all levels: managers, engineers, and scientists. Recently, there has been great interest in initiating Six Sigma training in college education. This paper reports the success of incorporating Six Sigma methodology into a traditional chemical engineering course, Engineering Experimentation, at Texas Tech University. CHE 3343/4372, Engineering Experimentation, is a tradi tional undergraduate elective course in the chemical engineer ing curriculum at Texas Tech University. The original catalog experiments; analysis of data, interpretation, and presenta tion results. The course provided an excellent opportunity to incorporate Six Sigma methodology training into traditional engineering education. In practice, the instructor starts the course with an introduction of the fundamentals of Six Sigma methodology, emphasizing the D.M.A.I.C. process that refers INCORPORATING SIX SIGMA METHODOLOGY TRAINING LENORE L. DAITexas Tech University Lubbock, TX 79409 Copyright ChE Division of ASEE 2007 ChE

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Chemical Engineering Education 54 Control (C). [3] The course is then organized to discuss various methodologies and tools in each process stage. For example, chart are heavily emphasized to evaluate measurement sys tems in the process stage of Measure (M). The tools in the process stage of Analyze (A) overlap with various classical topics in Engineering Experimentation, including: design of experiments (DOE) and analysis (focused on two-level full, half, and highly fractionated factorial designs and analyses), residual and model adequacy analyses, regression model, and while to note that a small fraction of Six Sigma management stage. For example, we have discussed a S.M.A.R.T. goal realistic, and time bounded), thought map (a road map that is composed of different paths of questions), Six Sigma team development, and effective meeting management. A summary of the different topics discussed in each stage of the course is included a request to write a S.M.A.R.T. goal for this course a group format, answer questions about the course includ improvement is needed (M, measurable), what do we agree upon as a team (A, agreed upon), whether the goal can be accomplished by the given available resources (R, realistic), and what the expected dates for major milestones are (T, time bounded). The full D.M.A.I.C. process is then practiced through a formal Catapult Project, discussed later, accounting SPECIAL HOMEWORK ASSIGNMENTS The homework assignments in CHE 3343/4372 include the problems in the textbook Design and Analysis of Experi ments [4] and special problems generated by the instructor. For example, the instructor provided raw data of several projects in CHE 4232, Unit Operations Laboratory (permitted by the class and the instructor Professor T. Wiesner), and requested students perform new analyses using the tools learned in CHE 3343/4372. Such assignments give students opportuni ties to work on practical problems related to other chemical engineering subjects and, more importantly, allow them to practice the Six Sigma methodology by solving practical chemical engineering problems. In addition, the instructor typically has several nontraditional homework assignments, such as a card-drop exercise related to variation and creativity, a paper airplane mini-project using a 2 2 full-factorial design to landing distance, and another card-drop exercise to conduct a 2 3 surface area, and releasing height on target landing.THE CATAPULT PROJECT Tell me, Ill forget; show me, Ill remember; involve me, I will understand. [5, 6] Without doubt, designing and practic ing are the heart of engineering majors. This is an important element in CHE 3343/4372, Engineering Experimentation. A formal Catapult Project assignment, which includes an individual project report, a group presentation, and a group competition, has been assigned for the last four successive years and counts 15% toward the total grade. Catapults are used by more than 200 companies as a training aid in Six Sigma methodology training. A snapshot of the catapult used in CHE 3343/4372 is shown in Figure 2. The project includes four major elements. First, the students are assigned to work in project teams (three to four students per team) to investigate the performance of their catapults includ ing evaluating the measurement system and performing factor(s). Second, each student works independently to analyze the collected raw experimental data and submit a formal individual project report. Third, the project performance prediction and makes a formal project pre sentation to the entire class. Lastly, the team will use its developed model for a project competition. During the project competition, the instructor will place the target each team needs to launch the ball within three minutes with the goal of hitting the target. Figure 3a shows a brief map of the setup in the project competition and Figure 3b is a snapshot of a ball approaching the target in a 2004 class competition. The Catapult Project has given the students a unique opportunity to practice the Six Sigma D.M.A.I.C. Define Measure Analyze Improve Control Six Sigma Concept; T.I.M.E. Probl em Statement; S.M.A.R.T. Goal; Thought Map; Process Map; Six Sigm a Team and Management; Creativity Run Chart; Moving Range Chart/Indi vidual Chart; Range Chart; Range Chart/X-bar Chart; Common Cause/S pecial Cause Model; Measurement System Evaluation; Factor Relati onship Diagram; Dot-frequency Diagram; Engineering Experimentation Method Full Factorial Design and Analysis; Half Factorial Design and Analysis; Highly Fractioned Design and Analysis; Residual and Model Adequacy; Regression Models; Normal Probability Plot; Other Miscellaneous Statistical Concepts. Practice in the Catapult Project and some special homework assignments Six Sigma D. M. A. I. C. Process Six Sigma Tools Discussed in Ch E 3343/4372 Figure 1 Figure 1. The Six Sigma D.M.A.I.C. process and different tools discussed in CHE 3343/4372.

