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An Optimization Model for Sub-Surface Utility Engineering during the Design Process

Permanent Link: http://ufdc.ufl.edu/UFE0042472/00001

Material Information

Title: An Optimization Model for Sub-Surface Utility Engineering during the Design Process
Physical Description: 1 online resource (105 p.)
Language: english
Creator: Coffey, Michael
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2010

Subjects

Subjects / Keywords: civil, conflicts, construction, cost, decision, engineering, highway, rating, subsurface, sue, system, uir, utility
Civil and Coastal Engineering -- Dissertations, Academic -- UF
Genre: Civil Engineering thesis, Ph.D.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: AN OPTIMIZATION MODEL FOR SUBSURFACE UTILITY ENGINEERING DURING THE DESIGN PROCESS By Michael Anthony Coffey December 2010 Chair: Ralph D. Ellis Major: Civil Engineering Implementation of Subsurface Utility Engineering (SUE) during the design process is becoming more and more of a mainstream operational standard for civil engineering projects. Many states are developing systems of implementation within their Department of Transportation (DOT) for SUE to become part of the highway and roadway design process. However, there are still traditional sequences of design development that exist which do not consider the benefits of SUE early enough in the design process or not at all. The proper application to optimize the use of SUE by the Quality Level (QL) of information, the timing, and the designer decision based on project complexity is still needed. This research found a correlation between SUE investment on projects and the cost growth due to utility relocations and conflicts. Understanding that relationship, it was possible to identify an optimization of an investment level. The results helped to create a scoring system that could be used for all types of civil engineering projects which is parallel to the Utility Impact Rating system (Sinha 2008) that was developed for highway projects. The scoring is linked to a decision matrix. The purpose of the matrix is to guide SUE use during the design to result in optimum results. The research demonstrated that an increase in SUE investment would lead to less cost contribution due to subsurface utility conflicts and proposed an optimization model for the use of SUE. The research identified an average cost increase across projects that did not utilize SUE in their design and referred to this percentage increase as a baseline in project cost. Then, looking at projects that involved SUE, the difference was found between the cost contribution and the baseline cost. The cost contribution became negative, representing a cost savings on projects. The data trend confirmed the initial statement of this research an increase in SUE expense above the quality level associated with typical topographic survey information would positively affect a project by reducing potential cost contributions due to utilities. Also, there is an optimized amount of SUE to be used on each project which can be estimated based on these assessments.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Michael Coffey.
Thesis: Thesis (Ph.D.)--University of Florida, 2010.
Local: Adviser: Ellis, Ralph D.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2010
System ID: UFE0042472:00001

Permanent Link: http://ufdc.ufl.edu/UFE0042472/00001

Material Information

Title: An Optimization Model for Sub-Surface Utility Engineering during the Design Process
Physical Description: 1 online resource (105 p.)
Language: english
Creator: Coffey, Michael
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2010

Subjects

Subjects / Keywords: civil, conflicts, construction, cost, decision, engineering, highway, rating, subsurface, sue, system, uir, utility
Civil and Coastal Engineering -- Dissertations, Academic -- UF
Genre: Civil Engineering thesis, Ph.D.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: AN OPTIMIZATION MODEL FOR SUBSURFACE UTILITY ENGINEERING DURING THE DESIGN PROCESS By Michael Anthony Coffey December 2010 Chair: Ralph D. Ellis Major: Civil Engineering Implementation of Subsurface Utility Engineering (SUE) during the design process is becoming more and more of a mainstream operational standard for civil engineering projects. Many states are developing systems of implementation within their Department of Transportation (DOT) for SUE to become part of the highway and roadway design process. However, there are still traditional sequences of design development that exist which do not consider the benefits of SUE early enough in the design process or not at all. The proper application to optimize the use of SUE by the Quality Level (QL) of information, the timing, and the designer decision based on project complexity is still needed. This research found a correlation between SUE investment on projects and the cost growth due to utility relocations and conflicts. Understanding that relationship, it was possible to identify an optimization of an investment level. The results helped to create a scoring system that could be used for all types of civil engineering projects which is parallel to the Utility Impact Rating system (Sinha 2008) that was developed for highway projects. The scoring is linked to a decision matrix. The purpose of the matrix is to guide SUE use during the design to result in optimum results. The research demonstrated that an increase in SUE investment would lead to less cost contribution due to subsurface utility conflicts and proposed an optimization model for the use of SUE. The research identified an average cost increase across projects that did not utilize SUE in their design and referred to this percentage increase as a baseline in project cost. Then, looking at projects that involved SUE, the difference was found between the cost contribution and the baseline cost. The cost contribution became negative, representing a cost savings on projects. The data trend confirmed the initial statement of this research an increase in SUE expense above the quality level associated with typical topographic survey information would positively affect a project by reducing potential cost contributions due to utilities. Also, there is an optimized amount of SUE to be used on each project which can be estimated based on these assessments.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Michael Coffey.
Thesis: Thesis (Ph.D.)--University of Florida, 2010.
Local: Adviser: Ellis, Ralph D.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2010
System ID: UFE0042472:00001


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1 AN OPTIMIZATION MODEL FOR SUBSURFACE UTILITY ENGINEERING DURING THE DESIGN PROCESS By MICHAEL ANTHONY COFFEY A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2010

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2 2010 Michael Anthony Coffey

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3 To Inge Lise

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4 ACKNOWLEDGMENTS I sincerely thank my wife for convincing me to go back, and finish what I started so long ago. I am grateful to Dr. Fazil Najafi for his influence and advice which set this all in motion I thank Dr. Karl Soderh lm who invested in hiring me as a materials research assistant. He sparked my interest in research and the journey to find n found yet. I appreciate the guidance and support of Dr. James Pohl during my undergraduate years at FAU. Thank s to Lt. Colonel Peer Lovfald (USAF Ret.), who has always been a true inspiration, as a friend, a scholar, and a gentlemen. Chuck Pigeon, PE w as my first career boss and remains a brilliant engineer that I am glad to have learned by and worked with I thank Ron Ratliff, AICP, who has served as my sounding board and advisor away from campus for the last three years Mr. Dan Carroll, PE deserves all the thanks I can issue for his support. My friends at the Florida Department of Transportation deserve many t hanks for providing me with requested data and answers to my many questions, especially Gordon Morgan, Michael Johnston, Diane Perkins, and S cott Blocker. Thank you Mark Pitchford, PSM for the data you and your staff could supply along with good feedback to my questions during this research I would like to thank Dr. Ralph Ellis, PE who has always been a strong source of inspiration for me bot h professionally and academically. Sharing his professional career. His real world experience and common sense approach to civil engineering made a great impact on ho w I wanted to proceed with my own career. To my chil dren, I love you so much for continuing to show me how simple life can be when we have laughter. Last but not least I thank my parents for their continuing support in whatever I have taken on a s a challe nge throughout my life.

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5 TABLE OF CONTENTS page ACKNOWLEDGMENTS ................................ ................................ ................................ .. 4 LIST OF TABLES ................................ ................................ ................................ ............ 8 LIST OF FIGURES ................................ ................................ ................................ .......... 9 LIST OF ABBREVIATIONS ................................ ................................ ........................... 10 ABSTRACT ................................ ................................ ................................ ................... 12 CHAPTER 1 INTRODUCTION ................................ ................................ ................................ .... 14 1.1 Backgr ound ................................ ................................ ................................ ....... 14 1.1.1 Current Practices ................................ ................................ ..................... 17 1.1.2 Typical Roadway Design Process ................................ ........................... 17 1.1.3 Typical Coordination in Roadway Projects ................................ .............. 21 1.2 Research Objective ................................ ................................ ........................... 22 1.3 Scope ................................ ................................ ................................ ................ 24 2 LITERATURE REVIEW ................................ ................................ .......................... 25 Experience ................................ ................................ .......................... 25 2.2 Research on Cost/Benefit Analysis ................................ ................................ ... 26 2.3 Risk Management Research ................................ ................................ ............. 28 2.4 Best Management Practices ................................ ................................ ............. 29 2.4.1 Utilize Best Technology ................................ ................................ ........... 29 2.4.2 Effective Communication ................................ ................................ ......... 29 2.4.3 Utility Coordination ................................ ................................ .................. 30 2.4.4 Long range Planning ................................ ................................ ............... 30 2.4.5 Include Utility Owners in Design Process ................................ ................ 30 2.4.6 Design for The Future ................................ ................................ .............. 31 2.5 Analytic Hierarchy Process ................................ ................................ ............... 31 2.6 Conclusions ................................ ................................ ................................ ...... 31 3 METHODOLOGY ................................ ................................ ................................ ... 33 3.1 Data Collectio n ................................ ................................ ................................ 33 3.1.1 Construction Project Data ................................ ................................ ........ 34 3.1.2 SUE Cost Data ................................ ................................ ........................ 36 3.1.4 Cost Variable Survey ................................ ................................ ............... 36 3.2 Mo del Concept ................................ ................................ ................................ .. 38

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6 3.2.1 SUE Quality Level Assignment for Data ................................ .................. 39 3.2.2 Variables of the Model ................................ ................................ ............. 40 3.2.2.1 SUE variable representation ................................ .......................... 40 3.2.2.2 Cost contribution increase variable representation ........................ 41 3.2.3 AHP Process for Cost Variable Survey ................................ ................... 41 3.2.4 Anticipated Trend in Data Behavior ................................ ......................... 42 3.2.5 Modification to the Utility Impact Rating System ................................ ...... 42 3.2.5.1 Weighting of cost variables in the UIR system ............................... 42 3.2.6 Decision Matrix ................................ ................................ ........................ 43 4 DATA ANALYSIS ................................ ................................ ................................ .... 51 4.1 Overview ................................ ................................ ................................ ........... 51 4.2 Data Deduction ................................ ................................ ................................ 51 4.2.1 Data Frequency ................................ ................................ ....................... 52 4.2.2 QL A/B Project Performance ................................ ................................ ... 52 4.2.2.1 Regression analysis ................................ ................................ ....... 53 4.2.2.2 Analysis results ................................ ................................ .............. 54 4.2.3 Influenc e of SUE Use on Projects ................................ ........................... 54 4.3 Modified Utility Impact Rating System ................................ ............................... 55 4.3.1 UIR Score and SUEP AB Relationship ................................ ....................... 55 4.3.2 Assessment of Potential CR AB Based on SUEP AB from UIR ................... 56 4.3.3 Decision Matrix ................................ ................................ ........................ 57 4.3.4 Cost Variable Survey Analysis ................................ ................................ 57 5 CONCLUSIONS AND RECOMMENDATIONS ................................ ....................... 69 5.1 Conclusions ................................ ................................ ................................ ...... 69 5.2 Recommendations ................................ ................................ ............................ 70 5.2.1 UIR Scoring System Use ................................ ................................ ......... 70 5.2. 2 SUE Data Recording ................................ ................................ ............... 71 5.2.3 Application to Other Project Types ................................ .......................... 71 5.2.4 Future Research ................................ ................................ ...................... 72 5.2.4.1 The optimization goal ................................ ................................ ..... 72 5.2.4.2 The UIR and SUE AB relationship ................................ .................... 72 5.2.4.2 Project types and outcomes ................................ ........................... 73 5.2.4.3 Design build as compared to traditional procurement .................... 73 APPENDIX A DATABASE OF TRADITIONAL DESIGN BID BUILD PROJECT ........................... 74 B LIST OF PROJECTS INVOLVING SUE FOR STUDY ................................ ............ 85 C SURVEY FORM FOR AHP PROCESS ................................ ................................ .. 87 D DATA FOR CR AB and SUEP AB COMPARISON AND PROJECTION ...................... 89

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7 E SUPERDECISIONS RESULTS AND STATISTICS ................................ ................ 91 F EXAMPLE UIR SYSTEM RESULT ................................ ................................ ......... 97 G UTILITY CONFLICT MATRIX EXAMPLE ................................ ............................. 100 LIST OF REFERENCES ................................ ................................ ............................. 103 BIOGRAPHICAL SKETCH ................................ ................................ .......................... 105

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8 LIST OF TABLES Table page 3 1 Summary statistics of 285 traditional design bid build contracts ............................ 36 4 1 Summary of contract amounts for 26 studied projects ................................ ........... 59 4 2 Summary of CCP UTILITY for 26 studied projects ................................ ...................... 59 4 3 Summary of SUEP AB for 26 studied projects ................................ .......................... 59 4 4 Summary overall statistics of 26 studied projects ................................ ................... 59 4 5 Summary statistics of cost variable rankings from AHP ................................ ......... 60

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9 LIST OF FIGURES Figure page 3 1 Example of scoring from a portion of the cost variable survey ............................... 37 3 2 Pie chart breakdown of all traditional project types ................................ ............... 44 3 3 Graph of OCC and CCP UTILITY for 285 traditional projects ................................ ..... 45 3 4 Graph of OCC and CC UTILITY for bridge projects ................................ .................... 46 3 5 Graph of OCC and CC UTILITY for new construction projects ................................ ... 47 3 6 Graph of OCC and CC UTILITY for rehabilitation projects ................................ ......... 48 3 7 Graph of OCC and CC UTILITY for resurfacing projects ................................ ............ 49 3 8 Graph of OCC and CC UTILITY for traffic operations projects ................................ ... 50 4 1 Frequency of contract values for 26 studied projects ................................ ............ 61 4 2 Frequency of CCP UTILITY for 26 studied projects ................................ .................... 62 4 3 Frequency of SUEP AB for 26 studied projects ................................ ....................... 63 4 4 CR AB graphed against SUEP AB for the 26 stud ied projects ................................ ... 64 4 5 UIR graphed against SUEP AB ................................ ................................ ................ 65 4 6 Graph of cost variable weighting by project type ................................ ................... 66 4 7 Decision matrix of the modified UIR scoring page 1 ................................ .............. 67 4 8 Decision matrix of the modified UIR scoring page 2. ................................ ............. 68

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10 LIST OF ABBREVIATION S AASHTO American Association of State Highwa y and Transportation Officials AHP Analytic Hierarchy Process BIC Business Impact Cost CC UTILITY Cost Contribution Due t o Utility Conflicts CCC Contractor Contingency Cost CCO Contractor Claims and Change Order Cost CCP AB Cost Contribution Due to Utility Conflicts For QL A/B Projects CC UTILITY Cost Contribution Due t o Utility Conflicts CCP UTILITY Pe rcent of Cost Contribution Due t o Utility Conflicts CCV I Cost Contribution of Variable CCVP i Cost Contribution Percentage f or Variable CIC Contractor Injury Cost CIP Capital Improvement Plan CR AB Cost Reduction f or SUE Use CS SUE Cost Sav ings f or SUE Use CTS Cost of Topographic Survey DOT Department of Transportation DSC Design Cost EIC Environmental Impact Cost FDO T Florida Department of Transportation GIS Global Information System HPDP Highway Project Development Process MOT Maintenance of Traffic OCC Original Construction Cost

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11 PD&E Planning, Development and Environment PD Preliminary Design PIC Personal Injury Cost PVC Polyvinyl Chloride QL Quality Level of SUE ROW Right of Way SUE Subsurface Utility Engineering SUE EXP Expenditure on SUE SUEP AB Percent of SUE Expenditure SIC Service Interruption Cost SSE Sum o f Squares Error TDC Travel Delay Cost UIR Utility Impact Rating UIC Utility Information Cost URC Utility Relocation Cost UVC Utility Verification Cost UDC Utility Damage Cost Vvh V erification of Vertical and Horizontal L ocation w i AHP Weighting Factor

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12 Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy AN OPTIMIZATION MODE L FOR SUBSURFACE UTI LITY ENGINEERING DUR ING THE DESIGN PROCESS By Michael Anthony Coffey D ecember 2010 Chair: Ralph D. Ellis Major: Civil Engineering Implementation of Subsurface Utility Engineering (SUE) during the design process is becoming more and more of a mainstream operat ional standard for civil engineering projects Many states are developing systems of implementation within their Department of Transportation (DOT) for SUE to become part of the highway and roadway design process. However, there are still traditional sequences of design develop ment that exist which do not consider the benefits of SUE early enough in the design process or not at all T he proper application to optimize the use of SUE by the Quality Level (QL) of information, the timing, and the designer decision based on project complexity is still n eeded. This research found a correlation between SUE investment on projects and the cost growth due to utility relocations and conflicts. Understanding that relationship, it was possible to identify an optimization of an investment level. The result s h elped to create a scoring system that could be used for all types of civil engineering projects which is parallel to the Utility Impact Rating system (Sinha 2008) that was developed for highwa y projects. The scoring is linked to a decision matrix The pu rpose of the matrix

