GEORGIA DOT RESEARCH PROJECT 17-18 Final Report Innovative Training Modules for Rapid and Continuous Deployment of MEPDG Office of Performance-based Management and Research 600 West Peachtree Street NW | Atlanta, GA 30308 TECHNICAL REPORT DOCUMENTATION 1. Report No. 2. Government Accession No. FHWA-GA-20-1718 N/A 4. Title and Subtitle Innovative Training Modules for Rapid and Continuous Deployment of MEPDG 7. Author(s) S. Sonny Kim, Ph.D., P.E.; Hampton Worthey; Wouter Brink, Ph.D.; Harold L. Von Quintus, P.E.; Stephan A. Durham, Ph.D., P.E.; Mi G. Chorzepa, Ph.D., P.E. 3. Recipient's Catalog No. N/A 5. Report Date August 2020 6. Performing Organization Code N/A 8. Performing Organization Report No. 17-18 9. Performing Organization Name and Address University of Georgia, College of Engineering Driftmier Engineering Center, Athens, GA 30602 Phone: (706) 542-9804, Email: kims@uga.edu 12. Sponsoring Agency Name and Address Georgia Department of Transportation Office of Performance-based Management and Research 600 West Peachtree Street NW, Atlanta, GA 30308 10. Work Unit No. N/A 11. Contract or Grant No. PI# 0015713 13. Type of Report and Period Covered Final Report (October 2017August 2020) 14. Sponsoring Agency Code N/A 15. Supplementary Notes Conducted in cooperation with the U.S. Department of Transportation, Federal Highway Administration 16. Abstract The American Association of State Highway and Transportation Officials (AASHTO) Joint Task Force on Pavements in cooperation with the National Cooperative Highway Research Program (NCHRP) and the Federal Highway Association (FHWA) sponsored the development of an AASHTO Mechanistic-Empirical (ME) pavement design procedure. NCHRP project 1-37A produced rudimentary software that utilized existing ME-based models and databases reflecting current state-of-the-art pavement design procedures. The Mechanistic-Empirical Pavement Design Guide (MEPDG) was completed in 2004 and released to the public for review and evaluation. A formal review was completed by an independent set of consultants under NCHRP Project 1-40A, and version 1.0 of the MEPDG was submitted in 2007 to NCHRP, FHWA, and AASHTO for further consideration as an AASHTO Standard Practice. The MEPDG was formally adopted by AASHTO as an Interim Guide in 2008. Pavement ME Design is a software upgrade to version 1.0 that became available in 2013. AASHTO is distributing and managing the software as an AASHTOWare product. This User Input Guide is more of an engineering manual for determining the inputs needed for pavement design engineers in Georgia to begin to use Pavement ME Design. Many State Highway Agencies (SHAs) implementing Pavement ME Design conduct a local calibration or verification effort to establish local inputs and determine the calibration factors that result in unbiased predictions. Forensic investigations, including materials testing and pavement performance data, are needed to establish the accuracy and bias of the distress transfer functions and International Roughness Index (IRI) prediction models. GDOT also sponsored a local calibration effort and the results from that effort were used in preparing this User Input Guide. This manual has been updated from the previous MEPDG training manual with recently measured materials properties, climate data, and traffic inputs. 17. Key Words MEPDG, Pavement ME, Training 19. Security Classification (of this report) Unclassified 18. Distribution Statement No Restrictions 20. Security Classification (of this 21. No. of Pages page) Unclassified 185 22. Price Free i GDOT Research Project 17-18 Final Report INNOVATIVE TRAINING MODULES FOR RAPID AND CONTINUOUS DEPLOYMENT OF MEPDG By S. Sonny Kim, Ph.D., P.E Associate Professor Civil Engineering, College of Engineering University of Georgia Harold Von Quintus, P.E. Project Manager Applied Research Associates, Inc Hampton Worthey Graduate Research Assistant Civil Engineering, College of Engineering University of Georgia Stephan Durham, Ph.D., P.E. Professor Civil Engineering, College of Engineering University of Georgia Wouter Brink, Ph.D. Senior Civil Engineer Transportation and Infrastructure Division Applied Research Associates, Inc Mi G. Chorzepa Associate Professor Civil Engineering, College of Engineering University of Georgia Contract with Georgia Department of Transportation In cooperation with U.S. Department of Transportation Federal Highway Administration August 2020 The contents of this report reflect the views of the authors who 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. ii DISCLAIMER STATEMENT This document is disseminated under the sponsorship of the Georgia Department of Transportation and the United States Department of Transportation in the interest of information exchange. The State of Georgia and the United States Government assume no liability of its contents or use thereof. The contents of this report reflect the views of the authors, who are responsible for the facts and accuracy of the data presented herein. The contents do not necessarily reflect the official policies of the Georgia Department of Transportation or the United States Department of Transportation. The State of Georgia and the United States Government do not endorse products of manufacturers. Trademarks or manufacturers' names appear herein only because they are considered essential to the object of this document. iii SI* (MODERN METRIC) CONVERSION FACTORS APPROXIMATE CONVERSIONS TO SI UNITS Symbol When You Know Multiply By To Find Symbol LENGTH In Inches 25.4 Millimeters Ft Feet 0.305 Meters Yd Yards 0.914 Meters Mi Miles 1.61 Kilometers AREA in2 square inches 645.2 square millimeters ft2 square feet 0.093 square meters yd2 square yard 0.836 square meters Ac Acres 0.405 Hectares mi2 square miles 2.59 square kilometers VOLUME fl oz fluid ounces 29.57 Milliliters Gal Gallons 3.785 Liters ft3 cubic feet 0.028 cubic meters yd3 cubic yards 0.765 cubic meters [NOTE: volumes greater than 1,000 shall be shown in m3] MASS Oz Ounces 28.35 Grams Lb Pounds 0.454 Kilograms T short tons (2000 lb) 0.907 megagrams (metric tons) TEMPERATURE (exact degrees) oF Fahrenheit 5 (F-32)/9 Celsius or (F-32)/1.8 ILLUMINATION mm m m km mm2 m2 m2 ha km2 mL L m3 m3 g kg Mg (or t) oC Fc Fl Lbf lbf/in2 (psi) k/in2 (ksi) lb/ft3 (pcf) foot-candles foot-Lamberts Pounds pounds per square inch kips per square inch DENSITY pounds per cubic foot 10.76 Lux 3.426 candela/m2 FORCE and PRESSURE or STRESS 4.45 Newtons 6.89 kiloPascals 6.89 megaPascals 16.02 kilograms per cubic meter APPROXIMATE CONVERSIONS FROM SI UNITS lx cd/m2 N kPa MPa kg/m3 Symbol When You Know Multiply By To Find Symbol LENGTH Mm Millimeters 0.039 Inches in M Meters 3.28 Feet ft M Meters 1.090 Yards yd Km Kilometers 0.621 Miles mi AREA mm2 square millimeters 0.0016 square inches in2 m2 square meters 10.764 square feet ft2 m2 square meters 1.195 square yards yd2 Ha Hectares 2.47 Acres ac km2 square kilometers 0.386 square miles mi2 VOLUME mL Milliliters 0.034 fluid ounces fl oz L Liters 0.264 Gallons gal m3 cubic meters 35.314 cubic feet ft3 m3 cubic meters 1.307 cubic yards yd3 MASS G Grams 0.035 Ounces oz Kg Kilograms 2.202 Pounds lb Mg (or t) megagrams (metric tons) 1.103 short tons (2000 lb) T TEMPERATURE (exact degrees) oC Celsius 1.8C+32 Fahrenheit oF ILLUMINATION lx cd/m2 N kPa Mpa kg/m3 Lux candela/m2 Newtons kiloPascals MegaPascals pounds per cubic foot 0.0929 foot-candles 0.2919 foot-Lamberts FORCE and PRESSURE or STRESS 0.225 Pounds 0.145 pounds per square inch 0.145 kips per square inch DENSITY 0.062 kilograms per cubic meter fc fl Lbf lbf/in2 (psi) k/in2 (ksi) lb/ft3 (pcf) *SI is the symbol for the International System of Units. Appropriate rounding should be made to comply with Section 4 of ASTM E 380. (Revised March 2003) iv TABLE OF CONTENTS LIST OF TABLES..................................................................................................................... viii LIST OF FIGURES .................................................................................................................... xi EXECUTIVE SUMMARY .......................................................................................................... xii CHAPTER 1--INTRODUCTION .................................................................................................1 CHAPTER 2--OVERVIEW OF THE MEPDG DESIGN METHODOLOGY ..................................3 2.1 DISTRESS TRANSFER FUNCTIONS INCLUDED IN PMED SOFTWARE .................3 2.2 PAVEMENT DESIGN STEPS USING PAVEMENT ME DESIGN SOFTWARE ...........5 2.3 INPUT CATEGORIES ...............................................................................................11 2.4 HIERARCHICAL APPROACH FOR DETERMINING INPUTS ...................................14 CHAPTER 3--GENERAL PROJECT INFORMATION ..............................................................16 3.1 DESIGN AND PAVEMENT TYPE STRATEGIES ......................................................16 3.1.1 New/Reconstructed Flexible Pavements and HMA Overlays ...............................17 3.1.2 New/Reconstructed Rigid Pavements and PCC Overlays....................................19 3.1.3 Pavement Preservation and Preventive Maintenance ..........................................20 3.2 PROJECT FILE/NAME ..............................................................................................20 3.3 DESIGN LIFE ............................................................................................................21 3.4 BASE AND PAVEMENT CONSTRUCTION & TRAFFIC OPENING DATES .............21 3.4.1 New Construction ................................................................................................21 3.4.2 Rehabilitation .......................................................................................................23 3.5 SCREEN SHOTS FOR GENERAL INFORMATION ..................................................23 CHAPTER 4--PERFORMANCE CRITERIA .............................................................................25 4.1 INITIAL INTERNATIONAL ROUGHNESS INDEX (IRI)..............................................25 4.2 DISTRESS CRITERIA OR THRESHOLD VALUES ...................................................26 4.2.1 Terminal IRI Criterion...........................................................................................28 4.2.2 Fatigue (Load-Related) Cracking Criterion--Flexible Pavements.........................28 4.2.3 Permanent Deformation (Rut Depth) Criterion--Flexible Pavements ...................30 4.3 DESIGN RELIABILITY...............................................................................................30 4.4 SCREEN SHOTS FOR THE PERFORMANCE CRITERIA ........................................32 CHAPTER 5--TRAFFIC INPUTS .............................................................................................36 5.1 AVERAGE ANNUAL DAILY TRUCK TRAFFIC (TRAFFIC VOLUME INPUTS)..........36 5.2 TRAFFIC CAPACITY.................................................................................................38 5.3 AXLE CONFIGURATION...........................................................................................38 5.4 LATERAL WANDER..................................................................................................39 5.5 WHEEL BASE ...........................................................................................................39 5.6 VEHICLE CLASS DISTRIBUTION AND GROWTH ...................................................40 5.7 MONTHLY ADJUSTMENT ........................................................................................42 5.8 HOURLY ADJUSTMENT...........................................................................................45 5.9 AXLES PER TRUCK CLASS .....................................................................................45 5.10 AXLE LOAD DISTRIBUTION FACTORS...................................................................46 5.11 SCREEN SHOTS FOR THE TRAFFIC INPUTS ........................................................47 CHAPTER 6--CLIMATE INPUTS .............................................................................................52 6.1 PROJECT LOCATION INFORMATION .....................................................................52 6.2 DEPTH TO WATER TABLE ......................................................................................53 v 6.3 CLIMATE STATIONS ................................................................................................54 6.4 CREATION OF SIMULATED CLIMATE STATION ....................................................55 6.5 USE OF CUSTOM CLIMATE FILES..........................................................................56 6.6 SCREEN SHOTS FOR THE CLIMATE INPUTS........................................................60 CHAPTER 7--DESIGN FEATURES AND LAYER PROPERTY INPUTS..................................62 7.1 AC (HMA) LAYER PROPERTIES: NEW AND EXISTING LAYERS ..........................62 7.1.1 Multi-Layer Rutting Calibration Parameters..........................................................62 7.1.2 HMA/AC Surface Shortwave Absorptivity.............................................................62 7.1.3 Endurance Limit ...................................................................................................63 7.1.4 Layer Interface Friction ........................................................................................63 7.1.5 Rehabilitation: Condition of Existing Flexible Pavement .......................................63 7.1.6 Milled Thickness of Existing HMA Layers.............................................................67 7.1.7 Screen Shots for the AC (HMA) Layer Properties: New and Existing Layers .......67 7.2 JPCP: NEW AND EXISTING LAYERS .....................................................................69 7.2.1 PCC Surface Shortwave Absorptivity ...................................................................69 7.2.2 Joint Spacing .......................................................................................................69 7.2.3 Sealant Type........................................................................................................69 7.2.4 Dowels.................................................................................................................69 7.2.5 Widened Slab ......................................................................................................70 7.2.6 Tied Shoulders.....................................................................................................70 7.2.7 Erodibility Index ...................................................................................................70 7.2.8 PCC-Base Contact or Interface Friction for JPCP ................................................70 7.2.9 Pavement Curl/Warp Effective Temperature Difference .......................................71 7.2.10 Foundation Support for Rehabilitation of Rigid Pavements ..................................72 7.2.11 Condition of Existing PCC Surface for JPCP Rehabilitation Design .....................72 7.2.12 Screen Shots for the JPCP Layer Properties: New and Existing Layers...............73 7.3 CRCP: NEW AND EXISTING LAYERS ....................................................................76 7.3.1 Inputs...................................................................................................................76 7.3.2 Screen Shots for the CRCP Layer Properties: New and Existing Layers..............77 CHAPTER 8--LAYER/MATERIAL PROPERTY INPUTS..........................................................79 8.1 PAVEMENT LAYERS FOR FLEXIBLE PAVEMENT DESIGN ...................................79 8.1.1 HMA and Asphalt Stabilized Base Layers ............................................................79 8.1.2. Base Layers ............................................................................................................83 8.1.3. Stabilized Subgrade ................................................................................................84 8.1.4. Embankment/Foundation Layers or Subgrade.........................................................85 8.1.5. Bedrock ...................................................................................................................85 8.2 PAVEMENT LAYERS FOR RIGID PAVEMENT DESIGN..........................................85 8.2.1. JPCP or CRCP Layers ............................................................................................86 8.2.2. Base Layers ............................................................................................................86 8.2.3. Stabilized Subgrade ................................................................................................87 8.2.4. Embankment/Foundation Layers or Subgrade.........................................................87 8.3 ASPHALT CONCRETE (AC) .....................................................................................87 8.3.1 Asphalt Layer, Thickness .....................................................................................87 8.3.2 Mixture Volumetric Properties ..............................................................................88 8.3.3 Mechanical Properties .........................................................................................90 8.3.4 Thermal Properties ..............................................................................................94 8.3.5 Screen Shots for the AC Properties: New and Existing Layers ............................95 8.4 PORTLAND CEMENT CONCRETE (PCC) NEW MIXES .......................................97 vi 8.4.1 General Properties...............................................................................................98 8.4.2 Thermal Properties ............................................................................................100 8.4.3 Mix Physical Properties: New and Intact Existing PCC Slabs............................101 8.4.4 Strength Properties ............................................................................................103 8.4.5 Screen Shots for the PCC Properties: New Layers ............................................106 8.5 PORTLAND CEMENT CONCRETE (PCC) EXISTING FOR REHABILITATION DESIGNS ..................................................................................109 8.5.1 Existing Intact PCC Slabs ..................................................................................109 8.5.2 Fractured PCC Slabs .........................................................................................110 8.5.3 Screen Shots for the Fractured PCC Properties.................................................111 8.6 UNBOUND AGGREGATE BASE MATERIALS AND SOILS....................................112 8.6.1 General Physical and Volumetric Properties ......................................................113 8.6.2 Resilient Modulus ..............................................................................................114 8.6.3 Poisson's Ratio ..................................................................................................120 8.6.4 Hydraulic Properties...........................................................................................121 8.6.5 Screen Shots for the Unbound Base and Subgrade Layer Properties ................122 8.7 CEMENT AGGREGATE BASE MIXTURES ............................................................124 8.8 STABILIZED SUBGRADE FOR STRUCTURAL LAYERS .......................................125 8.8.1 Screen Shots for the Stabilized Base/Subgrade Layer Properties......................126 8.9 BEDROCK...............................................................................................................128 8.9.1 Screen Shots for the Bedrock Properties ...........................................................128 CHAPTER 9--GEORGIA CALIBRATION FACTORS .............................................................130 9.1 BASELINE FILES FOR THE CALIBRATION FACTORS .........................................131 9.2 TRANSFER FUNCTION CALIBRATION COEFFICIENTS.......................................132 9.3 SCREEN SHOTS FOR THE CALIBRATION COEFFICIENTS.................................135 CHAPTER 10--CONCLUSIONS AND IMPLEMENTATION PLAN .........................................138 10.1 IMPLEMENTATION ACTIVITIES.............................................................................138 10.2 REMAINING IMPLEMENTATION ITEMS ................................................................140 10.2.1 Truck Traffic Input Library ..................................................................................141 10.2.2 Climate Data ......................................................................................................141 10.2.3. Materials/Layer Input Library ...............................................................................141 10.2.4. Recalibration and Verification ..............................................................................143 10.3 CONCLUSIONS ......................................................................................................144 CHAPTER 11--INPUT WORKSHEET ....................................................................................146 APPENDIX A--HMA DATABASE (KIM et al., 2019) ...............................................................162 APPENDIX B--UNBOUND LAYER MATERIAL PROPERTIES (KIM et al., 2013) ..................180 REFERENCES .......................................................................................................................183 vii LIST OF TABLES Table 2.1--Performance Indicators Predicted by Pavement ME Design .................................... 