GEORGIA DOT RESEARCH PROJECT 17-24 FINAL REPORT GEORGIA LONG-TERM PAVEMENT PERFORMANCE (GALTPP) PROGRAM MAINTAINING GEORGIA S CALIBRATION SITES AND IDENTIFYING THE POTENTIAL FOR USING MEPDG FOR CHARACTERIZATION OF NONSTANDARD MATERIALS AND METHODS PHASE 2 OFFICE OF PERFORMANCE-BASED MANAGEMENT AND RESEARCH 15 KENNEDY DRIVE FOREST PARK GA 30297-2534 1. Report No. FHWA-GA-19-1724 2. Government Accession No. 4. Title and Subtitle Georgia Long-Term Pavement Performance (GALTPP) Program Maintaining Georgia s Calibration Sites and Identifying the Potential For Using MEPDG For Characterization Of NonStandard Materials and Methods Phase 2 7. Author(s) Yiching Wu Yichang Tsai 9. Performing Organization Name and Address Georgia Institute of Technology 790 Atlantic Drive Atlanta GA 30332-0355 12. Sponsoring Agency Name and Address Georgia Department of Transportation Office of Performance-Based Management and Research 15 Kennedy Drive Forest Park GA 30297-2534 3. Recipient s Catalog No. 5. Report Date April 2019 6. Performing Organization Code 8. Performing Organ. Report No. 17-24 10. Work Unit No. 11. Contract or Grant No. PI 0015304 13. Type of Report and Period Covered Final September 2017 September 2018 14. Sponsoring Agency Code 15. Supplementary Notes Prepared in cooperation with the U.S. Department of Transportation Federal Highway Administration. 16. Abstract The Georgia Department of Transportation (GDOT) has initiated a Georgia long-term pavement performance (GALTPP) program to provide data for the calibration of the Mechanistic-Empirical Pavement Design Guide (MEPDG) and to monitor sites for evaluating the effect of various materials and treatment methods on pavement performance. Phase 2 of the project has 1) expanded the GALTPP database with concrete pavement sites used in the local calibration of the MEPDG 2) identified and managed special test sites of GDOT s interest 3) documented and analyzed the data collected from the cold in-place recycling (CIR) and open-graded interlayer (OGI) test sites on State Route 16 and 4) conduct the soil cement pavement performance analysis by comparing the observed pavement performance and the predicted pavement performance. First the tables and fields for concrete pavement were designed and populated in the GALTPP database. Concrete pavement data collected by ARA from the Georgia calibration (GaCal) sites were acquired processed and populated into the corresponding tables designed in the GALTPP database. Second eighty-seven special test sites including selected soil cement sites cold in-place recycling (CIR) open-graded interlayer (OGI) micromilling and thin overlay etc. were identified georeferenced and entered into the GALTPP database. Third the CIR and OGI test sites on State Route 16 were documented and the performance prior to the treatment was analyzed using historical COPACE Finally the soil cement pavement performance was analyzed using historical COPACES data and compared to the predicted pavement performance predicted by the using the MEPDG. The results show fair correlation between the predicted and measured fatigue cracking (R2 0.92). The MEPDG mostly overpredicts transverse cracking when the observed cracking is less than 1500 ft per mile and underpredicts when the observed cracking is greater than 1500 ft per mile. The latter case occurs because the MEPDG predicts the maximum transverse cracking at about 1500 ft per mile. 17. Key Words 18. Distribution Statement Georgia long-term performance monitoring GALTPP No Restriction MEPDG cold in-place recycling CIR open-graded interlayer OGI 19. Security Classification 20. Security classification (of 21. Number of 22. Price (of this report) Unclassified this page) Unclassified Pages 56 Form DOT 1700.7 (8-69) ii GDOT Research Project No. 17-24 Final Report GEORGIA LONG-TERM PAVEMENT PERFORMANCE (GALTPP) PROGRAM MAINTAINING GEORGIA S CALIBRATION SITES AND IDENTIFYING THE POTENTIAL FOR USING MEPDG FOR CHARACTERIZATION OF NONSTANDARD MATERIALS AND METHODS PHASE 2 By Yiching Wu Research Engineer Yichang (James) Tsai Ph.D. P.E. Professor of Civil and Environmental Engineering Georgia Institute of Technology Contract with Georgia Department of Transportation In cooperation with U.S. Department of Transportation Federal Highway Administration April 2019 The contents of this report reflect the views of the author(s) who is (are) responsible for the facts and the accuracy of the data presented herein. The contents do not necessarily reflect the official views or policies of the Georgia Department of Transportation or the Federal Highway Administration. This report does not constitute a standard specification or regulation. iii TABLE OF CONTENTS Page LIST OF TABLES ............................................................................................................. vi LIST OF FIGURES .......................................................................................................... vii EXECUTIVE SUMMARY ............................................................................................... ix ACKNOWLEDGEMENTS ............................................................................................. xiv 1. INTRODUCTION ....................................................................................................... 1 1.1. Background and Research Need .......................................................................... 1 1.2. Significance of Research ...................................................................................... 4 1.3. Research Objectives and Scope............................................................................ 4 1.4. Organization of This Report................................................................................. 6 2. MANAGEMENT OF GALTPP DATA ...................................................................... 8 2.1. Overview of the GALTPP Program ..................................................................... 8 2.2. Design of the GALTPP Database....................................................................... 11 2.3. Populating GALTPP Database........................................................................... 14 2.4. GALTPP GIS Integration................................................................................... 16 3. COLD IN-PLACE RECYCLING (CIR) AND OPEN-GRADED INTERLAYER (OGI) TEST SITES ON SR 16 ......................................................................................... 19 3.1. Site Information.................................................................................................. 19 3.2. Data Collected before CIR and OGI .................................................................. 21 3.2.1. Performance base on historical COPACES data ........................................ 22 3.2.2. Field Test Data ............................................................................................ 24 3.3. Cold In-Place Recycling (CIR) .......................................................................... 26 iv 3.4. Open-Graded Interlayer (OGI)........................................................................... 29 3.5. Data Collected after CIR and OGI ..................................................................... 31 3.6. Summary ............................................................................................................ 32 4. ANALYSIS OF SOIL CEMENT PAVEMENT PERFORMANCE......................... 34 4.1. Soil Cement Sites ............................................................................................... 34 4.2. Observed Pavement Performance using Historical COPACES Data ................ 36 4.3. Predicted Pavement Performance using MEPDG .............................................. 41 4.4. Comparison of Observed and Predicted Pavement Performance....................... 45 4.5. Summary ............................................................................................................ 49 5. CONCLUSIONS AND RECOMMENDATIONS.................................................... 51 REFERENCES ................................................................................................................. 56 APPENDIX A GALTPP DATABASE TABLES .......................................................... A-1 APPENDIX B SITE 3D PAVEMENT SURFACE IMAGES SHOWING PAVEMENT DISTRESS CONDITIONS............................................................................................. B-1 APPENDIX C CORE PICTURES SHOWING SUBSURFACE CONDITIONS ......... C-1 v LIST OF TABLES Tables Page Table 1-1 Work by Phases .................................................................................................. 2 Table 2-1 Summary of the GALTPP sites .......................................................................... 9 Table 3-1 Test Site Information ........................................................................................ 20 Table 3-2 Pavement conditions based on 3D pavement data ........................................... 25 Table 3-3 FWD Back-calculation results.......................................................................... 25 Table 3-4 Core information on State Route 16 ................................................................. 26 Table 4-1 Locations of Selected Sites and Pavement Designs ......................................... 35 Table 4-2 Georgia s asphalt pavement calibration coefficients (Harold et al. 2016) ...... 42 vi LIST OF FIGURES Figures Page Figure 2-1 A map of the GALTPP sites.............................................................................. 9 Figure 2-2 Illustration of GALTPP database schema ....................................................... 12 Figure 2-2 Special test site locations ................................................................................ 16 Figure 2-3 An example of roadway images that can be accessed using GIS function ..... 18 Figure 3-1 Test site location ............................................................................................. 20 Figure 3-2 Illustration of pavement designs of travel lane (left) and passing lane (right) 21 Figure 3-3 Historical COPACES data on State Route 16................................................. 22 Figure 3-4 Load cracking before CIR and OGI treatment ................................................ 23 Figure 3-5 Block cracking before CIR and OGI treatment............................................... 23 Figure 3-6 Segment-level COPACES Ratings on State Route 16 .................................... 24 Figure 3-7 Removal of a Thin Layer of Pavement ........................................................... 27 Figure 3-8 Application of Lime on the Milled Surface .................................................... 27 Figure 3-9 Mixture of Pavement and Additives ............................................................... 28 Figure 3-10 Compaction of Recycled Material ................................................................ 28 Figure 3-11 Compaction of Recycled Material ................................................................ 29 Figure 3-12 Removal of the Existing Pavement Surface.................................................. 30 Figure 3-13 Application of Asphalt .................................................................................. 30 Figure 3-15 Application of 1" OGI................................................................................... 31 Figure 3-15 Historical COPACES Data Before and After CIR and OGI Application ..... 32 Figure 4-1 Selected Soil Cement Pavement Sites............................................................. 35 vii Figure 4-2 COPACES rating and distresses on selected soil cement projects ................. 37 Figure 4-3 Relationship between load cracking from GDOT COPACES and alligator cracking from LTPP (Harold et al. 2016)................................................................. 39 Figure 4-4 Observed fatigue cracking............................................................................... 40 Figure 4-5 Observed longitudinal cracking (non-wheel path) .......................................... 41 Figure 4-6 Observed rutting.............................................................................................. 41 Figure 4-7 Predicted distresses by the ME Design (v2.3.1) ............................................. 43 Figure 4-8 Pavement structure analysis using the ME Design (v2.3.1)............................ 45 Figure 4-9 Observed vs. Predicted fatigue cracking (percent of total area) ..................... 46 Figure 4-10 Predicted vs. Observed transverse crack (ft per mile)................................... 47 Figure 4-11 Predicted vs. Observed rut depth (in.)........................................................... 47 Figure 4-12 Predicted vs. Observed IRI (ft/mile) ............................................................. 48 viii EXECUTIVE SUMMARY The Georgia Department of Transportation (GDOT) has initiated a Georgia Long-term Pavement Performance (GALTPP) program to provide data for calibrating the Mechanistic-Empirical Pavement Design Guide (MEPDG) and more importantly to monitor sites of GDOT s interest for evaluating the effect of materials and treatment methods on pavement performance. This supports subsequent long-term performance analysis and life-cycle cost analysis for GDOT to use in critically assessing and justifying the application of different pavement maintenance and rehabilitation (M&R) methods for cost-effective annual M&R planning and prioritization. The GALTPP program includes LTPP sites Georgia s calibration (GaCal) sites and special test sites and a GALTPP database serves as a centralized source of the data on these sites. The objectives of Phase 2 are 1) to expand the GALTPP database with concrete pavement sites used in the local calibration of the MEPDG 2) to identify and manage special test sites of GDOT s interest 3) to document and analyze the data collected from the cold in-place recycling (CIR) and open-graded interlayer (OGI) test sites on State Route 16 and 4) to conduct the soil cement pavement performance analysis by comparing the observed pavement performance (acquired from historical COPACES data) and the predicted pavement performance (analyzed using the MEPDG). The AASHTOWare Pavement ME Design (hereafter referred as ME Design) software was used for predicting pavement performance in this project. Below are the findings from Phase 2 1) The GALTPP database tables and fields for concrete pavement sites were designed to store and manage the data collected by ARA at GACal for the initial MEPDG local ix calibration (Harold et al. 2016). A GIS project was used with the GALTPP database for visualizing the sites. They are summarized below a. A relational GALTPP database with location reference information was designed to host the LTPP GaCal and special test sites and store the data related to these different sites. Tables fields and relationships among tables (i.e. primary keys and foreign keys) were designed to store and manage the input parameters used in the MEPDG calibration and testing data collected at GaCal sites for easy query and data integrity. b. Twenty-three concrete pavement sites including LTPP and GaCal sites used for previous MEPDG local calibration were stored in the GALTPP database. The MEPDG inputs as well as the measured distresses can be easily accessed in support of future validation and calibration of the MEPDG. c. A GALTPP geodatabase containing the three types of sites was developed it can be integrated into GDOT s GIS systems. 