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13 is to guide SUE use during the design to result in optimum results The research demonstrated that an increase in SUE investment would lead to less cost contribution due to subsurface utility conflicts and proposed an optimization model for the use of SUE The research identified an average cost increase across projects that did not utilize SUE in their design and referred to this percentage increase as a baseline in project cost. Then, looking at proj ects that involved SUE, the difference was found between the cost contribution and the baseline cost. The cost contribution became negative, representing a cost savings on projects. The data trend confirmed the initial statement of this research an inc rease in SUE expense above the quality level associated with typical topographic survey information would positively affect a project by reducing potential cost cont ributions due to utilities. Also, there is an optimized amount of SUE to be used on each pr oject which can be estimated based on these assessments

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14 CHAPTER 1 INTRODUCTION 1.1 Background In the United States, utility companies typically in stall their facilities within state owned, federally owned, or privately owned right of ways (ROW) or they may purchase utility easements for where their facilities are placed. When utilities are placed in right of ways, they are subject to future adjustm ents or relocations as the corridor of this right of way may change. Such changes could include a re alignment of the roadway section, an increase in roadway width for additional travel lanes, or vertical grade changes to raise or lower sections of a road way. When this occurs, the utilities in the corridor may need to be adjusted. Many facilities are essential and must remain operational at all times. There is a variable of difficulty in planning the relocation or adjustment of utilities while keeping the existing facilities in operation, all the while providing a design that can a dhere to the overall construction schedule with minimal impacts and harmonizing the different phases of work. Down time needs to be minimized, so both accuracy and precision play a key role in the development of sub surface utility adjustment plans. In o rder to plan precisely, the utility location must be known in the three dimensional space relative to other physical features surrounding the utility. In order to plan accurately, the utility size, the material type, and the condition of the utility play a vital role in preparing buildable construction documents that incorporate these adjustments. Utility corridors along roadways are becoming limited in their capacity for accommodation of additional utilities or replacements that may need to occur. Agi ng utilities must periodically be replaced. Newer technologies are being introduced to

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15 replace older technologies, such as fiber optic for communications. Older materials are being replaced with newer materials, examples would include asbestos pipe or vi trified clay pipe replaced with polyvinyl chloride (PVC) pipe for water and sewer mains. As the available space for subsurface utilities diminishes, the success of construction projects involving subsurface utility work depend heavily on accuracy of the d epiction and the attributes listed for existing subsurface utilities that are present in the area of the work. Utility conflicts are a leading cause for roadway project delays (Ellis 2005). The depiction and attributes of utilities shown in construction plans vary depending on the professional who prepared them. For the past 20 years, subsurface utility engineering (SUE) has constantly evolved to become a means which better characterize the quality of subsurface utility information and management of the risks associated with construction activities which may involve these facilities. Subsurface utility location started out with survey crews hand diggi ng to expose the utility, gathering information, and covering the utility back up. This created a new ri sk and liability for surveyors as information that was not shown or discovered would be considered a deficiency of the survey and a potential for litigation. Therefore, many surveyors avoided this by purposely excluding the type of work from their scope of services and As the need for this service grew, other methods of detecting, exposing, and recording subsurface utility information became available. Geo sensi ng units, vacuum trucks, and tracer wire are common place for utility locations performed today. The American Society of Civil Engineers created a standard in 2002 as a guideline for attribution of utility information quality, known as ASCE Standard 38 02,

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16 02, Subsurface Utility Engineering (SUE) is the convergence of technologies that collects, depicts, and manages subsurface utility location da ta (ASCE 2002). The goal of this document was to form a consensus of understanding for various levels of information. There are four levels of information quality for subsurface utilities in order to create a common understanding of the data integrity. A brief description of the four quality levels are mentioned below: Quality Level D This level of information has the least integrity. It can include information plotted on plans as interpreted from records, from site visit evidence, former drawings d imensioned or un dimensioned schematic plans. Quality Level C This level of information is based on limited topographic survey of above ground utility features with existing utility plans to produce a representation of the underground utility locations based on schematics in QL D and other utility records differing from field observation. This is more of a correlation between the confirmed as built records and the data found at Level D, since the above ground features may indicate more verification fo location, i.e. valve boxes, manholes, or other structures. Quality Level B This information is derived from non evasive methods, utilizing geo sensing equipment such as electromagnetic waves, geo sensing units, and utilizing manual method s such as dowsing rods or tracing wire. At this level the horizontal location is verified by horizontal control, and the vertical location is approximated based on interpretation of the Level C information. At this stage there is no verification of size or material type for the utility. Quality Level A This is the highest level of information integrity, because it is the full exposure of the subsurface utility for visual inspection. It is typically performed by vacuum excavation or test holes dug manua lly. This Level verifies the horizontal location as in Level B, but also verifies the vertical elevation based on datum reference, so there is a three dimensional coordinate assigned. This Level also includes the measured size, material type, and conditi on of the conduit or structure. It can also include pictures of the utility for reference. Utility owners, engineers, contractors and surveyors often employ this level of subsurface utility cal/horizontal (Vvh). They are utilized during the process of plans preparation or called for in the field during construction when a need arises for exact location information.

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17 1.1.1 Current Practices Utility owners that have facilities in the DOT right of way are required to provide their facility locates when requested by the DOT (FDOT 2009) Many DOTs also have direct contracts for SUE providers for occasions when locates need to be verified or cannot be provided by the utility owner. H owever, it is not always a standard requirement for the utility location plans submitted by the utility owner or the SUE provider to be certified to a specific quality level. This practice can vary state to state. In some cases, the information is not si gned and sealed by a registered professional surveyor or engineer. In some states, there is no commonly acknowledged standard for the information that is provided by various utilities and SUE providers nor is it acquired before the design occurs or as pa rt of the design contract The mechanism for location requests can also vary from office to office within a DOT operation. Some DOT offices can assign the task of subsurface exploration to the Right of Way or Survey office, others can assign it through th e Utility Engineer for that region, and some are directly issued by the DOT project manager for the roadway designer to sub contract (FDOT 2009). 1.1.2 Typical Roadway Design Process The roadway design engineer has the responsibility for setting the alig nment of a roadway corridor section and considering the existing features of the topography and physical objects within this established right of way corridor. This corridor has usually been established by a planning study that has been completed prior to commencement of the design. These studies have various names from state to state. They could be called a Project Development and Environment study (PD&E), or a Highway Project Development Process ( HPDP) in other regions of the US. Essentially the study has

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18 narrowed down the corridor location based on physical and environmental considerations. The roadway designer then applies the geometric design of the road to this corridor in accordance with the American Association of State Highway Transportation Of ficials (AASHTO) standards and state regulations The alignment can be adjusted for above ground features that are evident or the feature can be removed or relocated depending on its size. Another important consideration of the roadway design lies beneath the surface. Underground utilities of various types must be avoided, adjusted, removed and installed within the roadway corridor. These utilities can include potable water supply, sanitary sewer gravity systems, sanitary forcemains, electrical conduit, gas transmission lines, fiber optic telecommunication conduit, and storm sewer conveyance systems. Often times, the re is little to no QL A or B data collected prior to or at the 30% design stage to influence the design approach for the project. Nor is i t requested by the roadway designer at this point. In the be ginning of the roadway design, the typical section that was developed during the planning stage is applied to the given alignment which has resulted from the corridor study. A stormwater treatment area/pond location study has also been performed during this stage of the project, and a rough profile has been generated based on the preliminary master drainage plan. The profile sets the crests and sags in the roadway, and the division of dr ainage sub basins starts to take shape, which eventually leads to the inlet locations and the stormwater conveyance system design. the profile view of the plan set. I n most cases, only the proposed centerline or station

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19 line elevation of the roadway surface is shown. So at this point in the design, subsurface utilities are hardly considered an influence during development. At this stage, all known utility owners that Call system as having utilities in the DOT right of way for the corridor are notified of the of drawings with information know n about their facilities horizontal location, size, route, and any proposed installations that may be anticipated. The information provided by the utility owner approximates to a QL C/D, which is submitted back to the designer. In most cases, there is little to no vertical information provided. Some utilities are non responsive and no information is received by the roadway designer. The designer then takes all the respondents information and compiles this information into the roadway drawings. By the 60% completion level, the stormwater conveyance system is designed and shown in the profile of the updated drawings. The update is sent to the utility owners and Level A/ B locates are requested by the DOT. The util ities respond with QL A/ B information to augment their original submittal. Typically, the information is not entirely and vice versa, and locations are based on surface markings which were spray painted, not w here they actually reside. The roadway designer must incorporate a massive amount of information into the design, and make judgment calls in order to progress the design. The responsibility is intense: to produce a plan set and specification that can be bid and come in at or under budget, which is shown correctly and can be built, with minimal change orders, and finally professionally certifying those documents. The 60%

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20 design stage is where most occurrences of inaccuracy take place. This stage is wher e inaccuracies could be caught and corrected in time to produce a better product. It is intended for the 90% progress set to finalize the locations of all utilities proposed, adjusted, abandoned, or removed within the roadway project. It is also the stage where the utility work schedules are coordinated with the overall roadway construction schedule. Finalizing this set becomes the basis for the agreements between the utility owner and the DOT as to what work will be performed, who will perform the adjust ment and installation work (utility or DOT), at will be scheduled. The scope of work for the general contractor is defined and the job is bid out to prospective contractors at the 100% stage. Many DOT s have a policy for utility lia isons to hold prog ress meetings during each stage of design and during construction of projects (FDOT 2006). Not all utilities participate. Many utility owners do not have the specialization of SUE in house or contract on a regular basis to enhance their locations Data interpretation does not always render precise location information. When a utility representative is given a roadway design plan set that can be hundreds of pages, it can be overwhelming to identify and interpret their own utility while coordinating with other utilities and the proposed roadway design at the same time. These representatives also have to consider how to phase the adjustment work while keeping their facilities in service and remain on schedule a very tedious task. Some D OTs utilize a system of best management practices for incorporating subsurface utility engineering into the roadway design process. Processes vary state to state. Not every state has a uniform system of practice currently in place for utility

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21 coordinatio n efforts during the roadway design process. More times than not, there are still delays to construction schedules and overruns to construction budgets due to utility conflicts on state road projects. In the early design stages, the integrity of the locat ion data could be in question because of the collection methods used, the amount of data that was submitted, and the tracer wire, and other non intrusive methods leave s room for question of what lies beneath the surface and where it actually is. Also, how this information is presented plays a key role. It may be submitted to the roadway designer in various formats and at various quality levels. What may be considered accurate by the utility owner may in fact, not be accurate enough for roadway design considerations. actual location of underground utilities is known. By this time th e design has been completed and a contract has been execut ed for the work, resulting in change order s for the unforeseen conflict s that are foun d by excavation or accidental damage 1.1.3 Typical Coordination i n Roadway Projects The numerous utilities that exist within the corridor also do not submit their data at the same time during the review stages. Nor is the information received from each utility evenly distributed to all parties involved prior to the next design stage submittal. This lends to the pr actice of one utility designing adjustments without the benefit of real time location information of an adjacent utility. The result of this miscommunication creates an internal conflict between utilities, separate from the roadway and drainage conflicts anticipated. Throughout the roadway design process, utility owners do not have enough incentive to provide the highest accuracy of locates earlier in the process. Even in the

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22 final design stage there is a great deal of missing or inaccurate information w hich ends in conflicts, schedule overruns, disputes and change or delay claims. Maintenance of traffic (MOT) diverts the volume of flow around the work being performed. Lanes can be closed or entire roads are detoured due to the amount of work necessary f or adjustment. The full capacity of the roadway may not be available for hours, days, weeks, months, even years. If one would consider the amount of commerce that is affected when these activities take place, and consider the delay of vehicles traveling through this construction, this could drastically change the opinion of how much benefit subsurface utility engineering is to a state as a whole when used during the roadway plans production process. To be effective, the level of SUE must be closely monitored and tuned to each individual project. There is also the possibility of too much information on a project, which would drive the scope of SUE and the cost to soar (Osman 2005). Therefore, the lev el of SUE performed on a project is important to also remain practical. 1.2 Research Objective This study is fundamentally based on the hypothesis that a relationship exists between the extent of utilization of sub surface utility engineering and project o utcomes. Further, by understanding and defining that relationship, optimization of the use of SUE may be possible. As the use of SUE is optimized, a reduction in cost contributions due to utility conflicts on a project can occur. This research proposes the development of an optimization model based on investigation and analysis of the re lationship between the utilization of sub surface utility information during design and the resulti ng construction project outcome in terms of percentage cost contribution d ue to utility conflicts. F irst it looks at all parameters of

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23 the data collected for trends. It identifies an average baseline of cost contribution for projects that did not utilize SUE and establishes this baseline as a starting point to measure cost growth or decline. It analyzes projects for their cost contribution beyond the baselin e percentage due to utility conflicts, and relates this to the percent expenditure for SUE beyond the topographic survey level summarized as a typical QL C The model p rojects a cost savings percentage of original construction due to s pending beyond the QL C, using QL A/B fo r the SUE. A decision matrix i s created to optimize the synchronization of the design and integration of SUE information during plans pr oduction. T his is accomplished by assessing the project with a questionnaire and scoring method based on a modified version of the Utility Impact Rating first introduced by Sinha et al. (2008). The score translates into a mode of the decision matrix to enter for tha t particular project, and follows the decision steps of that mode. The goal of this model is to lead to better efficiency in decision making during the design process and to standardize the use of SUE. Anticipated results would include improving costs sav ings on projects, better schedules wit h shorter construction times with less impact to the public due to conflict delays, and projects that are better understood by all parties involved avoiding claims and costly litigation between parties. Proper appli cation of SUE could also improve the safety on jobsites by avoiding damage to existing utilities. There are quantitative benefits that have been stated by previous research, which show ed the cost benefit for subsurface utility locations being performed as compared to overall construction dollars. They were described in terms of cost variables or benefit factors by Osman et al. (2005) This research proposes measures of results which

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24 complement the c ommon method of benefit analysis. It ass esses the effect s on associated cost variables by importance through a ranking system It uses the Analytic Hierarchy Process (AHP) (Saaty 1980), to establish a hierarchy of those cost variables, based on the surveys of designers, engineers, and planners. It als o looks at various types of civil engineering work and how these cost variables score between each type of work This is a qualitative approach which could be utilized for a specific project to estimate quantitative benefits in terms of dollars saved for each var iable and determine the most influential variable on a particular project. 1.3 Scope The outset of this research was to find correlations between existing project data for SUE use during design an d how this affected project cost in terms of co st contribution due to utility conflicts The data for cost contribution was found in change order recordings related to utility adjustments. The invest igation would try to predict a bene fit from SUE involvement during design process and assess the variabl es of cost and establish a system to best manage the use of SUE during design The intent of the model is to give the planner/ design engineer /contractor a general sense of what impact SUE use has on reducing project cost contribution due to utility conflic ts The scoring system wou ld rate projects for the use of SUE during the design process by selecting the appropriate mode to follow in the decision matrix as assigned by the UIR score The model would also yield some forecast of cost variable effects on a project, and identify the variable most concerned for that project by the hierarchy established by the AHP.

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25 CHAPTER 2 LITERATURE REVIEW The literature review for this research needed to zero in on the following factors: the practic e of subsurface utility engineering as a whole, the current operational practice of DOTs concerning roadway plans production and incorporation of utility adjustment designs, the reasons for construction schedule delays and cost overruns on roadway projects and the existing studies of cost benefits for utilizing subsurface utility engineering according to the ASCE 38 02 standard. Subject titles included: subsurface utility engineering, construction delay, construction risk, highway construction, decision model, roadway plan production, utility conflicts, utility mapping, cost benefit analysis, construction engineering, utility mapping, and scheduling. As mentioned in the beginning of this article, a leading cause of delay on highway construction projects is due to utility professional experience, every roadway project encountered involved some form of utility conflict related delay. In some cases the utility location was inaccurately reporte d which caused field modifications and damage to existing facilities. Other reasons for delay have been attributed to the work performed by the utility owner or utility contractor prior to the roadway project work, and conflicts with other utilities overr an the schedule for adjustments, bringing about a claim for delay by the roadway contractor. In rare cases, the utility coordination efforts of the roadway designer were simply ignored or not taken seriously by the utility representative, which led to mis sing information and in turn, exposing a utility conflict in the field during construction.