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Winter 2007 55 organizing a thought map, and managing a project team. Dur ing the stages of Measure and Analyze, the students evaluate the measurement system and perform two-level full, half, and/or highly fractionated factorial design experiments and dition, they will develop a regression model [4] quantitatively relating the distance as a function of setting parameters such as launching angle, type of ball, rubber band position, and stop pin position. An example of a regression model developed from a 2 3 full factorial design is: 0 1 2 (parameter 2) + 3 12 (parameter 1parameter 2) + 13 23 (parameter 2 123 (parameter 1parameter 2 parameter 3) + error (1) 0 i ij ijk are calculated from the main effects of single pa rameters, two-way interactions, and three-way interactions, respectively. Eq. (1) is the regression model that involves all parameters and interactions in a 2 3 full-factorial design. For practicality, the students have choices of including only by various residue analyses. Finally, the students move to the Improve and Control stage to optimize and apply the developed regression model. For example, during the project competition, each project team will measure the distance where the instructor randomly locates the target (within the target area) and use the model to decide the settings for dif ferent parameters. The accuracy and robustness of the model will directly determine whether the ball can hit the target or how close the ball is landing to the target. It is worthwhile to note the Catapult Project also gives stu dents an opportunity to integrate business decision making to engineering practice, as each team is allowed a maximum of 45 shots with no deduction of scores during the entire project. Upon completing the project, the students practice applying Six Sigma methodology to solve a real-life problem as well as obtaining the experience of improving the performance of THE JMP IN SOFTWARE TRAINING Other than traditional classroom lectures, the course also provides two or three training sections of the JMP In statistical software. The software is a statistical program that is widely used in Six Sigma methodology training and at companies such as Dow Chemical, Procter & Gamble, HP, and PPG. The software allows students to solve complicated statistical problems. For example, we have used the JMP In software to generate a contour plot to view all the possible combina tions for desirable properties from the model developed in the factorial design. CREATIVITY Another learning impact of CHE 3343/4372, Engineering Experimentation, is on creativity. Most chemical engineering education focuses on problem solving based on well-estab lished principles, placing less emphasis on creativity. Hueter states that modern peoples creative abilities increase in ele mentary school up to eight years old and then steadily decrease with further education, including college education. [6, 7] The importance of creativity in engineering can be summarized as follows: Engineering is an art as well as a science, and good engineering depends upon leaps of imagination as well as painstaking care. [7, 8] Creativity is also heavily emphasized in Six Sigma methodology. [9] The project, as well as a few Figure 2. A sample catapult. Target Area 8 4 in c h e s 9 6 i n c h e s 3 6 in c h e s a. b. Figure 3 Figure 3. (a) A map illustrating the setup for the Catapult Project competition; (b) a ball is approaching the target in an actual competition in the class of 2004.

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Chemical Engineering Education 56 of the homework assignments (paper airplane competition, card drop exercises, etc.), provide students opportunities not only to practice the multidisciplinary methodology but also to maximize their potential to be creative during the exercises. EVALUATION The course is among the most popular electives in the chemical engineering curriculum at Texas Tech University. In the spring semesters of 2003-2006, the enrollment was 16, 26, 13, and 14, respectively. The course has received excel lent student evaluation, with an average rating of 4.9/5.0, 5.0/5.0, 5.0/5.0, and 5.0/5.0 out of the 16 university-level questionnaires [scores rank from 1 (poor) to 5 (excellent)] on the instructor and course. Multiple students have said this class was their favorite class and the best experience in a training and work experience include: to attack and solve problems at my new job this sum mer. courses that I have taken. Really enjoyed this class being directly applicable to my work today. Im glad that the department decided to give this course, with industry changing year to year. This class will be extremely useful when we go to work! Great course. It should be offered every year. It helped me get my job.SUMMARY We have successfully incorporated Six Sigma methodol ogy training into a traditional chemical engineering course, CHE 3343/4372, Engineering Experimentation, at Texas Tech University. The course is structured along the Six Sigma D.M.A.I.C. process and different technical and nontechnical tools have been discussed in each stage of the process. Some of the nontraditional aspects in this course include industrial need, special homework assignments, the Catapult Project, the JMP In statistical software training, and emphasis on creativity. In addition, students have also obtained hands-on experience to practice Six Sigma methodology and a unique and integrative experience to practice engineering and busi ness concepts simultaneously. ACKNOWLEDGMENTS The author would like to thank Professor T. Wiesner for his invaluable encouragement and discussion. In addition, the author is grateful to the support from the Texas Tech Fac ulty Incentive Grant Award (2003) and the National Science Foundation (CTS-0500323). REFERENCES 1. Stamatis, D.H., Six Sigma and Beyond CRC Press LLC (2002) content/c010101a.asp>, (2006) 3. Rath & Strongs Six Sigma Pocket Guide Rath & Strong Management Consultants, Lexington (2002) 4. Montgomery, D.C., Design and Analysis of Experiments 5th Ed., John Wiley & Sons, Inc. (2001) 5. Eastlake, C.N., Tell Me, I Will Forget; Show Me, Ill Remember; Undergraduate Curriculum), Proceedings ASEE Annual Conference Washington, (1986) 6. Hueter, J.M. Innovation and Creativity: A Critical Linkage, Proceed ings ASEE Annual Conference Washington, 1634 (1990) 7. Wankat, P.C., and F.S. Oreovicz, Teaching Engineering McGraw-Hill (1993) 8. Florman, S.C., The Civilized Engineer St. Martins Press, New York (1987) 9. Pyzdek, T., The Six Sigma HandbookA Complete Guide for Greenbelts, Blackbelts, and Managers at All Levels, McGraw-Hill (2001)