4 Table 2.2--Example Design Features to Revise for Flexible Pavement and HMA Overlay Designs Not Meeting the Design Criteria or Target Reliability .......................................12 Table 2.3--Example Design Features to Revise for Jointed Plain Concrete Pavement and Overlay Designs Not Meeting the Design Criteria or Target Reliability ..........................13 Table 2.4--Example Design Features to Revise for Continuously Reinforced Concrete Pavement and Overlay Designs Not Meeting the Design Criteria or Target Reliability ..14 Table 2.5--Hierarchical Input Levels.........................................................................................15 Table 3.1--Calibration Factors Recommended for New/Reconstructed Pavement Designs .....16 Table 3.2--Construction and Traffic Opening Dates .................................................................22 Table 4.1--Initial IRI Values......................................................................................................26 Table 4.2-- Flexible Pavement and HMA Overlay Design Criteria or Threshold Values............27 Table 4.3-- Jointed Plain Concrete Pavement Design Criteria or Threshold Values .................27 Table 4.4-- Continuously Reinforced Concrete Pavement Design Criteria or Threshold Values .....................................................................................................................................27 Table 4.5-- Composite and/or Semi-Rigid Pavement Design Criteria or Threshold Values ......28 Table 4.6--Terminal IRI and Corresponding GDOT HRI Ratings or Values ..............................29 Table 4.7--Reliability Level Recommended for Use with Pavement ME Design .......................32 Table 5.1--Lane Distribution Factor Recommended for Use with Pavement ME Design ..........37 Table 5.2--Median Truck Traffic Classification Groups Common to Georgia Roadways...........41 Table 5.3--Monthly Adjustment Factors for Non-Freight Routes; Seasonally Dependent .........43 Table 5.4--Monthly Adjustment Factors for Freight Routes; Seasonally Independent...............44 Table 5.5--Hourly Distribution Factors Recommended for Georgia ..........................................45 Table 5.6--Default Values for the Number of Axles per Truck Class.........................................46 Table 5.7--Normalized Axle Load Distribution Files included in the GDOT Database Library ...47 Table 5.8--Normalized Axle Load Distribution Factors for Vehicle Class 9 Tandem Axles........47 Table 6.1--Annual Depth to Water Table Recommended for Use.............................................54 Table 6.2--Climate Stations Available from AASHTOWare for Georgia....................................56 Table 6.3--Climate Stations Available from Custom Database for Georgia (To be updated when climate research is finalized) ...............................................................................57 Table 7.1--Ratios to Distribute Total Rut Depth to Individual Layers ........................................64 Table 7.2--MEPDG Condition Ratings for the GDOT PACES Rating or Composite Pavement Condition Index.............................................................................................................67 viii Table 7.3--Erodibility Category Index Recommended for Different Base Materials ..................71 Table 7.4--Base/Slab Friction Coefficient Recommended based on Different Layers below CRCP (AASHTO, 2015)................................................................................................77 Table 8.1--Minimum and Maximum Layer Thicknesses ...........................................................82 Table 8.2--HMA/AC Layer Thickness Ratios (R) to be Used in Combining Thin Layers with Lower Dense-Graded HMA/AC Layers .........................................................................82 Table 8.3--Volumetric Properties for Georgia's Dense-Graded Mixtures ..................................88 Table 8.4--HMA Mixtures with Level 1 Dynamic Modulus ........................................................90 Table 8.5--Binder Grades Typically Used in Georgia's Dense-Graded Mixtures ......................92 Table 8.6--Gradation for Georgia's Dense-Graded Mixtures ....................................................93 Table 8.7--Georgia Concrete Mixture Properties......................................................................98 Table 8.8--Georgia Concrete Fresh Mixture Properties ............................................................99 Table 8.9--Poisson's Ratio for Georgia Concrete Mixtures.......................................................99 Table 8.10--CTE for Georgia Concrete Mixtures ....................................................................100 Table 8.11--Recommended CTE Values for PCC Mixtures in Georgia that Contain Type I Portland Cement and Natural Sand (Kim, 2013) .........................................................100 Table 8.12--Recommended PCC Aggregate by Source ........................................................102 Table 8.13--Time Dependent Compressive Strength for Georgia Concrete Mixtures .............104 Table 8.14--Time Dependent Elastic Modulus for Georgia Concrete Mixtures .......................105 Table 8.15--Time Dependent Modulus of Rupture for Georgia Concrete Mixtures .................106 Table 8.16--Recommended Effective Modulus Values for Existing Intact PCC Slabs.............110 Table 8.17--Recommended Modulus Values for Fractured and Rubblized PCC Slabs ..........111 Table 8.18--Material Library Subgrade Properties..................................................................113 Table 8.19--Resilient Modulus Values for Granular Aggregate Base Materials in Georgia .....115 Table 8.20--Resilient Modulus Values Derived for Selected Subgrade Soils in Georgia.........115 Table 8.21--Resilient Modulus Values Derived for Subgrade Soil from DCP Tests for Use in Georgia ....................................................................................................................... 118 Table 8.22--Summary of the Adjustment Factors Recommended for Use in Georgia to Convert Backcalculated Layer Modulus Values to Laboratory Equivalent Modulus Values ......119 Table 8.23--Poisson's Ratio Suggested for Use for Unbound Layers.....................................120 Table 8.24--28-Day Strength and Elastic Moduli Suggested for Use for Cement Aggregate Base Layers................................................................................................................125 Table 8.25--Resilient Modulus and Poisson's Ratio Values Suggested for Use for Stabilized Subgrade Layers ........................................................................................................125 Table 8.26--Layer Properties for Bedrock ..............................................................................128 Table 9.1-- Input Levels used in Calibration of PMED Transfer Functions..............................130 ix Table 9.2-- GDOT Baseline Files ...........................................................................................132 Table 9.3-- HMA/AC Rutting: GDOT Calibration Factors........................................................133 Table 9.4-- Unbound Layer Rutting: GDOT Calibration Factors .............................................134 Table 9.5-- HMA/AC Bottom-Up Fatigue Cracking: GDOT Calibration Factors ......................134 Table 9.6--HMA/AC Thermal Transverse Cracking: GDOT Calibration Factors .....................134 Table 9.7--JPCP Mid-Slab Cracking: GDOT Calibration Factors (Use for all JPCP Applications: Overlays and Restoration) ..........................................................................................134 Table 9.8--JPCP Faulting: GDOT Calibration Factors (Use for all JPCP Applications: Overlays and Restoration) .........................................................................................................135 Table 9.9--CRCP Punchout: GDOT Calibration Factors (All CRCP Applications) ..................135 x LIST OF FIGURES Figure 2.1--Conceptual Flow Chart of the MEPDG Three-Stage Design/Analysis Process for AASHTOWare PMED (AASHTO, 2015)......................................................................... 6 Figure 2.2--MEPDG Output Summary Sheet ............................................................................ 9 Figure 5.1--Freight Routes Identified in Georgia ......................................................................44 Figure 6.1--MEERA-2 Grid Cell Locations................................................................................55 Figure 7.1--Relationship between GDOT's Load Cracking Number (All Severity Levels) included in PACES and the Total Area of Alligator Fatigue Cracking ............................66 Figure 8.1--New Pavement Structures Typically Required by GDOT .......................................81 Figure 8.2--HMA Database Collection Regions........................................................................91 Figure 8.3--Subgrade Classification and Modulus Inputs by County ......................................116 Figure 8.4--Estimating the Resilient Modulus from the Optimum Water Content ....................120 Figure 8.5--Limiting Layer Modulus Criterion of Unbound Aggregate Base Layers ................122 xi EXECUTIVE SUMMARY From the early 1960's through 1993, all versions of the American Association of State Highway and Transportation Officials (AASHTO) Design Guide were based on the empirical performance equations developed from the American Association of State Highway Officials (AASHO) Road Test (AASHTO 1993). The need for and benefits of a mechanistic-based pavement design procedure were recognized at the time when the 1986 Design Guide was adopted (AASHTO 1986). To meet that need, the AASHTO Joint Task Force on Pavements in cooperation with the National Cooperative Highway Research Program (NCHRP) and the Federal Highway Association (FHWA) sponsored the development of an AASHTO Mechanistic-Empirical (ME) pavement design procedure. NCHRP project 1-37A (ARA 2004a,b,c,d) produced rudimentary software that utilized existing ME-based models and databases reflecting current state-of-the-art pavement design procedures. The Mechanistic-Empirical Pavement Design Guide (MEPDG) was completed in 2004 and released to the public for review and evaluation. A formal review was completed by an independent set of consultants under NCHRP Project 1-40A, and version 1.0 of the MEPDG was submitted in 2007 to NCHRP, FHWA, and AASHTO for further consideration as an AASHTO Standard Practice. The MEPDG was formally adopted by AASHTO as an Interim Guide in 2008 (AASHTO, 2008). Pavement ME Design is a software upgrade to version 1.0 that became available in 2013. AASHTO is distributing and managing the software as an AASHTOWare product. This User Input Guide is more of an engineering manual for determining the inputs needed for pavement design engineers in Georgia to begin to use Pavement ME Design. Many State Highway Agencies (SHAs) implementing Pavement ME Design conduct a local calibration or xii verification effort to establish local inputs and determine the calibration factors that result in unbiased predictions. Forensic investigations, including materials testing and pavement performance data, are needed to establish the accuracy and bias of the distress transfer functions and International Roughness Index (IRI) prediction models. Georgia Department of Transportation (GDOT) also sponsored a local calibration effort and the results from that effort were used in preparing this User Input Guide. This manual has been updated from the previous MEPDG training manual (Report No. FHWA/GA-DOT-RD-014-1117) with recently measured materials properties, climate data, and traffic inputs. GENERAL NOTE: The final report for this project discusses the recommended default values to be used in design for the primary pavement design and rehabilitation strategies used in Georgia. xiii CHAPTER 1--INTRODUCTION The Georgia Department of Transportation (GDOT) currently uses the American Association of State Highway and Transportation Officials (AASHTO) Interim Design Guide for Design of Pavement Structures 1972 Chapter III Revised, 1981 for new pavement and rehabilitation design. As of 2008, however, AASHTO no longer supports this empirical-based pavement design procedure. AASHTO is supporting use of a mechanistic-empirical (ME) based procedure for both new and rehabilitation design of flexible and rigid pavements. An ME based design method represents a rational engineering approach that has been used by some agencies to replace the empirical AASHTO Guide for Design of Pavement Structures (AASHTO, 1993). The primary advantage of an ME based design system is that it is based on pavement fracture and deformation characteristics of all layers, rather than solely on the pavement's surface condition (ride quality). The Mechanistic-Empirical Pavement Design Guide (MEPDG), developed under National Cooperative Highway Research Program (NCHRP Project 1-37A, is a ME based method for designing new and rehabilitated flexible and rigid pavements (ARA, 2004). The concepts of ME based methods allow the pavement design engineer to quantify the effect of changes in materials, load, climate, age, and construction practices on pavement performance. Such a rational engineering design approach provides a reliable and cost-effective method of diagnosing pavement problems, as well as forecasting maintenance and rehabilitation needs. AASHTO adopted this procedure in 2008 and published the first edition of the Mechanistic-Empirical Pavement Design Guide - A Manual of Practice (MOP) for its use (AASHTO, 2008). A second edition of the MOP was published in 2015 and is included with the current version of the design software. A third edition was balloted and approved by AASHTO Committee of Materials and Pavements (COMP) and was published in early 2020. 1 This Input Guide was prepared for use by GDOT to determine the inputs for the AASHTOWare Pavement ME Design (PMED) software and to provide guidance on the use of PMED. 2 CHAPTER 2--OVERVIEW OF THE MEPDG DESIGN METHODOLOGY The MOP is based on ME design concepts, which means that the design procedure calculates pavement responses such as stresses, strains, and deflections, and accumulates the incremental damage from these responses over time. The procedure empirically relates the calculated responses in terms of damage to pavement distresses observed on roadway segments over time. This ME based procedure is shown in flowchart form in Figure 2.1. For a more complete discussion of the ME based concepts, procedure and transfer functions used to predict distress and smoothness, the designer is referred to the MOP, as well as to the "HELP" manual that is included in the PMED software and the NCHRP project 1-37A reports (ARA, 2004 a,b,c,d). This chapter of the Input Guide provides an overview of the transfer functions, design steps, input categories, and hierarchical input approach included in the MOP. The remaining chapters of this Input Guide are focused on determining the inputs to the software for predicting distress and smoothness over the design life of the pavement structure. 2.1 DISTRESS TRANSFER FUNCTIONS INCLUDED IN PMED SOFTWARE Chapter 5 in the MOP Second Edition includes a summary of the transfer functions for all types of pavements that are included in the MEPDG design and analysis methodology (AASHTO, 2015, 2020). Table 2.1 lists the performance indicators and the type of model or equation used to predict performance for use in design for each family of pavements included in the PMED software. Table 2.1 also lists the transfer functions and regression equations that are recommended for use in Georgia and whether or not they were locally calibrated for current versions of the software. The different pavement types are defined in Chapter 3 and local calibration is outlined in Chapter 9. In Table 2.1, the types pf pavement include flexible pavement and Hot Mix Asphalt (HMA) Overlays, inverted pavement, semi-rigid pavement, and rigid pavement such as Joint Plain 3 Concrete Pavement (JPCP), Continuous Reinforced Concrete Pavement (CRCP), and Short Joint Plain Concrete Pavement (SJPCP). Table 2.1--Performance Indicators Predicted by Pavement ME Design Type of Pavement Performance Indicator Type of Model3 Recommended for Use in Georgia Calibrated PMED Version4 HMA Rutting ME Transfer Function Yes, locally calibrated 2.3 Unbound Aggregate Base and ME Transfer Subgrade Rutting Function Yes, locally calibrated 2.3 Alligator Area Cracking; Bottom-Up ME Transfer Function Yes, locally calibrated 2.3 Fatigue Cracking Flexible Pavement and Cracking HMA Overlays Longitudinal Cracking; Top-Down ME Transfer Function No (see note 1) Cracking Thermal, Low-Temperature Cracking (Transverse) ME Transfer Function Yes, locally calibrated 2.3 International Roughness Index Regression Equation Yes, locally calibrated 2.3 Reflection Cracking; confined to HMA overlays Regression Equation Yes, locally calibrated 2.3 Alligator Fatigue Cracking ME Transfer Function Yes, not locally calibrated 2.3 HMA Rutting ME Transfer Function Yes, not locally calibrated 2.3 Inverted Pavement Unbound Aggregate Base and ME Transfer Subgrade Rutting Function Yes, not locally calibrated 2.3 Thermal, Low-Temperature Cracking (Transverse) ME Transfer Function Yes, locally calibrated 2.3 International Roughness Index Regression Equation Yes, not locally calibrated 2.3 Fatigue Cracking of Cementitious Layer ME Transfer Function No (see note 2) HMA Rutting, Fatigue Semi-Rigid Pavement Cracking, and LowTemperature Cracking; same ME Transfer Functions Yes, locally calibrated 2.3 as for flexible pavements International Roughness Index Regression Equation No (see note 1) Rigid Pavements JPCP & JPCP Overlays Faulting Fatigue Mid-Slab Cracking International Roughness Index ME Transfer Function ME Transfer Function Regression Equation Yes, locally calibrated Yes, locally calibrated Yes, locally calibrated 2.3 2.3 2.3 CRCP & CRCP Overlays Punchouts International Roughness Index ME Transfer Function Regression Equation Yes, not locally calibrated Yes, not locally calibrated 2.3 2.3 4 Type of Pavement SJPCP Overlay of HMA Performance Indicator Longitudinal Cracking Type of Model3 ME Transfer Function Recommended for Use in Georgia No (see note 1) Calibrated PMED Version4 NOTES: 1. The predicted distress or performance indicator should not be used to make design decisions or change the design, until that transfer function has been locally or globally calibrated. 2. The current GDOT policy is to allow base alternates in South Georgia. Granular aggregate base (GAB) or soil cement are typical options. In these cases, designs will be done using GAB base and current GDOT policy on thicknesses, until the semi-rigid designs are calibrated. 3. "ME Transfer Function" refers to those functions listed in the MOP 2nd/3rd Edition (AASHTO, 2015). 4. Transfer functions are verified up to referenced PMED version only. Future validation is necessary for subsequent versions of the software due to changes in model. 2.2 PAVEMENT DESIGN STEPS USING PAVEMENT ME DESIGN SOFTWARE Pavement design using the PMED software is an iterative process that can result in multiple acceptable designs. The specific design strategy for a project is selected external to the PMED software and is based on other factors, such as constructability, life cycle costs, and other policies established by GDOT. PMED, however, does include an optimization tool which defines the minimum thickness of an identified layer that satisfies all design criteria or threshold values entered by the user. The design-analysis process includes the following six steps. 