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26 State roadway projects usually involve miles of work. In the corridor there are many utilities that share the existing right of way: water, sewer, gas, fiber opti c, telephone, and electric. This results in a large amount of data that must be processed by a representative of an individual utility identifying and keeping track of their own utility locations progressing through the roadway control stationing, and k nowing where adjacent utilities are while establishing new locations and adjustments. Multiply the number of projects that this certain individual must handle, and it can be overwhelming. Like everything else in the project, the design has a schedule, an d most times it is too short to arrange all the proposed or adjusted underground locations in a design to result with no conflicts during construction. 2.2 Res earch o n Cost/Benefit Analysis Former studies have been done on SUE and the benefit of its implem entation. Many of these studies suggest a cost benefit ratio as a measurement. This measurement was derived by simply dividing the estimated utility adjustment construction cost by the actual cost of the subsurface utility engineering activity. The purp ose of this was to exhibit the cost of the subsurface utility engineering being far less than what the utility adjustments would have cost. The author finds this subjective in nature. First, the potential utility adjustment work stated in the research wa s estimated it was not hard cost. Unless adjustment plans had been prepared, the work was let and contractor prices for the scope of work were established, this becomes an opinion of cost potential only. Secondly, the timeline for these adjustments was not mentioned. One could reason that time would have a direct correlation to t he cost for these adjustments. As an example, if the schedule was too short, one would expect the unit

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27 cost to be much higher as compared to the other extreme of a schedule tha t was extended for years beyond the roadway completion date. Stevens (1993) used a pie chart to exhibit the various costs associated with a project. For his presentation, he assumed 5% of the construction cost equated to saving half of the utility reloc ations. He further assumed saving 1/3 of the cost overruns would equate to an additional 5%, and 2.25% savings would result from construction efficiency when SUE is used. Somehow the statement is made that between 10 15% can be saved on a project that ut ilizes SUE, based on the pie chart breakdown. The issue with this is not the assumptions that Stevens (1993) made in his paper, but that his percentages and cost breakdowns have been cited by subsequent authors as a reference point, when in fact they were assumptions all along. In a Purdue study of 71 projects, the FHWA established that subsurface utility engineering saved an average of $4.62 of construction dollars for every dollar spent on SUE, Lew (2000). utility adjustment construction dollars to actual SUE dollars. The report concluded that qualitative measurements could have provided a much larger benefit in terms of additional cost savings to the quantitative amounts stated. These were not measured in the Purdue report. The report by Sinha et al. (2008) performed an analysis of the benefit to cost ratio for SUE projects, non SUE projects and total projects. The benefit was calculated by dividing the sum of the cost of the anticipated relocations, anticipated design cost, and anticipated informati on gathering cost (B SUE ) by the amount spent on SUE designating and locating ( C SUE ).

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2 8 These costs were anticipated and not real since they never occurred. Also, there is no comparison with a baseline of topographical survey that typically occurs on all proj ects. there is some level of information which would be QL C that would need to be included as part of the calculation for the benefits or the costs. 2.3 Risk Management Research Sinha et al. (2008) was the first to propose the idea of a Utility Impact Ra ting ( UIR ) system, which led to predict three outcomes: 1) the need for subsurface utility engineering on a project, 2) the recommended quality l evel of information to be used for the project as a function of risk score, and 3) the ratio of cost increase from one level to the next. The purpose was to assess what level of quality needed to be done and what risk level equated to it. The qualitative variables were taken into account for the Impact Rating Analysis he created. Still, the cost of utility adju cost anal ysis are estimated. Also, he continues to cite the report by Stevens that the average savings for projects that utilize SUE is between 10 15%. The Utility Impact Rating system devised is useful. However, more variable s need to be considered in the scoring and some characteristics could be r emoved altogether. The cost variables are : UIC Utility Information Cost UVC Utility Verification Cost URC Utility Relocation Cost DSC Design Cost OCC Overall Construction Cost CCC Contractor Contingency Cost CCO Contractor Claims and Change Order Cost CIC Contractor Injury Cost UDC Utility Damage Cost PIC Personal Injury Cost TDC Travel Delay Cost BIC Business Impact Cost SIC Service Interruption Cost

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29 2.4 B est Management Practices Many papers have focused on the application of SUE as a best management practice. Early location and depiction of subsurface utilities during the design and construction process has been a common theme throughout these articles. The earlier the information is gathered and considered, the better the outcome with regard to less subsurface conflicts. It would be ideal to have utility relocations performed prior to roadway construction. However, this is not practical as there may be no location available for placement, due to restricted right of way, population of other utilities in the same corridor, or the area proposed has not been cleared. (Ellis 2005). The American Association of State Highway and Transportation Officials (AASH TO) issued a guideline for right of way and utility accommodation best practices. It centered on effective communication between parties, utilizing the best technologies available for locating and storing utility location information, the timeliness and scheduling of adjustment plans, avoidance of late plan changes, and good record keeping. All of these practices lessen the risk on a project involving subsurface utilities if applied during the design to construction process. 2.4.1 Utilize Best Tech nology AASHTO recommends utilizing the most up to date technology for data collection and record keeping. This includes SUE and mapping utilities with systems such as Geographic Information Systems, ( GIS ). It also recommends keeping track of cost savings and time savings as a result of the technology. 2.4.2 Effective Communication communication. The timing of sub surface utili ty adjustments and relocations during

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30 construction are an essential factor in overall project outcome. For roadway projects, the DOT assigns a utility liaison whom is either a DOT representative or a consultant to manage the information distribution to ex isting utility owners. The issue is not with forming this entity to convey the information, it is with the actual practice and the utility owners taking this coordination seriously. 2.4.3 Utility Coordination On larger projects the DOT has implemented t he contractor to also become the utility coordinator on the project. This way the contractor can schedule and align progress of relocations with the overall work schedule. This helps to minimize schedule delays since it is the contractor that is aligning these relocations to take place under t he same MOT or under the same excavation activity. 2.4.4 Long range Planning AASHTO recommends distribution of long range schedules to utility owners for future projects, so that they are made aware of these plans we ll in advance of the design. This helps utility owners to consider aligning their own maintenance work such as line replacements and system upgrades with the impending roadway projects in the same area. This also helps the utility owner with their capita l improvement plan ( CIP ) and long range budgeting for maintenance to their systems so that the dollars are available at the time of construction. 2.4.5 Include Utility Owners in Design Process AASHTO recommends including the utility owners in the design pr ocess to coordinate utility relocation work at the onset, not after the design is complete. This includes the roadway design consultant to meet with each utility individually during the design process.

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31 2.4.6 Design for T he Future AASHTO recommends establi shing and designating utility corridors for future use. These can be for either longitudinal installation or major crossings. This allows for installation at a later date with little to no interruption of the roadway during construction by the utility. 2 .5 Analytic Hierarchy Process This process was developed by Saaty (1980) for dealing with complex decision making. It is a rational method that uses math and psychology to set up a problem for decision making. When variables of the problem are inter depe ndent, the AHP quantifies them and relates them to the decision goal. This is accomplished by comparing each variable to every other variable in the set by pair wise comparison Each variable is then weighted by its relationship to the other variables o f the decision. This comparison is translated into a numerical value between 0 and 1 for each variable. The sum of all variables is the goal, which has the value of 1, and the hierarchy is the weighting of the variables. The process does not spell out an answer, but guides the user by outlining the problem in a logical manner. 2.6 Conclusions Cost savings estimates from Stevens (1993) have been carried through in subsequent publications as the basis for the cost/benefit argument. Osman et al. (2005) stated that the savings associated with performing SUE is the reduction in certain variable values above. But which variables are outside of the base price for the project scope of work? Where in the project timeline does that measure ment start? S inha et al. (2008) SUE, which numbered 11 total. Some of the se variables correlated with the cost variables presented by

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32 Osman et al. (2005), however some did not exist, some were new, and others were considered combined For a fair comparison and assessment of increase in costs, the equation of cost variables should be from one set point in time of the project to create a baseline price. Either from the point of design, prior to construction ( budget) or upon contract aw There is one consideration that needs to be included when discussing project c ost. Environmental impacts. They do play a part in the entire scheme of a project and can be a major factor i n some cases. EIC Environmental Impact Cost should be considered in the cost variable equation, as it pertains to accidental spills, leaks, required clean up and other environmental impact costs that are outside the base scope of work that are the resul t of damage to sub surface utilities during construction. This could be extreme and a major cost of not performing SUE. I t is the decision of designer or roa dway PM to decide when and how much SUE to use on FDOT projects. There is no systematic procedure in place and the process varies from designer to designer and District to District. There is no standardized method for subsurface utility information retrieval in the FDOT system This can vary in each district. Also, there is no cost tracking of what i s spent on SUE to measure its benefits. There is no set point in time during the preliminary engineering design for which QL A information is request ed on projects, sometimes it is too late for adjustment of plan concept There is no standard quality level of information set from project to project The quality l evel designations according to ASCE 38 02 are not used. Terminology of SUE is greatly misused in the Florida industry and not clearly defined. Former studies have focused on the ratio of benefits to costs as compared to overall project cost. The benefits being defined by project interviews, historical cost data, and project specific information. All studies have performed a dollar for dollar comparison of amount spent on SUE versus the amount of utility conflicts, but there is a base cost of SUE level that is performed on every project. No research has been found that has shown a relationship betw een the SUE investment beyond the topographic survey QL C level and the reduction in cost growth due to this investment to perform QL A/B They have only shown total anticipated costs that were not real based on estimates and historical costs

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33 CHAPTER 3 METHODOLOGY 3.1 Data Collection The data collection for this research centered on the Florida Department of Transportation ( FDOT ) as a database since this was the best source to find real numbers for SUE expenditure and the resulting utility change orders for common project types. Data was collected from the Contracts Administration Office, the Procurement Office, Project Managemen t Office of Design, and individual District offices between December 2009 and August 2010. Foresight strategy to data collection included identifying what project data would be relevant to the research from what was available, and from what existing FDOT systems to mine this data. This was difficult because the record systems in place at FDOT do not record the specific costs for SUE separately. Sometimes the SUE cost was a part of the survey cost, other times it was included in the design cost. Some dis tricts utilize a district wide continuing contract for SUE, so those costs were never linked to the individual projects where the SUE was performed. The research also found there is no link between the Preliminary Design ( PD ) phase of a project and the c onstruction phase of work in the FDOT records management systems The Contracts Office only stored data concerned with construction contracts and they had no access to the PD phase of the project which would have the SUE amounts related to the job. Their database references the construction contract number for the project. The Procurement Office did not have specific project data records that was left up to the individual District offices to manage. They too had separate design contract numbers for th e design phase which

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34 had no relation to the construction records. Therefore, to cross reference the two sets of data, the researcher requested a search for projects by work number. All projects have a Financial Project ID number, (FPID). This number co nsists of an eleven digit sequ ence. For e xample: 555555 1 52 01 would be the format of the project number. The first six digits reflect the work program and this number remains the same between different phases of the project. The next digit is the item segment, which is a portion of a project if it is segmented. The following two digits are the phase group The contract numbers for the construction projects were cross referenced for their FPID number. The list of FPIDs were then truncated to the first seven digits and District offices with the request for SUE and survey expense on the project s. 3.1.1 Construction Project Data The Construction Office initially supplied data for 2,056 projects. This data included all project through the last 10 years. Information included the original contract award amount (OCC), resulting contract amount, c ost of total change orders, cost of utility conflict change orders, time extensions due to utility conflicts, location of project by district and county, and more classifications. The targeted amount for this study was the total contribution of costs due to utility conflicts, (CC UTILITY ), which was where the trend was being sought. The data set was comprised of all types of projects including traditional design bid build, design build, PPPs, emergency contracts, push button contracts, and continuing servi ces contracts. The various types of projects would not render a clear correlation between the use of SUE during design and the project outcome. Therefore, the data set was reduced to only traditional design bid build

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35 They totaled $4.2 billion in total original contract amount. From Figure 3 2 the majority of projects were resurfacing projects at 46%. The next largest group was r ehabilitation projects at 34%. For the remainder of the proje cts, ten percent were new construction, seven percent were traffic operations, and three percent were bridge projects. Graphing all projects in the set of 285 traditional projects shows that the cost contribution due to utility conflicts is not proportiona l to project size in dollar amounts. The percentages vary from range to range of construction dollars and do not show a specific trend. This is exhibited in Figure 3 3 When t he data set was isolated to bridge work, and graphed, the cost contribution due to utilities was not proportional to the amount of the original contract. It was more inversel y proportional to the contract amount, but so staggered that no trend was found here as shown in Figure 3 4 The data set was isolated to new construction in Fi gure 3 5 and the cost contribution due to utilities showed a small proportion to the amount of the original contract between 0.11% and 0 60%, but with outliers. Beyond 0.60%, the trend was staggered. No trend was found for this comparison. The data set in Figure 3 6 was isolated to rehabilitation projects, and the cost contribution due to utilities showed a small trend which was inversely proportional to the amount of the original contract between 0% and 7%, but with outliers. The values staggered throu ghout and no trend was found for this comparison.

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36 The data s et for only resurfacing projects is shown in Figure 3 7 and the cost contribution due to utilities was not proportional to the amount of the original contract. The data was so staggered that no trend was found here either. Staggered data is shown for the traffic operations projects in Figure 3 8 Again, no trend in the data behavior was evident for this specific group of projects. Below is the summary table of the cost contribution of utility conflicts to the projects and the original construction contract amounts. Table 3 1 Summary statistics of 285 traditional design bid build contracts Mean OCC Mean Percentage of CC UTILITY Standard Deviation of OCC Standard Deviation of CC UTILITY $ 14,736,768.69 2.24% $ 19,196,924.93 3 .04 % 3.1.2 SUE Cost Data The second step of the data collection was to find the amount of SUE that was spent during the design phase for these projects. This information was sought from SUE providers, consultants, the Procurement Office in Tallahassee, the seven FDOT District offices, and the Turnpike Authority. Cross referencing the design contract FPID with the construction project FPID made it possible to associate the design phase of the project with the construction phase. Still there was a large deficit of SUE and survey cost data for all projects. Responses numbered only 26 of the initial 285 projects being sought. The data li st for the 26 projects is shown in Appendix B. 3.1.4 Cost Variable Survey A s urvey was created to rank the 13 cost variables into a hierarchy of influence on projects. It compar ed each variable to the other 12 and ranked their importance on a

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37 scale of 0 to 5 in both the left and right direc tions, wit h zero in the middle. Figure 3 1 shows how Business Impact Cost (BIC) due to temporary business closure due to a project is scored against the remaining cost variables individually. "What element would have mo re influence on the overall construction project, (both schedule and budget) by affecting the opposite element it is compared to?" Enter "x" in the box you select. Enter in only one box for each question. Zero is no influence in either direction. If a question doesn't apply to your type of project, enter '0' for no comparison. Five is the most influence in one direction. Rely on your own interpretation of the statement, there is no right answer. 5 4 3 2 1 0 1 2 3 4 5 Temporary Business Closure Due To Project BIC X CCC Contractor Contingency Cost Temporary Business Closure Due To Project BIC X CCO Contractor Change Orders Temporary Business Closure Due To Project BIC X CIC Contractor Injuries On Job Temporary Business Closure Due To Project BIC X DSC Re design During Construction Temporary Business Closure Due To Project BIC X EIC Environmental Impacts Due To Utility Work Temporary Business Closure Due To Project BIC X EOC Errors and Omissions Insurance Temporary Business Closure Due To Project BIC X PIC Personal Injury of Travelers Due To Utility Work Temporary Business Closure Due To Project BIC X SIC Service Interruptions Due To Utility Work Temporary Business Closure Due To Project BIC X TDC Travel Delay Due to MOT or Re routing Temporary Business Closure Due To Project BIC X UDC Utility Damage Caused During Construction Temporary Business Closure Due To Project BIC X URC Utility Relocation Construction Temporary Business Closure Due To Project BIC X UVC Verifying Underground Utilities (VVH) with Soft Digs Figu re 3 1 Example of scoring from a portion of the cost variable survey

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38 A score of 5 would mean the variable had c omplete influence over the variable it was being compared to A score of zero would mean both variables have no relationship or influence between them. The purpose was to take the results of the pair wise comparison survey scores and perform the AHP process with the SuperDecisions software. This would identify a ranking of the variables for each discipline. The full survey that was issued is shown as Appendix C Design engineers from four specific areas of specialty were asked to fill out the survey. These specialty areas included: Aviation, Highway, Site, and Port design. Participants were asked the question, "What element would have m ore influence on the overall construction project, (both schedule and budget) by affecting the opposite element it is compared to?" The participant would then choose zero or between 1 and 5 on the left or right side of the chart for each pair wise compari son The respondents numbered 11 of the total 53 surveys that were sent out. 3.2 Model Concept Th e model will propose a relationship between the utilization of sub surface utility information during the design process and resulting cost contribution duri ng const ruction due to utilities. It would further suggest that an optimization of this relationship could produce an optimum outcome, as a sub optimization would produce a sub optimum outcome. For instance, low integrity information used explicitly thro ughout a design could result in a sub optimum construction project due to increases in cost associated with un foreseen utility conflicts and adjustments. At the same time, too high of a data integrity level for a very small project might cost more than th e actual construction work itself; lending to unnecessary expense during design.