2) Special test sites with different materials and treatment methods including soil cement base cold in-place recycling (CIR) open-graded interlayer (OGI) micromilling and thin overlay fog seal crack filling high friction surface treatment (HFST) and light weight aggregates (alternative treatment of HFST with bauxite and resin) were identified and entered into the GALTPP database. In addition beyond the scope of this project the spatial location information of these additional efforts were made to identify and locate special these sites by searching the GeoPI for project numbers and locating projects. Eighty-seven special test sites were georeferenced and entered into the GALTPP database. x 3) Field test data including prior CIR and OGI pavement surface condition data FDW data coring data etc. from the CIR and OGI test sites on State Route 16 were acquired documented and entered into GALTPP. The 3D pavement surface data before CIR and OGI application were collected and the detailed distresses were analyzed to provide a pavement condition reference to support subsequent analysis for treatment timing. Historical COPACES data was analyzed to reveal the long-term pavement performance prior to CIR and OGI application. It shows a pavement has 7 to 8 years of life between a rating of 100 to a rating of 70. This performance can be used as a reference with which to compare the long-term performance of CIR and OGI applications. With the unit cost the life cycle cost analysis or the new treatment methods can be critically evaluated in the future. 4) The soil cement pavement performance analysis was conducted by comparing the observed pavement performance (acquired from historical COPACES data) and the predicted pavement performance analyzed using the ME Design software. Conclusions are as follows a. Bias has been found in all distresses (transverse cracking rutting and IRI) except fatigue cracking. b. The ME Design predicts little or no fatigue cracking for these soil cement sites. The results show fair correlation between the predicted and measured fatigue cracking (R2 0.92). c. The ME Design mostly overpredicts transverse cracking when the observed cracking is less than 1500 ft per mile and underpredicts when the observed xi cracking is greater than 1500 ft per mile. The latter case occurs because the ME Design predicts the maximum transverse cracking at about 1500 ft per mile. d. The ME Design predicted little rutting on these soil cement sites. Poor correlation (R2 0.1) was found between the predicted and measured rut depths. e. The ME Design overpredicted the IRI. The initial IRI was about 50 in per mile and on average IRI was overpredicted by 70%. Poor correlation (2 0.07) was found between the predicted and measured IRI. The following recommendations are made 1) The GALTPP geodatabase can be integrated into GDOT s existing GIS systems such as GeoPI for disseminating the information and better coordinating the work on the GALTPP sites. 2) Pavement distresses on CIR and OGI test sites should continue to be monitored even though the preliminary performance shows that the project rating is 100 and there are no pavement distresses one year after the application of CIR and OGI. 3) There are two changes in the flexible pavement design in the new release of AASHTOWare Pavement ME Design version 2.5. Instead of a constant value C2 in fatigue cracking is now dependent on the asphalt concrete thickness. The lab test coefficients (B) are used in the model instead of using 1. With these significant changes and the expected calibration tool it is recommended that GDOT verify the performance using the global coefficients included in Pavement ME Version 2.5. 4) The new ME Design (version 2.5) includes the global coefficients for semi-rigid pavement which were for the first time globally calibrated. Although a large portion of semi-rigid data used for the global calibration were from Virginia the accuracy of xii the predicted distresses should be verified by comparing the predicted distresses with the distresses observed in the field. 5) Because the change to GDOT s pavement data collection approach full-coverage 3D pavement data will be available on state routes. The variability and representativeness of the distresses on the test sites can be evaluated using 3D pavement data. 6) Additional test sites (covering common design features used in Georgia) should be included to further verify and calibrate the predicted distresses using the MEPDG. xiii ACKNOWLEDGEMENTS We would like to thank the Georgia Department of Transportation (GDOT) for its support. The work conducted in this report was sponsored by the GDOT Office of Performance-Based Management and Research (Research Project 17-24). We would also like to thank Mr. David Jared and Mr. Binh Bui from the Office of Performance-Based Management and Research and Mr. Ian Rish and Mr. Yusuf Ahmed from the Office of Materials and Testing for their technical support. We would also like to thank the members of the research team at the Georgia Institute of Technology including Georgene Geary Mingshu Li and Zhongyu Yang for their diligent work on data collection processing and analysis in this research project. xiv 1. INTRODUCTION 1.1. Background and Research Need The Georgia Department of Transportation (GDOT) is in the process of implementing the AASHTO Mechanistic-Empirical Pavement Design Guide (MEPDG) developed under the National Cooperative Highway Research Program (NCHRP) Project 1-37A (NCHRP 2004) for the design of new and rehabilitated pavement structures. The MEPDG models pavement responses (stresses strains and deflections) using traffic loading material properties and environmental data to compute incremental damage over time and it empirically relates the cumulative damage to observed pavement distresses using pavement distress and smoothness transfer functions. Therefore validating and calibrating the transfer functions to local conditions (e.g. designs materials and environment) is a crucial step in implementing the MEPDG. As part of the initial implementation efforts GDOT has undertaken several projects to establish the groundwork for the MEPDG calibration. These include 1) conducting tests to characterize material properties 2) studying traffic load spectra 3) establishing a Georgia Long-term Pavement Performance (GALTPP) program to provide data for the MEPDG calibration and 4) developing user manual for the AASHTOWare Pavement ME Design (hereafter referred as ME Design) software (AASHTO). The GALTPP program includes LTPP sites in Georgia and additional Georgia s calibration sites (referred as GaCal sites) to cover common design features used in Georgia for support of the MEPDG calibration (ARA 2015a). Besides MEPDG calibration and validation it is important for GDOT to track special test sites with different pavement designs materials and treatment methods to provide the basic information of site location and site characteristics this test site information enables GDOT to assess the long-term 1 performance of alternative treatment methods in support of GDOT s efforts to achieve costeffective pavement maintenance and rehabilitation (M&R) planning. This project consists of three consecutive one-year phases with each phase focusing on one component for maintaining the data collected for the GALTPP program and one specific method and material identified by GDOT. Table 1-1 lists the work by phases. This allows GDOT to prioritize the methods and materials to study in this project and provides the flexibility to study the sites that are relatively new in later phases. Phase 1 of this project focused on developing a GALTPP database for maintaining the data collected from the flexible pavement sites and evaluating the design of pavement structure of Georgia s interstate highways based on the MEPDG (using the ME Design software). Phase 2 focuses on extending the database to the concrete pavement sites and studying the performance of soil cement pavement. Phase 3 will focus on the procedures for incorporating additional special test site data (e.g. performance data). The potential topics for Phase 3 will be determined at the end of Phase 2. Phase 1 Phase 2 Phase 3 Table 1-1 Work by Phases Maintaining GALTPP data Potential Topics Flexible pavement sites Interstate highway Concrete pavement sites and special test sites Soil cement pavements Incorporating research sites To be determined While the initial calibration was completed in 2016 it is recognized that the recalibration of the MEPDG is needed as the models are improved as more distress data become available over time as new pavement methods and materials are implemented in Georgia and as testing methods and MEPDG models (e.g. the coefficient of thermal expansion) are improved. 2 Especially the initial calibration is based on the sites that have a limited set of standard methods and materials and it does not cover all materials used by GDOT. For example soil cement base one of the bases commonly used in southern Georgia did not have enough information to be included in the initial calibration. In addition over the years GDOT has built test sections with new methods and materials such as the use of micromilling and thin overlay cold in-place recycling (CIR) open-graded interlayer (OGI) fog seal crack filling and high friction surface treatment (HFST). There is a need to incorporate these special test sites into the GALTPP program to monitor their performance so research outcomes can be used to improve GDOT s practices of pavement design construction and maintenance. In addition these special test sites need to be considered in the implementation of the MEPDG. To pave the way for future calibration efforts GDOT has identified the following needs 1) Inclusion of concrete pavement sites used in the MEPDG local calibration 2) Inclusion of special test sites built with non-standard methods and materials into the GALTPP program in support of GDOT s long-term performance analysis and life-cycle cost analysis (LCAA) for GDOT s cost-effective pavement maintenance and rehabilitation planning 3) Inclusion of pavement techniques that have been critically assessed as alternative maintenance and rehabilitation methods in Georgia e.g. CIR and OGI in the GALTPP program to evaluate their performance and benefits and to study the feasibility of applying them as the alternative pavement maintenance and rehabilitation methods in Georgia 3 4) Identification of the potential for the characterization of non-standard methods and materials or materials not adequately covered in local calibration (e.g. soil cement base) using the ME Design to provide suggestions on the calibration of these sites. 1.2. Significance of Research Maintaining the data collected for the GALTPP program will allow GDOT to track and share data collected from sites that have different designs materials construction methods and maintenance levels this will support GDOT s long-term pavement performance analysis and life-cycle cost analysis for pavement maintenance and rehabilitation planning and pavement management. The GALTPP database and GIS project will serve as one of the most important sources of data for further validation and calibration of the MEPDG models and for evaluating the effects of different pavement designs materials etc. The outcomes/findings can be used to improve GDOT s practices for pavement design material selection construction methods and maintenance strategies. In addition the outcomes impact on the potential for characterizing nonstandard (special) methods and materials used in Georgia will enable GDOT to better utilize the MEPDG for understanding distresses based on different designs and materials. The terms "nonstandard" and "special test sites" are used interchangeably in this report. 1.3. Research Objectives and Scope The objectives of Phase 2 of the project are 1) to expand the GALTPP database with concrete pavement sites used in the local calibration of the MEPDG 2) to identify and manage special test sites of GDOT s interest 3) to document and analyze the data collected from the cold in-place recycling (CIR) and open-graded interlayer (OGI) test sites on State Route 16 and 4) to conduct 4 the soil cement pavement performance analysis by comparing the observed pavement performance (acquired from historical COPACES data) and the predicted pavement performance (analyzed using the ME Design). Four research tasks are included in Phase 2. The specific activities to be performed under each work task are presented below 1) Work Task 1 Manage the data collected at GACal concrete sites and incorporate additional special test sites. In this task the Georgia Tech research team acquired the data including FWD LTPP distress survey data and coring data collected at GACal sites and processed and integrated the data into a geodatabase that can be easily integrated into GDOT s existing GIS systems. 2) Work Task 2 Collect process and manage the data collected at the CIR and OGI test sites including the analysis of the historical COPACES data on State Route 16. To study the performance of two pavement techniques (CIR and OGI) GDOT has conducted a test project on State Route 16 in Coweta County Georgia. Five sites were selected to assess these two types of pavement techniques. OGI was applied in all travel lanes in this project. CIR on the other hand was only applied to a small portion of this section in passing and/or left turn lanes. The Georgia Tech research team collected processed and managed the data collected at the CIR and OGI test sites. 3) Work Task 3 Characterize Georgia s cement-treated base materials to support a local calibration of the distress transfer functions in the MEPDG This work task is to critically assess the applicability of the global coefficients for soil cement pavement designs and to develop a detailed plan for a local calibration for soil cement-flexible pavement. The distresses predicted using the MEPDG were compared to the observed distresses (based on COPACES data) to assess applicability of the MEPDG for soil 5 cement pavements in Georgia and recommendations will be made for further local calibration. 4) Work Task 4 Summarize research findings. This task documents organizes summarizes and disseminates research findings obtained in the previous work tasks. The GAPLTPP database is in a geodatabase format that can be opened using desktop ArcGIS. 1.4. Organization of This Report This report is organized as follows 1) Chapter 1 introduces the background significance scope objectives and work tasks of this project. 