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Winter 2007 57 First, I want to applaud the authors for making a substantial, well-thought-out revision to their textbook. I have used the book to teach my introductory process control course but had not really read the additional material in the new chapters until this review. I was very impressed with the depth and breadth of the material. I am amazed that the authors were able to eliminate so much material and yet not dilute the critical a struggle to decide what to eliminate and what to keep, just due to the fact that three personalities were involved. They did an excellent job. Since the authors did eliminate so much material, espe cially on digital control, I see the two versions being more like Volume 1 and Volume 1.5 (not quite two volumes) and working to complement each other in advanced courses in process control. I see potentially three semester courses (at one is a general process control course for all undergraduate chemical engineering students covering Chapters 1-9, 11-12, and 15-16; a course in advanced methods covering Chapters and an application toward plantwide control and plant design covering Chapters 10, 22-24, and all the Appendices. a good textbook as well as a good reference manual. Faculty that are not, however, yet are teaching process control might rently using the text and that was his feeling. I kept this in mind while reviewing the text and I could understand his feeling of insecurity with it. One way the text could be improved is to revisit the chapters I mentioned for an introductory course and work to rewrite it in such a way that faculty in this category could feel more comfortable with the material. 1 needs more problems. I am disappointed that they took the block diagram out of this chapter. I have used it to tell students where we are going and why we need Chapters 2-7 and how each block represents certain chapters that we will tie back together in Chapter 11 (what used to be Chapter 10). Chapter 2 is essentially the same as before just with some new problems (I particularly like the additional application on bioprocesses and the exercises). Chapter 3 is essentially the same but the authors should have left Exercises 3.16 and 3.20 in this edition. These were two of my most popular problems for homework. Chapter 4 also did not change much but could be made shorter by giving a general method using Section 4.3 material, which covers all cases. I like the addi tion of state-space formulation. Chapter 5 has been basically untouched, which I applaud, but it does have more good problemssomething faculty always appreciate. Section 6.3.1 is a good addition to Chapter 6 and is explained well. I have always appreciated this chapter and I am glad to see it is even better. The problems are good, especially the ones Chapter 7, I feel that all the emphasis on graphical methods should be removed and replaced with regression. In illustrat ing regression techniques I think it is more important to show how software packages would do this rather than to give the mathematical equations on how they are done. Although they give Matlab and Excel examples they do not show, step by step, how this is exactly done. I think professors and students would appreciate this detail. Example 7.4 needs to be revised or removed. Who would Chapter 8 is basically the same but this chapter has always needed, as it does now, more problems. Chapter 9 is done well but needs more explanation of hardware and more problems. Other textbooks are much stronger in this material such as Riggs (2001). I just skipped the material in Chapter 10 and went straight to Chapter 11. It is good material but out of step with how I do my course. It is important for the material on plantwide control and design. I do not like the way the mate rial in the new Chapter 11 has combined Chapters 10 and 11 There are, however, plenty of good exercises in this chapter. Chapter 12 is done well and has excellent problems. Chapters 13 and 14 are a good condensation of the three chapters on to remain but not be overemphasized, in my opinion. Chapter 15 is an excellent chapter with good problems. For Chapter 16, the addition of Fuzzy Logic Control is an this topic. In Chapter 17 I am glad that they left the mate remove much of the material on z-transforms and sample ChE Process Dynamics and Control, 2nd Ed. by Dale Seborg, Tom Edgar, and Duncan Mellichamp Wiley (2003) $138.95 Reviewed by Iowa State University of Science and Technology Copyright ChE Division of ASEE 2007

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Chemical Engineering Education 58 these eliminations if necessary. It would help to actually have an example for obtaining the poles and zeros. Also, what hap pened to C 0 U z in Eq. 17-46? The C 0 is there but where is U z ? I appreciate the addition of Section 17.6 and I am glad they did not go into a lot of detail [it would be hard to match the material of Ogunnaike and Ray (1994) on the topic]. There are a lot of good problems in the exercises. commendable considering the amount of new material and re organization. In Chapter 18, however, n! on page 477 should be n 2 . Also, on page 479, hidden is mistakenly printed as, hidd en. On page 492, just below Eq. 18-58, should be w. I commend the authors for adding the SVD material and updating this chapter. It may be the most important chapter for the control design engineer in terms of theory. I am glad that they shortened the material in Chapter 19 since optimization is a course in itself and only an overview is critical to any process control course. Chapter 20 is a sub basic fundamentals and concepts of model predictive control (MPC) appear to be present. At least it gives a good overview and introduction on the subject. Although I have not taught from this chapter yet, the exercises appear to be excellent. The authors did an excellent job on Chapter 21. They did it just right and the critical material is here in just the right chart, Cusum, EWMA, Cpk, Six Sigma, and multivariate MPC. They need, however, to point out which ones detect a mean shift vs. a variance shift. For example, there is no add the use of Minitab in this chapter as they did Mathlab and Simulink for chapters exploiting their use. Finally, Chapters 22-24 appear to be done quite well and I look forward to using them in future courses. improvement to this textbook by bringing it up to date with current practices and needs, and enhancing its use as a textbook in process control for undergraduate as well as graduate students. I have used the earlier book since 1991, and with the improvements they have made in the second edition, this text will be useful in the courses I teach for many years to come.

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Winter 2007 59 A by measuring or computing several rheological prop rheological properties while kinetic theory calculations using dumbbells allow the prediction of these rheological properties. the viscosity is dependent. It gets easier or harder to stir faster Thus, the shear-thickening property of this non-Newtonian its liquid-like behavior. that can serve as the basis for multiple fun experiments students can perform in the laboratory. These include dye swelling, rod climbing, and suspensions of particles behavior dents can determine the terminal fall velocity and rotation direction of a single settling particle as well as wall effects and interaction between particles. Problems involving nonas blood, which is non-Newtonian, has important applications in biomedical engineering. In the present paper, we show how one can use the mathematical software Mathematica to The object of this column is to enhance our readers collections of interesting and novel prob lems in chemical engineering. Problems that can be used to motivate the student by presenting a particular principle in class, in a new light, or that can be assigned as a novel home problem Manuscripts should not exceed 14 double-spaced pages and should be accompanied by the origi wilkes@umich.edu), Chemical Engineering Department, University of Michigan, Ann Arbor, MI 48109-2136. ChE INTRODUCING NON-NEWTONIAN FLUID MECHANICS COMPUTATIONS HOUSAM BINOUS National Institute of Applied Sciences and Technology Tunis, Tunisia Copyright ChE Division of ASEE 2007