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39 The mode l starts with a questionnaire. The project is scored from a modified UIR system b ased on the responses to the questions that are answered (not all must be answered as they may not be applicable). T he UIR translates the score to one of four modes of a decision matrix chart. Upon entering a mode of the chart, the designer is given steps to take with decision points to assist in best managing the application of SUE durin g the design process. When the design has utilized the SUE, one would be able to take the expenditure beyond the level of topographic survey, and estimate the range of cost contribution or savings percentage as compared to not utilizing SUE at all. In ad dition to projecting an estimated cost savings, one could also assess the impact to cost variables ranked by the AHP process. This would indicate which variables are of the highest importance on a project and may assist the designer in making special cons iderations during a design approach. 3.2.1 SUE Quality Level Assignment f or Data As it currently is, SUE in Florida DOT (FDOT) work terminology is referred to only as Vvh and not by the quality levels defined by ASCE 38 02. The cost data that was retrieved from the FDOT contract system refers only to that amount spent on Vvh or vacuum excavation that occurred on the project. There were essentially only two quality levels available for this study. The data associated with an equivalent to QL C the topographic survey data, and that of QL A/B further verification by geophysical or exposure methods beyond conventional survey. There was no differentiation between QL A an d QLB in the cost data. For the 26 projects of this study, each was assigned a QL. If they included SUE, they were labeled QL A/B projects. If they did not use SUE, they were labeled QL C projects.

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40 3.2.2 Variables of t he Model Variables were identified to compare how the use of SUE affected the construction outcome. Each variable had to be able to represent a project regardless of size. Therefore, it was decided to discuss in terms of percentages and not hard dollars spent. The concept was to compare the increase/decrease between two variable sets and identify any trends that occurred. The dollar amounts cited to calculate the percentages were: 1) The amount spent beyond the topographical survey for subsurface utility locating (SUE EXP ), and 2) The c onstruction cost contribution due to subsurface utility conflicts or adjustments, whether part of the construction documents or as they are found in the field cost contribution due to utility conflict ( CC UTILITY ). Finding the percentage increase or dec rease for these two items would allow one to apply the resulting projections to other projects of any size and scope. 3.2.2.1 SUE variable r epresentation The researcher first tried to correlate the various inputs in terms of dollars, but no correlations existed. For instance, SUE EXP averaged less than 0.128% of the original construction contract while CC UTILITY averaged 2.24%. Graphical representations between SUE EXP and CC UTILITY could not be interpreted due to the scale of each variable. Therefore ano ther approach was made to compare these two variables relatively. All projects involved some form of survey work, whether it was a re surfacing project, a rehabilitation or new construction project. The expenditure for survey also varied depending on th e type of work, the information available for that specific project (meaning if a recent survey had been performed), physical environment and number of topographic data shots necessary for densification. Knowing that this survey cost would

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41 be proportional to the size of the project, and that SUE EXP was for those utility location services above and beyond the established cost for the topographic survey level ( CTS ), (geo sensing, vacuum excavation, etc.), the quantification of SUE was represented as a percen t increase over and above the survey expenditure (SUEP AB ), represented by: (Equation 1) 3.2.2.2 Cost contribution increase variable r epresentation Projects were ranked by the cost contribution due to utility work (CC UTILITY ) divided by the original construction contract price ( OCC ) to calculate the cost contribution for utility work as a percentage of the original contract (CCP UTILITY ). (Equation 2) The construction cost increase variable then becomes proportional to the project size for the amount of utility conflicts found on a project. 3.2.3 AHP P rocess f or C ost V ariable S urvey The survey created for the AHP process were collected from the participants and grouped according to project type o r specialty. There were four groups: Aviation, Highway, Site, and Ports. The average scores for each specialty were to be used as the input for the SuperD ecisions software program in each case. Each cost variable was

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42 input as a cluster. A cluster comparison was performed and the weighted super matrix was created. 3.2.4 Anticipated Trend i n Data Behavior The hypothesis of this study stated that an increase in SUE P AB would decrease CCP UTILITY and that this relationshi p would be inversely proportional. If more was invested in SUE, then this would reduce the cost contribution on projects due to utility conflicts. The researcher initial ly anticipated that by using this model of measurement for the use of SUE a savings projection of close to half of the 10 15% Stevens (1993) stated would be found 3.2.5 Modification t o t he Utility Impact Rating System Sinha et al. (2008) introduced the UIR system to assess projects for the appropriate QL of SUE to utilize on projects. I t consisted of 20 questions, the first six sorting out if QL A or B should be used at versus only using QL C and D for sub surface utility information. The remaining 16 questions assign a score of 1, 2 or 3 to each question. T he sums are then weighted and a sco ring is made in the range of 1 through 3. The UIR was centered only for roadway projects. This research enhanced the questionnaire and scoring system to include a variety of projects beyond roadway, such as maritime, site, rail, manufacturing/chem ical plants, and airfields. It also included more questions about the project scope and environment. This way, the UIR could be used for more than just roadway design. 3.2.5.1 Weighting of cost variables in the UIR system The modified version of the UIR linked the cost variables to each scoring. The individual variable weighting of the AHP analysis ( w i ), is assumed to be the percentage of the total cost impact or the total cost benefit associated with that particular variable.

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43 When this weighting is mul tiplied b y the CCP UTILITY it results in the percent age of cost contribution for that particular variable ( CCVP i ). This result can be multiplied by the OCC to estimate the total cost contribution of the variable in dollars ( CCV i ) due to not utilizing SUE on the project (Equation 3) (Equation 4) (Equation 5) (Equation 6) Where Cost NP is the total cost in dollars f or not performing SUE. 3.2.6 Decision Matrix Once the UIR is completed, the resulting score is then entered in the decision matrix. A mode of operation is then recommended for subsurface utility data collection, review and analysis on a project. This exercise should be performed during the PD&E or very early in the preliminary d esign stage of the project so that the scope of SUE work can be clearly defined for the survey and SUE crews.

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44 Figure 3 2 Pie chart breakdown of all traditional project type s. 34% 10% 46% 3% 7% Types of Projects Pie Chart 285 Traditional Projects Rehabilitation New Construction Resurfacing Bridge Traffic Ops

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45 Figure 3 3 Graph of OCC and CC P UTILITY for 285 traditional projects. $ $20,000,000.00 $40,000,000.00 $60,000,000.00 $80,000,000.00 $100,000,000.00 $120,000,000.00 $140,000,000.00 $160,000,000.00 0.00% 0.04% 0.11% 0.20% 0.29% 0.41% 0.54% 0.62% 0.75% 0.83% 0.92% 1.01% 1.08% 1.21% 1.34% 1.39% 1.57% 1.65% 1.88% 2.09% 2.29% 2.56% 2.78% 3.28% 3.67% 4.32% 5.12% 7.14% 12.42% Overall Construction Cost OCC Cost Contribution Percentage Due To Utilities CCP UTILITY Original Construction Cost versus Percent Cost Contribution of Utility Original Construction Cost

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46 Figure 3 4 Graph of OCC and CC UTILITY for bridge projects. $ $10,000,000.00 $20,000,000.00 $30,000,000.00 $40,000,000.00 $50,000,000.00 $60,000,000.00 $70,000,000.00 0.06% 0.21% 0.55% 0.56% 0.87% 0.93% 5.03% 6.62% 12.15% Overall Construction Cost OCC Cost Contribution Percentage Due To Utilities CCP UTILITY Original Construction Cost versus Percent Cost Contribution of Utility Bridges Original Contract Amount

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47 Figure 3 5 Graph of OCC and CC UTILITY for new construction projects. $ $20,000,000.00 $40,000,000.00 $60,000,000.00 $80,000,000.00 $100,000,000.00 $120,000,000.00 $140,000,000.00 0.02% 0.03% 0.04% 0.05% 0.11% 0.17% 0.17% 0.19% 0.21% 0.29% 0.51% 0.52% 0.58% 0.62% 0.62% 0.65% 0.70% 0.83% 0.93% 1.05% 1.05% 1.09% 1.29% 1.39% 1.58% 2.61% 2.65% 3.59% 9.68% 17.32% Overall Construction Cost OCC Cost Contribution Percentage Due To Utilities CCP UTILITY Original Construction Cost versus Percent Cost Contribution of Utility New Construction Original Contract Amount

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48 Figure 3 6 Graph of OCC and CC UTILITY for rehabilitation projects. $ $20,000,000.00 $40,000,000.00 $60,000,000.00 $80,000,000.00 $100,000,000.00 $120,000,000.00 $140,000,000.00 $160,000,000.00 0.00% 0.02% 0.06% 0.19% 0.23% 0.28% 0.41% 0.47% 0.57% 0.66% 0.75% 0.80% 0.89% 0.92% 0.96% 1.01% 1.12% 1.39% 1.41% 1.64% 1.99% 2.09% 2.20% 2.32% 2.70% 2.90% 3.12% 3.67% 4.51% 5.12% 7.53% 12.23% OCC Cost Contribution Percentage Due To Utilities CCP UTILITY Original Construction Cost versus Percent Cost Contribution of Utility Rehabilitation Original Contract Amount

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49 Figure 3 7 Graph of OCC and CC UTILITY for resurfacing projects. $ $10,000,000.00 $20,000,000.00 $30,000,000.00 $40,000,000.00 $50,000,000.00 $60,000,000.00 $70,000,000.00 $80,000,000.00 0.01% 0.06% 0.22% 0.31% 0.53% 0.67% 0.81% 1.02% 1.12% 1.21% 1.27% 1.34% 1.39% 1.58% 1.74% 1.83% 2.02% 2.28% 2.43% 2.78% 3.28% 3.52% 3.69% 4.32% 5.12% 8.24% OCC Cost Contribution Percentage Due To Utilities CCP UTILITY Original Construction Cost versus Percent Cost Contribution of Utility Resurfacing Original Contract Amount

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50 Figure 3 8 Graph of OCC and CC UTILITY for traffic operations projects. $ $5,000,000.00 $10,000,000.00 $15,000,000.00 $20,000,000.00 $25,000,000.00 $30,000,000.00 OCC Cost Contribution Percentage Due To Utilities CCP UTILITY Original Construction Cost versus Percent Cost Contribution of Utility Traffic Operations Original Contract Amount

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51 CHAPTER 4 DATA ANALYSIS 4.1 Overview The research started with 2,056 FDOT projects spanning over the last 10 years and it included various types of procurement methods Of this total, 285 projects were traditional design bid build projects. These projects were selected to limit variations in the types of contract s tructures in order to arrive at a true comparison of the values sought for SUE use and its affect on cost contribution due to utility conflicts For instance, push button or emergency contracts are on a continuing basis with the FDOT and would not render a true before after result Design build contracts include design as a part of the total construction contract. This research wanted to focus on construction plans being produced with or without the benefit of SUE during the design process then assessin g the result s during construction. Traditional des ign bid build contract data provided a way to measure this 4.2 Data Deduction The data set started at 285 projects that were traditional design bid build. These projects were divided by district and the district offices were solicited for supporting information such as expenditure on topographic survey and SUE during the design process. Due to the fact that these costs are not recorded in the same manner project to project, and the eight districts pract ice differently as to how this information is recorded into the system, the list of projects greatly reduced. T he respondent data numbered 26 projects. These included both projects that did not us e SUE above a QL C and those that used QL A/B.

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52 4.2.1 Data Frequency The data for the 26 projects was analyzed for frequency of various attributes such as the contract value, utility related change orders, and the increase in survey cost s for SUE. Most project s were in the range of $5M. The utility related chang e order s were mostly one percent or less. T h e projects that utilized QL A/B totaled 11 of the sample lot Five of these projec ts had a cost increase of approximately 30% for the QL A/B addition. Summary d ata for the results of thi s analysis are shown in Table 4 1 The frequency of the da ta for the contract values showed that a majority of the contracts were $5M and none of the studied pro jects were over the $60M mark. It was interesting that these projects had the survey and SUE cost data, where the lar ger projects of the 285 projects for traditional de sign bid build had none of this data available on record The frequency of the CCP UTIILITY shows that a majority of the contracts were one percent to two percent. A smaller population resided between four and nine percent. One project resulted in 11.36% of the total contract price for CCP UTILITY For most of the projects in the study, their CCP UTILITY was in the range of zero to one percent. A second place probability fell between the one and two percent range. Very few projects had above three percent for utility costs. Th is showed no trend in the CCP UTILITY as related to the dollar amounts of contract s for the projects studied. F our tables that quantify the statistics from each analysis of the dataset are shown at the end of this chapter 4.2.2 QL A/B Project Performance Total contracts were $511 million for the 26 projects in this study Fifteen proj ects of the 26 analyzed did not use QL A/B on the job. The average CCP UTILITY for those

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53 projects was 2.2 6 % (ACCP UTILITY ). This percentage was close to the overall average cost of utility change orders for the original 285 projects, which was 2.24%. Ther efore, a baseline of cost growth was established with this percentage in order to compare the QL A/B project performance. The difference between the individual project change order percentage s for the QL A/B projects (CCP AB ) and the ACCP UTILITY was taken to find the cost reduction for utilizing QL A/B on projects (CR AB ) which would be the negative value of the cost savings due to utilizing the QL A/B level (CS SUE ). A negative number for cost reduction would be a positive savings of that same percent age of the original contract amount. (Equation 7 ) A graphica l representation is shown in Figure 4 4 This graph sho ws a very distinct trend in the data. As expenditure for SUE at the QL A/B increases, the difference between the project CCP AB and the ACCP UTILITY shows the cost contributi on due to utilities is reduced. 4. 2.2.1 Regression a nalysis A two degree polynomial regression function was fit to the data to exhibit any trend in data behavior based on regression analysis The resulting equation for the regression is shown below as Equation 8. (Equation 8 )

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54 The function was plotted to the graph containing the original data points as shown in Figure 4 4. The shape of the function revealed that as the expenditure on QL A/B increased, the cost reduction slope is negative and continues until it comes to the minimum point on the graph. This would be the maximum reduction of costs due to utilizing SUE. This is also where the slope of the reduction turns from zero and starts to become positive, as the cost reduction becomes less and less as more expenditure on SUE occurs The function was used to project beyond the range of the original data in or der to complete a shape for a wider ran ge of the percentages for SUE expenditure. 4.2.2.2 A nalysis r esults The derivative of the resulting function was taken to find t he local minimum, which would equate to the optimized point for the original data set. The derivative is shown as Equation 9 below. (Equation 9 ) The function was solved for the derivative equal to zero. The resulting value for the SUEP AB was approximately 51.7% at the maximum cost reduction that equated to a value of 1.74% for the cost reduction CR A B. 4.2.3 Influence of SUE Use o n Projects for the original data was less than anticipated but still showed a true benefit. This could be because of the limited amount of data availabl e for this study. Also, many variables are different between this study and the former research conducted. Such variables could include: geographic location, site conditions, contract amounts, bid process, types of projects, difficulty of projects and spec ial circumstances for construction to name a few.