5 Figure 2.1--Conceptual Flow Chart of the MEPDG Three-Stage Design/Analysis Process for AASHTOWare PMED (AASHTO, 2015, 2020) 6 Step 1: Select a trial design strategy (new pavement or rehabilitation design). The pavement designer can use GDOT's current design procedure (guidelines and catalog) to determine the trial design cross section as a starting point. Establishing the layer structure for all pavements as discussed under Chapters 7 and 8 of this User Input Guide. For ease of use within the initial implementation of the PMED Software, a set of baseline files was established and included in the GDOT MEPDG library. These files are listed and defined in Chapter 9 of this User Input Guide, because they are specific to the transfer function calibration coefficients to be used in Georgia. One of the appropriate files should be selected in setting up the trial design strategy. Step 2: Select the appropriate performance indicator or distress criteria and design reliability level for the project. Performance criteria can include bottom-up fatigue (alligator) cracking, total rut depth, thermal transverse cracking, and roughness (as estimated using the International Roughness Index [IRI]) for flexible pavement design. Transverse fatigue (midslab) cracking, joint faulting, and IRI are the performance criteria for jointed plain concrete pavements (JPCP), while punchouts, crack width, and IRI are the criteria for continuously reinforced concrete pavement (CRCP) design. The performance indicator criteria are obtained from GDOT policies for triggering major rehabilitation or reconstruction and are included in Chapter 4 of this User Input Guide. Step 3: Obtain all inputs for the trial design under consideration. This step can be a time consuming effort but is necessary for evaluating pavement designs using mechanisticempirical analysis. The designer must determine the inputs based on their impact on pavement performance. The inputs required to run the software can be obtained using one of three levels of effort. The hierarchical input levels are defined in Section 2.4 of this chapter. 7 The input categories include general project information, traffic, climate, design features, and pavement structure. The latter chapters of this User Input Guide are focused on determining values for the inputs to the PMED software. Worksheets are included in Chapter 11 for documenting the inputs for a specific design problem. These worksheets are intended to facilitate use of the PMED software. Step 4: Run PMED software and examine the inputs for engineering reasonableness. The pavement design engineer should examine the input summary to ensure the inputs are correct and what the designer intended. This step should be completed before or after each run. Step 5: Review and interpret the output in terms of the pavement performance and predicted reliability levels. The PMED software provides a summary of the predicted distresses and IRI of the pavement design as well as the reliability of the prediction for each distress. The user should assess if the trial design has met each of the performance indicator criteria at each of the chosen reliability levels for the project. Figure 2.2 shows an example of the summary output for a new HMA pavement design. The target distress (performance criteria) and predicted distress at the specified reliability level are listed followed by the target reliability level and achieved reliability level for the target distress. If the "Achieved" reliability is equal to or greater than the "Target" reliability, the pavement structure passes. If the reverse is true, however, the pavement fails. If any key distress fails, the designer must alter the trial design to correct the problem. If further design changes are no longer feasible, available preventative maintenance practices may be considered as alternative solutions at the time of failure. 8 Design Inputs Design Life: 20 years Design Type: Flexible Pavement Design Structure Base construction: July, 1993 Pavement construction: August, 1993 Traffic opening: September, 1993 Climate Data 30.783, -83.277 Sources 31.536, -84.194 33.948, -83.327 34.272, -83.83 Traffic Layer type Flexible NonStabilized Subgrade Subgrade Material Type Default asphalt concrete Crushed stone A-2-7 A-6 Thickness (in.): 4.0 10.0 12.0 Sem i-infinite Volumetric at Construction: Effective binder content (%) 9.1 Air voids (%) 6.0 Age (year) 1993 (initial) 2003 (10 years) 2013 (20 years) Heavy Trucks (cumulative) 170 310,463 620,925 Design Outputs Distress Prediction Summary Distress Type Terminal IRI (in./mile) Permanent deformation - total pavement (in.) AC bottom-up fatigue cracking (percent) AC thermal cracking (ft/mile) AC top-down fatigue cracking (ft/mile) Permanent deformation - AC only (in.) Distress @ Specified Reliability Target Predicted 172.00 137.26 0.50 0.32 25.00 3.46 1500.00 511.81 2000.00 4463.29 0.50 0.17 Reliability (%) Target 90.00 90.00 50.00 50.00 90.00 90.00 Achieved 99.36 100.00 93.63 100.00 57.70 100.00 Criterion Satisfied? Pas s Pas s Pas s Pas s Fail Pas s Figure 2.2--MEPDG Output Summary Sheet The distress and IRI are output by graphs and tables at the end of each month over the design period, so the designer knows the time at which any of the design criteria are exceeded. In addition, materials properties and other factors are output on a month by month basis over the design period. The designer should examine the output material properties, climate summaries, traffic graphs, layer moduli, joint load transfer for JPCP, and other factors to assess their reasonableness. For flexible pavements, the output includes the HMA Dynamic Modulus (E*) and resilient modulus (Mr) for unbound layers for each month over the design period, while for rigid pavements the slab elastic modulus and flexural strength, the base elastic modulus, and subgrade k-value are also provided for each month throughout the design period. If the trial design has either input errors, material output anomalies, or has exceeded the performance criteria at the given level of reliability, revise the inputs/trial design and rerun the 9 program. Iterate until the performance criteria have been met or use the optimization tool to determine the minimum layer thickness for the design features selected. When the target reliability level has been achieved, the trial design may be considered a feasible design strategy. Step 6: Revise the trial design, as needed. If any of the criteria has not been met (target reliability not achieved), determine how this deficiency can be remedied by altering the design and rerun the software until all criteria have been met at the target reliability level. While layer thickness is important, many other design factors also affect distress and IRI or smoothness. The designer must examine the performance prediction and determine which design feature to modify to improve performance (e.g., layer thickness, materials properties, layering combinations, geometric features, dowel diameter, and other inputs). This User Input Guide identifies the design features commonly used in Georgia that should be considered to reduce specific performance indicators. Tables 2.2 through 2.4 provide some general guidelines for revising a design for which the calculated reliability of a specific distress is less than the target value. In addition, the MOP provides general guidance on revising the trial design when the performance criteria have not been met. This "trial and error" process allows the pavement designer to essentially "build the pavement in his/her computer" prior to building it in the field to see if it will perform. If there is a problem with the design and materials for the given subgrade, climate, and traffic, it can be corrected, and an early failure avoided. 10 2.3 INPUT CATEGORIES The inputs are grouped into five categories: (1) General Project Information (including the performance criteria), (2) Traffic, (3) Climate, (4) Design Features, and (5) Structure (including material properties). Each one of these is discussed separately in latter chapters. The GDOT PMED input library contains predefined project elements for traffic, climate, and material inputs. This Guide discusses the various categories of default inputs available in GDOT's PMED input library. Some of the features listed in Tables 2.2 through 2.4 include layer properties that should not be changed when doing traditional designs. However, there are cases when those features can be revised to achieve an acceptable design--as an example, design-build type projects. 11 Table 2.2--Example Design Features to Revise for Flexible Pavement and HMA Overlay Designs Not Meeting the Design Criteria or Target Reliability Distress & IRI Design Feature Revisions to Minimize or Eliminate Distress Increase thickness of HMA layers. For thicker HMA layers (> 5-inches), increase dynamic modulus by using stiffer or harder asphalt. Alligator Cracking (Bottom Initiated) For thinner HMA layers (<3-inches), reduce dynamic modulus by using softer asphalt. Use a polymer modified asphalt in the lower HMA layer. Increase density, reduce air void of HMA base layer. Use an unbound granular aggregate base with a higher resilient modulus. Increase the thickness of the granular aggregate base layer. Use softer asphalt in the wearing surface or asphalt with a colder lower temperature grade. Thermal Transverse Reduce the creep compliance of the HMA surface mixture. Cracking Increase the indirect tensile strength of the HMA surface mixture. Increase the thickness of the HMA layers. Increase the asphalt content of the surface mixture. Increase the dynamic modulus of the HMA layers by using harder or stiffer asphalt. Rutting in HMA Use a polymer modified asphalt in the layers near the surface. Reduce the asphalt content in the HMA layers Increase the amount of crushed aggregate. Increase the amount of manufactured fines in the HMA mixtures. Increase the resilient modulus of the aggregate base; increase the density of the Rutting in Unbound Layers and Subgrade aggregate base. Stabilize the upper foundation layer for weak or collapsible soils. Use a thicker layer of a granular aggregate base layer. Place a layer of select embankment material with adequate compaction. Increase the HMA thickness. Reduce the predicted distresses that deteriorate smoothness. Require more stringent smoothness criteria and greater incentives (building the IRI HMA pavement smoother at the beginning). Improve the foundation; use thicker layers of non-frost susceptible materials Stabilize any expansive soils Place subsurface drainage system to remove ground water. Use an engineered interlayer to mitigate reflective cracks. Reflection Cracking Increase HMA overlay thickness. Increase the modulus of the HMA overlay. 12 Table 2.3--Example Design Features to Revise for Jointed Plain Concrete Pavement and Overlay Designs Not Meeting the Design Criteria or Target Reliability Distress & IRI Modifications to Minimize or Eliminate Use dowels and increase their diameter as needed. Do not increase slab thickness to achieve faulting criteria. Increase erosion resistance of base (specific recommendations for each type of base). Joint Faulting Minimize permanent curl/warp through curing procedures that eliminate built-in temperature gradient (e.g., construct pavement at night, or pave in later afternoon to avoid high solar radiation). Portland Cement Concrete (PCC) tied shoulder. Widened slab (by 1 foot maximum to 13 feet). Reduce joint spacing. Increase slab thickness. Use PCC with lower coefficient of thermal expansion. Increase PCC strength (but not more than 10 percent). Slab Cracking Reduce joint spacing. Minimize permanent curl/warp through curing procedures that eliminate built-in temperature gradient (e.g., construct pavement at night, or pave in later afternoon to avoid high solar radiation). PCC tied shoulder (separate placement or monolithic placement better). Widened slab (by 1 foot maximum to 13 feet). Decrease joint spacing. Joint Crack Width (to reduce joint faulting) Reduce PCC coefficient of thermal expansion. Build JPCP to set at lower temperature (cool PCC, place at cooler temperatures). Reduce drying shrinkage of PCC (increase aggregate size, decrease water-cement ratio, decrease cement content). Joint Load Transfer Efficiency (LTE) to reduce joint faulting Use mechanical load transfer devices (dowels). Increase diameter of dowels. Reduce joint crack width (see joint crack width recommendations). Increase the size of the larger aggregate particles. Reduce the predicted joint faulting and cracking distresses that will reduce roughness. IRI JPCP Require more stringent smoothness criteria and greater incentives (e.g., reduce the initial as constructed IRI). Improve the foundation; use thicker layers of non-frost susceptible materials. 13 Table 2.4--Example Design Features to Revise for Continuously Reinforced Concrete Pavement and Overlay Designs Not Meeting the Design Criteria or Target Reliability Distress & IRI Modifications to Minimize or Eliminate Build CRCP to set at lower temperature (cool PCC, place during cooler temperatures). Transverse Crack width Reduce drying shrinkage of PCC (increase aggregate size, decrease w/c ratio, decrease cement content). Increase percent longitudinal reinforcement. Reduce depth of reinforcement (minimum cover over steel: 3.5 in). Reduce PCC coefficient of thermal expansion (change larger aggregate). Transverse Crack Reduce crack width (see crack width recommendations). LTE Reduce depth of reinforcement. Increase slab thickness. Increase percent longitudinal reinforcement. Reduce crack width over analysis period (see crack width recommendations). Punchouts Increase PCC strength (maximum of 10 percent). Increase erosion resistance of base (specific recommendations for each type of base). Minimize permanent curl/warp through curing procedures that eliminate built-in temperature gradient. PCC tied shoulder or widened slab. Reduce the predicted distresses that deteriorate smoothness. IRI CRCP Require more stringent smoothness criteria and greater incentives (e.g., reduce the initial IRI at construction). Improve the foundation; use thicker layers of non-frost susceptible materials. 2.4 HIERARCHICAL APPROACH FOR DETERMINING INPUTS The hierarchical input approach provides the designer with a great deal of flexibility to obtain the inputs for a project based on the importance of the parameter and/or project and available resources. The hierarchical approach is employed with regard to traffic, materials, and condition of existing pavement inputs.1 1 The hierarchical approach for determining the inputs needed by the MEPDG is a feature not found in existing versions of the AASHTO Guide (AASHTO 1986, 1993) and other ME-based methods. Currently, input level has no effect other than accuracy of the input parameter (which is important for critical inputs), except for low-temperature thermal cracking of HMA wearing surfaces. For thermal cracking, the standard error of the transfer function is dependent on the input level (see Chapter 9 of this User Input Guide or Section 5 of the MOP Second Edition). 14 Three levels for most of the inputs are available to the designer. Table 2.5 defines each input level. One of three levels can be used to estimate the values for each input. However, the highest level of input available was used in calibrating the MEPDG transfer functions, both at the global and regional levels. Further discussion on this topic is found in Chapter 9. For a given design project, inputs can be obtained using a mix of levels, such as dynamic modulus of HMA mixtures from Level 1, traffic load spectra from Level 3, and subgrade resilient modulus from Level 2. It is important to realize that no matter what input design levels are used, the computational algorithm for damage and distress is identical. The same models or transfer functions are used to predict distress and smoothness no matter what input levels are used. Input Level 1 2 3 Table 2.5--Hierarchical Input Levels Definition of the Level Input parameter based on site specific data and information. Level 1 represents the case when the user has the greatest knowledge about the input parameter for the specific project. This input level has the highest level of testing (data collection costs) for determining the input value. Input level 1 is recommended for projects having unusual site features and/or considering the use of new materials. Regression equations are used to determine the input value. The data collection and testing for this input level is simpler and less costly. Input level 2 is recommended for use for routine pavement designs and standard materials. Level 3 inputs are based on "best-guessed" (default) values. The Level 3 inputs are based on global or regional default values. This input level requires the minimum amount of testing, and as such, results in the least knowledge about the input parameter for the specific project. Input level 3 is recommended for use when the other input levels are unavailable. 15 CHAPTER 3--GENERAL PROJECT INFORMATION This chapter provides guidance on determining the input values for the General Project Information parameters for designing new and rehabilitated pavements in Georgia. Example screen shots are included at the end of this chapter for the general project information inputs. 3.1 DESIGN AND PAVEMENT TYPE STRATEGIES The following sections outline general pavement design strategies for common pavement project types in Georgia. Table 3.1 provides a summary of the recommended calibration factors for each pavement design strategy listed in this section based on their inclusion in the local calibration process. Table 3.1--Calibration Factors Recommended for New/Reconstructed Pavement Designs Pavement Type Pavement Design Strategy Recommended Calibration Factors Conventional Local GDOT Deep Strength & Full depth Local GDOT Flexible and HMA Overlays Semi-rigid HMA Overlays of Conventional, Deep-strength, and Full-depth Flexible Pavements, and JPCP HMA Overlays of CRCP, Fractured JPCP and CRCP Local GDOT Global Global HMA with soil cement Global Rigid and PCC Overlays Inverted Pavements JPCP CRCP PCC Overlays (All Types) Global Local GDOT Global Global NOTE: Local GDOT calibration factors values are located in Chapter 9. 16 3.1.1 New/Reconstructed Flexible Pavements and HMA Overlays New and reconstructed HMA surfaced pavements, as well as HMA overlays, included in the PMED software are listed below in two groups: those verified using the Long Term Pavement Performance (LTPP) sites and non-LTPP pavement management sections and those not included in the verification-calibration process. If pavement design strategies are used that were not included in the local calibration process, the global calibration factors have to be used.2 More detailed discussions on the types of pavement included in the local calibration and verification process are found in Chapter 9 and the final research report for this project (RP 11-17). 1. Flexible pavements included in verification-local calibration process: GDOT calibration coefficients of the transfer functions are provided for all of the following flexible pavement types (see Chapter 9): 1) Conventional flexible pavements: Thin HMA layers (total HMA thickness less than 7 inches) and thick aggregate base layers (crushed gravel and soil-aggregate mixtures), greater than 10 inches in thickness with and without stabilized subgrades. 2) Deep strength and full-depth flexible pavements: Full-depth and deep-strength were combined into one type of flexible pavement for the GDOT calibration study. Fulldepth is defined as HMA layers placed directly on the prepared embankment or on a stabilized subgrade. Deep-strength is defined as a thick HMA (a wearing surface, a binder layer, and a base layer exceeding 7 inches in thickness) placed over a granular aggregate base (GAB) material with or without a stabilized subgrade. 2 Fourteen baseline files (6 for new pavement designs and 8 for rehabilitation designs) are included in the GDOT database library, which can be used as a starting point in setting up the trial design structure. These baseline files contain the appropriate GDOT calibration coefficients for each transfer function, even for the design strategies used on an infrequent basis in Georgia. The ten baseline files are listed and defined in Chapter 9 of this User Input Guide. 17 3) Semi-rigid pavements: HMA mixtures placed over Cement Treated Base (CTB), Cement Aggregate Mixtures (CAM), or lime-fly ash stabilized base layers without an unbound aggregate layer. Semi-rigid pavements were excluded in the original calibration completed under NCHRP Projects 1-37A (ARA 2004 a,b,c,d) and 1-40D (NCHRP 2006). More recently, semi-rigid pavements were included during the 2018 global recalibration efforts. The global calibration factors should not be used for semirigid pavements until they have been verified using the GDOT semi-rigid pavement sections. Six semi-rigid pavement test sections were included in the local calibration study for GDOT. Most of the six projects had little alligator area cracking. Calibration factors are provided from these sections in Chapter 9 of this User Input Guide, but additional sections need to be included over time to confirm these calibration coefficients. 4) HMA overlays of all conventional, deep-strength, and full-depth flexible pavements, and JPCP. 2. Flexible pavements not Included in verification-local calibration process: Calibration coefficients of the transfer functions and layer inputs were established and recommended from other agency studies for the following pavement types (see Chapter 9): 1) HMA overlays of CRC pavements, as well as HMA overlays of fractured JPCP and CRCP. 2) Inverted pavements which include an HMA surface over a GAB layer over a CTB or soil cement layer. 