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Chemical Engineering Education 60 relevant Mathematica commands [1] are inserted in the text and can be found in any introductory book such as Math ematica, A System for Doing Mathematics by Computer by Stephen Wolfram. [2] We start by reminding the reader of the few simple constitutive equations for the power-law, Carreau, rate expressions and representative data. CONSTITUTIVE EQUATIONS FOR NON-NEWTONIAN FLUIDS the strain rate, () 1 viscosity is a function of the strain rate: () 2 Different constitutive equations, giving rise to various models press the viscosity as a function of the strain rate. In power-law n1 3 () obtained when n < 1. We see that viscosity decreases with strain rate for n < 1, which is the case for pseudo-plastic presents a plateau at low and high shear rates separated by a shear-thinning region: 0 2 12 1 1 4 () () () / n 0 shear viscosity. At lo ws hear ra te s At high sh :( :) ( ) 1 2 05 0 2 e ear ra te s: (: ), 1 2 0 2 0 ( () 6 HORIZONTAL FLOW OF CARREAU AND POWER-LAW FLUIDS IN A PIPE 0 whose units appear under Nomenclature at the end of this article: = 8.9 10 -4 = 10 -6 = 5 10 -3 = 0.2, 0 = 1.72 10 -3 and = 0. This problem is treated using Polymath, a numerical com putational package, [3] in Problem Solving in Chemical Engi neering with Numerical Methods by Cutlip and Shacham. [4] The governing equation is the z-component of the equation of motion in cylindrical coordinates: 1 7 r d dr r dv dr P L z n () Eq. (7) is subject to the following split boundary condi tions: At r At rR v rz z 0 0 8 0 9 : ( ) : ( ) These kinds of mathematical problems often require the use of a particular numerical approach called the shooting technique. This method consists of guessing different values of v z at r = 0, solving the differential equation, and checking that the noits derivation can be found in Fluid Mechanics for Chemical Engineers by Wilkes: [5] vr P L Rr n z n nn () / // 1 2 1 1 11 11 1 1 10 () L=50 R=0.02 V x (r) P 1 P 2 P=P 1 -P 2 =100 Figure 1 Flow of Carreau and power-law uids in a pipe.

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Winter 2007 61 since no analytical solution is available. rz D[v z rz rz )^(1/n), rz rz z z rz z /. r The graphical capability of Mathematica allows the student tonian, dilatant, Carreau, and pseudo-plastic cases using the commands: z RGB conditions. The velocity near the wall is higher for Carreau convection. The approach to solve split boundary problems using Mathematica is more systematic than the one proposed by Cutlip and Shacham [4] using Polymath, despite a steeper initial learning curve for students. In fact, it automatically no-slip boundary condition and using the Mathematica com mand FindRoot HORIZONTAL FLOW OF A CARREAU AND A POWER-LAW FLUID IN AN ANNULUS Figure 3. Use the following values, where R 1 and R 2 are the inner and outer radii, 1 = 0.02 and R 2 =0.05 = 8.9 10 -4 = 4.7 10 -4 = 4.5 10 -3 = 0.2, 0 = 2.04 10 -3 and = 0. Cutlip and Shacham [4] have solved this example using Polymath. The governing equation is again the z-component of the equation of motion in cylindrical coordinates: 1 11 r d dr r dv dr P L z n () Eq. (11) is subject to the following split boundary condi tions: At rR v At rR v z z 1 2 0 1 2 0 1 3 : ( ) : ( ) To solve this problem, we make use of the shooting technique in a similar fashion as the previous example. This method rz at r = R 1 solving the differential equation, and checking that the no-slip boundary condition at r = R 2 [4] is vr P L Rr RR RR z () ln (/ 4 2 22 2 2 1 2 2 1 1 2 14 ) ln (/ )( ) rR There is no analytical solution for dilatant, pseudo-plastic, and 0 0.005 0.01 0.015 0.02 0.05 0.1 0.15 0.2 0.25 r v z Dilatant Carreau Newtonian Pseudo-plastic Figure 2. Velocity proles of dilatant, pseudo-plastic, Carreau, and Newtonian uids in a pipe. R 2 =0.05 L=10 V z (r) P 1 P 2 R 1 =0.02 P=P 1 -P 2 =100 Figure 3. Flow of Carreau and power-law uids in an annulus.

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Chemical Engineering Education 62 rz D[v x rz 0, rz )^(1/n), rz rz z z rz z /. r Newtonian, dilatant, Carreau, and pseudo-plastic cases using the Mathematica commands: x RGB not symmetric. In fact, they reach a maximum value close to the radial position, given by r = 0.033, slightly less than halfway from R 1 and R 2 VERTICAL LAMINAR FLOW OF A BINGHAM LIQUID FILM of the gravitational acceleration, g, the density, the yield 0 0 are given by: g = 9.81; = 950; 0 = 5; 0 = 0.15 and = 0.005 Cutlip and Shacham [4] have presented a solution of this example using Polymath. The governing equation is the z-component of the equation of motion in rectangular co ordinates: d dx g xz () 15 Eq. (15) is subject to the following split boundary condi tions: At x At xv xz z 0 0 16 0 1 7 : ( ) : ( ) applying the shooting technique: xz D[v z xz 0 0, xz 0 0 xz 0 0 xz 0 xz z z xz z /. r For the Newtonian case, an analytical expression for the veloc ity, v z as a function of position, x, can be easily derived: v gx z 2 2 2 1 1 8 () Mathematica commands: 0.02 0.025 0.03 0.035 0.04 0.045 0.05 0 0.05 0.1 0.15 0.2 0.25 r v z Dilatant Carreau Newtonian Pseudo-plastic Figure 4. Velocity proles of dilatant, pseudo-plastic, Carreau, and Newtonian uids in an annulus. z x V z ( x ) xz ( x ) Figure 5. Vertical ow of a Bingham uid in a liquid lm. 0 0.001 0.002 0.003 0.004 0.005 0 0.2 0.4 0.6 Newtonian Pseudoplastic x v z Bingham Newtonian Figure 6. Velocity proles of Bingham and Newtonian uids in a liquid lm.