2) Chapter 2 presents the management of GALTPP data especially the addition of special test sites into the GALTPP geodatabase. It includes the spatial location reference and general description of these special test sites. 3) Chapter 3 presents the data collection processing and management of CIR and OGI test sites on State Route 16 in detail which will support the subsequent long-term performance analysis to critically assess and justify the suitability of applying CIR and OGI on Georgia roadways. This chapter presents the test sites information including route location lane and direction. Before and after pavement performance using COAPCES ratings is also analyzed. The detailed pre-treatment conditions including field tests and data collected such as cores falling weight deflectometer (FWD) and LCMS are presented. The 3D pavement surface data on the pavement distresses prior to CIR and 6 OGI treatments is also presented. The procedures for the CIR and OGI on SR 16 are summarized. 4) Chapter 4 presents the soil cement pavement analysis. First the soil cement pavement sites are presented. Second the observed pavement performance is analyzed using historical COPACES data. Third the pavement performance is predicted using the MEPDG. Finally the observed and predicted pavement performance are compared and discussed. 5) Chapter 5 summarizes the findings of this project and makes recommendations. 7 2. MANAGEMENT OF GALTPP DATA 2.1. Overview of the GALTPP Program The Georgia Long-term Pavement Performance (GALTPP) program was initiated by GDOT to provide a sufficient number of sites for the initial MEPDG local calibration and more importantly to conduct long-term performance monitoring on the sites of GDOT s interest to support the performance evaluation and/or future MEPDG recalibration. The GALTPP program comprises three type of sites LTPP sites in Georgia Georgia s calibration (GaCal) sites and special test sites. Both LTPP and GaCal sites were used for the initial location calibration of the MEPDG conducted by ARA (Harold et al. 2016). Though the initial calibration was completed it is recognized that the recalibration of the MEPDG is still needed in the future as MEPDG performance models (e.g. reflective cracking model) are improved as more distress data becomes available over time and as new pavement methods and materials are implemented in Georgia. The rich data collected on the GALTPP sites (both LTPP and GaCal sites) are valuable to GDOT and essential for support of MEPDG recalibration in the future. Therefore the GALTPP program includes both LTPP and GaCal sites. Besides these sites the GALTPP program includes special test site(s) for evaluating the effects of different designs materials construction methods maintenance levels etc. on pavement performance. Phase 2 of this project have 1) expanded the GALTPP database with concrete pavement sites used in the local calibration of the MEPDG and 2) identified and managed special test sites of GDOT s interest. Figure 2-1 shows a map of the sites included in the GALTPP program and Table 2-1 summarizes the three types of sites. 8 Site Type LTPP sites GaCal sites Sub total Special test sites Figure 2-1 A map of the GALTPP sites Table 2-1 Summary of the GALTPP sites Flexible pavement sites 17 21 38 87 Rigid pavement sites Jointed plain Continuous concrete pavement reinforced concrete (JPCP) pavement (CRCP) 9 2 12 0 21 2 Sub total 28 33 87 Currently the GALTPP program comprises 28 LTPP sites and 33 GaCal sites. The 28 LTPP sites include 17 flexible pavement sites and 11 concrete pavement sites located in Georgia 9 each site is about 500 ft long. Comprehensive information including site information construction history traffic load pavement design (i.e. layer structure) material properties and distresses on LTPP sites are available in the LTPP program. It is noted that distress surveys were conducted by the LTPP contractor based on the LTPP Distress Identification Manual (FHWA 2003). The 28 LTPP sites are insufficient to cover the range of pavement structures materials and other design features commonly used by GDOT and the levels of distress exhibited on these LTPP sites are inadequate for the MEPDG local calibration. Therefore additional 33 GaCal sites (21 flexible pavement sites and 12 concrete pavement sites) were selected in 2014 based on the pavement design and distresses to support the local calibration. Limited field and laboratory testing including condition surveys in accordance with LTPP Distress Identification Manual (FHWA 2003) core falling weight deflectometer (FWD) dynamic cone penetration (DCP) tests of the base and subgrade bulk specific gravity measured on each layer etc. were conducted on the GaCal sites to obtain the layer thickness and material properties for the MEPDG inputs. It is noted that the pavement condition survey based on the LTPP distress protocol (FHWA 2003) was conducted only once in 2014 by ARA (Harold et al. 2016). Historical COPACES data on GaCal sites were converted into the distresses predicted by the MEPDG (including fatigue cracking transverse cracking etc.) for the validation and calibration of the MEPDG (Tsai and Wu 2016). Special test sites refer to sites GDOT constructed with specific materials (e.g. HFST) construction methods (e.g. micromilling) and treatment methods (e.g. crack filling fog seal CIR and OGI) for evaluating their long-term performance. Compared to LTPP and GaCal sites 10 there are very limited data available on these sites. Some sites may be associated with research project(s). There is a need to keep track of these special research projects so their long-term performance can be evaluated. 2.2. Design of the GALTPP Database A database is used to store and organize various data collected for the GALTPP program and to manage the data efficiently. A GALTPP database has been established to serve as a centralized source of the GALTPP data. The GALTPP database is a relational database composed of separate but related tables of data. All data is stored in a simple row/column format. Each row is uniquely identified by a primary key (often a combination of columns e.g. GALTPP_ID and CONSTRCTION_NO). In addition relationships exist among the tables. Relationships are associations between tables that enable you to retrieve and combine data from one or more tables. For example many tables contain a GALTPP_ID column used to locate data for a specific site in different tables. The GALTPP database was designed to do the following Store and manage LTPP GaCal and special test sites that serve different purposes Provide easy access to the inputs and measured distresses used for the MEPDG local calibration Provide spatial information for each site so it can be integrated into a GIS geodatabase Add additional sites in the future when available Be consistent with the LTPP database where possible. While the GALTPP database was designed to be consistent with the LTPP database when possible the GALTPP database is not intended to duplicate the completed LTPP database. Instead it was designed to provide easy access and management of the inputs and distresses used 11 for the MEPDG calibration and to provide the flexibility to track the long-term performance of the special test sites. The design of the GALTPP database involved identifying data elements to be stored designing a database architecture that relates foreign and primary keys and table structures. Figure 2-2 describes the schema and relationships of the GALTPP database. Appendix A lists the tables in the GALTPP database. Figure 2-2 Illustration of GALTPP database schema A master table (GALTPP_SITE) serves as a container for all three types of sites (LTPP GaCal and special test sites) it includes the basic information of these sites such as site type pavement type and location information (e.g. route number county milepoint and coordinates). A primary key GALTPP_ID uniquely identifies a site in the GALTPP database. 12 For special test sites a separate site information table (SPECIALTEST_SITE) was designed to store the characteristics of the site such as the type of test (e.g. CIR OGI HFST etc.) project number associated research project(s) year of construction etc.The table can be expanded to include additional information identified later. For LTPP and GaCal sites a table (MEPDG_SITE) was designed to store the site information including the type of test (e.g. new design or rehabilitation) sampling factors (e.g. PMA vs. Neat thickness etc.) the date open to traffic etc. A field CONSTRUCTION_NO is used to differentiate the pavement cycle on the same site. A value of 1 typically represents a new construction a value greater than one represents rehabilitation. The combination of GALTPP_ID and CONSTRUCTION_NO is the primary key for uniquely identifying a specific new design or rehabilitation on a site. A set of tables with a MEPDG prefix stores 1) the inputs (including traffic layer structure and layer properties) for predicting the distresses and 2) the measured distresses for validation and calibration. While much of the data is derived from the LTPP database the MEPDG tables were created for easy access and management of the ME Design inputs. First a table (MEPDG_LAYER) was designed to store layer structure modeled in the ME Design. Second a set of tables were designed to store layer properties used in the ME Design. For example the asphalt concrete properties of air void and gradation are stored in different tables in the LTPP database. It would provide the user easy access if all the material properties were stored in limited table (e.g. MEPDG_AC_MATERIAL and MEPDG_UNBOUND_MATERIAL). Third a set of tables were designed to store various traffic inputs used in the ME Design (e.g. MEPDG_TRAFFIC_INPUT MEPDG_TRAFFIC_AXLES MEPDG_TRAFFIC_MAF etc.). In addition the 13 distresses predicted by the ME Design can be a combination of LTPP distresses. Fatigue cracking predicted by the MEPDG includes both fatigue cracking and longitudinal cracking in the wheelpaths defined in the LTPP distress protocol. Therefore a set of tables were designed to store in the observed distresses that were converted from the LTPP distress data or historical COPACES data. A set of tables with a GaCal prefix are included to store field tests conducted on the GaCal sites including dynamic cone penetration tests (GACAL_DCP) cores (GACAL_CORE GACAL_CORE_MEASURE etc.). Additional tables can be added for different tests. Additional tables (e.g. GACAL_FILE GACAL_IMAGE etc.) were designed to store the images documentation and files related to each site. 2.3. Populating GALTPP Database The data of the 33 GaCal sites (21 flexible pavement sites and 12 concrete pavement sites) were acquired from the ARA. The majority of the data are stored in Excel files. Additional efforts were made to go through each file organize and extract the data needed for site and enter the data into the associated tables. For example nine dynamic cone penetration test data were stored on one work sheet with figures for each site. The data were extracted and organized into one table format so the data can be imported into the GALTPP database. The MEPDG inputs for LTPP and GaCal sites used for the initial location calibration by ARA were obtained by manually going through the input values specified in the report (ARA 2016) and the MEPDG files. Traffic layer structures layer properties and distress data were populated in corresponding tables (e.g. MEPDG_LAYER MEPDG_PCC_MATERIAL 14 MEPDG_AC_MATERIAL MEPDG_UNBOUND_MATERIAL MEPDG _TRAFFIC MEPDG_TRAFFIC etc. The special test site data gathered in Phase 2 include cold in-place recycling (CIR) open graded interlayer (OGI) micromilling and thin overlay fog seal crack filling high friction surface treatment (HFST) light aggregate asphalts and soil cement sites. Table 2-2 lists the special test sites. Additional efforts were also made to search the project number and more importantly the special test sites using GeoPI. The project location information was typically available in text format (e.g. SR 27/US 341 FM 4700 SE/CR 266 TO WEST CL/CHAUNCEY) without RCLINK and milepoints for georeferencing the site. For soil cement sites a list of projects with old or sometimes incomplete project numbers was provided. Using available information the research team searched GeoPI for the project number and project location information. Then the project location was determined by manually identifying the intersecting routes on a map. Figure 2-2 shows the GIS map of the special test site locations. The test sites include alternative maintenance and rehabilitation such as micromilling and thin overlay CIR OGI fog seal crack filling HFST and soil cement base. The GIS map and the information above provide important information for GDOT to use when studying the long-term performance of these alternative treatment methods. The long-term performance and life-cycle costs of these treatment methods are critical for GDOT s cost-effective annual maintenance and rehabilitation planning and pavement management. 15 Figure 2-2 Special test site locations 2.4. GALTPP GIS Integration With the geodatabase the GALTPP sites can be easily integrated into GDOT s GIS systems (such GeoPi) and/or GIS software (such as ArcGIS). The integration allows the users to visualize the geographic distribution of candidate sites and to perform spatial query/selection on the sites. The integration into GDOT s GIS systems can also facilitate the communication among different parties and streamline coordination among GDOT s offices. The functions in the GIS systems are described below Case 1 Visualize various data 16 Using GDOT s LRS and the dynamic segmentation function in GIS COPACES and CPACES data were spatially integrated onto a map with other data such as traffic data and soil data. GDOT s engineers can navigate the map to visualize information on the map as shown in Figure 2-2. With their knowledge of Georgia s soil weather and pavement conditions GDOT engineers can effectively identify any issue in the geographic distribution of the GALTPP sites. For example the distribution of the sites in northern and southern Georgia may be a concern for the GALTPP sites because of the significant differences in the geologic conditions. In addition a cluster of sites in certain areas (e.g. in one district) can be identified effectively Case 2 Facilitate the communication among different offices Coordination among GDOT s offices is essential for maintaining the GALTPP sites. For example it is likely some of the sites will be resurfaced in the near future and these activities should be coordinated among the Office of Materials and Testing and the Office of Maintenance. Integrating GALTPP geodatabase into GDOT s GIS systems such as GeoPi can help facilitate the communication among different offices. For example using GeoPi the users can overlay project and GALTPP sites to identify (or flag) any GALTPP sites within a specific project and coordinate the work on the GALTPP sites. The Office of Materials and Testing can check the coming work on the GALTPP sites and conduct data collection in advance. Case 3 Extract information using spatial analysis One of the advantages of GIS is its capability to perform spatial analysis. For example the subgrade soil characterization can be extracted by superimposing the GALTPP sites on the soil maps (e.g. NCHRP 9-23A soil maps) to find the corresponding alphanumeric 17 soil unit code. This function can be extended to extract other information if the data is available. Figure 2-3 An example of roadway images that can be accessed using GIS function 18 3. COLD IN-PLACE RECYCLING (CIR) AND OPEN-GRADED INTERLAYER (OGI) TEST SITES ON SR 16 GDOT has tested two pavement maintenance and rehabilitation methods cold in-place recycling (CIR) and open-graded interlayer (OGI) on State Route 16 in Coweta County Georgia to evaluate the suitability of applying OGI and CIR to Georgia roadways. This chapter presents the data collection processing and management of CIR and OGI test sites on State Route 16. The goal is to document the detailed pavement design construction information tests and pavement condition data in support of the subsequent long-term performance analysis to critically assess and justify the suitability of applying CIR and OGI on Georgia roadways. This chapter first describes the information from the test sites including route location lane and direction. The second section presents the pavement performance prior to CIR and OGI treatment and summarizes the data collected for pre-treatment conditions including field tests such as cores falling weight deflectometer (FWD) and 3D pavement data. Pavement ratings of road segments in which these sites located are also summarized. The third and fourth sections summarize the procedures for the CIR and OGI respectively. The fifth section summarizes the data collected after CIR and OGI treatment. 