18 3.1.2 New/Reconstructed Rigid Pavements and PCC Overlays New and reconstructed PCC surfaced pavements, as well as PCC overlays, that were included or excluded from the local calibration refinement process are listed below.3 1. Rigid pavements included in verification-local calibration process: GDOT calibration coefficients of the transfer functions are provided for the following rigid pavement types (see Chapter 9): 1) Jointed Plain Concrete pavements (JPCP) include transverse joints spaced to accommodate temperature gradient and drying shrinkage stresses to minimize cracking. The joints include dowels to complement the aggregate interlock in providing load transfer. GDOT JPCP sections used in the calibration had a thickness range of 8 to 12 inches and were placed on HMA, cement stabilized, and granular aggregate bases. Joint spacing ranged from 15 to 30 feet. 2. Rigid pavements not included in verification-local calibration process: Calibration coefficients of the transfer functions and layer inputs were established and recommended from other agency studies (see Chapter 9): 1) CRC pavement includes PCC slab cast without transverse joints and containing longitudinal steel typically in the range of 0.5 0.8 percent of the cross-sectional area. The PCC surface develops transverse cracks and the design should ensure that the cracks remain tight and provide good load transfer during the service life of the pavement. A few CRCP sections were included in the verification-calibration process for GDOT, but the design features were generally confined to specific values. 3 Footnote 2 also applies to rigid pavements. 19 Calibration factors are provided from these sections, but additional sections need to be included over time to confirm the GDOT calibration coefficients (see Chapter 9). 2) PCC Overlays of all types of rigid and flexible pavements, including bonded PCC overlay of rigid pavements, unbonded PCC overlay of rigid pavements, and PCC overlay of flexible pavements. The same calibration factors used for new JPCP or CRCP can be used for these designs. 3.1.3 Pavement Preservation and Preventive Maintenance Pavement preservation treatments have shown to impact the structural performance and regional calibration factors when applied to the HMA surface early in the pavement's life (Von Quintus and Moulthrop, 2007a and 2007b). Most of the roadway segments included within the local calibration process for GDOT included the use of pavement preservation and/or preventive maintenance strategies, with the exception of the LTPP SPS projects. Thus, the local calibration values presented in Chapter 9 account for the effects of pavement preservation and preventive maintenance activities commonly used by GDOT. If GDOT's preservation/maintenance policies change over time, the local calibration factors should be checked to validate whether there is a further reduction in the structural related distresses (bias between the predicted and observed values). 3.2 PROJECT FILE/NAME The designer should use a simple but descriptive name for the analysis that can be easily identified in the projects files created by the PMED software. The designer should enter appropriate information to identify the project for pavement design purposes and future reference. 20 The amount of detail is up to the designer.4 The information for this category of inputs has no impact on the analyses or distress predictions. 3.3 DESIGN LIFE The design life of a newly reconstructed pavement is the time from opening to traffic until the pavement has structurally deteriorated to the point when significant rehabilitation/reconstruction is needed exceeding one of the threshold values or design criteria (refer to step #8 of Section 4 in the Pavement ME Design software manual). The design life for all new pavement and rehabilitation designs is 20 years. The software can handle design lives from 1 year (e.g., detour) to over 50 years. In fact, the software program has the ability to analyze 100-year designs. The design life for "long-life" pavements is defined as 35 to 50 years. However, the distress models have not been calibrated using sections with 35+ year service lives and therefore the user needs to exercise caution while interpreting results using design lives greater than 35 years. 3.4 BASE AND PAVEMENT CONSTRUCTION & TRAFFIC OPENING DATES 3.4.1 New Construction Construction completion and traffic opening dates are site construction features. These dates are keyed to the monthly traffic loadings and monthly climatic inputs which affect all layer moduli, including the subgrade modulus. The time reference is keyed to the first day of the month. 4 The name of the baseline files included in the GDOT database library can be used as an example (see Chapter 9). 21 In the case of rigid pavements, the construction month also determines the PCC set (or zerostress) temperature, strength, and elastic modulus. The set temperature provides the temperature baseline for the calculation of joint openings during the design life. The strength and elastic modulus vary monthly over the entire design life and are used in fatigue cracking and joint faulting predictions. Different construction months can affect performance due to climatic conditions for that month. For larger projects, these dates are difficult to accurately define during design. The designer should select the most likely month for construction and opening the roadway to traffic. These dates are more important for rigid pavements than for flexible pavements, and more importantly, distresses are less sensitive to these dates than for other inputs except for designing temporary pavement structures for detours. Table 3.2 provides the recommended months when the roadway is periodically opened to traffic as different segments of the project are completed or if the dates are unknown because construction scheduling and phasing have yet to be defined. Specifying any month is defined as the first day of that month. For large projects that extend into different paving seasons, each paving season can be evaluated separately. Table 3.2--Construction and Traffic Opening Dates Design Pavement Base Construction Pavement Type Month Construction Month New Flexible May June Construction Rigid NA June Rehabilitation HMA Overlay PCC Overlay NA NA June June NOTE: NA Not applicable. Traffic Opening Month July August June August 22 3.4.2 Rehabilitation The construction completion date of the existing pavement is required for all rehabilitation designs. This date should represent the time when pavement construction was completed. The predicted distresses and performance indicators are less sensitive to this date than for the construction and opening to traffic date for the overlay. Table 3.2 lists the recommended overlay and traffic opening months for rehabilitation projects when they are unknown. Another issue related to rehabilitation design is when an overlay is being designed for an existing pavement that already has one or more overlays, because only one overlay can be simulated in the program. The following provides some guidance on determining the date of original construction. 1. If the existing overlay is thin or most of it is being milled as part of the rehabilitation strategy, the year the original pavement was opened to traffic should be entered. 2. If a thick structural overlay exists (relative to the existing original pavement surface) and most of that overlay is left in place, the year the structural overlay was opened to traffic should be entered for the original pavement construction. 3. If the user is unsure what date to use, enter the date the original pavement was built or constructed, or just assume the pavement is 30 years old. 3.5 SCREEN SHOTS FOR GENERAL INFORMATION The following are screen shot examples that show the General Information for the rehabilitation of flexible such as Asphalt Concrete (AC) over AC and rigid pavements (AC over JPCP). The drop-down arrows are used to access or select different design and pavement types and other information for a specific project. 23 AC over AC and AC over JPCP 24 CHAPTER 4--PERFORMANCE CRITERIA Performance criteria are used to ensure a new pavement or rehabilitation design strategy performs satisfactorily over its design life. Performance of a pavement is measured in terms of the key distresses and smoothness, as measured by the IRI (refer to Table 2.1 in Chapter 2 of this User Input Guide and Section 5 of the Pavement ME Design software manual). The designer selects performance criteria or threshold limits that relate directly to the need for rehabilitation. Example screen shots showing the performance criteria are included at the end of this chapter. 4.1 INITIAL INTERNATIONAL ROUGHNESS INDEX (IRI) The initial IRI is the average IRI value measured after construction and is entered into the input screen for the performance criteria (refer to step #10 of Section 5 in the GDOT Pavement ME Design software manual). This initial value should be determined from construction records of previously placed HMA or PCC surfaces under comparable conditions--previous year construction records. The IRI reported by GDOT is based on a half car simulation of the longitudinal profile data, while the IRI reported by LTPP and used in the development of the global IRI regression equation was based on a quarter car simulation. The values resulting from a quarter car simulation will be consistently higher in comparison to a half car simulation. As such, the GDOT initial IRI values cannot be entered directly in the PMED. If this value is unknown for some conditions and/or pavement type, the values in Table 4.1 are recommended for use for different pavement types. 25 Table 4.1--Initial IRI Values Type of Pavement Type of Wearing Surface GDOT HRI Rating, Initial IRI Rating, mm/km in./mi. Open-Graded Friction Flexible & Course/Porous European Mix (PEM) 750 53 HMA Stone Matrix Asphalt (SMA) Mixture 825 59 Overlays Dense-Graded HMA State Routes 900 64 Dense-Graded HMA Urban Routes 1175 84 Rigid JPCP CRCP 900 64 700 50 NOTE: GDOT HRI Rating is based on an analysis of the longitudinal profile data using a half car simulation, while the IRI Rating above is based on an analysis of the longitudinal profile data using a quarter car simulation. 4.2 DISTRESS CRITERIA OR THRESHOLD VALUES Performance criteria (or Analysis Parameters on the software window) are used to ensure that a pavement design will perform satisfactorily over its design life. Critical limits are selected and used by the designer to judge the adequacy of a design, which represent the condition of pavements that trigger some type of major rehabilitation or reconstruction activity. These criteria are similar in concept to the current AASHTO Design Guide (AASHTO, 1993) with the use of only the terminal serviceability index levels. These design criteria should not represent levels of distress or surface conditions that trigger some type of maintenance or non-structural repair. Distress specific design criteria are a policy decision of GDOT and determined from information included in GDOT pavement management database (Pavement Condition Evaluation System [PACES] for flexible pavements and Concrete Pavement Condition Evaluation System [CPACES] for rigid pavements). The consequence of a project exceeding a performance criterion is requiring earlier than programmed major rehabilitation. The distress or performance indicator values recommended for design at the design reliability are listed in Tables 4.2 to 4.5 by type of pavement, which are defined and measured in accordance 26 with the Distress Identification Manual (FHWA, 2003). The following paragraphs provide more discussion on the MEPDG design criteria relative to the GDOT values and policy decisions. Table 4.2-- Flexible Pavement and HMA Overlay Design Criteria or Threshold Values Performance Indicator Roadway Type (number of lanes are in both directions) Fatigue (Load) Cracking AC TopDown Fatigue CrackingA, ft/mile AC BottomUp Fatigue Cracking, % Thermal Cracking, ft./mi. Permanent Deformation (Rutting) Total Pavement, in. AC Only, in. Non- 2-Lane State Route 5,000 25 1,500 0.40 0.35 Interstate 4-Lane Roadway 5,000 15 1,500 0.40 0.35 Interstate Rural and Urban 5,000 10 1,000 0.35 0.30 Note A: A value of 5,000 ft./mi. is recommended so the program does not iterate on this value when using the optimization tool. The MOP does not recommend using the AC Top-down fatigue cracking model for design purposes. Future versions of PMED (v2.6+) has a new top-down cracking model. Table 4.3-- Jointed Plain Concrete Pavement Design Criteria or Threshold Values Roadway Type (number of lanes are in both directions) Performance Indicator Mean Joint Transverse Faulting, in. Cracking, % slabs Non-Interstate 2-Lane, State Route 4-Lane Roadway 0.20 10.0 0.20 10.0 Interstate Rural and Urban 0.125 10.0 Table 4.4-- Continuously Reinforced Concrete Pavement Design Criteria or Threshold Values Roadway Type (number of lanes are in both Performance Indicator directions) Punchouts, 1/mile Non-Interstate 2-Lane, State Route 4-Lane Roadway 10 10 Interstate Rural and Urban 5 27 Table 4.5-- Composite and/or Semi-Rigid Pavement Design Criteria or Threshold Values Performance Indicator Roadway Type (number of lanes are in both directions) Fatigue (Load) Cracking AC TopDown Fatigue CrackingA, ft/mile AC Bottom- Up Fatigue Cracking, % Thermal Cracking, ft./mi. Fatigue Fracture of Chem. Stabilized LayerB, % Permanent Deformation (Rutting) Total AC Pavement, Only, in. in. AC Total Cracking Fatigue Cracking (Bottom- Up & Reflective), % Transverse Cracking (Thermal & Reflective)A, ft/mile NonInterstate 2-Lane State Route 4-Lane Roadway 5000 5000 25 1,500 25 15 1,500 25 0.40 0.35 25 0.40 0.35 15 5000 500 Rural Interstate and 5000 10 1,000 25 0.40 0.35 10 5000 Urban Note A: A value of 5,000 ft./mi. is recommended so the program does not iterate on this value when using the optimization tool Note B: No information is available to provide recommendation for this value. 25% is currently the default value in PMED 4.2.1 Terminal IRI Criterion The terminal IRI for which the pavement is considered too rough and requires some type of rehabilitation is a required input. The IRI is predicted over time from the initial IRI and other predicted distresses and a site factor, which is explained in Chapter 5 of the MOP Second and Third Editions (AASHTO, 2015, 2020). Table 4.6 lists the terminal IRI ratings considered to be too rough, and the corresponding GDOT HRI Ratings for these criteria. 4.2.2 Fatigue (Load-Related) Cracking Criterion--Flexible Pavements Two types of load-related cracking in flexible pavement are included in the PMED Design software: alligator or bottom-up fatigue cracking in terms of percent of total lane area and longitudinal or top-down fatigue cracking in terms of feet per mile (refer to Table 2.1). 28 In the MEPDG design methodology, bottom-up fatigue (alligator) cracking is assumed to initiate at the bottom of all HMA layers, while top-down (longitudinal) fatigue cracking is assumed to initiate at the surface of the HMA wearing surface (top-down cracking). Alligator or bottom-up fatigue cracking should be used as the design criteria. The surface initiated--longitudinal cracking is not recommended for use as a design criterion at this time. GDOT should consider top down cracking model when the model is fully implemented in the PMED software. The designer should review the predicted longitudinal cracking values but not make any design changes based on the predicted length of longitudinal cracks. Bottom-up fatigue cracking is the input for new construction design problems, while asphalt concrete (AC) total cracking (bottom-up plus reflective cracks) are the inputs for a rehabilitation design problem HMA overlays. Reflective cracking calculated by the PMED software is the percentage of cracks in the existing wearing surface that reflect through the HMA overlay. Total cracking is the combined area of new bottom-up fatigue cracks in the HMA overlay plus any cracks in the existing HMA wearing surface that have reflected through the HMA overlay. Table 4.6--Terminal IRI and Corresponding GDOT HRI Ratings or Values Pavement Type Flexible Roadway Type Pavements & Semi-Rigid JPCP CRCP (number of lanes HMA Overlays are in both directions) GDOT HRI Rating; mm/km IRI Rating; in/mi GDOT HRI Rating; mm/km IRI Rating; in/mi GDOT HRI Rating; mm/km IRI Rating; in/mi GDOT HRI Rating; mm/km IRI Rating; in/mi NonInterstate Route 2-Lane, State 4-Lane Roadway 3090 2460 220 175 3230 2460 230 175 3090 2460 220 175 2460 2460 175 175 Interstate Rural & Route Urban 2460 175 2460 175 2460 175 2460 175 29 4.2.3 Permanent Deformation (Rut Depth) Criterion--Flexible Pavements The PMED software requires the entry of two rut depth (permanent deformation) design criteria for flexible pavements: HMA rutting and total rutting (refer to step #11 of Section 5 in the GDOT Pavement ME Design software manual). The design criteria should be the same for both the HMA rutting and total rutting (refer to Table 4.2). 4.3 DESIGN RELIABILITY The design reliability included in the MEPDG design methodology is similar, in concept only, to that in the AASHTO Design Guide (AASHTO, 1993). In PMED, a design may specify the desired level of reliability for each distress type and smoothness. Selected design reliability levels may vary by distress type and IRI or may remain constant for each. The level could be decided by weighing the consequence of reaching the terminal condition earlier than the desired design life. Since reliability can significantly impact the pavement predictions, engineering judgement and experience should always be used when selecting a particular value. Design reliability is defined as the probability that the predicted distress will be less than the critical level over the design period. For example, if 10 projects were designed and constructed using PMED and the design reliability for rutting was set to 90 percent for each project, one of those projects, on average, would show more rutting than the threshold value at the end of the design period. In other words, the reliability level of 90 percent represents the probability (9 out of 10 projects) that the mean rutting for the project will not exceed the total rut depth criterion. As a result, design reliability should be selected in balance with the desired performance criteria. The selection of a high design reliability level (e.g., 99 percent) and a very low performance criterion (3 percent alligator cracking) might make it almost impossible to build. At the present 30 time, the selection of a very high level of design reliability (e.g., greater than 96 percent) is not recommended because this may significantly increase construction costs. Table 4.7 lists the reliability levels recommended for different types of roadways, except for reflection and thermal or transverse cracks. The design reliability for reflection and thermal cracks is 50 percent. The design reliability for reflection cracks is hard-coded in the PMED software as 50 percent and cannot be changed. The design reliability for thermal cracking is not hard-coded and needs to be entered by the user as 50 percent. If GDOT uses PMED software Version 2.5.5 or newer, Table 4.7 should be updated as total cracking (reflected and new) has its own reliability input. The reason 50 percent reliability is recommended for thermal cracks is the mechanism for these cracks in Georgia is different from the mechanism included in the PMED software thermal cracks caused by one or more cold temperature events. The PMED software does not predict any thermal cracks (caused by cold temperature events) for typical mixtures and climates in Georgia. Many roadway segments used in the calibration process, however, exhibited significant lengths of block cracking that are interpreted in the software as transverse cracking. Therefore, thermal cracks predicted in PMED are not believed to be a result of a low temperature event and instead are indications of block or transverse cracking in the roadway section. Bias was removed between the predicted thermal cracks and observed transverse cracks, but the standard error of the transfer function is large because the mechanisms for the predicted thermal cracks and observed transverse cracks are different. As such, the predicted mean amount of thermal cracks is suggested for use in determining the design features and binder grade of the HMA wearing surface. It should be noted that the PMED software V2.5.5 and newer version adjust the calibration factor for transverse cracking based on Mean Annual Air Temperature (MAAT). Therefore, the predicted amount of transverse cracks will be increased in warm climates. 