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55 The different percentages cited by the previous authors are inclusive of much more than what may be rec orded by the project records, and do include estimated dollar values for design or installation of opt ions that were no t performed and documented They remain as estimates based on historical pricing. Still the conclusion is the same but to a lesser extent. P revious studies did not compare the difference in the inc rease in QL A/B with the topographic su rvey set a baseline of cost percentage This may have something to do with the erratic results of the report by Sinha et al. (2008) for the B/C comparison. 4. 3 Modified Utility Impact Rating System The answers to the questions in the UIR generate the scor e to be used for assessment of a project and the need for SUE. To stay consistent with the existing model, the scoring system was kept between 1.00 and 3.00. More types of questions were asked to cover more of a variety of projects. The original model on ly addressed highway and roadway work. Still, the score weighting was performed in the same manner as the Sinha (2008) model to stay consistent with the concept and continue the same thought process An example of the modified UIR scoring sheet is found in Appendix F. 4.3 1 UIR Score a nd SUEP AB Relationship A relationship was proposed at the beginning of thi s research between the UIR scoring and the SUEP AB It can be deduced that the SUEP AB will increase as project complexity increases: the more need fo r data in the form of SUE, the more the percent of the total survey cost will be incurred for performing this need It is reasonable to estimate that as a project becomes more complex, the level of SUEP AB will not be proportional to the increase in survey cost such as a straight line. I n extremes it would exceed the total base value of the topographic survey. This relationship would behave

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56 more like a natural log or polynomial equation. The SUEP AB would in crease slightly at lower v alues of the UIR scor e, and gradually increase with the declining slope of the function as th e project complexity increased As the UIR score arrives at 3.0, the maximum score for the UIR, all following SUEP AB percentages woul d remain at a UIR score of 3.0 as they cannot be higher. Based on this mathematical relationship, an estimated equatio n was proposed Given that the maximum UIR score for QL C is 1.71 according to the method s outlined by Sinha (2008) and he re assumed to be relative to a typical topographic survey level and that there is a maximum score of 3.00 for the UIR scoring system, the equation formulation sta rted with the QL C level of 1.71 equal to the value of zero for SUEP AB A natural log eq uation was propose d for the behavior of this relationship to arrive at the score of 3.0 The relationship is not exact, but proposed here as a trend. The equation enables the resulting UIR score to be translated into an estimated SUEP AB for the project, which can then be t ranslated into an estimate of the CR AB Figure 4 5 shows this proposed relationship in graphical form. 4.3.2 Assessment of Potential CR AB Based on SUEP AB from UIR When the UIR score is related to the estimated SUEP AB this value can now be entered into the graph of the comparison between the CR AB and the SUEP AB to assess the CR AB that can be anticipated for a given data analysis. For instance in this example, for a UIR score of 2.70 the estimated SUEP AB would be approximately 21.3 %. Those values entered into the comparison of the SUEP AB and CR AB result in an estimated cost reduction of approximately 1.04 %.

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57 4.3 3 Decision Matrix When a UIR score is reached, this also translates to a mode of operation shown in the decision matrix. An exhibit of the matrix is shown in Figure 4 7 and Figure 4 8 For a certain UIR score, the designer is given four modes of operation he or she can follow. These modes are titled Low, Med ium, High, and Extreme. Once entering a mode, the designer can then follow the steps to take in order to acquire the subsurface utility data during the design. There are decision points in each mode that allow the designer to use their own judgment as t o what point they are acceptable to the information retrieved from the previous step. All modes can follow up with a report of the findings to the beginning, but this is a start to give the designer some idea of what the scope of SUE involvement may be nec essary to create a successful design. From the medium to extreme scorings, there is a utility conflict matrix that is referenced. There are many ways to create a conflict matrix, and there are many opinions on what information should be included in them. This report has included one such version that has been utilized on projects in the past. It is shown in Appendix H 4.3.4 Cost Variable Survey Analysis The SuperD ecisions software is a product offered by the Creative Decisions Foundation, created by Thomas and Rozann Saaty. It is downloadable and available on the Internet. The Windows based version was used for the analysis of this report. The user first inputs the clusters, the ma in building blocks which contain nodes. The cluster was the SUE variable ranking in order of importance to the designer. Here the nodes were the variables of the SUE cost impact node. A nodal comparison was performed for the network and the results were rep orted

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58 The results for the pair wise comparisons of the 13 cost variabl es have been summarized into four tables according to design specialty. T hese t a bular data outcome s are included in Appendix E. The summary graphic al result is shown in Figure 4.6 The weighting results show that there is a trend in what designe rs considered the hierarchy ranking of these v ariables during the design and construction of projects Utility damage cost ranked the highest throughout all of the scorings, with the exceptio n of Aviation. This may be because of the airfield environment: being a secured area and with limited exposure to construction work, airfield projects would have a more accurate utility location plan, better as built records, and higher emphasis on locat es than the other realms of work. Thus it would be less of a worry to the airfield designer as compared to the other realms. With that said, airfield ranked the utility verification cost highest and next was personal injury cost. All realms ranked utili ty verification cost as the highest influence on projects for both cost and schedule. Ports, highway and site ranked their second largest influence on utility damage costs. This would imply that there is more of an unknown on these types of projects, hen ce why utility verification cost ranked so highly across the board.

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59 Table 4 1. Summary of contract amounts for 26 studied projects Property Value Number of Projects 26 Number of QL C/D Projects 15 Number of QL A/B Projects 11 Alpha 0.05 Confidence Interval 90 Lower Bound Contracts $ 1,107,703.68 Upper Bound Contracts $39,976,307.70 Table 4 2. Summary of CCP UTILITY for 26 studied projects Property Value Number of Projects 26 Number of QL C/D Projects 15 Number of QL A/B Projects 11 Alpha 0.05 Confidence Interval 90 Lower Bound CCP UTILITY 0.01% Upper Bound CCP UTILITY 5.18% Table 4 3. Summary of SUEP AB for 26 studied projects Property Value Number of Projects 26 Number of QL C/D Projects 15 Number of QL A/B Projects 11 Alpha 0.05 Confidence Interval 90 Lower Bound CCP UTILITY 0.00% Upper Bound CCP UTILITY 29.98% Table 4 4. Summary overall statistics of 26 studied projects Property Value Mean OCC $ 16,236,287.66 Mean CCP UTILITY 1.78% Mean SUEP AB 10.91% Interquartile of OCC $ 19,920,303.22 Interquartile of CCP UTILITY 0.83% Interquartile of SUEP AB 22.62% Standard Deviation of OCC $ 15,647,884.70 Standard Deviation of CCP UTILITY 3% Standard Deviation of SUEP AB 17.65%

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60 Table 4 5. Summary statistics of cost variable rankings from AHP Variable Mean Median Variance Standard Dev Business Impact Cost 0.07159 0.07221 2.42E 06 0.001554236 Contractor Contingency Cost 0.07104 0.07097 2.15E 06 0.001466083 Contractor Change Order Cost 0.072298 0.07213 3.49E 06 0.001868427 Contractor Injury Cost 0.075178 0.074045 6.89E 06 0.002624951 Re Design Cost 0.074773 0.07445 6.96E 06 0.002638677 Environmental Impact Cost 0.07374 0.07278 7.51E 06 0.00273958 Errors and Omissions Cost 0.070745 0.07101 1.89E 06 0.001374 Personal Injury Cost 0.08387 0.082765 8.72E 06 0.002952584 Service Interruption Cost 0.074078 0.074355 1.11E 06 0.001055826 Travel Delay Cost 0.076073 0.07565 3.22E 06 0.001793967 Utility Damage Cost 0.08647 0.086375 2.17E 07 0.000466101 Utilility Relocation Cost 0.081245 0.080485 3.48E 06 0.00186567 Utility Verification Cost 0.088908 0.088975 2.43E 06 0.001557681

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61 Figure 4 1 Frequency of contract values for 26 studied projects. 0.00% 5.00% 10.00% 15.00% 20.00% 25.00% 30.00% 35.00% 40.00% Probability Cost Contribution Percentage Due To Utilities CCP UTILITY Frequency of Contract Values

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62 Figure 4 2. Frequency of CCP UTILITY for 26 studied projects. 0.00% 10.00% 20.00% 30.00% 40.00% 50.00% 60.00% 70.00% 0% 1% 2% 3% 4% 5% 6% 7% 8% 9% 10% 11% 12% 13% Probability Cost Contribution Percentage Due To Utilities CCP UTILITY Frequency of Percent Cost Contribution of Utility

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63 Figure 4 3 Frequency of SUEP AB for 26 studied projects. 0.00% 10.00% 20.00% 30.00% 40.00% 50.00% 60.00% 70.00% 0% 5% 10% 15% 20% 25% 30% 35% 40% 45% 50% 55% 60% 65% 70% 75% 80% Probability Percent Spent on SUE above Topographic Survey SUEP AB Frequency of Increase SUEP AB

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64 Figure 4 4 CR AB graphed against SUEP AB for the 26 studied projects. R = 0.2346 3.00% 2.00% 1.00% 0.00% 1.00% 2.00% 3.00% 0.00% 20.00% 40.00% 60.00% 80.00% 100.00% 120.00% Cost Reduction From Average Cost Contribution Due To Utility Conflicts CR AB Percent Spent on SUE above topographic survey SUEP AB CR AB versus SUEP AB Cost Reduction Effect From SUE Expenditure Data Projection Trendline

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65 Figure 4 5 UIR graphed against SUEP AB 2.00 2.10 2.20 2.30 2.40 2.50 2.60 2.70 2.80 2.90 3.00 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Utility Impact Rating Score UIR Percent Spent on SUE above Topographic Survey SUEP AB UIR Score Related To SUEP AB

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66 Figure 4 6 Graph of cost variable weighting by project type 0.065 0.07 0.075 0.08 0.085 0.09 0.095 BIC CCC CCO CIC DSC EIC EOC PIC SIC TDC UDC URC UVC Weight Cost Variable Cost Variable Weighting By Project Type Aviation Highway Site Ports

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67 Figure 4 7 Decision matrix of the modified UIR scoring page 1

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68 Figure 4 8 Decision matrix of the modified UIR scoring page 2

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69 CHAPTER 5 CONCLUSIONS AND RECO MMENDATIONS 5.1 Conclusions This research identified a definit e relationship between SUE expenditure and the reduction in cost contribution due to u tilities on proj ects. It also identified a method of finding the optimization of SUE use for a given data set. These relationship s were never found by previous research efforts on this subject Former research stated no relationship existed between SUE benefit cost ratios and construction contract values (Sinha 2008). However, all benefit values in the former studies were based on estimates and not ac tual costs This research utilized actual cost results for changes due to utility conflicts. It established a baseline cost of non SUE projects and compared the cost reduc tions of those projects utilizing SUE against the actual expenditure on the SUE abo ve the topographic survey level It found that uti lizing the QL A/B was beneficial to the project s involving su bsurface utilities as it showed a decrease in CCP UTILITY due to the increase in SUEP AB It projected the trend of this result to show that too m uch expenditure on SUE could result in a sub optimum choice. The model proposed a method for a modified UIR scoring system to be applied in a manner to estimate the range of SUEP AB to be used during the design process and with baseline cost data available estimate the influence of the cost variables for performing or not performing SUE Based on historical data of SUEP AB and the CR AB recorded during this research one can estimate the sa vings anticipated for other data sets by following this method ology First, the baseline cost would have to be established. Good record keeping of this type of data would be necessary over time to establish this baseline cost

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70 percentage. Secondly, the amounts for survey and SUE expenditure on projects would also have to b e documented in such a way to use them to create the trend. The result of this analysis was generated from com pleted projects and limited to only those specific projects The refore, the SUE AB and CR AB relationship cited in this report and the percentages stated were specific to this analysis. Th e relationship s and percentages may differ between different data sets, however the model and its methodology have been established and can be utilized for other case s This model demonstrated a trend in cost savi ngs for utilizing SUE a means to identify the optimum point of SUE use, and an implementation process to as sess the SUE need. The expenditure of SUEP AB show ed a reduction in cost contributions due to utility conflicts that occu r r ed when QL A/B SUE was p erformed as compared to no SUE being performed at all Again, this is to show a trend and is not to be interpreted as the absolute cost savings percentages that will happen on every project for every data set B y linking the UIR score to the SUEP AB of a system, one can identify a range of cost reduction for SUE expenditure. This was demonstrated by taking the resulting SUEP AB range and finding the corresponding CR AB for that system relations hip. This UIR scoring system could be used as a tool durin g the preliminary design, long before construction documents are produced to perform estimates of cost and assess the need for SUE during the design process. 5.2 Recommendations 5.2.1 UIR Scoring System Use The first recomme ndation of this research is for civil engineering p rojects that involve subsurface utilities to establish a level of evaluation during the planning and

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71 preliminary design stages This is the UIR scoring system linked to SUEP AB By using this system, one can attempt to optimize the amo unt of SUE to be used prior to or during the design of a project Scoring projects will bring a consistency to the marketplace and further the understanding of projects from many different angles by designers. Historical scoring could be used to prepare f or future projects and analyze market trends for specific kinds of work, by comparing the UIR SUEP AB relationships and reviewing project cost outcomes. 5.2.2 SUE Data Recording The second recommendation would be to s tandardize the manner in which SUE is co ntracted or recorded in any database so that the historical records can be utilized to establish a reference As mentioned before, there were many ways in which the SUE and survey costs were recorded by FDOT They were encompassed in the total design fee, or they were recorded separately as in the data set, or they were performed on a District wide contract where they could not be related to the project identification numbers. If these items were assigned specific code s as line item costs which could be separate d from other preliminary design costs one could eventually perform an analysis much greater than what was presented in this report to arrive at a more global perspective of SUE use and its influen ce on cost savings for projects. One specific r ecommendation for the FDOT would be to r ecord the topographic survey and the SUE costs on every project separately with specific codes in the ir CITS s ystem, to make this analysis possible 5.2.3 Application to Other Project Types SUE is not only used on ro adway and highway projects. It is used on many different types of civil engineering works. The modified UIR scoring system attempted

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72 to encompass more than just roadway projects so that this system could be used for other applications. It is a recommend ation of this report that the UIR system be applied to these other types of wo rk and that the same recording method f or SUE expenditures and cost savings be used for planning future work and budgeting purposes. 5.2.4 Future Research There is an endless am ount of potential for the research that can be done on this topic. The trends shown in this report are specific to the data that was available at the time. As historical data on topographic survey and SUE use during the design are recorded, completed pro jects that document cost contribution due to util ity conflicts can better establish the SUEP AB and CR AB relationship cited by this research. 5.2.4 .1 The optimization goal With more historical data available for topographical survey and SUE expenditures, on e would be able to take the relationship to further explore the optimization level of SUE use. Finding this optimum level of use over a larger data set would be a very useful tool for future planning efforts. 5.2.4.2 The UIR and SUE AB relationship T he proposed relationship between UIR score and SUE expenditure in this report was created from a reasonable behavior estimated between the two variables More definition of this relationship would be an ideal subject for study as more UIR scoring informat ion became available from projects that completed the UIR worksheet, along with more SUE an d survey data on record from completed projects The graphical result may change the slope of the increase in UIR score as compared to the expenditure on SUE above the topographic survey level.

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73 5.2.4.2 Project types and outcomes Specific to SUE use and project outcomes it would be interesting to further inves tigate SUEP AB and the types of civil engineering work involved if survey cost s and SUE costs were identified One example would be the difference in SUE use for various types of highway projects such as new construction, rehabilitation, resurfacing bridge work and traffic operations. Those types of projects could also be assessed by the ir own UIR scoring sys tem to find what types of projects need more SUE than others, or how much different the cost savings would be by utilizing a certain amount of SUE during their designs. 5.2.4.3 Design build as compared to traditional procurement Due to the nature of the da ta available, the design build process was eliminated from the data set of this report. There is another potential for research in comparing the use of SUE on design build projects as compared to the traditional method of design bid build for similar cont ract amounts and similar work types. It would be interesting to see how the UIR process is utilized and SUE implemented during the design build project infancy since a majority of the design is done up front at a faster pace than the traditional method of delivery. Also, the contractor has more control over the implementation of the work, as mentioned in the best management practices portion of this report. The outcome in terms of utility conflict avoidance for these design build projects compared to the same for traditional design bid build projects would be a good topic of study.