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Winter 2007 63 z RGBColor[0, xz 0 This behavior is typical EXPRESSIONS OF VOLUMETRIC FLOW RATES with Mathematica. rz as a func tion of the radial position, r: rz rz rz 0 We get the following result: rz L Pr () 2 19 Then, we determine the velocity distribution using the sym bolic command, Dsolve z rz )^(1/n), v z v z Finally, the symbolic command, Integrate is used, z rate, Q Rn RP L n n n 2 13 20 13 1 / / () rz as a function of the radial position, r: rz rz rz 0 We get the following result: rz L Pr () 2 19 0 condition v z (R) = 0 and the symbolic command, Dsolve : z rz 0 z v z 2 0 The symbolic command, Integrate is used to obtain the ex 0 and r = R, z 0 In the second part of the derivation, we determine the con stant velocity, v 0 0 following symbolic command: v 0 0 / (r-R) /. r 0 This is nothing more than expressing the continuity of the 0 0 = v z 0 The symbolic command, Integrate is used to obtain the 0 0 0 and we get the following expression for the overall volumetric Q RP L RL P 4 3 0 0 43 3 83 2 3 21 () NON-NEWTONIAN FLUID MODEL DETERMINATION Wilkes [5] provides representative values of the volumetric in a pipe. These values are reproduced in Table 1. The pipe radius is equal to R = 0.01m. Use these representative values, T ABLE 1 Volumetric Flow Rate vs. Pressure Gradient 10 5 3 /s) 10000 5.37 20000 26.4 30000 68.9 40000 129 50000 235 60000 336 70000 487 80000 713 90000 912 100000 1100 2 nR ( PR ) -1 /n 1 n L n 1

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Chemical Engineering Education 64 in conjunction with the analytical expression of the volumetric parameters of the constitutive equation. First, we compute the following sum: JQ Q i re p i th i () () 2 1 10 22 where Q i rep and Q i th are the representative value and analytical in command of Mathematica, FindMinimum to determine the values of n and 0 and tion, J. The approach used here is the least squares method. = 6.708, 0 0.0326. The value of the sum given by Eq. (22) is 9.89 10 -6 for the Bingham model and 2.67 10 -7 for the power-law representative data better. CONCLUSIONS conditions and were solved using the shooting techniques. Mathematica. The parameters of the constitutive equation gradients in a horizontal pipe. These problems are simple Institute of Applied Sciences in Tunis performed well de spite no previous knowledge of Mathematica. Mathematica notebooks are available from author upon request or at the information center. [1]NOMENCLATURE g gravitational acceleration ( m/s 2 ) 3 /s) L pipe length (m) n power-law exponent R pipe radius (m) R 1 ,R 2 annulus radii (m) r radial position (m) v z velocity (m/s) z axial position (m) power-law consistency index (N s n /m 2 ) 2 ) 0 zero-shear viscosity (kg/ms 2 ) 2 ) density (kg/m 3 ) 0 yield stress (kg/ms) rz shear stress (kg/ms) REFERENCES 1. 2. Wolfram, S., Mathematica, A System for Doing Mathematics by Com puter Addison-Wesley, Redwood City, CA (1988) 3. 4. Cutlip, M.B., and M. Shacham, Problem Solving in Chemical Engi neering with Numerical Methods Prentice Hall, Upper Saddle River, NJ (1999) 5. Wilkes, J.O., Fluid Mechanics for Chemical Engineers Prentice Hall, Upper Saddle River, NJ (1999)

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Winter 2007 65 T he recent boom in the biomedical/biochemical in dustry has necessitated the introduction of biological components into the chemical engineering curriculum. According to the U.S. Department of Labor, the job market for biomedical engineers is projected to increase 31.4% through 2012. [1] In 1990, less than 4,000 students were enrolled in undergraduate biomedical/biochemical programs; in 2002 there were more than 10,000 students enrolled. [2] In the next per year will take biomedical/biochemical courses. To enhance biomedical/biochemical engineering oppor tunities in chemical engineering, experiments involving enzymatic degradation of cellulose and dialysis of creatinine were introduced at Oklahoma State University (OSU) in the Unit Operations Laboratory (UOL). These projects enhance the instruction students receive in optional Introduction to Biomedical Engineering and Introduction to Bioprocess Engineering courses. In the UOL, students work in teams of IMPLEMENTATION AND ANALYSIS OF HEMODIALYSIS SUNDARARAJAN V. MADIHALLY Oklahoma State University Stillwater, OK 74078RANDY S. LEWISBrigham Young University Provo, UT 84602 ChE Copyright ChE Division of ASEE 2007