31 Table 4.7--Reliability Level Recommended for Use with Pavement ME Design Recommended Reliability Level, % Type of Roadway All Performance Indicators, except for AC Permanent Deformation (Total Pavement) & Thermal Cracking AC Permanent Deformation (Total Pavement) & Thermal Cracking Interstate & Primary Arterials 95 50 Minor Arterials & Major Collectors 90 50 Low Volume (less than 500 trucks per day in both directions) 75 50 & Local Roadways 4.4 SCREEN SHOTS FOR THE PERFORMANCE CRITERIA This section of Chapter 4 includes screen shot examples that show the Performance Criteria inputs discussed within this chapter for the rehabilitation of flexible and rigid pavements. The same distresses are used for new flexible and rigid pavement designs, with the exception of reflection cracking. The specific pavement distresses are dependent on the pavement type selected for a specific project. The following are screen shots for the major pavement types (AC, JPCP, and CRCP). 32 AC over JPCP 33 JPCP over JPCP (Unbonded) 34 CRCP over JPCP (Unbonded) 35 CHAPTER 5--TRAFFIC INPUTS This chapter summarizes the truck traffic inputs used for evaluating the adequacy of a design strategy. Example screen shots showing the traffic inputs are included at the end of this chapter. The Traffic Analysis Branch of the Office of Planning can generate most of the traffic inputs for a specific project. For roadway segments where project specific traffic data are unavailable, the traffic weigh in motion (WIM) study determined and recommended traffic default values to be used for design (Selezneva and Von Quintus, 2014). The traffic default values are included in the GDOT ME Design Database. These traffic input libraries were established to save time in entering the traffic data. Many other truck traffic input parameters are required for predicting the distresses of flexible and rigid pavements. Some of these inputs are difficult to determine and are unavailable within the GDOT truck traffic input library. Thus, the global default values are recommended for use in design and are defined and discussed within the NCHRP Project 1-37A reports (ARA, 2004a). These values were used in the regional validation/calibration refinement performed for Georgia, which are required for predicting distresses in both flexible and rigid pavements. 5.1 AVERAGE ANNUAL DAILY TRUCK TRAFFIC (TRAFFIC VOLUME INPUTS) The following traffic input parameters relate to traffic volume and are considered site specific and should be obtained from the Traffic Analysis Branch of the Office of Planning or the Office of Transportation Data within GDOT. If this information is unavailable, the following subsections provide the recommended default values (input level 3) to be used. 1. Two-way average annual daily truck traffic (AADTT): A project specific AADTT at the beginning of the design period is required for every design. AADTT is a weighted average 36 between weekday and weekend truck traffic. The designer should enter two-way and not one-way AADTT values. The Traffic Analysis Branch of the Office of Planning typically provides one-way traffic volumes, so those values need to be multiplied by 2 as an input in PMED. 2. Number of lanes: The number of lanes in the design direction. 3. Percent trucks in the design direction or directional distribution factor (DDF): The percentage of trucks in the design direction or directional distribution factor (DDF) is defined by the primary truck class for the roadway; usually vehicle class #9. If sufficient truck volume data is unavailable, a DDF value of 50 percent should be used. 4. Percent trucks in the design lane or lane distribution factor (LDF): The percentage of trucks in the design lane is defined by the primary truck class for the roadway; usually vehicle class #9. If sufficient truck volume data is unavailable, the values listed in Table 5.1 should be used. Table 5.1--Lane Distribution Factor Recommended for Use with Pavement ME Design Number of Lanes (Two-Directions) Lane Distribution Factor, % 4 90 6 80 8 70 10 60 5. Operational speed: This input parameter is taken as the posted speed limit or the average truck speed of the heavier or larger trucks through the project segment. Lower speeds result in higher incremental damage values calculated by the MEPDG design methodology. 37 5.2 TRAFFIC CAPACITY This input factor (traffic capacity cap) does not have any impact on the predictions of the performance indicators. Thus, it is recommended that it not be enforced. This input is used to determine if the growth in traffic over time will exceed the capacity of the roadway. 5.3 AXLE CONFIGURATION 1. Average axle width: The average distance between the outside edge of the tires of an axle; 8.5 feet, the PMED default value. 2. Dual tire spacing: The average distance between the center of the two tires; 12 inches, the PMED default value. 3. Tire pressure (hot inflation pressure): The average hot tire pressure; 120 psi, assumed for both single and dual tires, the PMED default value. 4. Tandem axle spacing: The average distance between the two axles of a tandem axle; 51.6 inches, the PMED default value. 5. Tridem axle spacing: The average distance between the three axles of a tridem axle; 49.2 inches, the PMED default value. 6. Quad axle spacing: The average distance between the four axles of a quad axle; 49.2 inches, the PMED default value. 38 5.4 LATERAL WANDER 1. Mean wheel location: The average distance from the outer edge of the wheel to the pavement edge marking; 18 inches, the PMED default value. This input is only required for a rigid pavement design analysis. 2. Truck traffic wander standard deviation: The standard deviation of lateral distribution of trucks traveling down the roadway; 10 inches, the PMED default value. 3. Design lane width: The width of the lane between the pavement lane designation markings and not the slab width. This input is a design feature and not a traffic input. It is included with the other traffic inputs because it has a significant impact on the stresses in the PCC slab based on the location of the wheel load relative to the edge of the pavement. The value is selected by the designer for the specific project. This input is only required for a rigid pavement design analysis. 5.5 WHEEL BASE The average axle spacing and percentage of trucks within each spacing are only required for a rigid pavement design analysis. The following are the Georgia default values recommended for use: 1. Average axle spacing: 1) 12 ft. for short axle spacing. 2) 15 ft. for medium axle spacing. 3) 18 ft. for long axle spacing. 39 2. Average percentage of trucks within each axle spacing: 1) 17 percent for short axle spacing. 2) 22 percent for medium axle spacing. 3) 61 percent for long axle spacing. 5.6 VEHICLE CLASS DISTRIBUTION AND GROWTH 1. Distribution Factors: Normalized vehicle (truck) class volume distribution: Determine the percentage of each vehicle or truck class within the mixed traffic (vehicle class 4 through 13 as defined by FHWA). These percentages represent the normalized truck volumes or truck volume distribution and are provided by the Traffic Analysis Branch of the Office of Planning. Vehicle class volume data are readily available on just about all roadways in Georgia so the normalized vehicle class distribution can be obtained from the Traffic Analysis Branch of the Office of Planning for most pavement designs. In the few cases, where vehicle class volume data are unavailable or for a new roadway (new alignment), the following paragraphs can be used to estimate the normalized vehicle class volume distribution factors. 1) Three truck class categories can be used to select one of the seventeen truck traffic classification (TTC) groups included in the PMED software for a specific roadway segment: single unit trucks (vehicle class [VC] 5 to 7), combination trucks or single trailers (VC 8 to 10), and multi-trailer trucks (VC 11 to 13). Estimate the amount of trucks expected within these three truck class categories. 40 2) Table 5.2 summarizes the TTC groups for those roadways that were used in the local calibration process for Georgia. These TTC groups represent the median groups or values for the LTPP and non-LTPP sites used in the Georgia local calibration study, as well as from the traffic WIM study to identify the common TTC groups found on Georgia's roadways (Selezneva and Von Quintus, 2014). As noted above, these TTC groups are recommended for use when actual truck traffic data are unavailable for use in design (refer to step #15.2 of Section 6 in the GDOT Pavement ME Design software manual). Table 5.2--Median Truck Traffic Classification Groups Common to Georgia Roadways Roadway Description Type of Truck Percentage of Trucks Applicable TTC Group Single Units 19.2 Rural Interstate Highways, 4-Lane Divided Highways Single Trailers Multi-Trailers 65.9 14.9 TTC-5 Single Units 42.9 Freight Routes Urban Interstate Highways, 4-Lane Divided Highways Single Trailers Multi-Trailers 56.4 1.7 TTC-6 Principal Roadways, 4-Lane Divided Highways Single Units 32.2 Single Trailers 65.0 Multi-Trailers 2.8 TTC 4 Minor Arterials and Major Collector Single Units 57.9 Routes (more than 1,000 AADTT Single Trailers 39.9 Non- in both directions) Freight Routes Local Two-Lane Routes with Low Multi-Trailers Single Units 2.2 73.9 Truck Volumes (less than 1,000 Single Trailers 25.1 TTC 12 TTC-14 AADTT in both directions) Multi-Trailers 1.0 NOTE: Single units include vehicle classes 4 to 7; single trailers include vehicle classes 8 to 10; and multi- trailers include vehicle classes 11 to 13. 2. Growth rate of truck traffic: Estimate the increase in truck traffic over time. The growth of truck traffic is difficult to accurately estimate because there are many site and social-economic factors that cannot be predicted 20+ years into the future. In most cases, the growth rate for each vehicle class will be provided by the Traffic Analysis Branch of the Office of Planning for a particular roadway segment. The type and 41 magnitude of the growth rate can be entered in the PMED software for each truck class (refer to step #15 in Section 6 of the Pavement ME Design software manual). The user has three options in choosing a traffic growth function, as listed below: 1) No growth: Truck volume for a specific truck class remains the same throughout the design life. 2) Linear growth: Truck volume increases by a constant percentage of the base year traffic for the specific truck class. 3) Compound growth: Truck volume increases by a constant percentage of the preceding year traffic for the specific truck class. Negative Growth should not be used. If truck traffic is expected to decrease within the design life, use the average truck volume throughout the design life for that truck class and assume no growth. 5.7 MONTHLY ADJUSTMENT The monthly distribution factors (MDF) represent the relative amount of trucks traveling on the roadway segment during any month within a typical year. The MDF can be provided by the Traffic Analysis Branch of the Office of Planning. Two sets of MDF were determined from the roadway segments with sufficient data and are defined as seasonally dependent and seasonally independent. Both sets of values are listed in Tables 5.3 and 5.4 and should be used when sufficient truck volume data are unavailable. The default MDF can be imported into the PMED software from the truck traffic data library established for GDOT. The values in Tables 5.3 and 5.4 are provided in this User Input Guide for checking 42 the values imported into the software. Table 5.3 includes the seasonally dependent values to be used for the non-freight routes, while Table 5.4 includes the seasonally independent values to be used for the freight routes. The Georgia freight routes are shown in Figure 5.1. All freight routes are generally along the interstate roadways, while the non-freight routes are along the noninterstate roadways. For any questions regarding freight routes, contact the Traffic Analysis Branch of the Office of Planning. Table 5.3--Monthly Adjustment Factors for Non-Freight Routes; Seasonally Dependent Truck Classification Month 4 5 6 7 8 9 10 11 12 13 January 0.17 0.11 0.79 1.6 0.22 0.22 1.94 0.16 0.51 1.12 February 0.23 0.06 0.74 1.53 0.28 0.39 2.06 0.39 0.67 0.65 March 0.74 0.56 0.91 0.89 0.91 0.84 1.42 0.74 0.86 0.74 April 1.41 1.26 1.08 0.6 1.29 1.34 0.65 1.28 1.07 0.81 May 1.71 1.65 1.08 0.12 1.51 1.45 0.36 1.61 1.26 0.57 June 1.54 1.97 1.08 0.12 1.53 1.5 0.24 1.72 1.32 0.57 July 1.49 2.14 1.02 0.12 1.4 1.4 0.19 1.46 1.07 0.65 August 1.41 1.95 1.19 0.12 1.52 1.63 0.25 1.63 1.3 0.96 September 1.46 1.2 1.03 0.56 1.54 1.55 0.42 1.61 1.56 1.11 October 1.29 0.78 1.15 1.19 1.18 1.17 1 1.01 1.13 2.18 November 0.33 0.16 1.08 2.87 0.39 0.34 1.93 0.28 0.79 1.28 December 0.22 0.16 0.85 2.28 0.23 0.17 1.54 0.11 0.46 1.36 43 Table 5.4--Monthly Adjustment Factors for Freight Routes; Seasonally Independent Truck Classification Month 4 5 6 7 8 9 10 11 12 13 January 0.6 0.84 1.56 0.96 0.96 1.06 1.32 0.96 1.08 1.32 February 0.72 0.96 1.2 0.96 1.08 1.06 1.2 0.96 1.14 0.96 March 0.96 1.08 0.96 0.6 1.08 1.06 0.96 0.96 1.14 0.96 April 1.44 1.2 0.96 0.48 1.08 0.96 0.96 0.96 1.08 0.84 May 1.08 0.96 0.84 0.48 1.08 0.96 0.96 0.96 0.84 0.48 June 1.08 1.08 0.72 0.6 1.08 0.96 0.96 1.08 0.96 0.6 July 0.72 0.84 1.08 1.08 0.96 0.84 0.84 0.96 0.84 0.6 August 0.84 0.72 0.96 1.32 1.08 0.96 0.84 1.08 0.96 0.84 September 0.84 0.84 0.84 1.32 0.84 0.96 0.96 1.08 0.96 0.84 October 1.44 1.32 0.96 1.44 0.96 1.06 0.96 1.08 1.08 1.32 November 1.32 1.2 0.96 1.44 0.96 1.06 0.96 0.96 1.08 1.44 December 0.96 0.96 0.96 1.32 0.84 1.06 1.08 0.96 0.84 1.8 NOTE: Freight routes are along the interstate roadways, while non-freight routes are for the noninterstate routes. Contact the Traffic Analysis Branch of the Office of Planning to confirm input. Figure 5.1--Freight Routes Identified in Georgia 44 5.8 HOURLY ADJUSTMENT Hourly distribution factors (HDF) are only required for rigid pavement analyses; they are not used for predicting distresses of flexible pavements and HMA overlays of flexible pavements. The global default values included in the PMED software were found to be appropriate for Georgia interstates and principle arterials. Insufficient truck traffic volume data were unavailable to determine the HDF for the other roadway functional classification. Thus, it is recommended that the global default HDF be used for all roadways. Table 5.5 lists the global HDF for verifying the inputs. [NOTE: The hourly distribution factors input fields in the PMED software are only visible for rigid pavement designs.] Table 5.5--Hourly Distribution Factors Recommended for Georgia Time of Day Hourly Distribution of Truck Traffic, % Midnight to 6 a.m. 2.3 6 a.m. to 10 a.m. 5.0 10 a.m. to 4 p.m. 5.9 4 p.m. to 8 p.m. 4.6 8 p.m. to Midnight 3.1 5.9 AXLES PER TRUCK CLASS The average number of axles per truck class was determined from an analysis of the GDOT's WIM data as part of the traffic WIM study (Selezneva and Von Quintus, 2014). The default number of axles per truck class is listed in Table 5.6. These values are also included in the traffic library as part of the GDOT database. Table 5.6 is provided for checking the values imported into the PMED software for a specific project. 45 Table 5.6--Default Values for the Number of Axles per Truck Class Number of Axles per Truck Class Truck Class Single Axles Tandem Axles Tridem Axles Quad Axles 4 1.3 0.7 0 0 5 2.0 0 0 0 6 1.0 1.0 0 0 7 1.0 0.26 0.83 0 8 2.4 0.6 0 0 9 1.2 1.6 0 0 10 1.3 1.3 0.5 0.02 11 4.7 0.1 0.01 0 12 3.9 1.0 0.01 0 13 2.0 2.0 0.20 0.06 5.10 AXLE LOAD DISTRIBUTION FACTORS Table 5.7 lists the files with the normalized axle load spectra (NALS) or distribution factors included in the GDOT database library. The default NALS were determined from the traffic WIM project (Selezneva and Von Quintus, 2014) for use in design to save time in entering the axle load distribution data. In addition, the Traffic Analysis Branch of the Office of Planning can provide these values from the permanent WIM sites as more sites are installed on Georgia's roadways. Table 5.8 includes the tandem axle NALS factors for the heavier axle weights of vehicle class 9 to verify the values imported into the PMED software. The three NALS classifications or files were derived from a limited number of WIM sites with relatively few over loaded trucks. If the designer is concerned with overloaded trucks along the route in question, the global NALS developed under NCHRP Project 1-37A should be selected for use. For roadways where the designer wants more accurate weight data, the portable weigh in motion (WIM) equipment can be used to measure the NALS over a short time period (minimum of 3 weeks) for the specific roadway in question. 46 Table 5.7--Normalized Axle Load Distribution Files included in the GDOT Database Library Axle Loading Classification Description of Normalized Axle Load Distribution Global default axle load distributions developed under Default NCHRP 1-37A; not specific to GDOT roadways and includes higher percentages of overloaded trucks. Non-Freight urban and rural routes with an AADTT less GDOT_M than 1,000 in both directions (minor arterials, collectors and state routes). Non-Freight urban and rural routes with an AADTT greater GDOT_H1 than 1,000 in both directions (principle and non-interstate routes). GDOT_H2 Freight routes and rural and urban interstate roadways with an AADTT greater than 2,000 in both directions. Table 5.8--Normalized Axle Load Distribution Factors for Vehicle Class 9 Tandem Axles Axle Loading Tandem Axle Weight for Class 9 Trucks, lbs. Classification 30,000 32,000 34,000 36,000 38,000 40,000 42,000 Global Default, NALS 6.13 6.28 5.67 4.46 3.16 2.13 1.41 GDOT_M, NALS 5.43 8.15 7.68 3.86 1.48 0.55 0.21 GDOT_H1, NALS 6.38 9.51 10.94 5.19 1.21 0.34 0.11 GDOT_H2, NALS 7.82 11.10 12.79 7.51 2.44 0.83 0.37 NALS Normalized Axle Load Spectra (values in percentages). 5.11 SCREEN SHOTS FOR THE TRAFFIC INPUTS This section of Chapter 5 includes screen shot examples for the different traffic inputs discussed within this chapter. The drop-down arrows are used to access or select specific information for the project. 47 Overall Screen Shot for Traffic Vehicle Class Distribution and Growth 48 Monthly Adjustments Number of Axles Per Vehicle (Truck) Class 49 AADTT, Traffic Capacity, Axle Configuration, Lateral Wander, and Wheelbase Note: As stated previously, average axle width, mean wheel location, design lane width, and all wheelbase inputs are only used for the rigid pavement analyses. These inputs parameters are not used in the flexible pavement analyses. Normalized Axle Load Distribution 50 Hourly Adjustment Note: as previously stated, hourly adjustments are only used in the rigid pavement analyses and are not used in the flexible pavement analyses. 51 CHAPTER 6--CLIMATE INPUTS Detailed climatic data are required for predicting pavement distresses in PMED and include hourly temperature, precipitation, wind speed, relative humidity, and cloud cover. These data are used to predict the temperature and moisture distribution in each of the pavement layers and provide inputs to the JPCP joint opening/closing and faulting as well as the site factors for the IRI regression equations for all pavement types. The climate files that are included with the PMED software were updated in 2016. The new hourly climate data is an assimilated dataset which is based on various ground-based observations. The North American Regional Reanalysis (NARR) climate data is the default for rigid pavements while the Modern Era Retrospective-analysis for Research and Applications-2 (MERRA-2) is the default for flexible pavement designs. 6.1 PROJECT LOCATION INFORMATION The average latitude, longitude, elevation of the project location should be determined and entered in the software. The latitude and longitude are included on the cover sheet for the plans of a specific roadway project. The mid-point of the project can be selected for the location information. In PMED versions 2.5 or later, the location and elevation may be input by selecting the mid-point of the project using the map function in the climate input window. The PMED software climate module uses a map based selection and will identify nine weather locations that are closest to the project location based on similar elevation. The designer can select a single weather grid node or multiple locations that are applicable to the project location to create a virtual weather station for the project location. The virtual weather station hourly data is calculated using the inverse squared distance interpolation method. (refer to subsections 6.3 and 6.4 of this chapter). 52 6.2 DEPTH TO WATER TABLE The depth to the water table is a parameter that gets entered on the climate screen. The depth to the water table or "free" water is the average distance between the pavement surface and the depth at which free water is encountered. This depth should be representative of cuts and fills along the project location. The depth to a water table is measured from borings taken along the project location. The depth to the water table has an effect on the moisture content of the unbound layers above the water table. The water table depth entered in the PMED software is the shallower depth to: free water, perched water, or the lateral flow of water. The following provides some guidance in determining the depth to the water table or free water. 