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74 APPENDIX A DATABASE OF TRADITIO NAL DESIGN BID BUILD PROJECT

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75 Primary Finproj Original Contract Amount Sum of All Utility Costs Percentage of Original Construction Cost Amount for Surveying (TSC) Amount for SUE Total Survey +SUE Percent Increase in Survey Amount for SUE SUE Percentage of Original Construction Contract Contract Type Project Work Type Description 24269515201 $ 25,994,636.78 $ 851.07 0.00% $ CLS Reconstruction 40900715201 $ 3,231,612.30 $ 240.00 0.01% $ CLS Resurfacing 2096 5955201 $ 60,822,107.64 $ 4,669.39 0.01% $ CLS New Construction 2132 6515201 $ 81,289,714.09 $ 6,404.05 0.01% $ 62,960.00 $0 $ 62,960.00 0% 0 CLS Interstate Rehabilitation 25866015201 $ 15,381,166.19 $ 2,138.09 0.01% $ CLS Miscellaneous Construction 22246715201 $ 53,910,045.50 $ 9,028.39 0.02% $ $ $ CLS Reconstruction 2287581 5201 $ 31,496,535.23 $ 5,484.20 0.02% $ CLS New Construction 4115 3335201 $ 14,746,194.97 $ 4,391.28 0.03% $ CLS Resurfacing 23842115201 $ 22,042,884.62 $ 7,350.59 0.03% $ CLS New Construction 20773435201 $ 6,653,701.00 $ 2,359.16 0.04% $ $ $ CLS Resurfacing 23972515201 $ 31,850,213.48 $ 13, 125.31 0.04% $ CLS Reconstruction 2092 7815201 $ 80,513,019.78 $ 33,384.00 0.04% $ 189,045.22 $0 $ 189,045.22 0% 0 CLS Interstate Construction (new) 24234115201 $ 73,163,378.17 $ 30,349.14 0.04% $ CLS Widening & Resurfacing 40846015201 $ 39,012,792.78 $ 18,615.80 0.05% $ CLS New Construction 2496 4815201 $ 80,159,992.21 $ 39,791.91 0.05% $ CLS Reconstruction 40359815201 $ 4,046,625.95 $ 2,406.43 0.06% $ CLS Resurfacing 24964015201 $ 63,723,862.19 $ 39,479.84 0.06% $ CLS Bridge Construction 41133215201 $ 5,215,912.13 $ 3,358.14 0.06% $ CLS Reconstruction 22949915201 $ 19,919,706.04 $ 12,837.34 0.06% $ CLS Widening & Resurfacing 23841215201 $ 21,888,888.90 $ 22,79 4.94 0.10% $ CLS Reconstruction 2320 7425201 $ 16,319,218.11 $ 18,070.24 0.11% $ CLS New Construction 41640615201 $ 2,332,105.64 $ 2,816.53 0.12% $ CLS Traffic Operations 40609215201 $ 31,340,908.58 $ 41,253.64 0.13% $ CLS Widening & Resurfacing 21974815201 $ 15,355,868.30 $ 20,493.55 0.13% $ 222,083.11 $ 64,361.91 $ 286,445.02 29% 0.004191356 CLS Reconstruction 1973 3225201 $ 4,499,900.00 $ 6,399.84 0.14% $ CLS Resurfacing

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76 Primary Finproj Original Contract Amount Sum of All Utility Costs Percentage of Original Construction Cost Amount for Surv eying (TSC) Amount for SUE Total Survey +SUE Percent Increase in Survey Amount for SUE SUE Percentage of Original Construction Contract Contract Type Project Work Type Description 19764515201 $ 19,241,288.05 $ 33,223.78 0.17% $ CLS New Construction 24270225201 $ 22,253,146.46 $ 38,818.87 0.17% $ CLS Interstate Construction (new) 20916815201 $ 25,664,852.48 $ 48,720.49 0.19% $ 70,211.48 $ 20,018.40 $ 90,229.88 29% 0.000779993 CLS New Construction 1976 7915201 $ 25,399,051.71 $ 49,365.99 0.19% $ CLS Reconstruction 22807515201 $ 5,144,512.69 $ 10,000.00 0.19% $ CLS Resurfacing 24249315201 $ 38,870,469.25 $ 77,618.23 0.20% $ CLS Reconstruction 24965015201 $ 36,785,850.12 $ 76,569.40 0.21% $ CLS New Construction 40460115201 $ 30,163,798.45 $ 62,890.75 0.21% $ CLS Bridge Construction 23191825201 $ 44,983,454.84 $ 95,305.38 0.21% $ CLS Reconstruction 4146 2125201 $ 1,700,000.00 $ 3,823.64 0.22% $ CLS Widening & Resurfacing 40609255201 $ 28,275,449.34 $ 63,686.58 0.23% $ C LS Reconstruction 4114 3115201 $ 2,800,586.75 $ 6,401.29 0.23% $ CLS Resurfacing 19770915201 $ 12,608,188.23 $ 30,289.00 0.24% $ CLS Reconstr uction 23192015201 $ 74,948,455.36 $ 197,239.84 0.26% $ CLS Reconstruction 2319 1815201 $ 58,830,990.14 $ 166,694.05 0.28% $ CLS Reconstruction 41379115201 $ 3,495,168.11 $ 9,965.31 0.29% $ CLS Resurfacing 25695715201 $ 29,959,073.94 $ 85,506.61 0.29% $ CLS New Construction 25585315201 $ 11,041,469.62 $ 32,413.08 0.29% $ CLS Resurfacing 25582225201 $ 20,080,363.92 $ 61,616.24 0.31% $ CLS Widening & Resurfacing 19753315201 $ 8,893,072.95 $ 27,765.32 0.31% $ CLS Resurfacing 25713715201 $ 13,787,433.31 $ 44,221.18 0.32% $ CLS Resurfacing 19770515201 $ 31,557,145.57 $ 112,450.02 0.36% $ CLS Reconstruction 2099 6915201 $ 39,976,307.70 $ 149,360.40 0.37% $ 78,890.00 $ 20,000.00 $ 98,890.00 25% 0.000500296 CLS Reconstruction 25718415201 $ 13,746,725.71 $ 54,484.39 0.40% $ CLS Reconstruction 2298 5815201 $ 3,539,411.94 $ 14,346.02 0.41% $ CLS Resurfacing 25022215201 $ 7,809,612.13 $ 31,739.24 0.41% $ CLS Reconstr uction 41540315201 $ 392,406.85 $ 1,606.00 0.41% $ CLS Other 2396 7315201 $ 35,625,560.06 $ 151,185.49 0.42% $ CLS Reconstruction 41170215201 $ 8,370,583.76 $ 36,534.04 0.44% $ 69,361.58 $ $ 69,361.58 0% 0 CLS Resurfacing 25013315201 $ 7,854,827.49 $ 36,587.65 0.47% $ CLS Reconstruction 23831415201 $ 30,844,444.43 $ 154,637.93 0.50% $ CLS Reconstruction

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77 Primary Finproj Original Contract Amount Sum of All Utility Costs Percentage of Original Construction Cost Amount for Surveying (TSC) Amount for SUE Total Survey +SUE Percent Increase in Survey A mount for SUE SUE Percentage of Original Construction Contract Contract Type Project Work Type Description 40611215201 $ 12,774,988.74 $ 64,889.94 0.51% $ CLS New Construction 2318 3515201 $ 34,362,394.68 $ 179,432.78 0.52% $ CLS New Construction 20857525201 $ 3,355,970.97 $ 17,655.00 0.53% $ CLS Resurfacing 23746615201 $ 12,096,291.30 $ 64,193.99 0.53% $ CLS Widening & Resurfacing 25713215201 $ 7,392,135.14 $ 39,657.11 0.54% $ CLS Resurfacing 23193715201 $ 34,313,610.45 $ 188,303.50 0.55% $ CLS Widening & Resurfacing 19967615201 $ 3,438,707.89 $ 18,995.2 6 0.55% $ CLS Bridge Construction 2387 6215201 $ 12,990,213.01 $ 72,114.09 0.56% $ CLS Reconstruction 25864315201 $ 73,537,983.63 $ 409,981.58 0.56% $ CLS Widening & Resurfacing 25709315201 $ 47,687,400.83 $ 269,165.21 0.56% $ CLS Bridge Construction 20121315201 $ 29,866,947.18 $ 170,500.86 0.57% $ CLS Miscellaneous Construction 2297 9715201 $ 46,967,992.34 $ 274,637.83 0.58% $ CLS New Construction 41637845201 $ 516,557.14 $ 3,135.02 0.61% $ CLS Oth er 40349725201 $ 56,199,002.29 $ 347,517.37 0.62% $ CLS New Construction 40349835201 $ 45,575,517.90 $ 283,219.68 0.62% $ CLS New Construction 21324515201 $ 53,439,693.37 $ 344,574.03 0.64% $ 42,990.63 $ 12,117.58 $ 55,108.21 28% 0.000226752 CLS Interstate Rehabilitation 2424 8425201 $ 118,920,731.95 $ 776,661.34 0.65% $ CLS Interstate Construction (new) 24271615201 $ 27,591,339.81 $ 182,175.78 0.66% $ CLS Interstate Rehabilitation 25710315201 $ 3,130,155.65 $ 21,024.44 0.67% $ CLS Resurfacing 41546415201 $ 2,848,638.69 $ 19,437.44 0.68% $ CLS Traffic Operations 23072515201 $ 28,478,352.19 $ 200,343.56 0.70% $ CLS New Construction 22259025201 $ 37,734,525.20 $ 269,499.44 0.71% $ 193,625.40 $ $ 193,625.40 0% 0 CLS Reconstruction 1970 2715201 $ 14,514,514.50 $ 105,506.39 0.73% $ CLS Reconstruction 24269615201 $ 21,679,438.39 $ 158,785.96 0.73% $ CLS Widening & Resurfacing 41525815201 $ 20,277,220.00 $ 152,199.36 0.75% $ 140,204.02 $ $ 140,204.02 0% 0 CLS Resurfacing 23745815201 $ 24,292,564.28 $ 182,387.99 0.75% $ CLS Reconstruction 24023125201 $ 11,908,221.64 $ 91,191.61 0.77% $ CLS Widening & Resurfacing 2084 1915201 $ 3,693,138.74 $ 29,111.63 0.79% $ 147,267.01 $ 44,145.78 $ 191,412.79 30% 0.011953458 CLS Resurfacing 41738415201 $ 1,457,018.30 $ 11,585.50 0.80% $ CLS Traffic Operations 20771415201 $ 19,330,210.29 $ 153,900.52 0.80% $ CLS Reconstruction 23796515201 $ 10,795,713.74 $ 86,345.64 0.80% $ CLS Reconstruction

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78 Pri mary Finproj Original Contract Amount Sum of All Utility Costs Percentage of Original Construction Cost Amount for Surveying (TSC) Amount for SUE Total Survey +SUE Percent Increase in Survey Amount for SUE SUE Percentage of Original Construction Contract Contract Type Project Work Type Description 24998515201 $ 22,170,722.31 $ 177,921.60 0.80% $ CLS Reconstruction 4061 2045201 $ 27,300,000.00 $ 221,112.21 0.81% $ CLS Miscellaneous Construction 22964815201 $ 6,356,050.02 $ 51,583.53 0.81% $ CLS Widening & Resurfacing 21327315201 $ 21,159,205.70 $ 175,220.98 0.83% $ CLS Widening & Resurfacing 22044255201 $ 17,845,976.87 $ 153,557.00 0.86% $ 224,468.96 $ 67,732.63 $ 292,201.59 30% 0.003795401 CLS Reconstruction 21869615201 $ 8,895,026.60 $ 76,851.26 0.86% $ 54,559.20 $ 40,583.46 $ 95,142.66 74% CLS Res urfacing 23750625201 $ 17,432,683.77 $ 151,583.20 0.87% $ CLS Bridge Construction 2100 0415201 $ 14,950,000.00 $ 131,959.72 0.88% $ 89,969.00 $ 89,969.00 0% 0 CLS Reconstruction 40763315201 $ 5,782,621.42 $ 51,172.71 0.88% $ CLS Resurfacing 25022415201 $ 13,175,409.10 $ 116,895.00 0.89% $ CLS Reconstruction 41464315201 $ 4,296,027.83 $ 38,400.00 0.89% $ CLS Reconstruction 4061 2025201 $ 14,208,634.18 $ 129,503.45 0.91% $ CLS Miscellaneous Construction 23028825201 $ 24,853,620.15 $ 227,210.52 0.91% $ C LS Reconstruction 22977115201 $ 32,990,609.97 $ 303,223.45 0.92% $ CLS Reconstruction 1980 0515201 $ 27,589,105.92 $ 254,931.57 0.92% $ CLS Reconstruction 19847815201 $ 1,716,705.70 $ 15,956.62 0.93% $ CLS Bridge Construction 23792515201 $ 7,277,957.84 $ 67,691.64 0.93% $ CLS New Construction 23929315201 $ 18,839,501.14 $ 179,752.00 0.95% $ CLS Reconstruction 22246915201 $ 38,313,273.35 $ 367,807.44 0.96% $ 111,875.03 $ $ 111,875.03 0% 0 CLS Reconstruction 20808525201 $ 6,510,067.03 $ 63,405. 55 0.97% $ 47,333.00 $ 6,820.00 $ 54,153.00 14% 0.001047608 CLS Resurfacing 4067 3825201 $ 35,332,172.85 $ 348,708.09 0.99% $ CLS Other 41695215201 $ 807,757.65 $ 8,000.00 0.99% $ CLS Other 4061 2415201 $ 11,697,180.00 $ 116,076.48 0.99% $ CLS Other 25020015201 $ 8,558,041.83 $ 86,343.18 1.01% $ CLS Widening & Resurfacing 21794715201 $ 12,472,551.99 $ 125,962.73 1.01% $12,247.28 $0 $ 12,247.28 0 CLS Reconstruction 41702415201 $ 15,581,272.18 $ 158,408.50 1.02% $ CLS Resurfacing 40609115201 $ 56,871,827.43 $ 579,267.73 1.02% $ CLS Widening & Resurfacing 2505 3415201 $ 6,390,781.89 $ 66,495.80 1.04% $ CLS Resurfacing 41227315201 $ 211,042.77 $ 2,199.22 1.04% $ CLS Traffic Operations 40723325201 $ 5,046,640.00 $ 52,912.19 1.05% $ CLS New Construction 41123715201 $ 13,968,873.29 $ 146,860.44 1.05% $ CLS New Construction

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79 Primary Finproj Original Contract Amount Sum of All Utility Costs Percentage of Original Construction Cost Amount for Surveying (TSC) Amount for SUE Total Survey +SUE Percent Increase in Survey Amount for SUE SUE Percentage of Original Construction Contract Contract Type Project Work Type Description 23026245201 $ 17,284,856.96 $ 181,766.90 1.05% $ CLS Reconstruction 2286 2315201 $ 12,823,706.53 $ 137,573.16 1.07% $ CLS Resurfacing 21327335201 $ 5,729,460.00 $ 61,660.16 1.08% $ 62,695.34 $ 2,101.36 $ 64,796.70 3% 0.000366764 CLS Interstate Construction (new) 41768015201 $ 18,437,280.80 $ 201,023.64 1.09% $ CLS Resurfacing 40723215201 $ 5,675,101.00 $ 61,944.00 1.09% $ CLS New Construction 2394 5425201 $ 28,775,089.28 $ 316,276.33 1.10% $ CLS Reconstruction 25014115201 $ 14,639,812.98 $ 164,086.00 1.12% $ CLS Reconstruction 23173615201 $ 9,096,304.70 $ 102,281.99 1.12% $ CLS Resurfacing 20761425201 $ 5,290,000.00 $ 61,431.33 1.16% $ 48,366.42 $ 4 8,366.42 0 CLS Resurfacing 2278 6115201 $ 12,574,699.84 $ 147,393.94 1.17% $ CLS Resurfacing 22861515201 $ 9,623,827.68 $ 112,920.00 1.17% $ CLS Resurfacing 411 43915201 $ 4,823,222.45 $ 58,110.18 1.20% $ CLS Resurfacing 22815815201 $ 4,414,675.52 $ 53,520.00 1.21% $ CLS Resurfa cing 22958725201 $ 17,981,627.25 $ 222,576.84 1.24% $ CLS Widening & Resurfacing 2558 0315201 $ 3,975,002.70 $ 49,444.16 1.24% $ CLS Resurfacing 41143815201 $ 6,634,603.43 $ 82,600.92 1.25% $ CLS Resurfacing 22815715201 $ 7,252,328.75 $ 91,508.19 1.26% $ CLS Resurfacing 41139325201 $ 6,945,967.69 $ 87,902.00 1.27% $ CLS Resurfacing 23061915201 $ 5,647,824.23 $ 72,591.25 1.29% $ CLS New Construction 25839845201 $ 24,316,389.41 $ 313,657.49 1.29% $ CLS Other 41379715201 $ 7,494,693.94 $ 96,813.50 1.29% $ CLS Resurfacing 40359615201 $ 8,384,439.93 $ 108,605.94 1.30% $ CLS Resurfacing 2317 3715201 $ 8,513,720.97 $ 113,674.66 1.34% $ CLS Resurfacing 22807315201 $ 7,005,087.92 $ 93,968.94 1.34% $ CLS Resurfacing 41379915201 $ 4,249,170.15 $ 57,005.05 1.34% $ CLS Resurfacing 21977715201 $ 6,782,932.95 $ 91,352.00 1.35% $ 38,354.96 $ $ 38,354.96 CLS Reconstruction 41384715201 $ 6,561,077.68 $ 89,212.65 1.36% $ CLS Resurfacing 4036 0415201 $ 4,785,294.27 $ 65,302.48 1.36% $ CLS Resurfacing 41379615201 $ 10,060,369.77 $ 137,923.40 1.37% $ CLS Resurfacing 40612215201 $ 6,739,300.00 $ 92,968.28 1.38% $ CLS Traffic Operations 22975015201 $ 7,977,226.12 $ 110,191.63 1.38% $ CLS Resurfacing