3.1. Site Information GDOT has tested CIR and OGI on a small section of State Route 16 in Coweta County Georgia. OGI was applied in all travel lanes in this project. CIR on the other hand was only applied to a small portion of this section in the passing and/or left turn lanes. During a field visit with GDOT s engineers five sites were selected for monitoring the performance of CIR and OGI on 19 State Route 16. The five selected sites span a 1.5-mile section on State Route 16 between Milepoints 25 and 26.5 as shown in Figure 3-1. Detailed site information including route direction milepost lane and treatments are summarized in Table 3-1. MP 25 MP 26 Figure 3-1 Test site location Site 1 2 3 4 5 Route SR16 SR16 SR16 SR16 SR16 Table 3-1 Test Site Information Direction WB WB WB WB EB Milepoint 26.5 26.3 26.1 25.6 24.9 Lane Travel Lane Left Turn Lane Passing Lane Center/Left Turn Lane Travel Lane M&R method OGI CIR (Control) CIR (Test) CIR (Test) OGI Pavement designs of this section are shown in Figure 3-3. As shown in the figure this road section was built in the late 1930 s and was later widened in the 1990 s. The asphalt layer thickness ranges from 8 in. to 10 in. 20 Figure 3-2 Illustration of pavement designs of travel lane (left) and passing lane (right) 3.2. Data Collected before CIR and OGI This section presents historical COPACES data and various field test data collected on the sites prior to CIR and OGI treatment. Historical COPACES data were analyzed to evaluate the pavement performance on State Route 16 prior to CIR and OGI treatment. This performance can be used as a reference with which to compare the long-term performance of CIR and OGI applications. In addition field test data including 3D pavement data core and FWD data were documented. 21 3.2.1. Performance base on historical COPACES data Historical COAPCES data were acquired and analyzed to evaluate the performance on this section of pavement. It is noted that there is no COPACES data yet after the completion of CIR and OGI treatment in 2016 a rating of 105 (i.e. under construction) was recorded in 2017 and 2018. A review of historical COPACES data shows this section of pavement was last resurfaced in 2000. The rating dropped below 75 in 2007. It took approximately 7 to 8 years for the project rating to drop from 100 in 2000 to 70 in 2007 or 2008. This provides a performance reference for evaluating the performance after applying CIR and OGI. However this section of pavement was not resurfaced until 2016 when the rating was in the 40s. The treatment has been delayed significantly for almost 8 years (from 2008 to 2016). Thus this section is ideal for assessing the performance of CIR and OGI as severe crack relief and as an effective crack treatment. COPACES Rating 120 100 80 60 40 20 0 1998 2000 2002 2004 2006 2008 2010 Year 2012 2014 2016 2018 2020 Figure 3-3 Historical COPACES data on State Route 16 The extents of load cracking and block cracking are shown in Figure 3-4 and Figure 3-5. Limited load cracking was first reported in 2005 (5 years after resurfacing). Level 2 load cracking had been reported since 2007. Prior to CIR and OGI treatment 80% of load cracking 22 (Levels 1 2 and 3) was reported on the section. Block cracking was first reported in 2005. Extensive block cracking had been reported since 2007. Extensive Level 2 block cracking was reported in 2015 prior to CIR and OGI treatment. Extent (%) Load Cracking 100 80 60 40 20 0 2000 2002 2003 2004 2005 2006 2007 2008 2009 2010 2010 2010 2011 2012 2013 2014 2015 LC3 0003330220001111 LC2 0 0 0 0 0 2 6 25 14 0 0 6 28 33 33 36 LC1 0 0 0 1 2 13 11 4 19 63 63 13 45 46 46 45 Figure 3-4 Load cracking before CIR and OGI treatment Extent (%) Block Cracking 100 80 60 40 20 0 2000 2002 2003 2004 2005 2006 2007 2008 2009 2010 2010 2010 2011 2012 2013 2014 2015 BC2 95 95 70 57 80 79 85 86 BC1 0 0 0 17 19 7 83 83 Figure 3-5 Block cracking before CIR and OGI treatment Pavement conditions of the segments in which the test sites located are depicted in Figure 3-6. All segments selected have extensive pavement cracks including load cracking transverse and block cracking and some reflective cracking. The segment between Milepoints 26 and 27 23 (e.g. Sites 1 and 2) has worse pavement conditions than other selected sites. Severe load cracking and block cracking can be observed in this segment. Similar but better conditions can be observed in the segments between Milepoints 24 and 26 (e.g. Sites 3 4 and 5). COPACES Rating 100 90 80 70 60 50 40 30 20 10 0 2004 2005 2006 2007 2008 2009 Year 2010 2011 2012 2013 2014 Sites 1&2 (MP27-26) Linear (Sites 1&2 (MP27-26)) Sites 3&4 (MP26-25) Linear (Sites 3&4 (MP26-25)) Site 5 (MP24-25) Linear (Site 5 (MP24-25)) Figure 3-6 Segment-level COPACES Ratings on State Route 16 3.2.2. Field Test Data 3D pavement data The 3D laser technology is a line laser system that collects high-resolution 3D range data of pavement surfaces. Using the collected 3D pavement data pavement surface distresses can be closely evaluated. Pavement distresses including rut depth load cracking block cracking and transverse cracking were inspected. Table 3-2 summarizes the results. Table 3-2 Pavement conditions based on 3D pavement data Average Load Cracking Site Rut Depth Severity/Extent (mm) (Level %) Block/Transverse Cracking Severity/Extent Converted COPACES Rating 24 (Level %) 1 40% 1 8.11 2 20% 2 100% 20 3 5% 2 4.79 N/A 1 100% 77 3 5.57 N/A 1 100% 77 4 4.06 N/A 1 100% 77 1 25% 5 4.59 2 15% 1 100% 60 3 5% Falling Weight Deflectometer For each site 5 falling weight deflectometer tests were performed and the results were averaged into layer moduli of the hot-mixed asphalt and the soil base layer. Table 3-3 summarizes the back-calculated modulus. Table 3-3 FWD Back-calculation results Site 1 2 3 4 5 HMA Modulus (ksi) 120 120 150 110 130 Soil Modulus (ksi) 7 19 28 20 12 Cores Table 3-4 summarizes the detailed information of the cores taken at each site including the location in the lane the thickness of the asphalt concrete (AC) layer and how deeply the cracks (if any) propagate downward. Some bottom-up cracks were observed in a few cores and their depths measured from the bottom of the cores are summarized. Detailed pictures of each core are shown in Appendixes B and C. Appendix B lists the 3D pavement surface images on different test sites showing the pavement condition. 25 Appendix C lists the pavement coring pictures showing the subsurface conditions of each test core. Site 1 2 3 4 5 Table 3-4 Core information on State Route 16 Core A3 A4 C2 C4 C5 C6 C7 C8 4-1 4-2 5-1 6-1 6-2 R1 R2 R3 R5 R6 N/A Core Location Lane Center Right Wheelpath Lane Center Right Wheelpath Lane Center Left Wheelpath Lane Center Lane Center Left Wheelpath Lane Center Lane Center Left Wheelpath Lane Center Left Wheelpath Right Wheelpath Left Wheelpath Left Wheelpath Lane Center AC Thickness 9.5" 7.75" 9" 9.5" 10.5" 10" 10" 10.5" 11" 11" 11" 10" 9.75" 10.5" 12.5" 10.5" 10.5" 10.5" Top-Down Crack Depth 3" 7.75" 9" N/A 3.5" 10" N/A N/A 11" N/A 3.5" N/A 5.5" 4.5" N/A N/A N/A 3.5" Bottom-Up Crack Depth N/A N/A N/A 5.5" N/A N/A N/A N/A N/A N/A N/A 4.75" N/A N/A N/A N/A 6.5" 3.5" 3.3. Cold In-Place Recycling (CIR) Cold in-place recycling is a pavement M&R technique in which the existing pavement material is recycled and mixed with chemical additives without heating. The CIR process is done in-place by a train of equipment. The complete CIR process carried out on State Route 16 is summarized below. Milling A milling machine removes a 1.5-in surface layer of pavement as shown in Figure 3-8. The thin layer removed is disposed of because the CIR process typically causes a bulking effect of the material and the removal of this layer would ensure an even surface after CIR process is finished. 26 Figure 3-7 Removal of a Thin Layer of Pavement Applying lime A dumper towed by a tractor applies a layer of hydrated lime to the milled surface as shown in Figure 3-8. This lime is incorporated into the final pavement as an anti-stripping agent. Figure 3-8 Application of Lime on the Milled Surface Incorporating additive A miller then mills a 3-in layer of pavement and mixes the pulverized pavement and lime with emulsified asphalt as shown in Figure 3-10. 27 Figure 3-9 Mixture of Pavement and Additives Mixture placement The mixture is then discharged into a paver that puts the material back into the 3-in deep milled trench as shown in Figure 3-11. Figure 3-10 Compaction of Recycled Material Compaction A rubber-tire roller and a vibratory steel-wheel roller compacts the recycled material into the desired density as shown in Figure 3-12. 28 Figure 3-11 Compaction of Recycled Material Overlay The entire road will be covered with a 1.5-in layer of polymer modified Superpave asphalt after 3 days of curing. 3.4. Open-Graded Interlayer (OGI) Using an open-graded interlayer (OGI) is a pavement maintenance and rehabilitation technique that involves the application of an interlayer with open graded material to minimize the transfer of stresses in the surface layer. Also known as a crack reliever layer OGI mitigates reflective cracking from the underlying layers and thermal cracking. The complete OGI process carried out on SR 16 is summarized below. Milling and cleaning A milling machine removes a 1.5-in surface layer of pavement and a sweeper and an excavator removes the milled material as shown in Figure 3-13. Figure 3-12 Removal of the Existing Pavement Surface 29 Applying asphalt binder Asphalt is applied onto the milled surface as shown in Figure 3-14. Figure 3-13 Application of Asphalt Applying the open graded interlayer A thin layer of open-graded material usually under 1 in is applied to the pavement as shown in Figure 3-15. After the installation of the interlayer the section can be opened to traffic. Figure 3-15 Application of 1" OGI 30 Overlay A final 1.5-in hot-mixed asphalt will be placed on top of the interlayer to complete the OGI process. 3.5. Data Collected after CIR and OGI Cores and international roughness index (IRI) data were collected in March 2018 two years after the CIR and OGI treatments to assess the condition of the treated pavements. A visual field inspection shows no distresses on either CIR or OGI sites. IRI data were collected on three lanes (east-bound travel lane west-bound travel lane and passing lane) between Milepost 25 and 27. Both east- and west-bound lanes were constructed with OGI and CIR was used in the passing lane which starts at Milepoint 25.8. Figure 3-16 shows the half-car simulation (HCS) IRIs on three lanes at every 0.02 mile. The majority of the IRIs are between 800 mm/km and 1200 mm/km with some outliers. There are no significant differences observed between CIR (passing lane) and OGI (east- and west-bound travel lanes). The section between Milepoints 25.2 and 25.4 has relatively higher HCS IRI (1000 mm/km and 2000 mm/km) in both directions. The can be further investigated. Figure 3-15 Historical COPACES Data Before and After CIR and OGI Application In addition cores were taken on both CIR and OGI sites for Hamburg Wheel Tracking Device (HWTD) testing. HWTD measures the combined effects of rutting and moisture damage by rolling a steel wheel across the surface of an asphalt concrete specimen that is immersed in hot water. HWTD testing was conducted on the surface layer of cores taken from both CIR and OGI 31 sites and on the second layer of CIR sites. Results show the surface layer of both CIR and OGI pass the rut depth testing with an average rut depth of 3 mm and 5 mm at 20 000 cycles. The CIR layer did not pass the rut depth testing it failed at 15 mm at 8 000 cycles. It is recommended that the rutting on these two test sites be closely monitored. 3.6. Summary GDOT has tested CIR and OGI on State Route 16 to critically evaluate the suitability of applying CIR and OGI to Georgia roadways based on its long-term performance. This chapter documented and analyzed the following to support subsequent long-term performance analysis on CIR and OGI sites 1) Documented site information and pavement design on SR 16 pre-treatment conditions including field tests and data collected such as cores FWD 3D pavement data and the CIR and OGI procedures applied. 2) Analyzed long-term pavement performance prior to CIR and OGI applications using historical COPACES data. It shows that this project has 7 to 8 years of life before dropping from a rating of 100 to a rating of 70. This performance can be used as a reference with which to compare the long-term performance of CIR and OGI applications. With the unit cost the life cycle cost analysis of the new treatment methods can be critically evaluated in the future. It should be noted that the treatment of this project has been delayed significantly (approximately 8 years from 2008 to 2016). This should be taken into account when comparing the roadway s performance. In addition significant cracking occurred due to delayed treatment. This project is ideal for assessing the performance of OGI and CIR for severe crack relief and an effective crack treatment. 