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Chemical Engineering Education 66 semester. While assigning projects, bio-related ones are al located preferentially to students enrolled or committed to biomedical and/or bioprocess courses. The dialysis experiment demonstrates the fundamental concepts of a hemodialysis device using creatinine as the target agent for removal. Creatinine (MW 113) is one of several waste products produced in a human that must be removed by the kidney. Although some dialysis experiments have previously been demonstrated in the chemical engineer ing curriculum using salt solutions with short experimental times, [3] the use of creatinine has several advantages. These advantages include its larger relative size to other waste products and its use, along with urea, as a marker for effec tive dialysis treatment. [4] The larger creatinine size leads to a longer removal time in comparison to other waste products. The waste product with the longest removal time is often used in determining dialysis treatment time. Thus, the use of creatinine leads to a more realistic dialysis experimenteven with the drawback of longer dialysis time. This work presents a dialysis model that demonstrates the assessment of model assumptions. It will detail the dialysis project statement de livered to the student team, the experimental protocol, the dialysis model, experimental results, and student feedback is that the student can integrate a number of concepts such as material balances/modeling ( i.e. blood and dialysate bal ances with assumptions), transport issues ( i.e. evaluation of solving differential equations ( i.e. using Polymath) toward a bioengineering project that allows the student to expand the scope of his/her chemical engineering education. PROJECT STATEMENT A biomedical engineering company makes many biomedical machines. Hospitals use dialysis to process the blood of patients whose kidneys do not effectively remove toxins and excess water from the blood. The machine has many features that you will not need to use. We are interested in the hol Please develop and validate an unsteady-state model for one of several toxic metabolites, from blood (represented by water in this experiment). Using your model, determine of creatinine. Metabolites and electrolytes affect the osmotic pressure, which affects the transport of water across the membrane. This osmotic pressure effect must be included in your model to determine the amount of water removed from (or added to) the blood during the dialysis treatment. As part of the model, you need to generate experimental (composed of salts similar to normal blood concentrations) metabolites and electrolytes in the blood diffuse through the ously circulating within his/her body. The blood compartment of the body can be assumed as a Continuous Stirred Tank kidney dialysis unit is returned to the body. EXPERIMENTAL PROTOCOL The experiment consists of a hemodialysis unit connected to a bucket of water containing creatinine (representing the patients blood), as shown in Figure 1. A schematic of the Figure 1. Dialysis unit, dialyzer, and a continuously stirred tank containing creatinine that represents the patients blood.

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Winter 2007 67 experimental system is shown in Figure 2. Although hemo dialysis units are expensive, many dialysis centers regularly replace their units on an annual or bi-annual basis. Since there is often a cost for disposal of the units, the supplier of hemodialysis units at a local dialysis center was contacted and the supplier donated 10 units to OSU at no charge. It is likely that such donations can be obtained from other hemodialysis unit suppliers in the same fashion. Manometers were placed at all inlets and outlets of the dialyzer to measure pressure drops from one end of the dialyzer to the other end as well as to measure transmembrane pressure differences. Three to four liters of a solution (denoted blood) containing up to 4.1 mM creatinine were used to simulate the patients initial blood concentration. The blood was continuously mixed using a magnetic stirrer. The blood was pumped to the tube side of the dialyzer at rates varying between 300-500 ml/min, con trolled by the dialysis unit, and blood volume changes were monitored at regular intervals by weighing the bucket on an electronic scale. Water (denoted dialysate) was continuously added at rates between 815-865 ml/min to the shell side of the dialyzer and, upon exiting, emptied into a waste sink. Experiments were conducted over a two-hour period. In the entering the dialyzer from the bucket contained a constant creatinine concentration and the blood exiting the dialyzer was sent to a waste bucket. This experiment was performed to C neces sary to predict the creatinine concentration with time in the closed-loop experiment. In the closed-loop experiment, the blood continuously circulated such that the blood volume and creatinine concentration decreased with time. The changing creatinine concentration was used to compare model predic tions with experimental results. During the experiments, the inlet and outlet pressures across the dialyzer and the volume the weight of the blood). Samples (0.3-0.5 mL) were collected for analysis of the creatinine concentration. To analyze the creatinine concentration, one part sample was mixed with three parts of a solution containing a 10:1 ratio of 0.14% picric acid and sodium hydroxide. Note that picric acid is hazardous, highly explosive, and should only be used under the careful guidance of an instructor. In this analysis, creatinine reacts with alkaline picrate to form a reddish-yel low solution from which the absorbance can be detected in a spectrophotometer at 490 nm. [5] The absorbances were converted to concentrations via a linear calibration curve. Spectrophotometers are a common component in many labo ratories and thus there is a possibility that arrangements could be made to use existing spectrophotometers for the creatinine analysis. Inexpensive spectrophotometers may be purchased, however, for as little as $1,500. Other calorimetric methods also exist for assaying creatinine, although the methods are more expensive. [6] DIALYSIS MODEL AND SOLUTION To meet the objectives of the project statement, students needed to develop a mathematical model for the process. The blood in the bucket was modeled as a CST with a given volume (V CST ). During the closed-loop experiment, the CST creatinine concentration ( C C C S T ) changes with time accord ing to: dC dt Q V CC C CS TB out CS T C B out C CS T , () () 1 where Q B,out the dialyzer and C c B,out is the blood creatinine concentration exiting the dialyzer (and entering the CST). Since the CST volume changes with time, the creatinine material balance and the total mass balance (assuming constant density) were combined to obtain Eq. (1). The total mass balance, assuming constant density, is represented by: dV dt QQ CS T B out Bi n , () 2 where Q B,in the dialyzer. To solve Eqs. (1) and (2) to predict V CST and C C C S T with time (as part of the project statement objective), it is important to know how C c B,out and Q B,out are related to Patient Blood Dialysis Unit Pump Dialyzer Dialysis solution to waste sink Patient Blood Dialysis Unit Pump Dialyzer Dialysis solution to waste sink CST C C CST C C outB C C inD C C outD C C V CST Figure 2 Schematic of Figure 1 showing the dialysis unit and countercurrent ow in the dialyzer. The creatinine concentration (C) parameters and volume (V CST ) of the continuously stirred tank used in Eqs. (2) and (3) and (7) through (9) are shown.