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80 Pri mary Finproj Original Contract Amount Sum of All Utility Costs Percentage of Original Construction Cost Amount for Surveying (TSC) Amount for SUE Total Survey +SUE Percent Increase in Survey Amount for SUE SUE Percentage of Original Construction C ontract Contract Type Project Work Type Description 23173415201 $ 8,838,303.47 $ 122,493.93 1.39% $ CLS Resurfacing 2095 1385201 $ 23,542,815.80 $ 326,480.59 1.39% $ CLS Widening & Resurfacing 25010525201 $ 11,381,394.29 $ 158,217.33 1.39% $ CLS New Construction 23753215201 $ 8,434,389.43 $ 118,246.70 1.40% $ CLS Reconstruction 41384015201 $ 4,239,757.40 $ 59,447.82 1.40% $ CLS Other 25840115201 $ 149,898,506.15 $ 2,116,365.21 1.41% $ CLS Reconstruction 41539715201 $ 14,112,750.00 $ 204,219.48 1.45% $ CLS Resurfacing 40936645201 $ 8,391,702.02 $ 124,543.94 1.48% $ CLS Other 40627815201 $ 6,906,293.34 $ 102,706.62 1.49% $ CLS Resurfacing 1980 1815204 $ 32,362,115.40 $ 493,324.98 1.52% $ CLS Reconstruction 21002125201 $ 4,079,905.20 $ 63,067.25 1.55% $ 111,881.78 $ 7,631.50 $ 119,513.28 7% 0.001870509 CLS Resurfacing 4175 7715201 $ 717,033.26 $ 11,237.63 1.57% $ CLS Traffic Operations 41384515201 $ 3,222,153.11 $ 50,524.76 1.57% $ CLS Resurfacing 22973915201 $ 6,741,714.80 $ 106,217.96 1.58% $ CLS Widening & Resurfacing 2502 3435201 $ 4,629,465.44 $ 73,009.66 1.58% $ CLS New Construction 24978315201 $ 12,929,611.17 $ 204,296.41 1.58% $ CLS Widening & Resurfacing 41611815201 $ 593,108.05 $ 9,489.80 1.60% $ CLS Traffic Operations 41383715201 $ 4,251,196.38 $ 68,669.99 1.62% $ CLS Resurfacing 40830125201 $ 3,724,989.88 $ 61,114.44 1.64% $ CLS Other 21794825201 $ 9,599,493.79 $ 157,808.56 1.64% $ CLS Reconstruction 41227625201 $ 4,721,204.51 $ 77,860.00 1.65% $ CLS Other 41140115201 $ 4,943,000.00 $ 81,717.83 1.65% $ 95,040.28 $ $ 95,040.28 0% 0 CLS Resurfacing 2294 9815201 $ 28,657,508.58 $ 474,581.98 1.66% $ CLS Widening & Resurfacing 22811015201 $ 6,673,030.24 $ 111,772.60 1.67% $ CLS Other 21000445201 $ 2,999,999.99 $ 52,206.47 1.74% $ CLS Resurfacing 21867815201 $ 3,045,338.40 $ 53,100.00 1.74% $51,754.20 $0 $ 51,754.20 CL S Resurfacing 41367015201 $ 9,691,600.00 $ 172,706.62 1.78% $ CLS Resurfacing 40357715201 $ 3,343,947.31 $ 60,469.14 1.81% $ CLS Resurfacing 40564135201 $ 7,682,061.84 $ 139,477.43 1.82% $ CLS Reconstruction 22885315201 $ 2,495,669.34 $ 45,701.96 1.83% $ CLS Resurfacing 24952815201 $ 8,520,676.63 $ 156,189.80 1.83% $ CLS Widening & Resurfacing

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81 Primary Finproj Original Contract Amount Sum of All Utility Costs Percentage of Original Construction Cost Amount for Surveying (TSC) Amount for SUE Total Survey +SUE Percent Increase in Survey Amount for SUE SUE Percenta ge of Original Construction Contract Contract Type Project Work Type Description 40452515201 $ 14,868,709.44 $ 279,442.24 1.88% $ CLS Widening & Resurfacing 2516 8215201 $ 9,795,443.72 $ 187,857.50 1.92% $ CLS Traffic Operations 40516715201 $ 2,826,125.26 $ 54,293.39 1.92% $ CLS Resurfacing 22793815201 $ 5,199,076.06 $ 100,506.70 1.93% $ CLS Resurfacing 40758715201 $ 6,486,875.11 $ 128,313.21 1.98% $ CLS Resurfacing 19763815201 $ 7,101,180.98 $ 141,271.90 1.99% $ CLS Reconstruction 40651415201 $ 4,772,911.90 $ 95,859.77 2.01% $ CLS Other 24956125201 $ 2,697,735.80 $ 54,400.00 2.02% $ CLS Other 22792115201 $ 2,713,543.24 $ 54,806.99 2.02% $ CLS Resurfacing 4163 7835201 $ 3,839,405.65 $ 78,075.86 2.03% $ CLS Widening & Resurfacing 40651815201 $ 2,499,659.48 $ 52,286.95 2.09% $ C LS Other 2005 0715201 $ 2,581,658.10 $ 54,134.42 2.10% $ CLS Traffic Operations 22858335201 $ 4,985,000.00 $ 105,117.16 2.11% $ CLS Re construction 41143415201 $ 2,591,893.26 $ 54,793.21 2.11% $ CLS Resurfacing 4067 5815201 $ 3,997,107.82 $ 85,240.28 2.13% $ CLS Resurfacing 41380415201 $ 8,393,806.76 $ 182,532.60 2.17% $ CLS Resurfacing 41524015201 $ 4,700,747.44 $ 103,228.79 2.20% $ CLS Other 23966315201 $ 30,200,678.70 $ 665,654.77 2.20% $ CLS Reconstruction 41384315201 $ 2,442,222.00 $ 55,654.51 2.28% $ CLS Resurfacing 25705015201 $ 15,152,626.15 $ 345,714.38 2.28% $ CLS Reconstruction 41807115201 $ 2,307,756.90 $ 52,824.03 2.29% $ CLS Resurfacing 41687315201 $ 1,670,344.21 $ 38,427.68 2.30% $ CLS Resurfacing 4114 4015201 $ 7,739,818.33 $ 178,250.67 2.30% $ CLS Resurfacing 41585215201 $ 2,193,648.75 $ 50,599.32 2.31% $ CLS Other 2548 2215201 $ 5,358,635.01 $ 124,447.40 2.32% $ CLS Reconstruction 40723315201 $ 2,421,879.30 $ 56,298.63 2.32% $ CLS Traffi c Operations 19801735201 $ 2,105,992.48 $ 50,178.76 2.38% $ CLS Resurfacing 2558 8815201 $ 18,726,894.35 $ 455,687.44 2.43% $ CLS Widening & Resurfacing 40775915201 $ 8,349,183.87 $ 209,596.73 2.51% $ CLS Widening & Resurfacing 40564115201 $ 7,251,433.26 $ 182,563.14 2.52% $ CLS Reconstruction 25632215201 $ 16,111,111.11 $ 413,182.26 2.56% $ CLS Widening & Resurfacing

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82 Primary Finproj Original Contract Amount Sum of All Utility Costs Percentage of Original Construction Cost Amount for Surveying (TSC) Amount for SUE Total Survey +SUE Percent Increase in Survey Amount for SUE SUE Percentage of Original Construction Contract Contract Type Project Work Type Description 41823635201 $ 818,703.10 $ 21,298.00 2.60% $ CLS Other 2009 6615201 $ 31,795,405.41 $ 828,912.40 2.61% $ CLS Interstate Construction (new) 41227645201 $ 3,135,883.57 $ 82,499.32 2.63% $ CLS Miscellaneous Construction 20764825201 $ 2,464,000.00 $ 65,412.01 2.65% $ CLS Reconstruction 22822315201 $ 2,854,876.64 $ 76,998.84 2.70% $ CLS Miscellaneous Construction 22974815201 $ 8,387,866.27 $ 227,523.03 2.71% $ CLS Resurfacing 25010535201 $ 3,494,000.00 $ 94, 961.22 2.72% $ CLS Other 2568 1515201 $ 7,861,142.40 $ 215,350.52 2.74% $ CLS Widening & Resurfacing 40883415201 $ 71,642,526.48 $ 1,988,271.99 2.78% $ CLS Reconstruction 19539925201 $ 1,300,204.98 $ 36,100.55 2.78% $ CLS Resurfacing 22795415201 $ 2,770,848.40 $ 80,172.53 2.89% $ CLS Resurfacing 2564 1925201 $ 1,127,041.48 $ 32,660.57 2.90% $ CLS Other 19602245201 $ 23,534,106.50 $ 706,317.93 3.00% $ CLS Reconstruction 41528315201 $ 1,829,393.39 $ 55,208.03 3.02% $ CLS Resurfacing 22746215201 $ 11,294,686.55 $ 345,398.04 3.06% $ CLS Wideni ng & Resurfacing 41095615201 $ 6,267,319.77 $ 195,572.17 3.12% $ CLS Other 2132 3865201 $ 4,065,841.26 $ 126,946.98 3.12% $ CLS Traffic Operations 41318115201 $ 1,624,311.60 $ 50,823.33 3.13% $ CLS Other 22885115201 $ 7,645,488.76 $ 247,760.58 3.24% $ CLS Resurfacing 40763025201 $ 1,943,197.87 $ 63,775.00 3.28% $ CLS Resurfacing 41318915201 $ 797,341.82 $ 26,308.41 3.30% $ CLS Miscellaneous Construction 2570 7815201 $ 2,612,103.59 $ 86,814.68 3.32% $ CLS Resurfacing 2568 8815201 $ 45,938,400.12 $ 1,538,276.62 3.35% $ CLS Widening & Resurfacing 41647215201 $ 615,929.64 $ 20,694.11 3.36% $ CLS Resurfacing 1957 3715201 $ 17,927,799.99 $ 624,973.48 3.49% $ CLS Widening & Resurfacing 42132215201 $ 1,498,247.75 $ 52,698.00 3.52% $ CLS Widening & Resurfacing 19597025201 $ 1,564,000.00 $ 55,903.07 3.57% $ CLS Resurfacing 2516 6935201 $ 11,949,313.19 $ 429,178.37 3.59% $ CLS Interstate Construction (new) 22862015201 $ 1,482,335.75 $ 54,121.74 3.65% $ CLS Resurfacing 23929415201 $ 9,784,483.61 $ 359,195.62 3.67% $ CLS Reconstruction 40652315201 $ 2,762,935.33 $ 101,440.00 3.67% $ CLS Resurfacing

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83 Primary Finproj Original Contract Amount Sum of All Utility Costs Percentage of Original Construction Cost Amount for Surveying (TSC) Amount for SUE Total Survey +SUE Percent Increase in Survey Amou nt for SUE SUE Percentage of Original Construction Contract Contract Type Project Work Type Description 22818015201 $ 4,131,333.57 $ 152,072.59 3.68% $ CLS Resurfacing 4124 8115201 $ 1,963,280.13 $ 72,400.00 3.69% $ CLS Resurfacing 41143215201 $ 6,345,373.18 $ 242,801.68 3.83% $ CLS Resurfacing 19771015201 $ 9,519,327.33 $ 367,922.21 3.87% $ CLS Reconstruction 40371315201 $ 2,393,990.16 $ 97,438.56 4.07% $ CLS Resurfacing 22824315201 $ 5,146,787.04 $ 215,498.63 4.19% $ CLS Resurfacing 40625315201 $ 2,269,459.62 $ 95,187.58 4.19% $ CLS Traffic Operations 40361015201 $ 10,402,230.24 $ 442,989.24 4.26% $ CLS Resurfacing 22856815201 $ 2,278,124.06 $ 98,475.89 4.32% $ CLS Resurfacing 2570 7715201 $ 1,342,725.09 $ 58,068.00 4.32% $ CLS Resurfacing 40652115201 $ 1,215,515.42 $ 53,409.86 4.39% $ CLS Other 4165 9015201 $ 1,189,047.32 $ 53,359.07 4.49% $ CLS Widening & Resurfacing 19726435201 $ 595,599.50 $ 26,844.57 4.51% $ CLS Traffic Operations 41177215201 $ 605,442.64 $ 28,180.98 4.65% $ CLS Traffic Operations 4120 0315201 $ 1,002,931.36 $ 48,064.46 4.79% $ CLS Other 40392025201 $ 1,107,703.68 $ 53,699.79 4.85% $ 53,827.00 $ 7,250.00 $ 61,077.00 13% 0.006545072 CLS Resurfacing 41161215201 $ 1,068,000.00 $ 52,010.00 4.87% $ CLS Resurfacing 2497 8415201 $ 1,369,553.00 $ 68,879.14 5.03% $ CLS Bridge Repair 4120 0215201 $ 997,696.00 $ 51,034.00 5.12% $ CLS Miscellaneous Construction 40667615201 $ 1,217,104.18 $ 62,330.56 5.12% $ CLS Resurfacing 41042015201 $ 717,803.47 $ 37,174.00 5.18% $ 39,029.73 $ $ 39,029.73 0 CLS Miscellaneous Construction 24016715201 $ 19,373,916.24 $ 1,006,114.14 5.19% $ CLS Widening & Resurfacing 4227 0215201 $ 508,953.40 $ 28,456.00 5.59% $ CLS Traffic Operations 22885915201 $ 2,562,428.79 $ 161,953.65 6.32% $ CLS Resurfacing 21025325201 $ 220,785.00 $ 14,370.00 6.51% $ CLS Traffic Operations 40858115201 $ 4,214,081.10 $ 279,105.10 6.62% $ 67,651.82 $ $ 67,651.82 0% 0 CLS Bridge Construction 22949715201 $ 13,308,081.77 $ 914,295.97 6.87% $ CLS Reconstruction 2297 8115201 $ 4,889,661.67 $ 348,143.00 7.12% $ CLS Resurfacing 41247615201 $ 997,952.15 $ 71,227.24 7.14% $ CLS Resurfacing 41641915201 $ 222,994.75 $ 16,799.82 7.53% $ CLS Traffic Operations 41384615201 $ 6,051,401.81 $ 498,705.04 8.24% $ CLS Resurfacing

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84 Primary Finproj Original Contract Amount Sum of All Utility Costs Percentage of Original Construction Cost Amount for Surveying (TSC) Amount for SUE Total Survey +SUE Percent Increase in Survey Amou nt for SUE SUE Percentage of Original Construction Contract Contract Type Project Work Type Description 22974915201 $ 3,523,866.05 $ 290,481.50 8.24% $ CLS Resurfacing 4166 8715201 $ 111,000.00 $ 10,739.73 9.68% $ CLS New Construction 22986715201 $ 7,772,813.00 $ 834,958.64 10.74% $ CLS Resurfacing 20934215201 $ 9,925,637.31 $ 1,127,713.91 11.36% $125,918.13 $0 $ 125,918.13 0% 0 CLS Reconstruction 41924015201 $ 218,832.55 $ 25,160.04 11.50% $ CLS Other 24121115201 $ 2,799,914.17 $ 340,314.95 12.15% $ CLS Bridge Construction 22777615201 $ 1,064,243.45 $ 130,191.42 12.23 % $ CLS Reconstruction 4035 7815201 $ 964,052.30 $ 119,705.54 12.42% $ CLS Resurfacing 22040215201 $ 17,066,752.59 $ 2,956,230.83 17.32% $ CLS New Construction 40658415201 $ 1,465,642.85 $ 259,873.24 17.73% $ CLS Resurfacing 22977715201 $ 8,693,530.51 $ 1,641,718.72 18.88% $ CLS Reconstruction 2301 0815201 $ 11,081,616.09 $ 2,708,783.53 24.44% $ CLS Reconstruction

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85 APPENDIX B LIST OF PROJECTS INVOLVING S UE FOR STUDY

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86

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87 APPENDIX C SURVEY FORM FOR AHP PROCESS