32 3) It is recommended that the progress of pavement distresses be monitored to support longterm performance evaluation even though the preliminary performance shows that the project rating is 100 and there are no pavement distresses one year after the application of CIR and OGI. 33 4. ANALYSIS OF SOIL CEMENT PAVEMENT PERFORMANCE This chapter analyzes the pavement performance on the soil cement sites. First the soil cement pavement sites are presented. The observed soil cement pavement performance is then analyzed using historical COPACES data. The predicted pavement performance is obtained using the ME Design software. The observed and predicted pavement performances are then compared and then discussed. 4.1. Soil Cement Sites A total of 38 sites were used for calibrating Georgia s transfer coefficients for flexible pavements among them there are six soil cement sites including four LTPP sites (4092 4093 4096 and 4220) and two GaCal sites (on State Routes 1 and 38). Figure 4-1 shows these six sites located in southwestern Georgia including three sites on State Route 300 and one site each on State Routes 1 25 38 and 67C. In addition sixteen soil cement sites were identified and incorporated into the GALPP program as special test sites. These sixteen sites are located on State Routes 4 17 21 27 29 67 and 121 in southern Georgia. Table 4-1 lists the locations and the pavement designs of the six soil cement sites which were used in the initial calibration of the MEPDG. Four sites were built in the 1980s and two sites were built in the 1990s. They were built with 6-8 inches of soil cement base and 4-13 inches of dense-graded hot mix asphalt (HMA) on top of it. 34 Figure 4-1 Selected Soil Cement Pavement Sites Route County Table 4-1 Locations of Selected Sites and Pavement Designs SR 300 Thomas SR 300 Thomas SR 67C Early SR 25/ US 17 Bryan SR 1 Decatur Construction Year Pavement Design 1986 1.2 in HMA 4.5 in HMA 8.3 in soil cement Subgrade 1986 1.2 in HMA 4.6 in HMA 7.8 in soil cement Subgrade 1985 1.3 in HMA 2.8 in HMA 6.3 in soil cement Subgrade 1984 1.7 in HMA 2.9 in HMA 7.9 in soil cement Subgrade 1991 5.5 in HMA 6.0 in soil cement Subgrade SR 38 Thomas & Brooks 1994 5.5 in HMA 7.5 in HMA 5.5 in soil cement Subgrade 35 4.2. Observed Pavement Performance using Historical COPACES Data This section presents the observed distresses on the soil cement sites based on the historical COPACES data. First the distresses on multiple projects with soil cement bases were presented to provide overall performance. Second distresses on selected sites were discussed. Figure 4-2 shows the pavement rating load cracking and block cracking on four projects on State Routes 1 25 38 and 300 with soil cement bases. In general it took approximately 15 years to reach a rating of 70 as shown in Figure 4-2 (a) and the predominate distresses were load cracking and block cracking. Level 1 load cracking was typically reported in 2-3 years and the extent increased slowly each year. Load cracking extent increased at a fast pace (approximately 7%) after 12-13 years and a 50% of load cracking was reported at 20 years as shown in Figure 4-2 (b). A review of the data shows Level 2 load cracking was reported on most of the segments within each project but there were very few segments with load cracking at Levels 3 or 4. Block cracking was observed on all the projects typically after 2-3 years. The extent increased more rapidly after 10 years at a rate of 8% per year as shown in Figure 4-2 (c). Level 1 block cracking was mostly reported within the first 10 years 40% of the segments exhibited Level 2 block cracking after 10 years. According to the historical COPACES data rutting was not reported as an issue all projects had less than 3/8 in of rut depth after 10 years. 36 (a) Project rating (b) Load cracking (c) Block cracking Figure 4-2 COPACES rating and distresses on selected soil cement projects 37 It is noted that the COPACES and LTPP distress protocols are different in terms of distress definition severity and extent. COPACES defines load cracking as the type of cracking that is caused by repeated heavy loads and always occurring in the wheelpaths. Load cracking has four severity levels ranging from single longitudinal cracking (Level 1) to alligator cracking (Level 4). Load cracking is recorded as the percent of the length of two wheelpaths (200 ft). The LTPP records longitudinal cracking in wheelpaths (in length) and fatigue cracking (in percent of total area) separately. A function as depicted in Figure 4-3 was developed by ARA (Harold et al. 2016) to convert COPACES loading cracking into the fatigue cracking predicted in the MEPDG model. Using the conversion function 40% and 80% of load cracking are approximately 6.5% and 14% of fatigue cracking respectively. It is noted that the conversion function was developed based on limited data collected in 2014. Similarly there are differences in block/transverse cracking. COPACES identifies block and transverse cracking as the type of crack that is caused by weathering of the pavement or shrinkage of cement-treated base materials (not load related). Three levels of block and transverse cracking (ranging from a single transverse crack to polygon-patterned block cracking) are defined but only the predominant severity level is recorded. Block cracking is recorded as a percentage of total area. The LTPP defines block and transverse cracking separately and records the number and length of transverse cracks. Similarly a conversion function was developed to match the block cracking reported in COPACES into transverse cracking in the LTPP. Note that the variation is larger than the load cracking conversion. 38 Figure 4-3 Relationship between load cracking from GDOT COPACES and alligator cracking from LTPP (Harold et al. 2016) The observed fatigue cracking thermal cracking and rutting on the six soil cement sites are presented in Figures 4-4 4-5 and 4-6. Figure 4-4 shows the observed fatigue cracking on all of the six soil cement sites. It is noted the last measurements on these projects were at age 8 13 19 19 and 22 years. According to previous research (Tsai and Wu 2016) most of the pavements in Georgia are resurfaced approximately every 11.6 years. This resurfacing would remove distresses (e.g. cracking and rutting) on the surface layer which makes it difficult to accumulate cracking data. However these six soil cement sites have lives longer than the typical resurfacing life of 11.6 years. There were either no fatigue cracks or just little fatigue cracks recorded until the 15-year point. This means these sites had not been resurfaced in more than 15 years which is much longer than GDOT s average resurfacing years (Tsai and Wu 2016). Only one site (4420) recorded 9% and 21% fatigue cracking after 7 or 8 years. 39 Observed Fatigue Cracking percent total lane area 25 20 15 10 5 0 0 Fatigue Cracking 5 10 15 20 25 Age (year) Figure 4-4 Observed fatigue cracking Figure 4-5 shows the observed thermal cracking. There is dispersion in the thermal cracking with a range of 0 to 7 000 ft per mile among the 5 sites. It is noted that four sites did not exhibit thermal cracking in the first five years. In general the thermal cracking shows an increasing trend after approximately 9-10 years thermal cracking increased significantly. Again some sites show a minimum of thermal cracking after more than 15 years of service. Sites on State Routes 1 and 38 had the most thermal cracking. 40 Figure 4-5 Observed longitudinal cracking (non-wheel path) Figure 4-6 shows the observed rutting. Most of the observed rutting was between 0.05 in and 0.25 in. Four sites had rutting less than 0.25 in even after 10 years only one site (4420) exhibited rutting greater than 0.25 in. after 5 years. Figure 4-6 Observed rutting 4.3. Predicted Pavement Performance using MEPDG Based on findings of a technical audit by AASHTO and due to the fact that the existing semirigid model in AASHTOWare Pavement ME version 2.3.1 is not globally calibrated or locally calibrated for Georgia s pavements the semi-rigid model is not recommended for implementation in GDOT s plan. More importantly GDOT has set a minimal compressive strength of 300 psi which is lower than most semi-rigid pavements. It was recommended that soil cement be modeled as flexible pavements with chemically stabilized layers as base/subgrade materials that have higher resilient modulus value. Thus the soil cement sites were modeled as flexible pavements with locally calibrated coefficients and the performances were predicted. 41 This section presents the pavement performance predicted by using MEPDG. First Table 4-2 lists Georgia s asphalt pavement calibration coefficients. Table 4-2 Georgia s asphalt pavement calibration coefficients (Harold et al. 2016) Transfer Function Coefficient K1 AC Rutting K2 K3 Coarse-Grained Subgrade Rutting Bs1 Fine-Grained Bs1 AC Fatigue Cracking K1 K2 K3 C1 Bottom-up Cracking C2 C3 C1 Top-down Cracking C2 C3 Thermal Cracking Bt1 Bt3 1. Unmodified HMA mixtures 2. Polymer Modified Asphalt mixtures 3. Use global values Global Value -3.35412 1.5606 0.4791 1.0 1.0 0.007566 3.9492 1.281 1.0 1.0 6 000 7 3.5 0 1.5 1.5 GDOT Value Neat1 PMA2 Mixtures Mixtures -2.45 -2.55 1.56063 1.56063 0.30 0.30 0.50 0.30 0.000653 0.00151 3.94923 1.2813 2.2 2.2 6 0003 73 3.53 03 35 45 35 45 The predicted pavement distresses of soil cement pavements are presented in Figure 4-7. Figure 4-7 (a) shows limited (less than 5%) fatigue cracking are predicted on the soil cement sites. Only one site is predicted with more fatigue cracking at an age of 7 years. 42 Predicted Fatigue Cracking (% of total lane area) Predicted Thermal Cracking ft./mi. 25 20 15 10 5 0 0 5 10 15 20 25 Age (year) (a) Predicted fatigue cracking 3000 2500 2000 1500 1000 500 0 0 5 10 15 20 25 Age (year) (b) Predicted thermal cracking 0.5 0.4 0.3 0.2 0.1 0.0 0 5 10 15 20 25 Age (year) (c) Predicted rutting Figure 4-7 Predicted distresses by the ME Design (v2.3.1) Predicted Rut Depth inches 43 The same pavement structure was analyzed using the ME Design software with Georgia s coefficients (ARA 2015a). Results on all five sites are similar. Figure 4-8 shows the results on the site on State Route 38. This pavement structure meets the performance criteria except for thermal cracking. The predicted distresses including fatigue cracking rutting and IRI at the specified reliability were lower than the threshold values at the end of the 20-year design life because partly of its accumulated use by 16 million heavy trucks. It is noted that a 95% reliability is used for fatigue cracking and rutting as suggested in GDOT s user guide. When 50% reliability was used the predicted distresses were much lower (0.25 in of rutting 0.62% of fatigue cracking). When the reliability increased from 50% to 95% the predicted fatigue cracking significantly increased from 0.62% to 8.61%. This means the selection of reliability level has a big impact on the distress threshold values which determines whether or not the pavement structure design passes the criteria. At 95% reliability the MEPDG predicted pavement would have fatigue cracking of 8.61% rutting of 0.35 in and thermal cracking of 802 ft per mile at the end of 20 years. The pavement structure can last longer than 20 years and can reach the performance criteria in 21 years with 16 million heavy trucks. 44 Figure 4-8 Pavement structure analysis using the ME Design (v2.3.1) 4.4. Comparison of Observed and Predicted Pavement Performance This section compares the predicted and observed pavement performance (e.g. distresses) on the selected sites to verify the accuracy of the prediction models. Figure 4-9 shows the observed and predicted (at 50% reliability) fatigue cracking based on the data used in the calibration (Harold et al. 2016). There is no significant bias (under or overprediction) and the predicted fatigue cracking is reasonable with the data scattered around the equality line (R2 0.92). It is noted that most of the predicted and observed fatigue cracking was less than 6% after 20 years which meets the performance criteria of 10%. The only site with more fatigue cracking is Site 4420. 45 Figure 4-9 Observed vs. Predicted fatigue cracking (percent of total area) Figure 4-10 shows the predicted and observed thermal cracking. The points are not close to the equality line and the R2 is about 0.41 which indicates a poor fitness between the predicted and observed values. It is noted the thermal cracking is overpredicted when the observed values are less than 1500 ft per mile and underpredicted when greater than 1500 ft per mile. The predicted values do not exceed 1500 ft per mile given the traffic volume. It is noted there was a gap between the observed and predicted cracking for sites on State Routes 1 and 30. While more than 5000 ft per mile of thermal cracking was observed the MEPDG file output was only 1500 ft per mile. The MEPDG inputs should be further checked for future recalibration. 46 Figure 4-10 Predicted vs. Observed transverse crack (ft per mile) Figure 4-11 shows the predicted and observed rutting. Most of the sites have less than 0.25 in of rutting only one site exhibited more than 0.25 in of rutting. This site had higher truck traffic and thinner pavement design. Figure 4-12 shows the IRI were overpredicted (approximately 80% higher). The observed values were 40-60 ft per mile while the predicted values are about 80-100 ft per mile. Predicted Rut Depth inches 0.5 0.4 0.3 0.2 0.1 0.0 0 0.1 0.2 0.3 0.4 0.5 Observed Rut Depth inches Figure 4-11 Predicted vs. Observed rut depth (in.) 47 Figure 4-12 Predicted vs. Observed IRI (ft/mile) In summary with the locally calibrated coefficients the MEPDG reasonably predicts fatigue cracking for soil cement pavement sites. Six percent (or lower) fatigue cracking is predicted at the end of a 20-year design life. However the predicted thermal cracking does not fit the observation in the field. In the majority of the cases the thermal cracking was either overpredicted or underpredicted by more than 30%. With the local coefficients the MEPDG predicts approximately 1500 ft per mile of thermal cracking at the end of a 20-year design life. However on some sites (State Routes 1 and 38) more than 5000 ft per mile of thermal cracking was observed. The predicted rut depth was in general reasonable (within 20% of the observed values). It is noted that GDOT measures rut depth in 1/8 in units which is different from the continuous values predicted by the MEPDG. A rut depth of 0.125 in and 0.25 in is predicted after 8 and 15 years. The IRI was overpredicted at approximately 80% and needs to be further calibrated to achieve a reasonable prediction. 