1. The depth of borings usually does not exceed 10-feet for pavement design purposes, while the depth to the water table exceeds 10 feet in many locations. In addition, the borings are usually not monitored or left open over a sufficient amount of time to measure the depth to water. If seasonal or perched water table depths are known to exist along the project site, these seasonal values should be entered into the software. 2. The depth to the water table should be based on local experience and/or from a geotechnical engineer knowledgeable of the local conditions along the specific project. For example, the water depth from historical borings for bridges and other similar structures can be used to estimate that depth. 3. Georgia water table data for various locations and counties can be found at the U.S. Geological Survey web site: http://ga.water.usgs.gov/. 4. If borings are unavailable and no information can be obtained from other sources adjacent to the project, Table 6.1 can be used as a guide in selecting the annual values to be used. 53 Table 6.1--Annual Depth to Water Table Recommended for Use Location Annual Depth to Water Table, ft. Coastal Areas or Counties 6 Southern Counties: South of the Fall Line 10 Northern Counties: North of the Fall Line 15 Mountainous Areas or Higher Elevation Counties 20 6.3 CLIMATE STATIONS The PMED software has a number of national weather stations embedded in the software for ease of use (Figure 6.1). Table 6.2 lists the Georgia weather stations that are currently available in the Pavement ME Design software national database and those stations in adjacent states which are close to the state line. Any one of these weather stations can be selected for a project within the nearby area. The climate data for that station, however, will be used for the distress prediction computations rather than the specific project location. In selecting a climate station, pay attention to the elevation of the station. A climate station should be selected with a similar elevation as it can have a significant effect on air temperature. The AASHTOWare PMED procedure recommends two or more of these climate stations be selected as close to the project as possible to provide hourly temperature, precipitation, wind speed, relative humidity, and cloud cover information. This allows the user to create a virtual climate station (refer to Section 6.4) at the project location. Since moving to assimilated datasets, the amount of missing hourly climate data has reduced significantly and even eliminated completely. 54 Figure 6.1--MERRA-2 Grid Cell Locations 6.4 CREATION OF SIMULATED CLIMATE STATION After selecting the appropriate climate stations in the vicinity of the project and providing the depth to the water table, the user can select one station or simulate a weather station that is most representative of the project location. These simulated climate stations are typically referred to as virtual climate stations. The simulated or virtual climate station is saved by the software so that it can be used for all future trial designs or sensitivity studies relevant to a specific location. This can be done by 55 simply selecting the import option and picking the simulated climate station file created for the specific project. Table 6.2--Climate Stations Available from AASHTOWare for Georgia (North American Regional Reanalysis, NARR) City Climate Station Number Longitude (Degrees. Minutes) Latitude (Degrees. Minutes) Elevation, ft. Albany, GA 13869 -84.194 31.536 190 Alma, GA 13870 -82.507 31.536 193 Athens, GA 13873 -83.327 33.948 800 Fulton Co. Brown Field 03888 -84.521 33.779 801 Peachtree City Falcon Atlanta, Field 53819 -84.567 33.355 798 GA Dekalb Peachtree Airport 53863 -84.302 33.875 977 Hartsfield International 13874 -84.427 33.640 998 Augusta, Regional Bush Field 03820 -81.965 33.370 132 GA Daniel Field 13837 -82.039 33.467 412 Brunswick, GA 13878 -81.391 31.252 19 Cartersville, GA 53873 -84.849 34.123 754 Columbus, GA 93842 -84.942 32.516 392 Gainesville, GA 53838 -83.830 34.272 1266 Macon, GA 03813 -83.654 32.688 342 Rome, GA 93801 -85.161 34.348 692 Savannah, GA 03822 -81.202 32.119 25 Valdosta. GA 93845 -83.277 30.783 198 Troy, AL 03878 -86.012 31.861 385 International Jacksonville, Airport 13889 -81.693 30.494 26 FL; Craig Municipal Airport 53860 -81.515 30.336 46 Charleston, SC 13880 -80.041 32.899 39 Columbia, Downtown 53867 -80.996 33.971 180 SC Metropolitan Airport 13883 -81.118 33.942 225 Greenville, SC 13886 -82.346 34.846 1006 Greenwood, SC 53874 -82.159 34.249 631 Orangeburg, SC 53854 -80.858 33.462 196 Chattanooga, TN 13882 -85.200 35.033 671 6.5 USE OF CUSTOM CLIMATE FILES PMED allows for the establishment and use of custom climate files (*.hcd format) in the design process. Custom climate .hcd files developed through GDOT research projects 16-10 (Durham 56 et al, 2019) and 19-16 using MERRA-2 climate data have been created for use as climate inputs in GDOT designs. The custom .hcd files include corrected percent sunshine values based on the surface shortwave radiation values reported in the MERRA-2 climate files. Custom climate stations should be used for all GDOT pavement designs. Default stations using the hcd files provided through the Pavement ME Design software national database are recommended only when custom stations are not available. To access the custom climate station database, users must select the "Use custom hcd folder and station file" function in the Options dropdown of the Climate window. Table 6.3 lists the Georgia weather stations that have been developed using the custom Georgia climate database. It should be noted that the custom option might not even be needed other than for rigid pavements because the default is NARR. The only difference between the non-custom and custom selection is to tell the software where to look for the hcd files. If the custom climate station numbers match the original MERRA-2 station numbers then they can be used directly in the hcd folder instead of the "custom hcd folder". Table 6.3--Climate Stations Available from Custom Database for Georgia City Climate Station Latitude Number (Degrees. Minutes) Longitude (Degrees. Minutes) Elevation, ft. Panama City, FL 132632 30.000 -85.625 65.60 Eastpoint, FL 132633 30.000 -85.000 26.24 Panacea, FL 132634 30.000 -84.375 0.00 Perry. FL 132635 30.000 -83.750 3.28 Mayo, FL 132636 30.000 -83.125 82.00 Lake Butler, FL 132637 30.000 -82.500 137.76 Middleburg, FL 132638 30.000 -81.875 98.40 Chipley, FL 133208 30.500 -85.625 52.48 Blountstown, FL 133209 30.500 -85.000 45.92 Tallahassee, FL 133210 30.500 -84.375 101.68 Monticello, FL 133211 30.500 -83.750 78.72 57 City Jennings, FL Lake City, FL Callahan, FL Slocomb, AL Donalsonville, GA Whigham, GA Pavo, GA Lakeland, GA Manor, GA White Oak, GA Ozark, AL Fort Gaines, GA Albany, GA Sumner, GA Ocilla, GA Alma, GA Jesup, GA Crescent, GA Union Springs, AL Lumpkin, GA Plains, GA Cordele, GA Milan, GA Uvalda, GA Glennville, GA Savannah, GA Notasulga, AL Phenix City, AL Mauk, GA Perry, GA Dudley, GA Adrian, GA Statesboro, GA Clyo, GA Beaufort, SC Daviston, AL Climate Station Number 133212 133213 133214 133784 133785 133786 133787 133788 133789 133790 134360 134361 134362 134363 134364 134365 134366 134367 134936 134937 134938 134939 134940 134941 134942 134943 135512 135513 135514 135515 135516 135517 135518 135519 135520 136088 Latitude (Degrees. Minutes) 30.500 30.500 30.500 31.000 31.000 31.000 31.000 31.000 31.000 31.000 31.500 31.500 31.500 31.500 31.500 31.500 31.500 31.500 32.000 32.000 32.000 32.000 32.000 32.000 32.000 32.000 32.500 32.500 32.500 32.500 32.500 32.500 32.500 32.500 32.500 33.000 Longitude (Degrees. Minutes) -83.125 -82.500 -81.875 -85.625 -85.000 -84.375 -83.750 -83.125 -82.500 -81.875 -85.625 -85.000 -84.375 -83.750 -83.125 -82.500 -81.875 -81.250 -85.625 -85.000 -84.375 -83.750 -83.125 -82.500 -81.875 -81.250 -85.625 -85.000 -84.375 -83.750 -83.125 -82.500 -81.875 -81.250 -80.625 -85.625 Elevation, ft. 114.80 137.76 85.28 206.64 88.56 154.16 249.28 206.64 141.04 101.68 423.12 278.80 262.40 419.84 311.60 180.40 59.04 16.40 492.00 505.12 501.84 308.32 324.72 196.80 173.84 13.12 337.84 377.20 695.36 416.56 341.12 203.36 255.84 88.56 0.00 669.12 58 City Lagrange, GA Meansville, GA Juliette, GA Milledgeville, GA Bartow, GA Sardis, GA Allendale, SC Walterboro, SC Heflin, AL Carrollton, GA Jonesboro, GA Mansfield, GA Greensboro, GA Thomson, GA Burnettown, SC Springfield, SC Elloree, SC Piedmont, AL Rockmart, GA Sandy Springs, GA Winder, GA Comer, GA Mount Carmel, SC Saluda, SC Lexington, SC Rembert, SC Fort Payne, AL Calhoun, GA Jasper, GA Clermont, GA Gumlog, GA Belton, SC Clinton, SC Blackstock, SC Kershaw, SC New Hope, TN Climate Station Number 136089 136090 136091 136092 136093 136094 136095 136096 136664 136665 136666 136667 136668 136669 136670 136671 136672 137240 137241 137242 137243 137244 137245 137246 137247 137248 137816 137817 137818 137819 137820 137821 137822 137823 137824 138392 Latitude (Degrees. Minutes) 33.000 33.000 33.000 33.000 33.000 33.000 33.000 33.000 33.500 33.500 33.500 33.500 33.500 33.500 33.500 33.500 33.500 34.000 34.000 34.000 34.000 34.000 34.000 34.000 34.000 34.000 34.500 34.500 34.500 34.500 34.500 34.500 34.500 34.500 34.500 35.000 Longitude (Degrees. Minutes) -85.000 -84.375 -83.750 -83.125 -82.500 -81.875 -81.250 -80.625 -85.625 -85.000 -84.375 -83.750 -83.125 -82.500 -81.875 -81.250 -80.625 -85.625 -85.000 -84.375 -83.750 -83.125 -82.500 -81.875 -81.250 -80.625 -85.625 -85.000 -84.375 -83.750 -83.125 -82.500 -81.875 -81.250 -80.625 -85.625 Elevation, ft. 675.68 1151.28 482.16 232.88 252.56 295.20 154.16 88.56 885.60 974.16 869.20 701.92 610.08 495.28 183.68 236.16 164.00 754.40 970.88 852.80 1006.96 669.12 498.56 554.32 390.32 137.76 1590.80 659.28 1931.92 1413.68 688.80 800.32 587.12 498.56 518.24 783.92 59 City Apison, TN Copperhill, TN Hayesville, NC Clayton, GA Travelers Rest, SC Spartanburg, SC York, SC Monroe, NC Climate Station Number 138393 138394 138395 138396 138397 138398 138399 138400 Latitude (Degrees. Minutes) 35.000 35.000 35.000 35.000 35.000 35.000 35.000 35.000 Longitude (Degrees. Minutes) -85.000 -84.375 -83.750 -83.125 -82.500 -81.875 -81.250 -80.625 Elevation, ft. 954.48 1610.48 2063.12 2915.92 1105.36 751.12 718.32 652.72 6.6 SCREEN SHOTS FOR THE CLIMATE INPUTS The following are screen shot examples that show the climate inputs discussed within this chapter. The drop-down arrows are used to access or select specific information and other input values for the project. Overall Screen Shot for Climate 60 Depth to Water Table Climate Station Map Custom Climate Station Selection 61 CHAPTER 7--DESIGN FEATURES AND LAYER PROPERTY INPUTS Different features and properties are required by the PMED software for different pavement types or materials. The layer structure should be set up prior to entering any of the layer features and properties. This chapter discusses the features and properties required for specific pavement types. Example screen shots showing the design features and layer property inputs are included at the end of each section within this chapter. 7.1 AC (HMA) LAYER PROPERTIES: NEW AND EXISTING LAYERS 7.1.1 Multi-Layer Rutting Calibration Parameters The PMED version 2.1 and later permits the user to input layer specific plastic deformation parameters of the rut depth transfer function. This feature was unavailable when the local calibration work was completed for GDOT. As such, the same plastic deformation parameters should be used for all HMA layers (refer to Chapter 9 for the local calibration permanent deformation factors). The multi-layer rutting option in the PMED software should be false which is also the PMED default value. 7.1.2 HMA/AC Surface Shortwave Absorptivity Use the default value for the HMA surface shortwave absorptivity for all new pavement and rehabilitation designs; a value of 0.85. This value should not be changed without revising the local calibration parameters. 62 7.1.3 Endurance Limit The PMED software permits the user to enter an endurance limit for HMA layers or mixtures. The endurance limit represents the tensile strain at which no fatigue cracking damage accumulates within that layer. The global calibration of the fatigue cracking transfer function did not include the endurance limit as a mixture property or design feature. Similarly, the GDOT local calibration of the bottom-up fatigue cracking transfer function did not include the endurance limit as a mixture property or design feature. Thus, it is recommended that the endurance limit not be used in design. 7.1.4 Layer Interface Friction All global and regional calibration studies have been completed assuming full friction between each layer, because there is no standardized test for measuring this value. An interface friction value of 1.0 represents full friction. Thus, a value of 1.0 should be used for design. An interface friction value of 0 represents no friction between two adjacent layers (e.g., not including a tack coat between an existing HMA surface and HMA overlay). No friction should only be used for forensic investigations to answer "what if" questions. Interface friction values less than 1.0 will increase HMA rutting and fatigue cracking. All pavement designs should be completed with full interlayer friction. 7.1.5 Rehabilitation: Condition of Existing Flexible Pavement The condition of the existing flexible pavement surface is estimated from the distress measurements (condition surveys [input levels 2 or 3]) or determined from backcalculated elastic modulus (input level 1). Rehabilitation input level 1 should be used when deflection basin data 63 are available. For input levels 2 or 3, the distresses on the existing pavement can be obtained from current condition surveys or extracted from PACES or the computerized PACES (COPACES). The following summarizes the use of different input levels for rehabilitation designs. It is worth noting that the rehabilitation input option is not included for new flexible pavement designs. 1. Rehabilitation input level 1 Deflection basins provide valuable information and are believed to result in more reliable rehabilitation designs. Measured deflection basins are used to estimate the in place elastic modulus values for each structural layer and subgrade of the existing pavement. Backcalculation of the elastic layer modulus values are determined or calculated external to the PMED software. The average backcalculated values for a specific design section should be entered for each pavement layer and subgrade soil. These elastic modulus values for each pavement layer and subgrade are discussed in the next chapter of the User Input Guide. The other input required for rehabilitation input level 1 is the average rut depth within each pavement layer and subgrade. Table 7.1 lists the percentages to be used in distributing the total rut depth measured at the surface to each pavement layer and subgrade. Table 7.1--Ratios to Distribute Total Rut Depth to Individual Layers Flexible Pavement Layer Ratio of Total Rut Depth Distributed to Each Layer HMA/AC 0.75 Granular Aggregate Base 0.10 Subgrade 0.15 These percentages were determined through the global calibration process under NCHRP projects 1-37A and 1-40D, and based on a limited number of studies at the 64 global and local levels (Colorado, Montana, etc.). The values were verified based on the local calibration study for GDOT using the LTPP and non-LTPP roadway segments by determining the values that result in the lowest standard error of the rut depth transfer function. 2. Rehabilitation input level 2 If deflection data are unavailable to estimate the in-place condition of the HMA layers, the use of input level 2 is reasonable without significantly increasing the cost of the pavement evaluation costs. For input level 2, two inputs are required to determine the condition of the existing pavement layers. These inputs are listed and defined below: 1) The average total amount of fatigue cracking (load cracking per GDOT's PACES/COPACES) within the wheel path area in terms of percent of total lane area should be entered for each design section. The designer can also use the distress data and information included in GDOT's pavement management database. In this case, Figure 7.1 should be used to transform the historical information or data into the cracking values predicted by the MEPDG software. The designer simply enters the GDOT total amount of load cracking in Figure 7.1 to estimate the amount or area of bottom-up alligator fatigue cracking. 2) The average rut depth within each pavement layer and subgrade, which is the same as for rehabilitation input level 1, as defined above. 65 EXAMPLE: Enter the total load cracking number on the x-axis and project up to the intersection of the dashed line. At the intersection with the dashed line, project horizontally to the y-axis to determine the estimated total alligator cracking that would be measured in accordance with LTPP. NOTE: If the GDOT load cracking number is composed entirely of severity level 1, the total alligator cracking should be limited to a maximum value of 16 percent. If the GDOT load cracking number is composed of entirely severity levels 1 and 2, the total alligator cracking should be limited to a maximum value of 20 percent. For all other combinations of the GDOT load cracking number, the total alligator cracking should be limited to a maximum value of 30 percent. Figure 7.1--Relationship between GDOT's Load Cracking Number (All Severity Levels) included in PACES and the Total Area of Alligator Fatigue Cracking 3. Rehabilitation input level 3 Five subjective pavement ratings are used to describe the condition of the pavement surface, which are defined in the MOP and considered appropriate for GDOT. Table 7.2 relates the subjective condition survey ratings included in the PMED software to GDOT PACES rating reported for each roadway segment for planning purposes. The other input required for input level 3 is the average total rut depth measured at the surface of the HMA. The PMED software distributes that total rut depth measured at the surface to the different layers using the layer percentages determined under the NCHRP Project 1-37A project. 66 Table 7.2--MEPDG Condition Ratings for the GDOT PACES Rating or Composite Pavement Condition Index GDOT PACES and COPACES MEPDG Subjective Condition Rating Index Ratings; Input Level 3 > 90 Excellent 80 to 90 Good 70 to 80 Fair 60 to 70 Poor <60 Very Poor 7.1.6 Milled Thickness of Existing HMA Layers Milling a portion of the existing HMA is a common rehabilitation activity prior to placing the HMA overlay. The planned milled thickness is entered in the AC Layer Properties screen under Rehabilitation. The thickness of the combined existing HMA layers should be the thickness "after" milling. The milled-thickness is used for damage computations based on the dynamic modulus and is not subtracted from the existing HMA layer thickness. Additional discussion is provided under Section 8.1 on entering the thickness of the existing HMA layers when one or more overlays have already been placed on the original flexible pavement and/or when more than three HMA layers are placed. 7.1.7 Screen Shots for the AC (HMA) Layer Properties: New and Existing Layers The following are screen shot examples that show the AC Layer Property inputs discussed within this section of Chapter 7. The drop-down arrows are used to access or select specific information and other input values for the project. 67 Overall Screen Shot for the AC Layer Properties AC Layer Properties Screen Rehabilitation Screen Note: this drop down screen is only applicable for rehabilitation or overlay projects of flexible pavements. 68 7.2 JPCP: NEW AND EXISTING LAYERS 7.2.1 PCC Surface Shortwave Absorptivity Use the default value for the PCC surface shortwave absorptivity for all new pavement and rehabilitation designs; a value of 0.85. 7.2.2 Joint Spacing PMED allows two options for the joint spacing of JPCP: a constant or random joint spacing. GDOT only permits the use of a constant joint spacing. However, a random joint spacing has been used or allowed by GDOT in the past. The joint spacing used on most projects in Georgia is 15 to 20 feet. The recommended joint spacing for most jointed plain concrete pavements (JPCP) is 15 feet. This spacing provides a good balance between minimization of transverse cracking and joint costs. 7.2.3 Sealant Type PMED allows two options for the type of sealant used in the transverse joints: preformed and other sealants. The other sealants listed in the PMED software include liquid (hot and cold poured) sealants, silicone, and/or no sealant. Georgia currently seals the joint with silicone, so the `other sealant' option should be used. 7.2.4 Dowels GDOT typically uses dowels in all transverse joints of JPCP because appropriately sized dowels control joint faulting. The trial diameter and spacing of the dowels are inputs to PMED. GDOT typically uses 1.5 inch dowels for pavements 10 inches or thicker, but the Georgia Standard 69 5046H should be referenced to determine appropriate diameter for the design. The spacing of the dowels is typically 12 inches. The program outputs joint faulting predictions which must meet the faulting criteria at the designated reliability level. 