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88

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89 APPENDIX D DATA FOR CR AB AND SUEP AB COMPARISON AND PROJE CTION

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90

PAGE 91

91 APPENDIX E SUPERDECISIONS RESUL TS AND STATISTICS

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92 AHP Score from Averages of Each Design Industry Variable Aviation Highway Site Ports Mean Median Variance Standard Dev BIC Business Impact Cost 0.07189 0.07296 0.06898 0.07253 0.07159 0.07221 2.41565E 06 0.001554236 CCC Contractor Contingency Cost 0.07186 0.07008 0.06924 0.07298 0.07104 0.07097 2.1494E 06 0.001466083 CCO Contractor Change Order Cost 0.07146 0.07501 0.06992 0.0728 0.072298 0.07213 3.49102E 06 0.001868427 CIC Contractor Injury Cost 0.07965 0.0738 0.07297 0.07429 0.075178 0.074045 6.89037E 06 0.002624951 DSC Re Design Cost 0.07491 0.07399 0.07877 0.07142 0.074773 0.07445 6.96262E 06 0.002638677 EIC Environmental Impact Cost 0.07113 0.07213 0.07827 0.07343 0.07374 0.07278 7.5053E 06 0.00273958 EOC Errors and Omissions Cost 0.07009 0.07215 0.06881 0.07193 0.070745 0.07101 1.88788E 06 0.001374 PIC Personal Injury Cost 0.08884 0.083 0.08253 0.08111 0.08387 0.082765 8.71775E 06 0.002952584 SIC Service Interruption Cost 0.07237 0.07453 0.07418 0.07523 0.074078 0.074355 1.11477E 06 0.001055826 TDC Travel Delay Cost 0.07447 0.07866 0.07433 0.07683 0.076073 0.07565 3.21832E 06 0.001793967 UDC Utility Damage Cost 0.08626 0.08649 0.0872 0.08593 0.08647 0.086375 2.1725E 07 0.000466101 URC Utilility Relocation Cost 0.07989 0.07967 0.08434 0.08108 0.081245 0.080485 3.48072E 06 0.00186567 UVC Utility Verification Cost 0.08718 0.08753 0.0905 0.09042 0.088908 0.088975 2.42637E 06 0.001557681 Sum 1 1 1.00004 0.99998 1.000005 0.9962

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93 SUE Cost Variable Impact Aviation BIC CCC CCO CIC DSC EIC EOC PIC SIC TDC UDC URC UVC Normalized By Cluster Limiting BIC 0.065899 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.028348 0.07189 0.071895 CCC 0.059277 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.033356 0.07186 0.071856 CCO 0.056127 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.031374 0.07146 0.071457 CIC 0.150168 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.047831 0.07965 0.079653 DSC 0.122681 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.016098 0.07491 0.07491 EIC 0.043177 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.038307 0.07113 0.07113 EOC 0.048799 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.021743 0.07009 0.07009 PIC 0.186574 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.123195 0.08884 0.088841 SIC 0.036261 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.058203 0.07237 0.072368 TDC 0.043935 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.075947 0.07447 0.074466 UDC 0.086019 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.176538 0.08626 0.086262 URC 0.062412 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.12289 0.07989 0.079887 UVC 0.038672 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.226169 0.08718 0.087185

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94 SUE Cost Variable Impact Highway BIC CCC CCO CIC DSC EIC EOC PIC SIC TDC UDC URC UVC Normalized By Cluster Limiting BIC 0.080824 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.028348 0.07296 0.072956 CCC 0.035437 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.033356 0.07008 0.070083 CCO 0.105329 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.031374 0.07501 0.075008 CIC 0.069001 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.047831 0.0738 0.073799 DSC 0.10966 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.016098 0.07399 0.073987 EIC 0.057542 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.038307 0.07213 0.072129 EOC 0.077725 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.021743 0.07215 0.072151 PIC 0.104744 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.123195 0.083 0.083003 SIC 0.066589 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.058203 0.07453 0.074531 TDC 0.101959 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.075947 0.07866 0.078664 UDC 0.088508 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.176538 0.08649 0.086488 URC 0.059379 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.12289 0.07967 0.079667 UVC 0.043305 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.226169 0.08753 0.087535

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95 SUE Cost Variable Impact Self BIC CCC CCO CIC DSC EIC EOC PIC SIC TDC UDC URC UVC Normalized By Cluster Limiting BIC 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.028348 0.07253 0.072531 CCC 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.033356 0.07298 0.072984 CCO 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.031374 0.0728 0.072805 CIC 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.047831 0.07429 0.074293 DSC 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.016098 0.07142 0.071423 EIC 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.038307 0.07343 0.073432 EOC 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.021743 0.07193 0.071934 PIC 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.123195 0.08111 0.081107 SIC 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.058203 0.07523 0.07523 TDC 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.075947 0.07683 0.076835 UDC 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.176538 0.08593 0.08593 URC 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.12289 0.08108 0.081079 UVC 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.226169 0.09042 0.090417

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96 SUE Cost Variable Impact Site BIC CCC CCO CIC DSC EIC EOC PIC SIC TDC UDC URC UVC Normalized By Cluster Limiting BIC 0.025421 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.028348 0.06898 0.068975 CCC 0.022635 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.033356 0.06924 0.069236 CCO 0.035097 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.031374 0.06992 0.069916 CIC 0.057759 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.047831 0.07297 0.072968 DSC 0.183569 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.016098 0.07877 0.078774 EIC 0.147077 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.038307 0.07827 0.078267 EOC 0.031622 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.021743 0.06881 0.068805 PIC 0.097466 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.123195 0.08253 0.082528 SIC 0.061648 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.058203 0.07418 0.074175 TDC 0.040552 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.075947 0.07433 0.074326 UDC 0.095165 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.176538 0.0872 0.087196 URC 0.124068 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.12289 0.08434 0.084335 UVC 0.07792 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.076923 0.226169 0.0905 0.090498

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97 APPENDIX F EXAMPLE UIR SYSTEM R ESULT

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98

PAGE 99

99 Cost Variable Abbreviation Weighting CCPV Estimated Cost Utility Verification Cost UVC 0.09042 0.204% $ 11,034.86 Utility Relocation Cost URC 0.08108 0.183% $ 9,895.00 Re design Cost DSC 0.07142 0.161% $ 8,716.10 Contractor Contingency Cost CCC 0.07298 0.165% $ 8,906.48 Contractor Change Order Cost CCO 0.0728 0.165% $ 8,884.51 Contractor Injury Cost CIC 0.07429 0.168% $ 9,066.35 Utility Damage Cost UDC 0.08593 0.194% $ 10,486.90 Personal Injury Cost PIC 0.08111 0.183% $ 9,898.66 Travel Delay Cost TDC 0.07684 0.174% $ 9,377.55 Business Impact Cost BIC 0.07253 0.164% $ 8,851.56 Service Interruption Cost SIC 0.07523 0.170% $ 9,181.07 Errors and Omission Cost EOC 0.07193 0.163% $ 8,778.34 Environmental Impact Cost EIC 0.07343 0.166% $ 8,961.40 1.0000 2.260% $ 122,038.78

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100 APPENDIX G UTILITY CONFLICT MATRIX EXAMPLE

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101 UTILITY CONFLICT MATRIX Project Description: Project FPID#: County: Duval Roadway Station Offset Side Type of facility Description of Conflict Type of Conflict Depth to Top of Conflict 23+79 33.23 RT Water 6" CI water conflicting with 18" pipe between S 103 and S 102 Pipe 3.55 23+88 49.61 RT Water 6" CI water conflicting with 18" pipe between S 102 and S 104 Pipe 5.9 25+43 20.5 LT Water 6" PVC water conflicting with 30" pipe between S 105 and S 108 Pipe NA 25+96 19.5 LT CATV Buried CATV conflicting with Structure S 108 Manhole 2 25+96 19.5 LT Water 2" PVC water conflicting with Structure S 108 Manhole 4.34 26+04 18.42 LT Water 6" CI water conflicting with 30" pipe between S 108 and S 111 Pipe NA 26+77 17.08 LT Water 6" CI water conflicting with 30" pipe between S 108 and S 111 Pipe NA 26+87 18.05 LT CATV CATV Box suggests a possible CATV conflict with 30" pipe between S 108 and S 111 Pipe NA 27+05 19.79 LT CATV Buried CATV conflicting with Structure S 111 Inlet 1.95 27+05 19.79 LT Water 2" Galv water may conflict with Structure S 111 Inlet 1.92 27+37 17.01 LT Water 2" Galv water conflict with 30" pipe between S 111 and S 113 Pipe NA 27+41 15.33 RT CATV Buried CATV may conflict with Structure S 112 Inlet 1.75 27+90 16.97 LT Water 2" Galv water conflict with 30" pipe between S 113 and S 114 Pipe NA 28+20 19.5 LT Water 2" Galv water may conflict with Structure S 114 Manhole NA 28+74 16.66 LT Water 2" Galv water conflict with 30" pipe between S 114 and S 115 Pipe NA 29+13 15.2 LT Water 2" Galv water may conflict with Structure S 115 Inlet NA 29+13 15.33 RT FOC Buried FOC may conflict with Structure S 116 Inlet 2.48 29+31 17.28 LT Water 2" Galv water conflict with 24" pipe between S 115 and S 117 Pipe NA

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102 29+83 19.43 LT Water 2" Galv water conflict with 18" pipe between S 117 and S 118 Pipe NA 29+88 26.05 RT FOC Buried FOC conflicting with 18" pipe between S 118 and S 119 Pipe NA 29+89 24.74 LT FOC Buried FOC conflicting with 18" pipe between S 117 and S 120 Pipe NA 30+17 23.41 LT Water 2" Galv water conflict with 18" pipe between S 118 and S 120 Pipe NA 30+23 23.14 LT Water 6" CI water may conflict with 18" pipe between S 118 and S 120 Pipe 2.98 30+23 33.61 RT Water 8" CI water may conflict with 18" pipe between S 118 and S 119 Pipe 3.58 30+33 35.74 RT Water 6" CI water conflicting with Structure S 119 Inlet 3.2 30+64 14.33 LT Water 2" Galv water conflicting with Structure S 121 Inlet 2.38 30+64 8.39 RT Water 4" PVC water conflicting with 18" pipe between S 121 and S 122 Pipe NA 32+10 14.33 LT Water 2" Galv water conflicting with Structure S 123 Inlet 1.99 32+10 14.33 RT Water 4" PVC water conflicting with Structure S 124 Inlet 2.47 32+10 14.33 RT BT FOC BT FOC conflicting with Structure S 124 Inlet 2.47 32+10 14.33 RT Telephone /BT Buried I 50PR BT may conflict with Structure S 124 Inlet 2.03 32+56 16.01 LT FOC Buried FOC may conflict with 18" pipe between S 123 and S 128 Pipe NA 33+19 19.24 LT Telephone /BT BT may conflict with 18" pipe between S 123 and S 128 Pipe NA 33+25 19.53 LT Sewer 10" DI FM may conflict with 18" pipe between S 123 and S 128 Pipe 4

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103 LIST OF REFERENCES AASHTO. (2004). Right of Way and Utiliti es Guidelines and Best Practice. Strategic Plan 4 4. American Association of State Highway and Transportation Officials Standing Committee on Highways. 6, January 2004 AASHTO. (2005). A Guide For Accomodating Utilities Within Highway Right Of Way AASHTO Technical Committee On Geometric Design ISBN 1 56051 306 3. American Society of Civil Engineers (ASCE) ( 2002 ) Standard Guidline for the Collection and Depiction of Existing Subsurface Utility Data. Vols. ASCE 38 02. ASCE Codes and Standards Activity Committee (CCSAC). New York, NY. Anaspach, J.H. ( 1994 Integrating Subsurface Utility Engineering into Damage Prevention Programs The 1994 Excavation Damage Prevention Worksho p. Anaspach, J.H. ( 1996 ) Subsurface Utility Engineering: Utility Det ection Methods and Symposium on the Application of Geophysics to Engineering & Environmental Problems September 1996. Ellis, Jr., R. D (2003). egies for Avoiding Utility Related Delays During FDOT Construction Pro Transporation. Ellis, Jr., R. D. and Lee, S. (2005). Developing Best Practices for Avoid ing Utility ASCE Construction Research Congress FDOT ( 2009 ) Plans Preparation Manua l, Volume 2: Plans Preparation and Assembly Topic No. 625 000 008, Florida Department of Transportation, Lake City, FL. Subsurface Utility Engineering Federal Highway Administration, March 8, 2002. Jeong, H.S., Abraham D.M., and Lew J.J. ( 2004 ) Subsurface Utility Engineering ASCE Journal of Construction Engineering and Management. Vol. 130, No. 2. Lew, J.J. ( 2000 ) Cost Savings on Highway Projects utilizing Subsurface Utility Engineering. Federal Highway Administration Washington D.C. La DODT. ( 2009 ) Roadway Design Procedures and Details Chapter 4 Elements of Design. Louisiana Department of Transportation. Minn DOT. (2009) Utilities Manual. http://www.dot.state.mn.us/utility/files/pdf/policy/utilities manual web.pdf

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104 Osman, H. and El Diraby, T. E. (2005) Subsurface Utility Engineering in Ontario: Challenges & Opportunities. A Report To T he Ontario Sewer & Watermain Contractors Association Ontario, Canada. Pickering, B. ( 1999 ) Impacts of Utility Relocations on Highway and Bridge Projects. Transportation Infrastructure: GAO/RCED 99 131. Pitchford, M.R. ( 2009 ) Interview. Tampa, 29 July 2009. Saaty, T.L. (1980). The Analytic Hierarchy Process, New Your, NY, McGraw Hill. Stevens, R.E. (1993). Adding Value Through Innovations of Subsurface Utility Engineering. Society of American Value Engineering (SAVE) Annual Proceedings. Stutler, D ( 2006 ) Department and Utility Agency Owners Liason Florida Department of Transportation. www.dot.state.fl.us. Topic No.: 710 030 010 b. 25 April 2006. Sinha, S. K. Jung Y.J., Thomas R.H., and Wan g, M.C. ( 2008 ) Subsurface Utility Engineering for Highway Construction American Society of Civil Engineers Pipelines Congress 22 27 July, 2008. Atlanta, GA. Zimbillas, N Subsurface Utility Engineering: A Technology Driven Process that results in Increased Safety, Fewer Design Changes, and Lower Cost American Society of Civil Engineers Pipelines Congress 22 27, July 2008. Atlanta, GA Noone, J. F. Use of ASCE 38 02 and Subsurface Utility Engineering for Better Design, Cost Savings, and Damage Prevention in Airport Planning and D esig American Society of Civil Engineers ASCE Conf. Proc. 142, 72. Weldon, K. ( 2006 ) FDOT Policy & Processes To Avoid Utility Conflicts Florida Department of Transportation State Utility Office, July 2006. Zimbillas, N.M., and Beyer, B. J. (2004). Proactive Utilities Management: Conflict Analysis and Subsurface Utility Engineering, American Society of Civil Engineers Conference Proceedings. 4 October 2004. Calgary, Alberta, Canada.

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105 BIOGRAPHICAL SKETCH Michael Coffey P.E., LEED AP earn ed a BS in p hysics from Florida Atlantic University in 1996, a BS in Civil Engineering from the University of Florida in 1997, and a Master of Engineering from the University of Florida in 1998. Prior to graduating college, he was an instrument man and cr ew chief for Dennis Leavy & Associates, a survey and planning firm in south Florida. After graduation in 1998, he began working for Berryman & Henigar, a national municipal engineering and surveying firm, where he developed engineered designs for water an d sewer utilities, roadway, drainage, site development, and maritime projects. As a public sector consultant, he has assisted Florida municipalities with water capacity development, water and sewer system master planning, capital outlay projects, gra nt wr iting and procurement, engineering studies, supply/treatment fac ility design, permitting and construction He specialized in municipal water supply and wastewater facility design at B&H and was the design engineer or engineer of record for at least seven municipal or regional water supply facilities throughout Florida. He became a vice president of the firm in 2001, and was responsible for the Jacksonv ille, Florida office and opened another office location in Palm Coast, Florida. He is currently the civil discipline leader for the Corporate Commercial program at Reynolds, Smith, and Hills, in Jacksonville, Florida. He started his Ph.D. study at the University of Florida in June 2007. He received his Ph.D. in civil engineering in 2010, under the gui dance of Dr. Ralph Ellis. Mr. Coffey is a member of ASCE, NSPE, Delta Epsilon Iota, and the Green Building Council. He holds professional engineer registrations in Florida Georgia South Carolina, North Carolina, Virginia, and Kentucky