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Chemical Engineering Education 68 dialyzer inlet conditions. Q B,in is constant and set by the dialysis machine. Material balances around the dialyzer identify the inter relationship between C c B,out and Q B,out and demonstrate how these parameters can be used in Eqs. (1) and (2) to predict V CST and C C C S T tween the blood and dialysate, the material balances around the dialyzer are: QQ QQ PA dC dA Bi nB out D out Di n M C B C ,, , () 3 Q Q CC dC dA Q CC B C D C B C D C D C D C B () () () () 4 5 Eq. (3) represents that total water loss from the blood side into the dialysate side following a single pass, resulting from the blood and dialysate. Q B and Q D are the blood-side and B avg -P D avg where P B and P D are the average pressures of blood and dialysate, respectively. The M is the total transport area of the membrane. For the dialyzer used in this study, A M = 1.5 m 2 (CL T150L, Terumo Medical Corporation, Tokyo, Japan). Eq. (4) is the material balance for creatinine in the blood side ( C C B ) of C is the mass transfer per time) describing diffusive transport of creatinine across the membrane relative balance for creatinine in the dialysate side ( C C D ) of the dialyzer. The differential membrane transport area with integration proceeding from the blood inlet to the blood outlet is represented by dA. The assumptions in the development of Eqs. (3) to (5) include: 1) pseudo-steady the membrane and only diffusion occurs. [4] solutes, there is no osmotic driving force for water transport. For this study, the small MW of creatinine (113 Da) relative to the average pore size of the dialyzer (8,000-10,000 Da) [4] For analysis involving co-current D,out Q D,in in Eq. (3) is replaced with Q D,in Q D,out and the differential sign in Eq. (5) is negative. C must be assessed to use the model. absence of solutes (or the presence of any solute as long as CST Combining Eq. (3) with Eq. (2) suggests that a plot of V CST vs. M with the known value of A M C B,in and Q D,in for Eq. (3), such that Q B,out B,in and Q D,out D,in ( i.e. Q D and Q B are constant) according to Eq. (3). For these assumptions, integration of Eqs. (4) and (5) results in C c B,out = C C C S T (1-E) where E is E Nz z co cu rre nt fl ow E T 11 1 6 exp[ () ] () () ex p p[ () ] exp[ () ] Nz Nz z counter cu rre nt fl T T 11 1 o ow () 7 and N T C A M /Q B,in and Q B,in /Q D,in respectively. [7] The C can be obtained from the open-ended experi ment with a known z by measuring C C C S T (also equivalent to C c B,in ) and C c B,out solving for E, solving for N T from either C at the given Q B,in and A M The validity of the assumptions can be assessed by comparing C M with Q B,in and Q D,in The validity of assumptions should always be checked when applying models. Thus, the dialysis project is an excellent tool for allowing students to demonstrate the validation of assumptions. C are known, V CST and C C C S T can be predicted with time for ( i.e. a given z value) by utilizing C c B,out = C C C S T (1-E) and Q B,out = Q B,in M in the integration of Eqs. (1) and (2). Although beyond the scope of this article, solving Eqs. (3) to (5) simultaneously [with Eq. (3) in differential form] and then applying the solutions to Eqs. (1) and (2) allows a more rigorous approach for predicting V CST and C C C S T with time. The rigorous approach C and Q B and Q D are constant as demonstrated above. In many dialysis models, the assumption of negli [4,7] The rigorous approach is advantageous for students to use when the negligible portunity for students to compare the rigorous solution to with assumptions. This work presents a dialysis model that demonstrates the assessment of model assumptions. It will detail the dialysis project statement delivered to the student team, the experimental protocol, the dialysis model, experimental results, and student feedback and assessment.

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Winter 2007 69 In addition, the models can be further expanded to include mul the dialysis project has great potential for many applications involving model development, validation of assumptions, and comparison with experimental results. Exposing students to the various levels of model development helps them learn how to simplify models using certain assumptions. For example, blood contains proteins, salts, urea, and other metabolites. The proteins are too large to transport through the proteins contribute to an osmotic pressure. If only proteins (P) and creatinine (C) were present, Eqs. (3) to (5) would be expanded to: dQ dA dQ dA PR TC dC dA B D P B P B () 8 C Q dC dA Q CC dC dA P B B C B C B C D C B C D () () 9 10 C C D C D C B Q CC () 11 The RTC P B term in Eq. (8) is the osmotic pressure contribu tion due to proteins. Eq. (9) is the protein material balance on the blood side that demonstrates the protein concentration (note that protein is not in the dialysate, so a protein balance in the dialysate is not needed). The solutions to these equations [combined with Eqs. (1) and (2)] can be solved to provide V CST and C C C S T predictions with time. The value of RTC P B is typically 28 mmHg, and dialysis mmHg. [4] ing Q B along the length of the dialyzer. According to Eqs. (8) and (9), the protein concentration will increase due to the loss of water and the creatinine concentration in the blood will decrease. The model can be used to assess the degree to which increases and decreases occur. Unlike the example given in changes in protein concentration on the blood side (as a result of water loss) according to Eq. (9). A valuable exercise for students would be to derive Eqs. (8) through (11) and show how the equations can be solved with Eqs. (1) and (2) to predict time CST and C C C S T .EXPERIMENTAL RESULTS Figure 3 shows a plot of V CST vs. time for a closedloop experiment in which creatinine was initially present at 4.1 mM and Q B,in = 500 ml/min. With a negative slope of one ml/min ( i.e. 1 ml/min of water transports from the blood to the dialysate) and A M = 1.5 m 2 (CL T150L, 10 -5 M = 1 ml/min). According to Eq. (3), Q B,out / Q B,in = 0.998. Thus, Q B is essentially constant such that the M << Q B,in is valid. Since Q D was greater than Q B M << Q D,in is also valid for at Q B,in B,in -6 cm min -1 mmHg -1 C the open-loop experiment was per formed at Q B,in = 300 ml/min and Q D,in = 817 ml/min with C C C S T = 3.22 mM. The analytical measurements for this work were sensitive enough to distinguish differences between C C C S T and C C B o u t The measured value of C C B o u t was 2.03 0.03 mM, leading to C C B o u t = 0.63 C C CS T and E = 0.37. For of 0.5 for N T C is 0.01 cm/min, which validates the C C is similar to values observed for other hemodialyzers. [7] Once model parameters were obtained and the assump tions were validated, Eqs. (1) and (2) (with C C B o u t = C C CS T (1-E) and Q B,out = Q B,in M ) were solved simultaneously using Polymath [8] to predict V CST and C C CS T with time. The predictions were compared to experimental results from a closed-loop experiment in which 2.54 mM of creatinine was initially present in 4 liters with Q B,in = 300 ml/min and Q D,in = 865 ml/min (z=0.347). From Eq. (7) with A M =1.5 m 2 and 3.86 3.88 3.90 3.92 3.94 3.96 3.98 020406080100 Minutes V CST (liters) V CST =-0.001 t +3.96 Figure 3 Volume of the blood (V CST ) as a function of time (t). Creatinine was initially present at 4.1 mM with Q B,in = 500 ml/min. The line represents the solution to Eqs. (2) and (7), where the slope is used to evaluate K.