7.2.5 Widened Slab Widened slabs are used to reduce the edge stresses from wheel loads. The user enters the width of the widened slab for the specific project. A maximum of 1-ft widening of the slab should be used. Thus, the paint strip is placed at 12 feet, but the slab placement width is 13 feet. 7.2.6 Tied Shoulders Tied shoulders are used to reduce the edge stresses from the wheel loads. The user simply identifies whether the shoulders will be tied to the JPCP for the specific project. A longitudinal joint load transfer efficiency of 40 percent should be used. 7.2.7 Erodibility Index The erodibility index for JPCP is defined by the type of base material for the specific project, and is classified in five categories, which are listed in Table 7.3. More erosion resistant base material results in lower predicted joint faulting and a thinner PCC layer. 7.2.8 PCC-Base Contact or Interface Friction for JPCP JPCP design should be based on full friction between the slab and base course, and nothing should be done in construction to break the bond between layers. Some base types, however, are prone to debond after a few years and this increases stress in the slab that leads to cracking. 70 The following lengths of time for full contract friction between the PCC slab and base course are recommended (means and range obtained from the national or global calibration). This is one of the reasons GDOT uses either HMA (or asphalt stabilized base) or GAB for the base layer under the PCC slabs. 1. Asphalt Stabilized Base: Use full design analysis period. 2. Cement Stabilized Base: Use up to 120 months as there is a good chance of deboning after this stage. 3. Lime Treated Base: Use up to 150 months 4. Lean Concrete Base: Use zero (0) months if base is finished smooth and cured with wax based curing compound. 5. Unbound Granular Aggregate Base: Use full design analysis period. Table 7.3--Erodibility Category Index Recommended for Different Base Materials Erodibility Category Recommendation Based on Type of Base Material 1 Extremely Erosion Resistant Asphalt Stabilized Layer or HMA. 2 Very Erosion Resistant Cement Treated or Lean Concrete Base Layer. 3 Erosion Resistant Dense-graded crushed stone or granular aggregate base (GAB) materials with less than 10 percent fines. 4 Fairly Erodible Dense-graded or granular aggregate base materials with more than 10 percent fines; typical GDOT GAB. 5 Very Erodible Silts and other non-cohesive fine-grained soils and cohesive soils. 7.2.9 Pavement Curl/Warp Effective Temperature Difference Use the default value for the PCC pavement curl/warp effective temperature difference for all new pavement and rehabilitation designs; a value of -10 degree Fahrenheit (F). 71 7.2.10 Foundation Support for Rehabilitation of Rigid Pavements The foundation support (subgrade) resilient modulus at optimum moisture and maximum dry unit weight can be estimated based on soil class or California Bearing Ratio (CBR) and entered similar to the design of new rigid pavements. [See section 8.6.2 of this Guide for a more detailed discussion on Resilient Modulus.] If Falling Weight Deflectometer (FWD) testing is available, however, the K-value can be obtained from backcalculation and entered directly into the PMED software for the month tested. K-value can be calculated in accordance with the procedure documented in the 1993 AASHTO Design Guide or with other software programs (Von Quintus and Rao, 2015). This process is by far the most accurate approach that gives subgrade support along the project. 7.2.11 Condition of Existing PCC Surface for JPCP Rehabilitation Design The inputs to describe the condition of the existing PCC surface and any repairs made to the surface are listed below and discussed in the next chapter of the User Input Guide under rehabilitation of rigid pavements. Two inputs are required for the existing PCC layer when designing an HMA overlay of an existing JPCP or diamond grinding: (1) the user determines the percentage of slabs that are transversely cracked or have been replaced prior to rehabilitation or restoration, and (2) the percentage of slabs that will be replaced as part of the rehabilitation project after restoration. These two inputs are important because they define the in-place damage of the JPCP for predicting future damage and cracking of the PCC slabs. 72 7.2.12 Screen Shots for the JPCP Layer Properties: New and Existing Layers The following are screen shot examples that show the JPCP Design Property and other inputs discussed within this section of Chapter 7. The drop-down arrows are used to access or select specific information and other input values for the project. 73 Overall Screen Shot for the JPCP Design Properties, Foundation Support, and JPCP Rehabilitation JPCP Design Properties Screen Sealant Type Screen Shot 74 Erodibility Index Screen Shot Foundation Support JPCP Rehabilitation 75 7.3 CRCP: NEW AND EXISTING LAYERS 7.3.1 Inputs The inputs for the PCC layer of CRCP are the same as for JPCP listed above, except as summarized below: 1. Shoulder type: The type of shoulder is determined by the user. Four shoulder types are available for consideration: (1) tied PCC, separate; (2) tied PCC, monolithic, (3) asphalt, and (4) gravel or an unbound granular aggregate base material. A roller compacted concrete can be assumed as an asphalt shoulder since it is not tied into the PCC slab. If alternates are allowed, use an asphalt shoulder for the design. 2. Percent longitudinal steel included in the PCC slab is a project specific design input and varies between 0.65 and 0.80 percent area of slab. This is a critical input to the design. 3. Bar diameter of the longitudinal steel reinforcement is a project specific design input. 4. Depth of the longitudinal steel reinforcement is a project specific design input. The longitudinal steel is usually placed at the mid-depth or higher in the PCC slab. Placement just above mid-depth (3.5 inches of concrete cover minimum), however, will result in tighter cracks and improved performance. 5. Base/Slab friction coefficient or the coefficient of friction at the interface of the CRCP and layer supporting the CRCP. There is no test method for measuring the coefficient of friction between two pavement layers. Table 7.4 summarizes the default values recommended for design which are included in the most recent MOP Edition (AASHTO, 2020). 76 Table 7.4--Base/Slab Friction Coefficient Recommended based on Different Layers below CRCP (AASHTO, 2020) Base Type Friction Coefficient (mean) Asphalt treated base 8.5 Cement treated base 9.6 Lime treated base 10.7 Granular aggregate base 2.7 7.3.2 Screen Shots for the CRCP Layer Properties: New and Existing Layers The following are screen shot examples that show the CRCP Design Property and other inputs discussed within this section of Chapter 7. The drop-down arrows are used to access or select specific information and other input values for the project. 77 Overall Screen Shot for the CRCP Design Properties, Foundation Support, and JPCP Rehabilitation Shoulder Type Crack Spacing 78 CHAPTER 8--LAYER/MATERIAL PROPERTY INPUTS The inputs to define the structure are straightforward and include the material type and thickness of each layer included in the design strategy. Figure 8.1 shows the pavement layer structure typically required by GDOT, and Table 8.1 lists the minimum and maximum layer thicknesses appropriate for input in the PMED software. The values found in Table 8.1 do not reflect current GDOT design recommendations but instead provide the range of thickness values recorded for each material during the local calibration process. The GDOT Pavement Design Manual or Policy Design Manual should be referenced for design thicknesses from official design standards such as the 2018 guidelines for Superpave and other mix type selection Guidelines and the Geotechnical QA/QC Manual.5 8.1 PAVEMENT LAYERS FOR FLEXIBLE PAVEMENT DESIGN The following provides a recommendation for creating the pavement structure used in a new or rehabilitated flexible pavement analysis (see Figure 8.1). 8.1.1 HMA and Asphalt Stabilized Base Layers For both new construction and rehabilitation designs, thin HMA layers (less than 1.0 inch in thickness) should be combined with an adjacent structural layer. As an example, open graded or porous friction courses, PEM, 4.75 mm mixture, and other thin layers should be combined with the lower or adjacent dense-graded HMA/AC Superpave mixture or layer. 1. For new construction or reconstruction problems, limit the number of HMA layers to three (maximum number allowed). The lower layer controls bottom-up or alligator 5 The number of layers used in an analysis has an effect on the PMED run time--using more layers, increases the run time. 79 cracking, while the upper layers have more control on the predictions of rut depth and longitudinal or top-down cracking. For flexible pavements & HMA/AC overlays, the designer should iterate on the lower HMA/AC overlay layer for determining the required total thickness. When combining thin surface layers with a lower densegraded HMA/AC layer for new construction, the layer thickness ratios in Table 8.2 should be used in determining the equivalent thickness of the lower dense graded HMA/AC layer in accordance with equation 1 to be entered in the PMED software. ( ) D = D + R D equivalent Dense-Graded Thin - Layer (1) Where: Dequivalent - Thickness of the equivalent dense-graded mix. DDense-Graded - Use thickness of the lower dense-graded mix, see Table 8.1. R - Equivalent thickness ratio of the thin layer to the dense-graded layer; provided in Table 8.2. DThin-Layer - Thickness of the thin layer which is identified in Tables 8.1 and 8.2. 80 Rigid Pavement JPCP or CRCP (Table 8.1) Interlayer Granular Aggregate Base or Stabilized Base (Table 8.1) Subgrade NOTE: Interlayer is typically used for interstates and high truck volume roadways. Semi-Rigid Pavement HMA Surface (Table 8.1) HMA Binder Layer (Table 8.1) HMA Base Layer (Table 8.1) Flexible Pavement HMA Surface (Table 8.1) HMA Binder Layer (Table 8.1) HMA Base Layer (Table 8.1) Granular Aggregate Base (GAB; Table 8.1) Subgrade Inverted Pavement (A-Typical) HMA Surface (Table 8.1) HMA Binder Layer (Table 8.1) HMA Base Layer (Table 8.1) Cement Stabilized Base or Soil Cement Granular Aggregate Base (GAB) Cement Stabilized Base Subgrade Subgrade NOTE: Inverted pavements have typically not been used in Georgia. Figure 8.1--New Pavement Structures Typically Required by GDOT 81 Table 8.1--Minimum and Maximum Layer Thicknesses Layer/Material Designation Layer Thickness, in. Use Min. Max. JPCP DesignA 6.0 15.0 PCC CRCP DesignA 7.0 15.0 HMA Interlayer ManualB NA* Surface Layer ManualB 0.75 2.5 HMA/AC Binder Layer ManualB 1.75 3.0 Base Layer ManualB 3.0 12.0 GAB ManualB 7.5 16.0 Unbound Layers Asphalt Base Subgrade ManualB DesignA 3.0 12.0 NA* Stabilized Soil DesignA 7.5 12.0 *NA - Not Applicable. Note A: "Design" in the Use Column means the thickness is to be design for the specific project Note B: "Manual" in the Use Column means the thickness is to be designed in accordance with the GDOT Pavement Design Manual or Policy Design Manual Table 8.2--HMA/AC Layer Thickness Ratios (R) to be Used in Combining Thin Layers with Lower Dense-Graded HMA/AC Layers Thin Layers Ratio to a Dense-Graded Layer Open-Graded or Porous Friction Course 0.75 PEM 0.75 4.75 mm Mix 1.0 The above ratios were determined based on the equivalent stiffness method. 2. For rehabilitation, the existing HMA/AC and overlay layers are restricted to four total AC layers. When three layers are entered to represent the existing HMA, only one overlay layer can be used. For this case, the thickness entered into the software for the existing upper layer is defined as the existing layer thickness (prior to milling) minus the milled thickness (see Section 7.1.6). Conversely, if three overlay layers are entered, only one layer can be used to represent the existing HMA layers. For this case, the thickness entered into the software for the existing layer is defined as the total existing AC thickness (prior to milling) minus the milled thickness. For rehabilitation, it is recommended that the existing HMA/AC layers be combined as one 82 layer, unless there is a specific reason why two layers should be simulated. Results from deflection basin testing and the backcalculation of elastic layer modulus values should be used to determine whether the existing HMA layers are confined to one or two layers. 8.1.2. Base Layers GDOT typically uses one type of base layer along a project, which include additional asphalt base (25 mm HMA), soil cement, and granular aggregate base (GAB). Asphalt stabilized base layers were noted above, while the others are discussed in the bullets below. 1. Unbound Granular Aggregate Base (GAB) Layers: Limit the compacted GAB layers to two for both new and rehabilitation design; most of the designs will include only one GAB layer that is placed in two lifts. If more than two layers are being considered within the design strategy combine similar materials, especially any layer that is relatively thin (less than 6 inches). The number of unbound GAB layers of the existing pavement structure for rehabilitation design should coincide with the pavement structure used to backcalculate elastic layer modulus values from deflection basin data. 2. Cement Treated Base or Cementitious Layers: No more than one layer of cement, lime, or lime-fly ash stabilized base layer should be used in the analysis. This does not include stabilized subgrade soils, which is covered under the next major bullet item. When the cementitious layer is placed directly below the HMA layer, even if this layer is a stabilized subgrade, the pavement structure is defined as a semi-rigid pavement (see Figure 8.1). Semi-rigid pavements were calibrated nationally in 2018. 83 There were limited semi-rigid pavements with sufficient materials data for use in the local calibration process for GDOT (see Table 2.1). 3. Asphalt Base (25mm HMA): A layer of 25mm HMA may be used as replacement for a typical GAB layer in certain projects where GAB applications are less feasible. Only three total asphalt layers are permitted in the software for new design. Using asphalt base as a base layer substitute will limit the maximum number of asphalt surface layers to two. 8.1.3. Stabilized Subgrade No more than one layer of a stabilized subgrade should be used in the analysis. It is permissible to include a stabilized aggregate base layer and stabilized subgrade within the same run. In the past, GDOT has treated this layer as an equal thickness of GAB. Stabilized subgrades simulated in the PMED software, however, are treated separately and should be simulated as such in accordance with the following guidance. 1. If the stabilized subgrade is used as a construction platform with only minimum additive for improving the strength, the layer should be combined with the subgrade layer and not treated as a separate layer. 2. Conversely, a stabilized subgrade for improving the structural strength of the pavement is entered as a separate layer with a constant elastic or resilient modulus value for that layer. The inputs for these stabilized soils are included in Section 8.7 of the User Input Guide. 84 8.1.4. Embankment/Foundation Layers or Subgrade The subgrade should be limited to two layers; a compacted embankment layer and the natural or undisturbed soil. The exception to this recommendation is when a water table is located near the surface (less than 10 ft.) and the type of soil changes significantly between the water table and lower pavement layer because the properties of the soils can have a significant effect on the amount of water being moved through the subgrade--lowering the resilient modulus of the upper soil strata. 8.1.5. Bedrock For some projects, bedrock or a very stiff layer may be encountered. The maximum thickness of the subgrade above a rigid layer, however, is 100 inches. For depths greater than 10 feet, the bedrock has little impact on the predicted distresses. When bedrock is encountered within 10 feet of the surface, the designer can enter it as a separate layer. The material properties needed for each layer are discussed in separate sections of this chapter. 8.2 PAVEMENT LAYERS FOR RIGID PAVEMENT DESIGN Inputs in this category primarily define the structural layers of the PCC pavement including the material types and thicknesses (see Figure 8.1). Similar to the process defined in Section 8.1 for flexible pavements, each layer of the trial section is inserted by selecting the material type, the actual material classification, and the thickness. The following provides guidance for setting up the pavement structure used in a rigid pavement analysis. 85 8.2.1. JPCP or CRCP Layers For new construction, the rigid pavement is limited to one PCC layer and two PCC layers for rehabilitation designs of rigid pavements (PCC overlay and existing PCC layer). 8.2.2. Base Layers GDOT typically uses one type of base layer along a project, which include asphalt stabilized base (25 mm HMA), cement stabilized or treated base, and GAB. 1. HMA or Asphalt Stabilized Base Layers: For new construction or reconstruction problems, HMA or stabilized base layers are placed below the PCC slabs and are limited to one layer. The inputs for the asphalt stabilized base layer are the same as for flexible pavements. 2. Unbound Granular Aggregate Base Layers: Limit the compacted unbound GAB layers to one for both new and rehabilitation design of rigid pavements. If more than one layer is used within the design strategy combine similar materials, especially any layer that is relatively thin (less than 6 inches). The number of GAB layers of the existing pavement structure for rehabilitation design should coincide with the pavement structure used to backcalculate elastic layer modulus values from deflection basin data. 3. Cement Treated Base or Cementitious Layers: No more than one layer of cement, lime, or lime-fly ash stabilized base layer should be used in the analysis. This does not include stabilized subgrade soils, which is covered under the next bullet item. 86 8.2.3. Stabilized Subgrade No more than one layer of a stabilized subgrade should be considered in the analysis. It is permissible to consider or simulate a stabilized base layer and stabilized subgrade within the same run. 8.2.4. Embankment/Foundation Layers or Subgrade The subgrade should be limited to no more than two layers; a compacted embankment layer and the natural or undisturbed soil. The exception to this recommendation is when a water table is located near the surface (less than 10 ft.) and the type of soil changes significantly between the water table and lower pavement layer because the properties of the soils can have a significant effect on the amount of water being moved through the subgrade--lowering the resilient modulus of the upper soil strata. The material properties needed for each layer are discussed in separate sections of this chapter. 8.3 ASPHALT CONCRETE (AC) The layer or material properties for the AC or HMA layers are grouped into three categories: volumetric, mechanical, and thermal properties. Example screen shots showing the AC material property inputs are included at the end of this section. 8.3.1 Asphalt Layer, Thickness The thickness for different AC layers needs to be entered into the software. A maximum of three AC layers can be included in the pavement structure simulation, so some AC layers may need to be combined for a specific trial design. Section 8.1 provides discussion on combining different AC layers, while Table 8.1 listed the minimum and maximum AC layer thickness. 87 8.3.2 Mixture Volumetric Properties The volumetric properties include air voids, effective asphalt binder content by volume, aggregate gradation, mix unit weight, and asphalt grade. Gradation is included under the mechanical properties because it is only used to calculate the dynamic modulus of the mix for input levels 2 and 3. The volumetric properties should represent the mixture after compaction at the completion of construction. Obviously, the project specific values will be unavailable to the designer because the project is yet to be built. These parameters should be available from previous construction records. The following summarizes the recommended input parameters and values for the HMA mixtures. 