48 4.5. Summary The following conclusions were made based on the preliminary analysis of the six selected soil cement sites and the use of the recommended local calibration coefficients Bias has been found in all distresses (transverse cracking rutting and IRI) except fatigue cracking. The ME Design predicts little or no fatigue cracking for these soil cement sites. The results show fair correlation between the predicted and measured fatigue cracking (R2 0.92). The ME Design mostly overpredicts transverse cracking when the observed cracking is less than 1500 ft per mile and underpredicts it when the observed cracking is greater than 1500 ft per mile. The latter case is because the MEPDG predicts the maximum transverse cracking at about 1500 ft per mile. The ME Design predicted little rutting on these soil cement sites. Poor correlation (R2 0.1) was found between the predicted and measured rut depth. The ME Design overpredicted the measured IRI. The initial IRI was about 50 in per mile and on average IRI was overpredicted by 70%. Poor correlation (2 0.07) was found between the predicted and measured IRI. The following recommendations are made There are two changes in the flexible pavement design in the new release of Pavement ME Version 2.5. Instead of a constant value C2 in fatigue cracking is now dependent on the AC thickness. The lab test coefficients (B) are used in the model instead of using 1. With these significant changes and the expected calibration tool it is recommended that 49 GDOT verify the performance using the global coefficients included in of Pavement ME Version 2. Pavement ME Version 2.5 includes the global coefficients for semi-rigid pavement which was for the first time globally calibrated. Although it is noted that a large portion of semi-rigid data used for the global calibration were from Virginia it is recommended that the accuracy of the predicted distresses using global coefficients be verified by comparing the predicted distresses with the distresses observed in the field. Because the change to GDOT s pavement data collection approach full-coverage 3D pavement data will be available on state routes. The variability and representativeness of the distresses on the test sites can be evaluated using 3D pavement data. Additional test sections can be included to further verify and calibrate the predicted distresses using the Pavement ME. 50 5. CONCLUSIONS AND RECOMMENDATIONS The Georgia Department of Transportation (GDOT) is evaluating the use of the MEPDG for designing its new and rehabilitated pavement structures. GDOT wants to have a central database and a GIS project to document the information from the special test sites in Georgia to support subsequent long-term performance analysis and life-cycle cost analysis. GDOT will use the information to critically assess and justify the suitability of applying different pavement maintenance and rehabilitation methods to support cost-effective annual maintenance and rehabilitation (M&R) planning and prioritization operations. The objectives of Phase 2 are 1) to expand the GALTPP database with concrete pavement sites used in the local calibration of the MEPDG 2) to identify and manage special test sites of GDOT s interest 3) to document and analyze the data collected from the cold in-place recycling (CIR) and open-graded interlayer (OGI) test sites on State Route 16 and 4) to conduct the soil cement pavement performance analysis by comparing the observed pavement performance (acquired from historical COPACES data) and the predicted pavement performance (analyzed using the MEPDG). Below are the findings from Phase 2 1) The GALTPP database tables and fields for concrete pavement sites were designed to store and manage the data collected by ARA at GACal for the initial MEPDG local calibration (Harold et al. 2016). A GIS project was used with the GALTPP database for visualizing the sites. They are summarized below a. A relational GALTPP database with location reference information was designed to host the LTPP GaCal and special test sites and store the data related to these different sites. Tables fields and relationships among tables (i.e. primary keys 51 and foreign keys) were designed to store and manage the input parameters used in the MEPDG calibration and testing data collected at GaCal sites for easy query and data integrity. b. Twenty-three concrete pavement sites including LTPP and GaCal sites used for previous MEPDG local calibration were stored in the GALTPP database. The MEPDG inputs as well as the measured distresses can be easily accessed in support of future validation and calibration of the MEPDG. c. A GALTPP geodatabase containing the three types of sites was developed it can be integrated into GDOT s GIS systems. 2) Special test sites with different materials and treatment methods including soil cement base cold in-place recycling (CIR) open-graded interlayer (OGI) micromilling and thin overlay fog seal crack filling high friction surface treatment (HFST) and light weight aggregates (alternative treatment of HFST with bauxite and resin) were identified and entered into the GALTPP database. In addition beyond the scope of this project the spatial location information of these additional efforts were made to identify and locate special these sites by searching the GeoPi for project numbers and locating projects. Eighty-seven special test sites were georeferenced and entered into the GALTPP database. 3) Field test data including prior CIR and OGI pavement surface condition data FDW data coring data etc. from the CIR and OGI test sites on State Route 16 were acquired documented and entered into GALTPP. The 3D pavement surface data before CIR and OGI application were collected and the detailed distresses were analyzed to provide a pavement condition reference to support subsequent analysis for treatment timing. 52 Historical COPACES data was analyzed to reveal the long-term pavement performance prior to CIR and OGI application. It shows a pavement has 7 to 8 years of life between a rating of 100 to a rating of 70. This performance can be used as a reference with which to compare the long-term performance of CIR and OGI applications. With the unit cost the life cycle cost analysis or the new treatment methods can be critically evaluated in the future. 4) The soil cement pavement performance analysis was conducted by comparing the observed pavement performance (acquired from historical COPACES data) and the predicted pavement performance analyzed using the ME Design software. Conclusions are as follows a. Bias has been found in all distresses (transverse cracking rutting and IRI) except fatigue cracking. b. The ME Design predicts little or no fatigue cracking for these soil cement sites. The results show fair correlation between the predicted and measured fatigue cracking (R2 0.92). c. The ME Design mostly overpredicts transverse cracking when the observed cracking is less than 1500 ft per mile and underpredicts when the observed cracking is greater than 1500 ft per mile. The latter case occurs because the ME Design predicts the maximum transverse cracking at about 1500 ft per mile. d. The ME Design predicted little rutting on these soil cement sites. Poor correlation (R2 0.1) was found between the predicted and measured rut depths. 53 e. The ME Design overpredicted the IRI. The initial IRI was about 50 in per mile and on average IRI was overpredicted by 70%. Poor correlation (2 0.07) was found between the predicted and measured IRI. The following recommendations are made 1) The GALTPP geodatabase can be integrated into GDOT s existing GIS systems such as GeoPi for disseminating the information and better coordinating the work on the GALTPP sites. 2) Pavement distresses on CIR and OGI test sites should continue to be monitored even though the preliminary performance shows that the project rating is 100 and there are no pavement distresses one year after the application of CIR and OGI. 3) There are two changes in the flexible pavement design in the new release of AASHTOWare Pavement ME Design version 2.5. Instead of a constant value C2 in fatigue cracking is now dependent on the asphalt concrete thickness. The lab test coefficients (B) are used in the model instead of using 1. With these significant changes and the expected calibration tool it is recommended that GDOT verify the performance using the global coefficients included in Pavement ME Version 2.5. 4) The new ME Design (version 2.5) includes the global coefficients for semi-rigid pavement which were for the first time globally calibrated. Although a large portion of semi-rigid data used for the global calibration were from Virginia the accuracy of the predicted distresses should be verified by comparing the predicted distresses with the distresses observed in the field. 54 5) Because the change to GDOT s pavement data collection approach full-coverage 3D pavement data will be available on state routes. The variability and representativeness of the distresses on the test sites can be evaluated using 3D pavement data. Additional test sites (covering common design features used in Georgia) should be included to further verify and calibrate the predicted distresses using the MEPDG. 55 REFERENCES (1) AASHTO. 2010. Guide for the Local Calibration of the Mechanistic-Empirical Pavement Design Guide. American Association of State Highway and Transportation Officials (AASHTO) Washington DC. (2) AASHTO Pavement ME DesignTM (access http //www.medesign.com/MEDesign/ Index.html). (3) FHWA (Federal Highway Administration). 2003. Distress Identification Manual for Long Term Pavement Performance Program Fourth Revised Edition Publication Number FHWA-RD-03-031 Federal Highway Administration Washington DC. (4) Harold V. Darter N. Bhattacharya B. and Titus-Glover L. 2016. Implementation and Calibration of the Mechanistic-Empirical Pavement Design Guide in Georgia. FHWAGA-14 -11-17 Georgia Department of Transportation Atlanta GA. (5) NCHRP. 2004. Guide for Mechanistic-Empirical Design of New and Rehabilitated Structures. NCHRP Report 01-37A National Cooperative Highway Research Program Transportation Research Board Washington DC 2004. (6) Tsai Y. and Wu Y. 2016. Study of Georgia s Pavement Deterioration /Life and Potential Risks of Delayed Pavement Resurfacing and Rehabilitation. FHWA-GA-16-1405. Georgia Department of Transportation Atlanta GA. (7) Tsai Y. and Wu Y. 2015. Georgia Long-Term Pavement Performance (GALTPP) Program Maintaining Georgia s Calibration Sites and Identifying The Potential for Using MEPDG for Characterization Of Non-Standard Materials and Methods (Phase 1). Georgia Department of Transportation Atlanta GA. 56 APPENDIX A GALTPP DATABASE TABLES GALTPP_SITE Field Name GALTPP_ID Units Field Type CHARACTER Description An identification number SITE_TYPE CHARACTER Site type (LTPP GaCal or special test site PAVEMENT_TYPE CHARACTER(6) Pavement type COUNTY ROUTENO ROUTE_SUFFIX Milepoint_FROM Milepoint_TO CHARACTER(3) CHARACTER(4) CHARACTER(2) NUMBER NUMBER County in which the test section is located. The route number for the route that the section is located on. The route suffix for the route that the section is located on. Beginning mile point Ending mile point Milepost_FROM NUMBER Beginning mile post for interstate highways Milepost_TO DIRECTION_OF_TRAVEL LANE_NUMBER NUMBER CHARACTER(1) NUMBER(1 0) Ending mile post for interstate highways E for East W for West N for North S for South base on the direction of travel within the lane for which data is being collected. The number of the lane on which data is being collected. 1 is the outside lane. The others are numbered consecutively as you move to the inside edge of the pavement. FUNCTIONAL_CLASS CHARACTER Functional class of roadway on which section is located. TOT_LANES DIVIDED LATITUDE NUMBER(1 0) CHARACTER(1) Degrees NUMBER(5 3) Total number of lanes in one direction. Y or N indicating that the roadway does or does not have a median. Latitude of the test section in degrees. LONGITUDE ELEVATION Degrees NUMBER(5 3) Ft NUMBER(4 0) Longitude of the test section in degrees. Estimate of the elevation of the test section relative to sea level. RCLINK CHARACTER(10) LOCATION_INFO CHARACTER(100) Description of the location of the test section. A-1 SPECIALTEST_SITE Field Name GALTPP_ID PAVEMENT_TYPE TEST_TYPE PI_NO RES_PROJ CONSTRUCTION_YEAR SITE_DESC Units Field Type CHARACTER CHARACTER(6) CHARACTER CHARACTER CHARACTER NUMBER(4 0) CHARACTER Description An identification number Pavement type Test site type (e.g. CIR OGI HFST etc.) PI number if available Research project if available Year of the testing material or treatment being applied Description of the test site MEPDG_SITE Field Name GALTPP_ID CONSTRUCTION_ID PAVEMENT_TYPE TEST_TYPE ROUTE_SUFFIX LANE_WIDTH SHOULDER_TYPE SHOULDER_WIDTH DIVIDED DATE_EARTHWORK DATE_HMA_PLACED TRAFFIC_OPEN_DATE Units ft ft Field Type CHARACTER CHARACTER CHARACTER(6) CHARACTER(4) CHARACTER(2) NUMBER(2 0) CHARACTER(7) NUMBER(2 0) CHARACTER(1) DATE DATE DATE Description Test section identification number (one for each site). Construction event in sequence Pavement type New design or rehab The route suffix for the route that the section is located on. Width of the lane the test section occupies. Indication of whether the shoulder is "paved " "unpaved " or "none." The width of the shoulder in feet. Y or N indicating that the roadway does or does not have a median. Date the earthwork was completed in the construction of the project. Date the hot-mix asphalt was placed in the construction of the project. Date the test section was opened to traffic. A-2 GACAL_AC_ BULKSPECIFICGRAVITY Field Name GALTPP_ID Units Field Type CHARACTER Description Test section identification number. Core_ID CHARACTER Core ID. Date Date Date of coring. Bulk Gmm Gmm_Bulk Air_void GACAL_AC_DISTRESS Field Name GALTPP_ID SOURCE CONSTRUCTION_NO SURVEY_DATE GATOR_CRACK_A_L GATOR_CRACK_A_M GATOR_CRACK_A_H BLK_CRACK_A_L BLK_CRACK_A_M BLK_CRACK_A_H EDGE_CRACK_L_L EDGE_CRACK_L_M EDGE_CRACK_L_H Units ft2 ft2 ft2 ft2 ft2 ft2 ft ft ft Field Type Description CHARACTER Test section identification number. CHARACTER Source of the distress data (COPACES LTPP) 1 stands for new construction 2 stands for CHARACTER rehabilitation DATE (mm/dd/yyyyh h mi s) Date of distress survey. NUMBER(5 1) Area of alligator (fatigue) cracking of low severity NUMBER(5 1) Area of alligator (fatigue) cracking of moderate severity may be evident). NUMBER(5 1) Area of alligator (fatigue) cracking of high severity may be evident). NUMBER(5 1) Area of block cracking of low severity NUMBER(5 1) Area of block cracking of moderate severity Area of high severity block cracking (mean crack NUMBER(5 1) width greater than 19 mm or under 19 mm with moderate to high severity random cracking). NUMBER(4 1) Length of low severity edge cracking (cracks without break up or loss of material). Length of moderate severity edge cracking (cracks NUMBER(4 1) with some break up and loss of material for up to 10 percent of the affected length). Length of high severity edge cracking (considerable NUMBER(4 1) break up and loss of material for more than 10 percent of the affected length). A-3 Field Name LONG_CRACK_WP_L_L LONG_CRACK_WP_L_M LONG_CRACK_WP_L_H LONG_CRACK_WP_SEAL_L_L LONG_CRACK_WP_SEAL_L_M LONG_CRACK_WP_SEAL_L_H LONG_CRACK_NWP_L_L LONG_CRACK_NWP_L_M LONG_CRACK_NWP_L_H LONG_CRACK_NWP_SEAL_L_ L LONG_CRACK_NWP_SEAL_L_ M LONG_CRACK_NWP_SEAL_L_ H Units ft ft ft ft ft ft ft ft ft ft ft ft Field Type Description