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Chemical Engineering Education 70 C = 0.01 cm/min (N T =0.5), E=0.37. Figure 4 shows that the model results for C c CST 10 -5 cm/min (representing a are the same. Increased water transport can occur via either in general agreement with the experimental results although there is a small discrepancy. The time to remove 90% of the affect the C C CS T C ). After 100 minutes, however, the predicted V CST was 4000 ml, 3900 10 -5 cm/min, and 10 -5 critical for predicting water loss but does not affect predic B,in = 500 ml/min (E=0.24). As seen, the C C CS T drastically change and the time to remove 90% of the creati nine only decreases to 76 minutes. STUDENT FEEDBACK AND ASSESSMENT Some of the comments from students included this experi ment trained us with [nontraditional] equipment and I liked data. There were several indirect assessments. Students liked this project and explored more than they were asked to do in the project statement. For example, they explained the difference in various types of dialysis processes, pro vided statistics about each type, examined the relevance of creatinine in clinical settings, explored the importance of osmolarity, and developed an understanding for the need ings, they named their patient, talked about poor Charlie needing to sit for two hours while the dialysis was taking place, and worried about how creatinine generated in the body during dialysis would affect the creatinine removal process. To account for creatinine generation during dialy sis, a constant generation of creatinine could be introduced into the experiment. It was also observed that as students were told that they could present their results at the regional and national American Institute of Chemical Engineers (AIChE) student conferences, students were more willing to spend extra time on the project. One student presented his teams results at the 2004 Mid-America Regional AIChE Conference and won second place. dialysis project was that students tended to focus on the analysis ( i.e. measurements), and focused less on the mod eling aspects. For instance, students spent ample time on the creatinine analysis. One problem that was encountered, however, was that students were not used to using micropi pettes and error in the calibration curve could be dominant if proper volumes were not dispensed every time. Thus, it is important to train students in using equipment that is not often associated with traditional unit operations experiments. With regards to modeling, the students did not always explore the the instructor to direct students toward resources containing information about model development. The main point is that students involved in nontraditional experiments should resources) to help them achieve their objectives.CONCLUSIONS Through the incorporation of creatinine dialysis, under graduates can integrate a number of concepts such as material balances/modeling ( i.e. blood and dialysate balances with such as material balances/modeling (i.e., blood and dialysate balances with assumptions), and solving differential equations (i.e., using Polymath) toward a bioengineering project that allows the student to expand the scope of his/her chemical engineering education. Figure 4. Creatinine concentration (initially 2.54 mM) in the continuously stirred tank (CST originally at 4000 ml) as a function of time for Q B,in = 300 ml/min and Q D,in = 865 ml/min. The model is the solution to Eqs. (2) and (3) with C C B,out = C c CST (1-E) and Q B,out = Q B,in K A M A M is 1.5 m 2 0.0 0.5 1.0 1.5 2.0 2.5 3.0 0 204 0 Minutes 608 0 100 Creatinine Concentration (mM) E=0.24, K=0 cm/min Experimental E=0.37, K=0 to 20 x 10 -5 cm/min 90% removal

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Winter 2007 71 assumptions), transport issues ( i.e. C ), model validation ( i.e. validating assumptions), and solving differen tial equations ( i.e. using Polymath) towards a bioengineering project that allows the student to expand the scope of his/her chemical engineering education. The students enjoyed the exposure to nontraditional experiments and this project provided them an opportunity to connect bioengineering ex periments to material learned in the classroom. Deriving the differential equations from the continuity equation requires the student to draw on his/her math and engineering knowledge. It is important for students to assess the validity of assumptions when applying experimental results to model equations, and this project allowed for such opportunities. ACKNOWLEDGMENTS The authors would like to thank the following students in the School of Chemical Engineering at Oklahoma State University who conducted the experiments: Paul Engel, addition, we thank the Stillwater Dialysis Center for helping secure the dialysis machines and cartridges. REFERENCES 1. (2004) 2. (2004) 3. Cavanagh, D.P., and L.H. Herbertson, Effective Laboratory Exercises for an Introduction to Biomedical Engineering Course, Proceedings of the ASEE Annual Conference and Exposition Salt Lake City, UT. (2003) 4. Fournier, R.L., Basic Transport Phenomena in Biomedical Engineering Taylor and Francis, Philadelphia (1999) 5. Narayanan, S., and H.D. Appleton, Creatinine: A Review, Clin. Chem. 26 1119, (1980) Detection of Creatinine by a Designed Receptor, Science 269 (5224), 671, (1995) 7. Cooney, D.O., Biomedical Engineering Principles Marcel Dekker, New York (1976) 8. Cutlip, M.B., and M. Shacham, Problem Solving in Chemical Engineer ing with Numerical Methods Prentice Hall PTR, Upper Saddle River, NJ (1999)

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