Length of low severity longitudinal cracking in NUMBER(4 1) wheel path (cracks of unknown width well sealed or with mean width of 6 mm or less). NUMBER(4 1) Length of moderate severity longitudinal cracking in wheel path (mean crack width from 6 to 19 mm or under 19 mm with adjacent low severity random cracking). NUMBER(4 1) Length of high severity longitudinal cracking in wheel path (mean crack width greater than 19 mm or under 19 mm with adjacent moderate to high severity random cracking). Length of low severity well-sealed longitudinal NUMBER(4 1) cracking in wheel path (cracks of unknown width or with mean width of 6 mm or less). NUMBER(4 1) Length of moderate severity well-sealed longitudinal cracking in wheel path (mean crack width from 6 to 19 mm or under 19 mm with adjacent low severity random cracking). NUMBER(4 1) Length of high severity well-sealed longitudinal cracking in wheel path (crack mean width greater than 19 mm or under 19 mm with adjacent moderate to high severity random cracking). Length of low severity non-wheel path longitudinal NUMBER(4 1) cracking (cracks of unknown width well sealed or with mean width of 6 mm or less). NUMBER(4 1) Length of moderate severity non-wheel path longitudinal cracking (mean crack width from 6 to 19 mm or under 19 mm with adjacent low severity random cracking). NUMBER(4 1) Length of high severity non-wheel path longitudinal cracking (mean crack width greater than 19 mm or fewer than 19 mm with adjacent moderate to high severity random cracking). Length of low severity well-sealed non-wheel path NUMBER(4 1) longitudinal cracking (cracks of unknown width or with mean width of 6 mm or less). NUMBER(4 1) Length of moderate severity well-sealed non- wheel path longitudinal cracking (mean crack width from 6 to 19 mm or under 19 mm with adjacent low severity random cracking). NUMBER(4 1) Length of high severity well-sealed non-wheel path longitudinal cracking (mean crack width greater than 19 mm or fewer than 19 mm with adjacent moderate to high severity random cracking). A-4 Field Name REFL_CRACK_TRANS_NO_L REFL_CRACK_TRANS_NO_M REFL_CRACK_TRANS_NO_H REFL_CRACK_TRANS_L_L REFL_CRACK_TRANS_L_M REFL_CRACK_TRANS_L_H REFL_CRACK_TRANS_SEAL_L_L REFL_CRACK_TRANS_SEAL_L_M REFL_CRACK_TRANS_SEAL_L_H REFL_CRACK_LONG_L_L REFL_CRACK_LONG_L_M REFL_CRACK_LONG_L_H Units ft ft ft ft ft ft ft ft ft Field Type Description Number of low severity transverse reflection cracks NUMBER(3 0) (cracks of unknown width well sealed or with mean width of 6 mm or less). Number of moderate severity transverse reflection NUMBER(3 0) cracks (mean crack width of 6 to 19 mm or under 19 mm with adjacent low severity random cracking). NUMBER(3 0) Number of high severity transverse reflection cracks (mean crack width greater than 19 mm or under 19 mm with adjacent moderate to high severity random cracking). Length of low severity transverse reflection cracking NUMBER(5 1) at joints (cracks of unknown width well sealed or with mean width of 6 mm or less). NUMBER(5 1) Length of moderate severity transverse reflection cracking at joints (mean crack width of 6 to 19 mm or under 19 mm with adjacent low severity random cracking). NUMBER(5 1) Length of high severity transverse reflection cracking at joints (mean crack width greater than 19 mm or fewer than 19 mm with adjacent moderate to high severity random cracking). Length of well-sealed low severity transverse NUMBER(5 1) cracking (cracks of unknown width or with mean width of 6 mm or less). NUMBER(5 1) Length of well-sealed moderate severity transverse cracking (mean crack width from 6 to 19 mm or under 19 mm with adjacent low severity random cracking). NUMBER(5 1) Length of well-sealed high severity transverse cracking (mean crack width greater than 19 mm or under 19 mm with adjacent moderate to high severity random cracking). Length of low severity longitudinal reflection NUMBER(4 1) cracking at joints (cracks of unknown width well sealed or with mean width of 6 mm or less). NUMBER(4 1) Length of moderate severity longitudinal reflection cracking at joints (mean crack width from 6 to 19 mm or under 19 mm with adjacent low severity random cracking). NUMBER(4 1) Length of high severity longitudinal reflection cracking at joints (mean crack width greater than 19 mm or fewer than 19 mm with adjacent moderate to high severity random cracking). A-5 Field Name REFL_CRACK_LONG_SEAL_L_L REFL_CRACK_LONG_SEAL_L_M REFL_CRACK_LONG_SEAL_L_H TRANS_CRACK_NO_L TRANS_CRACK_NO_M TRANS_CRACK_NO_H TRANS_CRACK_L_L TRANS_CRACK_L_M TRANS_CRACK_L_H TRANS_CRACK_SEAL_L_L TRANS_CRACK_SEAL_L_M TRANS_CRACK_SEAL_L_H PATCH_NO_L PATCH_NO_M Units ft ft ft ft ft ft ft ft ft Field Type Description The length of well-sealed low severity longitudinal NUMBER(4 1) reflection cracking at joints (cracks of unknown width or with mean width of 6 mm or less). NUMBER(4 1) The length of well-sealed moderate severity longitudinal reflection cracking at joints (mean crack width from 6 to 19 mm or under 19 mm with adjacent low severity random cracking). NUMBER(4 1) The length of well-sealed high severity longitudinal reflection cracking at joints (mean crack width greater than 19 mm or under 19 mm with adjacent moderate to high severity random cracking). Number of low severity transverse cracks (cracks of NUMBER(3 0) unknown width well sealed or with mean width of 6 mm or less). Number of moderate severity transverse cracks NUMBER(3 0) (mean crack width from 6 to 19 mm or under 19 mm with adjacent low severity random cracking). Number of high severity transverse cracks (mean NUMBER(3 0) crack width greater than 19 mm or under 19 mm with adjacent moderate to high severity random cracking). Length of low severity transverse cracking (cracks of NUMBER(5 1) unknown width well sealed or with mean width of 6 mm or less). Length of moderate severity transverse cracking NUMBER(5 1) (crack mean width from 6 to 19 mm or under 19 mm with adjacent low severity random cracking). Length of high severity transverse cracking (mean NUMBER(5 1) crack width greater than 19 mm or under 19 mm with adjacent moderate to high severity random cracking). The length of well-sealed low severity transverse NUMBER(5 1) cracking (cracks of unknown width or with mean width of 6 mm or less). NUMBER(5 1) The length of well-sealed moderate severity transverse cracking (mean crack width from 6 to 19 mm or under 19 mm with adjacent low severity random cracking). NUMBER(5 1) The length of well-sealed high severity transverse cracking (mean crack width greater than 19 mm or under 19 mm with adjacent moderate to high severity random cracking). NUMBER(3 0) Number of patches/patch deteriorations with low severity distress of any type. NUMBER(3 0) Number of patches/patch deteriorations with moderate severity distress type. A-6 Field Name PATCH_NO_H PATCH_A_L PATCH_A_M PATCH_A_H POTHOLES_NO_L POTHOLES_NO_M POTHOLES_NO_H POTHOLES_A_L POTHOLES_A_M POTHOLES_A_H SHOVING_NO SHOVING_A BLEEDING POLISH_AGG_A RAVELING PUMPING_NO PUMPING_L OTHER Units ft2 ft2 ft2 ft2 ft2 ft2 ft2 ft2 ft2 ft2 ft Field Type Description NUMBER(3 0) Number of patches/patch deteriorations with high severity distress of any type. NUMBER(5 1) Area of patching with low severity distress or patch deterioration. NUMBER(5 1) Area of patching with moderate severity distress or patch deterioration. NUMBER(5 1) Area of patching with high severity distress or patch deterioration. NUMBER(3 0) Number of low severity potholes (less than 25 mm deep). NUMBER(3 0) Number of moderate severity potholes (from 25 to 50 mm deep). NUMBER(3 0) Number of high severity potholes (more than 50 mm deep). NUMBER(5 1) Area of low severity potholes (less than 25 mm deep). NUMBER(5 1) Area of moderate severity potholes (from 25 to 50 mm deep). NUMBER(5 1) Area of high severity potholes (more than 50 mm deep). NUMBER(3 0) Number of areas where shoving exists. NUMBER(5 1) The area of shoving localized longitudinal displacement of the pavement surface. Presence of excess asphalt on the pavement surface NUMBER(5 1) which may create a shiny glass-like reflective surface. NUMBER(5 1) Area of polished aggregate (binder worn away to expose coarse aggregate). Wearing away of the pavement surface caused by the NUMBER(5 1) dislodging of aggregate particles and loss of asphalt binder. NUMBER(3 0) Number of occurrences of water bleeding and pumping. NUMBER(4 1) Length of pavement affected by water bleeding and pumping. CHARACTER (80) A description of other surface distress. A-7 GALTPP_PCC_DISTRESS Field Name Field Type GALTPP_ID CHARACTER SOURCE CHARACTER CONSTRUCTION_NO CHARACTER SURVEY_DATE DATE SURVEYOR CHARACTER BEFORE_TEMP NUMBER AFTER_TEMP NUMBER AVG_FAULTING NUMBER MIN_FAULTING NUMBER MAX_FAULTING NUMBER STD_FAULTING NUMBER BROKEN_SLABS NUMBER CORNER_BREAKS_NO_L NUMBER CORNER_BREAKS_NO_M NUMBER CORNER_BREAKS_NO_H LONG_CRACK_L_L NUMBER NUMBER LONG_CRACK_L_M NUMBER LONG_CRACK_L_H LONG_CRACK_SEAL_L_L LONG_CRACK_SEAL_L_M NUMBER NUMBER NUMBER LONG_CRACK_SEAL_L_H NUMBER Description A unique identifier for GALTPP Source of the distress data (COPACES LTPP). 1 stands for new construction 2 stands for rehabilitation Date survey was performed. Person who conducts the survey. Pavement surface temperature at the beginning of the distress survey. Pavement surface temperature at the end of the distress survey. Average edge faulting calculated per site per survey. Minimum edge faulting per site per survey. Maximum edge faulting per site per survey. Standard deviation for edge faulting calculated per site per survey. Total number of broken slabs. Number of low severity corner breaks. (Notspalled for more than 10 percent of length no measurable faulting corner piece not broken in two or more pieces.) Number of moderate severity corner breaks. (Spalled at low severity for more than 10 percent or faulting less than 13 mm corner piece not broken in two or more Number of high severity corner breaks. (Spalled at moderate to high severity for more than 10 percent of crack or faulting exceeds 13 mm or corner piece in two or more pieces.) Length of low severity longitudinal cracking. (Crack widths less than 3 mm no spalling or measurable faulting.) Length of well-sealed moderate severity longitudinal cracking. (Crack widths between 3 and 13 mm or spalling less than 75 mm or faulting up to 13 mm.) Length of high severity longitudinal cracking. (Crack widths greater than 13 mm or spalling greater than 75 mm or faulting greater than 13 mm.) Length of well-sealed low severity longitudinal cracking. (Crack widths less than 3 mm no spalling or measurable faulting.) Number of transverse cracks for which moderate severity distress is the highest level observed for at least 10 percent of the crack. Length of well-sealed high severity longitudinal cracking. (Crack widths greater than 13 mm or spalling greater than 75 mm or faulting greater than 13 mm.) A-8 Field Name TRANS_CRACK_NO_L TRANS_CRACK_NO_M TRANS_CRACK_NO_H TRANS_CRACK_L_L TRANS_CRACK_L_M TRANS_CRACK_L_H LONG_SPALLING_L_L LONG_SPALLING_L_M LONG_SPALLING_L_H TRANS_SPALLING_NO_L TRANS_SPALLING_NO_M TRANS_SPALLING_NO_H TRANS_SPALLING_L_L TRANS_SPALLING_L_M TRANS_SPALLING_L_H SCALING_NO SCALING_A POLISH_AGG_A BLOWUPS_NO PATCH_FLEX_NO_L Field Type NUMBER NUMBER NUMBER NUMBER NUMBER NUMBER NUMBER NUMBER NUMBER NUMBER NUMBER NUMBER NUMBER NUMBER NUMBER NUMBER NUMBER NUMBER NUMBER NUMBER Description Number of low severity transverse cracks. (No spalling exceeding 10 percent of length). Number of transverse cracks for which moderate severity distress is the highest level observed for at least 10 Number of transverse cracks for which high severity distress exceeds 10 percent of the length. Length of low severity transverse cracking. (Crack widths less than 3 mm no spalling and no measurable faulting.) Length of moderate severity transverse cracking. (Crack widths between 3 and 6 mm or spalling fewer than 75 mm or faulting up to 6 mm.) Length of high severity transverse cracking. (Crack widths greater than 6 mm or spalling over 75 mm or faulting over 6 mm.) Length of low severity spalling of longitudinal joints. (Spalls less than 75 mm measured to center of joint with no loss of material.) Length of moderate severity spalling of longitudinal joints. (Spalls between 75 and 150 mm wide measured to center of joint with loss of material.) Length of high severity spalling of longitudinal joints. (Spalls greater than 150 mm measured to center of joint with loss of material.) Number of transverse joints with low severity spalling. (Spalls less than 75 mm wide measured to center of joint.) Number of transverse joints with moderate severity spalling. (Spalls between 75 and 150 mm wide measured to center of joint.) Number of transverse joints with high severity spalling. (Spalls more than 150 mm wide measured to center of joint.) Length of low severity spalling of transverse joints. (Spalls less than 75 mm measured to center of joint or with no loss of material.) Length of moderate severity spalling of transverse joints. (Spalls 75 to 150 mm wide measured to center of joint with loss of material). Length of high severity spalling of transverse joints. (Spalls more than 150 mm wide measured to center of joint with loss of material.) Number of areas with scaling. Area of scaling (Deterioration of upper slab surface between 3 and 13 mm). Area of polished aggregate (Surface worn away to expose coarse aggregate). Number of blowups. Number of flexible patches showing at most low severity distress of any type and no settlement at the perimeter. A-9 Field Name Field Type PATCH_FLEX_NO_M NUMBER PATCH_FLEX_NO_H NUMBER PATCH_FLEX_A_L NUMBER PATCH_FLEX_A_M NUMBER PATCH_FLEX_A_H NUMBER PATCH_RIGID_NO_L NUMBER PATCH_RIGID_NO_M NUMBER PATCH_RIGID_NO_H NUMBER PATCH_RIGID_A_L NUMBER PATCH_RIGID_A_M NUMBER PATCH_RIGID_A_H NUMBER PUMPING_NO NUMBER PUMPING_L NUMBER GACAL_CORE_DESCRIPTION Description Number of flexible patches showing moderate severity distress of any type or settlement of up to 6 mm at the perimeter. Number of flexible patches showing high severity distress or settlement of 6 mm or more at the perimeter. Area of flexible patching showing at most low severity distress of any type and no settlement at the perimeter. Area of flexible patching showing moderate severity distress of any type or settlement of up to 6 mm at the perimeter. Area of flexible patching showing high severity distress of any type or settlement of 6 mm or more at the perimeter. Number of rigid patches showing at most low severity distress of any type and no settlement at the perimeter. Number of rigid patches showing moderate severity distress of any type or settlement of up to 6 mm at the perimeter. Number of rigid patches showing high severity distress of any type or settlement of 6 mm or more at the perimeter. Area of rigid patching showing at most low severity distress of any type and no settlement at the perimeter. Area of rigid patching showing moderate severity distress of any type or settlement of up to 6 mm at the perimeter. Area of rigid patching showing high severity distress of any type or settlement of 6 mm or more at the perimeter. Number of occurrences of water bleeding and pumping. Length of pavement affected by water bleeding and pumping. Name GALTPP_ID CORE Description Description GACAL_CORE_HEIGHTMEASURE Name GALTPP_ID DATE LAYER NOTE Description A-10 Name Measure_1 Measure_2 Measure_3 Measure_4 Avg_in Avg_mm Description GACAL_DCP Name GALTPP_ID DATE NOTE CORE No_of_Blows Cummulative_Penetration_cm Cumulative_Penetration_mm Penetration_Rate_mm/blow Resilient_Modulus_ksi Depth_inches Other_Note Description GACAL_PCC_DISTRESS Field Name GALTPP_ID CORN_BREAK_L CORN_BREAK_M CORN_BREAK_H LONG_CRACK_L LONG_CRACK_M LONG_CRACK_H TRAN_CRACK_NO_L TRAN_CRACK_L_L TRAN_CRACK_NO_M TRAN_CRACK_L_M Description A-11 Field Name TRAN_CRACK_NO_H TRAN_CRACK_L_H SPALL_L_JOINT_L SPALL_L_JOINT_M SPALL_L_JOINT_H SPALL_T_JOINT_NO_L SPALL_T_JOINT_L_L SPALL_T_JOINT_NO_M SPALL_T_JOINT_L_M SPALL_T_JOINT_NO_H SPALL_T_JOINT_L_H PATCH_DET_RIGID_NO_L PATCH_DET_RIGID_AREA_L PATCH_DET_RIGID_NO_M PATCH_DET_RIGID_AREA_M PATCH_DET_RIGID_NO_H PATCH_DET_RIGID_AREA_H TOTAL_NO_SLAB LENGTH WIDTH Description A-12 MEPDG_UNBOUND_MATERIAL Name GALTPP_ID CONSTRUCTION_NO NOTE LAYER_NO Layer_Type Material_Code Material_Code_and_Description Last_Layer Bedrock Coefficient_Lateral_Earth_Pressure Layer_Thickness_in Poisson_Ratio Resilient_Modulus Type Liquid_Limit Plasticity_Index Compacted_Layer Max_Dry_Unit_Weight User_Defined_MDUW Saturated_Hydraulic_Conductivity User_Defined_SHC Gravity_of_Solids User_Defined_GS Water_Content User_Defined_WC User_Defined_SWCC af bf cf Description Test section identification number. 1 stands for new construction 2 stands for rehabilitation Note for routes Layer number Type of layer Code of material Code of material and description Identifies layer as the last layer of the pavement section Bedrock layer inputs Coefficient of lateral earth pressure Thickness of each layer (in) Poisson s ratio Resilient modulus (psi) Layer type Liquid limit of the non-stabilized material. This control allows you to define the plasticity index for nonstabilized material. Enable this control to indicate that the layer is compacted. Maximum dry unit weight. (pcf) User-defined Soil Water Characteristic Curve (SWCC) A-13 Name hr Gradation THREE_AND_HALF_PASSING THREE_PASSING TWO_AND_HALF_PASSING TWO_PASSING ONE_AND_HALF_PASSING ONE_PASSING THREE_QUARTER_PASSING HALF_PASSING THREE_EIGHTH_PASSING NO_4_PASSING NO_8_PASSING NO_10_PASSING NO_16_PASSING NO_20_PASSING NO_30_PASSING NO_40_PASSING NO_50_PASSING NO_60_PASSING NO_80_PASSING NO_100_PASSING NO_200_PASSING 0_02MM_PASSING 0_002MM_PASSING 0_001MM_PASSING PI LL Compacted_Layer Stabilized Unit_Wght Poisson_Ratio Description Gradation inputs for each unstabilized/stabilized layer Mean percent passing 3- in screen Mean percent passing 3 in screen Mean percent passing 2- in screen Mean percent passing 2 in screen Mean percent passing 1- in screen Mean percent passing 1 in screen Mean percent passing in screen Mean percent passing in screen Mean percent passing in screen Mean percent passing 4 screen Mean percent passing 8 screen Mean percent passing 10 screen Mean percent passing 16 screen Mean percent passing 20 screen Mean percent passing 30 screen Mean percent passing 40 screen Mean percent passing 50 screen Mean percent passing 60 screen Mean percent passing 80 screen Mean percent passing 100 screen Mean percent passing 200 screen Mean percent passing 0.020 mm screen Mean percent passing 0.002 mm screen Mean percent passing 0.001 mm screen Plasticity index Liquid limit Compacted layer Inputs for stabilized layer Unit weight (pcf) Poisson s ratio A-14 Name Elastic_Resilient_Mod Minimum_Mod Mod_of_Rupture Therm_Cndctvty Heat_Capacity Strength (for each layer) k1 k2 k3 Poisson_Ratio Ltrl_Pressure Modulus CBR R_Val Lyr_Coefnt DCP Description Elastic/resilient modulus (psi) Minimum elastic/resilient modulus (psi) Modulus of rupture (psi) Thermal conductivity (BTU/hr-ft-F) Heat capacity (BTU/lb-F) Strength inputs for each unstabilized/stabilized layer Regression constants (used for Level 1 calculation of MR) Regression constants (used for Level 1 calculation of MR) Regression constants (used for Level 1 calculation of MR) Poisson s ratio Lateral pressure Resilient modulus (psi) California Bearing Ratio R-Value AASHTO layer coefficient Dynamic Cone Penetrometer (mm/blow) A-15 MEPDG_PCC_MATERIAL Name Description GALTPP_ID Test section identification number. CONSTRUCTION_NO 1 stands for new construction 2 stands for rehabilitation NOTE LAYER_NO Note for routes Layer number CTE Coefficient of thermal expansion (per F x 10-6) Existing_Layer Existing layer as opposed to a new layer Poisson_Ratio Poisson s ratio Thickness Layer thickness Unit_Weight Unit weight (pcf) Thermal_Expansion PCC coefficient of thermal expansion (in/in/deg F x 10-6) Heat_Capacity Heat capacity (BTU/lb-F) Therm_Conduct Thermal conductivity (BTU/hr-ft-F) Mix Mix design properties Aggregate_Type Aggregate type Cmntitious_Cntnt Cementitious content Cmnt_Typ Cement type W_C_Ratio Water-cement ratio Curing_Type Curing type Reverse_Shrink Reverse shrinkage Ultimate_Shrinkage Ultimate shrinkage Strength Strength properties Age Age (yrs) Modulus_of_Rupture Modulus of rupture (psi) Elstc_Modulus Elastic modulus (psi) Comp_Strength Compressive strength (psi) Design Concrete pavement design features PCC_Surface_Shortwave_Absorbtion Dowel_Spacing PCC surface shortwave absorptivity the fraction of solar energy (sunshine) at the PCC surface. Dowel bar spacing (in) Dowel_Diameter Dowel bar diameter (in) Erodibility_Index Base_Slab_Friction_Coefficient Using an index on a scale of 1 to 5 1 for extremely erosion resistant 5 for very erodible Base/slab friction coefficient A-16 Name Joint_Spacing Curl_Warp_Effective_ Temperature_Difference Sealant_Type Tied_PCC Tied_LTE Widened_Slab Slab_Width PCC_Base_Interface Loss_of_Friction Steel_Reinforcement Reinforcement_Steel_Diameter Depth_of_Reinforcement Crack_Spacing Shoulder_Type Description Joint spacing (ft) Permanent curl/warp effective temperature difference (F) Joint sealant type Identifies the presence of a tied concrete shoulder Load transfer efficiency of the tied concrete shoulder Identifies the presence of a widened lane Width of the widened slab (ft) Level of friction between the base and PCC Loss of full friction (age in months) Percent steel (%) Bar diameter (in) Steel depth (in) Mean crack spacing (in) Tied vs untied PCC or asphalt concrete A-17 MEPDG_AC_CRACK Field Name GALTPP_ID CONSTRUCTION_NO NOTE SOURCE SURVEY_DATE FATIGUE_CRACK THERMAL_CRACK MEPDG_AC_RUT Field Name GALTPP_SEC_CON_ID CONSTRUCTION_NO NOTE SOURCE SURVEY_DATE WIRELINE_RUT Units ft/mi ft/mi Units in Field Type CHARACTER CHARACTER CHARACTER CHARACTER DATE NUMBER(4 1) NUMBER(4 1) Field Type CHARACTER CHARACTER CHARACTER CHARACTER DATE NUMBER(3 2) Description A unique identifier for GALTPP 1 stands for new construction 2 stands for rehabilitation Note of routes Source of the distress data (COPACES LTPP) Date of distress survey. Total length of fatigue cracking per lane-mile. Total length of thermal cracking per lane-mile. Description A unique identifier for GALTPP 1 stands for new construction 2 stands for rehabilitation Note of routes Source of the distress data (COPACES LTPP) Date of distress survey. Rut depth for the 500-ft test section MEPDG_PCC_CRACK Field Name GALTPP_ID CONSTRUCTION_NO NOTE LTPP_SECTION_ID SURVEY_DATE CRACKING Units % Field Type CHARACTER CHARACTER CHARACTER CHARACTER(6) DATE NUMBER(3 1) Description A unique identifier for GALTPP 1 stands for new construction 2 stands for rehabilitation Note of routes LTPP test section identification. Date of distress survey. % slabs cracked A-18 MEPDG_PCC_FAULT Field Name GALTPP_ID CONSTRUCTION_NO NOTE LTPP_SECTION_ID SURVEY_DATE FAULTING Units in Field Type CHARACTER CHARACTER CHARACTER CHARACTER(6) DATE NUMBER(3 1) Description A unique identifier for GALTPP 1 stands for new construction 2 stands for rehabilitation Note of routes LTPP test section identification. Date of distress survey. Mean joint faulting MEPDG_AC_MATERIAL Name GALTPP_ID CONSTRUCTION_NO NOTE LAYER_NO Layer_Type Material_Code Material_Code_and_Description Layer_Thickness Air_Voids Effctv_Bndr_Cntnt Poisson_Ratio_Calculated Poisson_Ratio ParameterA ParameterB Unit_Weight Existing_Layer Binder Binder_Type Binder_Grad Creep Load_Time Creep Load_Time Creep_-4F Description Test section identification number. 1 stands for new construction 2 stands for rehabilitation Note of routes Layer number Type of layer Code of material Code of material and description Layer thickness (in) Percent air voids Effective binder content (by weight) Calculated Poisson s ratio Poisson s ratio Total unit weight (pcf) Existing layer as opposed to a new layer Asphalt binder properties (Level 3). Binder Type Binder grade Creep Load time Creep compliance properties (thermal cracking). Loading time (sec). Low temperature (-4 F). A-19 Name Creep_-14F Description Mid temperature (14 F). Creep_-32F High temperature (32 F). E Dynamic modulus of asphalt mixture (Level 1) Temperature Temperature (F) E_0_1 Dynamic modulus (psi) at 0.1 Hz E_1 Dynamic modulus (psi) at 1 Hz E_10 Dynamic modulus (psi) at 10 Hz E_25 Dynamic modulus (psi) at 25 Hz HMA_Model Hot Mix Asphalt (HMA) model Reference_Temp Reference temperature (F) Indirect_Tensile_Strength Indirect tensile strength Heat_Capacity Heat capacity (BTU/lb-F) Thermal_Conductivity Thermal conductivity. (BTU/hr-ft-F) Thermal_Contraction Aggregate_Coefficient_Thermal_Contraction Mix_Coefficient_Thermal_Contraction A direct entry of the coefficient or allow the program to compute as a function of thermal contraction coefficient of the aggregates. Coefficient of thermal contraction of the aggregates (in./in./F) Coefficient of thermal contraction of the AC mix(in./in./F) Voidsin_Mineral_Aggregate Voidsin Mineral Aggregate RTFO_SP Superpave binder test data (Level 1 and Level 2) Temperature Temperature (F) G Binder dynamic modulus (Pa) Delta Phase angle RTFO_Conv Conventional binder properties (Level 1 and Level 2) Temp Temperature (F) Softening_Pnt Softening point (P) Abslt_Vscsty Absolute viscosity (P) Knmtc_Vscsty Kinematic viscosity (CS) Spcfc_Grvty Specific gravity Penetration Penetration Brkfld_Vscsty Brookfield viscosity Gradation Retained_3_4 Gradation properties of asphalt mixture (Level 2 and Level 3) Cumulative percent retained on the in sieve. Retained_3_8 Cumulative percent retained on the in sieve. A-20 Name Retained_ No_4 Passing_No_200 ThermCrk Tnsl_Strngth VMA Aggrgt_CTC Mix_CTC Description Cumulative percent retained on the 4 sieve. Percent passing the No. 200 sieve. Thermal cracking properties Average tensile strength at 14 F (psi) Mixture voids in mineral aggregate (%) Aggregate coefficient of thermal contraction (in/in/F) Mix coefficient of thermal contraction (in/in/F) A-21 MEPDG_TRAFFIC_INPUTS Field Name Description GALTPP_ID A unique identifier for GALTPP and Georgia test sites Construction_No 1 stands for new construction 2 stands for rehabilitation FunctionalClass Classification of pavement function MEPDFTTCGROUP Truck traffic classification AADTT Initial two-way average annual daily truck traffic Direction Direction of traffic No_Design_Lane Number of lanes in the design direction Percent_Trcks_Dsgn_Dir Percent of trucks in the design direction (%) Percent _Trcks_Dsgn_Lane Percent of trucks in design lane (%) Speed Operational speed (mph) Growth_Rate Traffic growth rate (%) General Traffic Inputs Wheel_Location Mean wheel location (inches from the lane marking) Trffc_Wander_Stdev Traffic wander standard deviation (in) Design_Lane_Width Design lane width (ft) Axle Configuration Avg_Axle_Width Average axle width (edge-to-edge) outside dimension (ft) Dual_Tire_Spacing Dual tire spacing (in) Tire_Pressure Tire pressure (psi) Axle_Spcing_Tandem Tandem axle spacing (in) Axle_Spcing_Tridem Tridem axle spacing (in) Axle_Spcing_Quad Quad axle spacing (in) Wheelbase Wheelbase_Short Average short axle spacing (ft) Percent Trucks_Short Percent of trucks short axle spacing (%) Wheelbase_Medium Average medium axle spacing (ft) Percent Trucks_Medium Percent of trucks medium axle spacing (%) Wheelbase_Long Average long axle spacing (ft) Percent Trucks_Long Percent of trucks long axle spacing (%) Traffic Volume Adjustment Factors VehicleDistribution_Class_4 Vehicle class distribution Class_4 Class_13 AADTT distribution by vehicle class (%) Axle Load Distribution Factors Single Single axle Month_S Month of the year (January December) Class_S FHWA truck class 1 13 Total_S Sum of axle load distribution factors (must total 100%) A-22 Field Name 3000 41000 Tandem Month_T Class_T Total_T 6000 82000 Tridem Month_Tr Class_Tr Total_Tr 12000 102000 Quad Month_Q Class_Q Total_Q 12000 102000_Q Description Percent of axles in each load interval (1000 lb increments) Tandem axle Month of the year (January December) FHWA truck class 1 13 Sum of axle load distribution factors (must total 100%) Percent of axles in each load interval (2000 lb increments) Tridem axle Month of the year (January December) FHWA truck class 1 13 Sum of axle load distribution factors (must total 100%) Percent of axles in each load interval (3000 lb increments) Quad axle Month of the year (January December) FHWA truck class 1 13 Sum of axle load distribution factors (must total 100%) Percent of axles in each load interval (3000 lb increments) MEPDG_TRAFFIC_AXLES_NO Number of axles/truck Field Name Description GALTPP_ID A unique identifier for GALTPP and Georgia test sites Vehicle_Class FHWA truck class 4 13 Single_Axles Average number of single axles per truck class Tandem_Axles Average number of tandem axles per truck class Tridem_Axles Average number of tridem axles per truck class Quad_Axles Average number of quad axles per truck class MEPDG_TRAFFIC_MAF Traffic Volume Monthly Adjustment Factors Filed Name Description GALTPP_ID A unique identifier for GALTPP and Georgia test sites Month Month of the year (January December) Class_4 Class_13 Monthly adjustment factor for each FHWA truck class 1 13 A-23 MEPDG_LAYER Field Name GALTPP_ID Layer_No Layer_Type Material_Code_Description Layer_Thickness Construction_No Material_Code Description A unique identifier for GALTPP and Georgia test sites Number of layer Type of layer Description of material code Layer thickness in inch 1 stands for new construction 2 stands for rehabilitation Material code A-24 APPENDIX B SITE 3D PAVEMENT SURFACE IMAGES SHOWING PAVEMENT DISTRESS CONDITIONS Site 1 B-1 B-2 B-3 Site 2 B-4 B-5 Site 3 B-6 Site 4 B-7 B-8 B-9 Site 5 B-10 B-11 B-12 B-13 B-14 APPENDIX C CORE PICTURES SHOWING SUBSURFACE CONDITIONS Site 1 - Core A3 C-1 Site 1 - Core A4 C-2 C-3 Site 2 - Core C2 C-4 Site 2 - Core C4 C-5 Site 2 - Core C5 C-6 Site 2 - Core C6 C-7 Site 2 - Core C7 C-8 Site 2 - Core C8 C-9 Site 3 - Core 4-1 C-10 Site 3 - Core 4-2 C-11 Site 3 - Core 5-1 C-12 Site 3 - Core 6-1 C-13 Site 3 - Core 6-2 C-14 Site 4 - Core R1 C-15 Site 4 - Core R2 C-16 Site 4 - Core R3 C-17 Site 4 - Core R5 C-18 Site 4 - Core R6 C-19 C-20