1. Air voids, effective asphalt content by volume, and unit weight: Use the average values from historical construction records for a particular type of HMA mixture. Table 8.3 includes the volumetric properties based on the target values for common HMA mixtures used in Georgia for the time period of 2012-2014. For higher design level inputs, The University of Georgia (UGA) developed an asphalt volumetric properties databased for 16 different Georgia asphalt mixtures (Kim et al., 2019). The properties are included in the material testing library and can be imported into the PMED software from the material library. The following volumetric equations can be used to estimate the input parameters. Table 8.3--Volumetric Properties for Georgia's Dense-Graded Mixtures Volumetric Property Superpave Mixture Surface Mixtures Binder 9.5 mm, Type I 9.5 mm, Type II 12.5 mm 19 mm Base 25 mm SMA Mix 12.5 19 mm mm Average Air Voids, % 6.0 6.0 6.0 6.0 6.0 6.0 6.0 Effective Asphalt Content by Volume, % 10.5 10.5 10.6 9.6 9.2 12.0 11.5 Density, pcf 148 148 148 148 148 152 152 88 Air Voids, Va: Va = 1- Gmb Gmm 100 (2) Void In Mineral Aggregate, VMA: VMA = 100 - ( Gmb Ps Gse ) (3) Effective Asphalt Content by Volume, Vbe: Vbe = VMA -Va (4) Where: Va = Air voids. VMA = Voids in mineral aggregate. Vbe = Effective asphalt content by volume. Gmb = Bulk specific gravity of the HMA mixture. Gmm = Maximum theoretical specific gravity of the HMA mixture. Gse = Effective specific gravity of the combined aggregate blend. Ps = Percentage of aggregate in mix by weight, % (Ps=100-Pb). Poisson's Ratio: Use the temperature calculated values from the regression equation included in PMED. 89 8.3.3 Mechanical Properties Kim (2013) conducted dynamic modulus test on multiple HMA mixtures. UGA later updated this database with 18 additional mixtures (Kim et al., 2019). Table 8.4 depicts the mixtures whose time-temperature dependent dynamic modulus values were acquired for Level 1 design. If data is not available for the project location, Figure 8.2 may be used along with Table 8.4 for regional approximations. The detailed results of both studies are included in the material testing library and can be imported into the PMED software via the material library. For those mixtures and binder grades not relevant to the GDOT materials library, input level 3 values must be entered into the PMED software. Region 1 2 3 4 Table 8.4--HMA Mixtures with Level 1 Dynamic Modulus Binder NMAS Grade (mm) Binder Location Material File Name 64-22 64-22 67-22 76-22 64-22 67-22 76-22 67-22 19 25 19 12.5 12.5 9.5 12.5 19 25 9.5 12.5 9.5 12.5 Dalton (Whitefield) Dalton (Whitefield) Athens (Clarke) Toccoa (Stephens) Kennesaw (Cobb) Albany (Dougherty) Vienna (Dooly) Forrest Park (Clayton) LaGrange (Troup) Albany (Dougherty) Vienna (Dooly) Vienna (Dooly) Columbus (Muscogee) Columbus (Muscogee) Statesboro (Bulloch) Statesboro (Bulloch) L*_PG64_19_A_R1 L*_PG64_25_A_R1 L*_PG64_19_A_R2 L*_PG67_12.5_A_R2 L*_PG76_12.5_A_R2 L*_PG64_9.5_B_R3-A L*_PG64_9.5_B_R3-V L*_PG64_12.5_A_R3-FP L*_PG64_12.5_A_R3-LG L*_PG64_12.5_B_R3 L*_PG64_19_B_R3 L*_PG64_25_B_R3 L*_PG67_9.5_C_R3 L*_PG76_12.5_C_R3 L*_PG67_9.5_B_R4 L*_PG67_12.5_B_R4 Note: The material file name indicates the mixture is included in the GDOT materials library. The exact dynamic modulus values for each temperature and frequency for every mixture are included in Appendix A. 90 Figure 8.2--HMA Database Collection Regions 91 Table 8.5 is a matrix of the HMA dense-graded mixtures that are included in the GDOT materials library in relation to the typical binder grades used in Georgia. For those mixtures and binder grades not included in the GDOT materials library, input level 3 values need to be entered into the PMED software. Table 8.5--Binder Grades Typically Used in Georgia's Dense-Graded Mixtures Mix Size Designation Asphalt Binder Designation PG64-22 PG67-22 PG76-22 9.5 mm 12.5 mm 19 mm 25 mm Note: A check mark in the above columns indicates the mixture is included in the GDOT materials library. The average values for the different mixtures are included in Appendix A. 2. New HMA mixtures: If an HMA mixture is included in a design strategy that is not included within the materials library, it is recommended that input level 3 inputs be used to estimate the dynamic modulus values. Two options are provided for estimating dynamic modulus using input levels 2 and 3: (1) NCHRP 1-37A (viscosity-based model), and (2) NCHRP 1-40D (dynamic shear rheometer [DSR] based model). Either one can be used but the DSR model was derived from the viscosity-based model. It is recommended that the NCHRP 1-37A viscosity-based model be used for all current designs as the global calibration factors for all HMA predictive equations were determined using this model. 3. Existing HMA mixtures: For rehabilitation design of flexible pavements, the dynamic modulus of the existing HMA layers is needed. Rehabilitation input levels 2 and 3 are the same as for new HMA mixtures discussed above. For rehabilitation input level 1, the dynamic modulus values represent the backcalculated elastic modulus values. 92 Deflection basins should be measured over a range of temperatures, even if the deflection testing is completed within the same day so that the backcalculated elastic layer modulus values can be determined for at least two temperatures: one representing the morning hours and one representing the late afternoon hours. If there is no significant difference between the backcalculated elastic modulus values, one average value can be used. Two other inputs that are needed include: (1) the frequency of deflection testing--a default value of 20 Hz is recommended; and (2) the temperature representative of the average backcalculated elastic modulus value--the mid-depth temperature of the layer used in the backcalculation process measured during deflection testing. 4. Aggregate gradation: It is needed when input levels 2 or 3 are used for dynamic modulus. Use either the values that are near the mid-range of the project specifications or the average values from previous construction records for a particular type of mix. Table 8.6 includes the gradation or percent passing for the common mixtures used in Georgia. It should be noted that all input levels will require aggregate gradation for the PMED software v2.6. Table 8.6--Gradation for Georgia's Dense-Graded Mixtures Superpave Mixtures SMA Mixtures Sieve Size Surface Mixes Binder Mix Base Mix Surface Binder 9.5 mm, Type I 9.5 mm, Type II 12.5 mm 19 mm 25 mm 12.5 19 mm mm 1.5 in (37.5 mm) 100 100 100 100 100 100 100 1 in. (25.0 mm) 100 100 100 100 95 100 100 0.75 in. (19 mm) 100 100 99 95 85 100 95 0.5 in. (12.5 mm) 99 99 95 82 65 92 60 3/8 in. (9.5 mm) 95 95 85 70 52 65 52 No. 4 (4.75 mm) 75 65 58 49 45 24 24 No. 8 (2.36 mm) 51 45 43 33 33 20 20 No. 200 (75 m) 6 6 5.8 5 4.8 10 9 93 5. Reference temperature: Use 70F. All of the GDOT calibration factors are tied to this default value. 6. Creep compliance and indirect tensile strength: Creep compliance and the indirect tensile strength may be determined in the software using other asphalt material properties such as gradation and binder-related inputs. Therefore, it is recommended that input level 3 be used to estimate these properties until a library of laboratory test results become available. Both the creep compliance and the indirect tensile strength inputs are used for the low temperature cracking transfer function. Because transverse cracking from low temperature events is not that prevalent on Georgia's roadways, GDOT has not yet expended the resources to measure these properties in the laboratory. Recent efforts have been made to acquire this data for appropriate characterization of the load related distresses in future designs. 8.3.4 Thermal Properties 1. Thermal conductivity of asphalt: Use default value set in program of 0.67 BTU/ft*h*F. All of the GDOT calibration factors are tied to this default value. 2. Heat capacity of asphalt: Use default value set in program of 0.23 BTU/lb*F. All of the GDOT calibration factors are tied to this default value. 3. Coefficient of thermal contraction of the mix: Use default values set in the MOP for different mixtures and aggregates. The PMED software will calculate this value. All of the GDOT calibration factors are tied to the global default values calculated by the software. 94 8.3.5 Screen Shots for the AC Properties: New and Existing Layers The following are screen shot examples that show the AC material property inputs discussed within this section of Chapter 8. The drop-down arrows are used to access or select specific information and other input values for the project. Overall Screen Shot for the Asphalt Concrete Material Properties 95 Asphalt Concrete Dynamic Modulus; New AC Layer Asphalt Binder; Superpave Performance Grade 96 Rehabilitation: Existing Asphalt Concrete Layer 8.4 PORTLAND CEMENT CONCRETE (PCC) NEW MIXES The layer or material properties for the PCC layers are grouped into four categories: general, thermal, mix, and strength properties. Example screen shots showing the PCC material property inputs are included at the end of this section. A recent study at UGA conducted under RP 18-03 established a database for 12 approved concrete mixtures based on previous projects with similar design characteristics. Table 8.7 provides a summary of the mixture characteristics along with mixture numbers that are referenced throughout this section. The layer or material properties for the PCC mixtures below are recommended for relevant PCC layer designs. 97 Mixture No. 1 2 3 4 5 6 7 8 9 10 11 12 Table 8.7--Georgia Concrete Mixture Properties Cementitious Content Fly Ash (%) Water / Coarse Coarse Cement Aggregate Aggregate ratio Type Fraction GDOT Project Number 541 0 0.431 Granite 11.91 IM-185-1(326)01 541 0 0.524 Granite 12.75 NH-IM-20-2(145)01 595 0 0.430 Granite 11.40 EDS00-0072-00(039) 600 0 0.470 Granite 11.62 NHS00-0005-00(320) 580 12.20 0.493 Granite 12.54 NH-IM-20-2(145)01 579 19.69 0.446 Granite 11.67 CSNHS-M002-00(965)01 622 26.00 0.422 Granite 12.14 NHS-M002-00(434)01 605 20.66 0.430 Dolomite 12.09 NHSTP-0075-03(203) 590 18.64 0.438 Granite 10.87 CSSTP-0007-00(239)01 590 18.64 0.430 Dolomite 10.87 CSSTP-0007-00(239)01 600 20.16 0.470 Granite 11.42 IMNH0-0075-01(227) 600 20.16 0.470 Granite 11.42 IMNH0-0075-01(227) 8.4.1 General Properties 1. Thickness: The trial layer thickness needs to be entered for the PCC layer. Table 8.1 listed the minimum and maximum layer PCC thickness. 2. Unit weight of PCC: Use the average value from historical construction records for a particular type of PCC mixture or those provided in Table 8.8. In cases where the unit weight is not readily available for the PCC mixes, use a default value of 150 pcf. 3. Poisson's ratio: All of the GDOT calibration factors are tied to a default Poisson's ratio of 0.20 because it was unavailable for the PCC mixes included in the LTPP program or for the non-LTPP sections. Ongoing research under RP 18-03 led to the development of Table 8.9, in which Poisson's ratio was recorded for several Georgia concrete mixtures. The below values were not included in the most recent calibration but have not shown to have significant influence on the transfer functions in PMED as they are within the 98 expected range. As a result, the use of the average value (0.22) versus the default recommendation (0.20) is at the discretion of the designer. Table 8.8--Georgia Concrete Fresh Mixture Properties Mixture No. Temperature (F) Slump (in) Air (%) Unit Weight (lb/ft3) 1 82.4 0.50 4.9 147.2 2 83.4 2.25 4.0 147.4 3 73.7 3.00 6.2 144.4 4 79.3 8.50 6.1 143.0 5 62.1 7.00 4.5 143.4 6 74.1 6.50 5.5 141.6 7 58.6 4.25 3.1 145.2 8 64.4 5.00 5.0 148.8 9 66.2 0.50 4.9 145.8 10 75.4 2.50 5.9 147.2 11 70.5 2.75 3.6 146.6 12 85.8 2.75 4.7 146.4 Table 8.9--Poisson's Ratio for Georgia Concrete Mixtures Age of Specimen (days) Mixture Number Mixture ID 7 14 28 90 Poisson's Ratio AVG 1 541/0FA/0.431/11.91G/4.9 0.21 0.22 0.22 0.23 0.22 2 541/0FA/0.524/12.75G/4.0 0.22 0.22 0.22 0.23 0.22 3 595/0FA/0.43/11.4G/6.2 0.21 0.21 0.23 0.24 0.22 4 600/0FA/0.47/11.62G/6.1 0.22 0.21 0.22 0.23 0.22 5 580/12.2FA/0.493/12.54G/4.5 0.17 0.21 0.21 0.26 0.21 6 579/19.69FA/0.446/11.67G/5.5 0.18 0.21 0.20 0.24 0.21 7 622/26FA/0.422/12.14G/3.1 0.19 0.18 0.20 0.25 0.21 8 605/20.66FA/0.43/12.09D/5.0 0.25 0.25 0.26 0.27 0.26 9 590/18.64FA/0.438/10.87G/4.9 0.17 0.20 0.20 0.20 0.19 10 590/18.64FA/0.439/10.87D/5.9 0.20 0.24 0.25 0.27 0.24 11 600/20.16FA/0.47/11.42G/3.6 0.20 0.22 0.21 0.23 0.22 12 600/20.16FA/0.47/11.42G/4.7 0.22 0.21 0.22 0.23 0.22 Average (AVG) 0.20 0.22 0.22 0.24 0.22 NOTE: Mixture IDs signify: Cement Content/Fly Ash %/Water-Cement Ratio/CA Fraction/Air Content 99 8.4.2 Thermal Properties PCC Coefficient of Thermal Expansion (CTE) is a very critical design input that will affect the pavement design. A CTE database was developed using the same 12 concrete mixtures found in the GDOT material library. The average tested CTE values for these mixes are listed in Table 8.10 and may be used for design Level 1. Default Level 2 CTE values are determined based on PCC coarse aggregate geological class. Designers must determine the source of PCC coarse aggregate and thus, the predominant geological class. With this information, select the most appropriate CTE value from the recommendations presented in Table 8.11 and Table 8.12. If the source of coarse aggregate is unknown, assume granite with the CTE selected from Table 8.11. Table 8.10--CTE for Georgia Concrete Mixtures Mixture Number Mixture ID Average CTE (10-6/F) 1 541/0FA/0.431/11.91G/4.9 4.91 2 541/0FA/0.524/12.75G/4.0 4.66 3 595/0FA/0.43/11.4G/6.2 5.25 4 600/0FA/0.47/11.62G/6.1 5.09 5 580/12.2FA/0.493/12.54G/4.5 5.13 6 579/19.69FA/0.446/11.67G/5.5 5.17 7 622/26FA/0.422/12.14G/3.1 5.31 8 605/20.66FA/0.43/12.09D/5.0 5.35 9 590/18.64FA/0.438/10.87G/4.9 5.31 10 590/18.64FA/0.439/10.87D/5.9 5.45 11 600/20.16FA/0.47/11.42G/3.6 4.97 12 600/20.16FA/0.47/11.42G/4.7 4.99 Average 5.13 NOTE: Mixture IDs signify: Cement Content/Fly Ash %/Water-Cement Ratio /CA Fraction/Air Content Table 8.11--Recommended CTE Values for PCC Mixtures in Georgia that Contain Type I Portland Cement and Natural Sand (Kim, 2012) Coarse Aggregate Type CTE (10-6/F) Granite 5.1 Dolomite 5.1 100 1. Thermal conductivity of PCC: Use default value set in program of 1.25 BTU/ft*hr*F. All of the GDOT calibration factors are tied to this default value. 2. Heat capacity of PCC: Use default value set in program of 0.28 BTU/lb*F. All of the GDOT calibration factors are tied to this default value. 8.4.3 Mix Physical Properties: New and Intact Existing PCC Slabs The PMED software requires several inputs for the PCC mix physical properties, which are listed below. The default values for these mix properties recommended for use represent the average value from the mixes included in the GDOT calibration. 1. Cement type: Most of the GDOT PCC mixtures are produced with Type I Portland cement. Type I should be used, unless Type II or III is specified for a specific design. Type I/II Portland cement was used for all of the PCC mixtures included in the calibration. 2. Cement content: The cement content (plus fly ash content) should be available from historical construction records or provided in Table 8.7 for the different PCC mixtures used in Georgia. A local default value of 660 lb./yd.3 total cementitious material should be used if information is unavailable to the user. 3. Water/Cement ratio: The water-cement ratio is available from historical construction records or Table 8.7 for the different PCC mixtures. A local default value of 0.45 should be used if information is unavailable to the user. 4. Coarse aggregate type: The common type of coarse aggregates used in the PCC mixes are listed in Table 8.11. The recommended input for most designs is Granite but Dolomite may be assumed for those counties listed in Table 8.12. 101 Table 8.12--Recommended PCC Aggregate by Source Location or County Coarse Aggregate Type Dade Catoosa Whitfield Floyd Dolomite Polk Bartow Cherokee All Remaining Counties Granite 5. Zero-stress temperature (new and existing intact PCC): Zero stress temperature (Tz) occurs after placement concrete has cured and hardened sufficiently that the temperature begins to drop, resulting in tensile stress. It can be input directly or calculated by the PMED software from monthly ambient temperature and cement content using the equation 5. It is recommended that the user allow the PMED software to calculate this input parameter. Tz = (CC*0.59328*H*0.5*1000*1.8/(1.1*2400) + MMT) (5) Where: Tz = Zero stress temperature (allowable range: 60 to 120 degrees Fahrenheit). CC = Cementitious content, lb/yd3. H = -0.0787+0.007*MMT-0.00003*MMT2. MMT = Mean monthly temperature for month of construction, degrees Fahrenheit. 6. Ultimate shrinkage: The ultimate shrinkage can be entered manually or calculated by the software. It is recommended the ultimate shrinkage be calculated by the software, because this value was unavailable for the PCC mixes used in Georgia. All of the GDOT 102 calibration factors were determined based on the software calculating the ultimate shrinkage. 7. Reversible shrinkage: Use default value set in program of 50 percent. All of the GDOT calibration factors are tied to this default value. 8. Time to develop 50 percent of ultimate shrinkage: Use default value set in program of 35 days. All of the GDOT calibration factors are tied to this default value. 9. Curing method: Two options are available within the software: wet curing or curing compound. Curing compound is typically used for GDOT PCC construction. Thus, it is recommended that curing compound be selected unless the designer knows that wet curing will be used for some reason. 8.4.4 Strength Properties Two mix strength properties are required for using the PMED software: flexural (modulus of rupture) or compressive strength and elastic modulus. Input levels 1 and 2 require time dependent flexural and compressive strengths, respectively, while input level 3 only requires 28day strength values. Time dependent flexural or compressive strengths were developed by the University of Georgia under RP 18-03 and are provided in the following sections. In cases where these mixtures are irrelevant, input level 3 is recommended for use: 28-day strength and elastic modulus. 1. 28-Day compressive strength: The median value from historical construction records for the 28-day compressive strength is 6,097 psi. It is recommended this value be used in Level 3 designs. The values provided in Table 8.13 are preferred for Level 1 and 2 designs. The mean flexural strength from the PCC calibration test sections was 705 psi. 103 Table 8.13--Time Dependent Compressive Strength for Georgia Concrete Mixtures Age of Specimen (days) Mix Number Mixture ID 7 14 28 90 20-yr/28 day Compressive Strength (psi) 1 541/0FA/0.431/11.91G/4.9 4,680 5,420 6,370 6,240 2 541/0FA/0.524/12.75G/4.0 4,810 5,440 6,300 6,680 3 595/0FA/0.43/11.4G/6.2 4,410 4,870 5,350 5,780 4 600/0FA/0.47/11.62G/6.1 3,130 3,820 4,280 4,490 5 580/12.2FA/0.493/12.54G/4.5 3,190 3,700 4,390 5,340 6 579/19.69FA/0.446/11.67G/5.5 3,090 3,580 4,140 5,420 1.20 7 622/26FA/0.422/12.14G/3.1 4,080 4,610 5,420 6,650 8 605/20.66FA/0.43/12.09D/5.0 4,240 4,920 5,700 7,450 9 590/18.64FA/0.438/10.87G/4.9 4,980 5,980 6,650 7,940 10 590/18.64FA/0.439/10.87D/5.9 4,150 4,450 5,220 6,570 11 600/20.16FA/0.47/11.42G/3.6 4,930 5,640 6,020 8,130 12 600/20.16FA/0.47/11.42G/4.7 3,820 4,520 5,190 6,950 NOTE: Mixture IDs signify: Cement Content/Fly Ash %/Water-Cement Ratio/CA Fraction/Air Content 104 2. 28-Day Modulus of elasticity: The modulus of elasticity (MOE) can be entered manually or calculated by the program based on the 28-day flexural or compressive strength value. Elastic moduli were acquired through RP 18-03 and presented in Table 8.14. For routine designs, it is recommended that the value be calculated by the software. The average elastic modulus from the PCC calibration test sections was 4,500,000 psi. Table 8.14--Time Dependent Elastic Modulus for Georgia Concrete Mixtures Age of Specimen (days) Mixture Number Mixture ID 7 14 28 90 20-yr/28 day Static MOE (ksi) 1 541/0FA/0.431/11.91G/4.9 5,100 5,150 5,350 5,650 2 541/0FA/0.524/12.75G/4.0 4,750 5,100 5,600 5,850 3 595/0FA/0.43/11.4G/6.2 4,350 4,450 4,600 5,100 4 600/0FA/0.47/11.62G/6.1 3,650 3,850 4,100 4,400 5 580/12.2FA/0.493/12.54G/4.5 2,650 2,950 3,150 3,700 6 579/19.69FA/0.446/11.67G/5.5 2,900 2,950 3,200 3,650 1.20 7 622/26FA/0.422/12.14G/3.1 3,150 3,350 3,550 4,250 8 605/20.66FA/0.43/12.09D/5.0 5,500 5,950 6,400 6,600 9 590/18.64FA/0.438/10.87G/4.9 3,550 3,900 4,150 4,600 10 590/18.64FA/0.439/10.87D/5.9 5,400 5,550 6,050 7,150 11 600/20.16FA/0.47/11.42G/3.6 4,950 5,050 5,350 5,950 12 600/20.16FA/0.47/11.42G/4.7 4,350 4,850 5,250 5,650 NOTE: Mixture IDs signify: Cement Content/Fly Ash %/Water-Cement Ratio/CA Fraction/Air Content 105 3. 28-Day modulus of rupture: The modulus of rupture (MOR) is only required for input level 1 and must be entered manually alongside elastic modulus values. Modulus of rupture values were acquired through RP 18-03 and are presented in Table 8.15. However, MOR specimens were tested using 3x4x16 inch beam sizes and may produce greater MOR values as a result. Table 8.15--Time Dependent Modulus of Rupture for Georgia Concrete Mixtures Age of Specimen (days) Mixture Number Mixture ID 7 14 28 90 20-yr/28 day MOR (psi) 1 541/0FA/0.431/11.91G/4.9 685 705 710 730 2 541/0FA/0.524/12.75G/4.0 640 695 725 730 3 595/0FA/0.43/11.4G/6.2 670 665 805 690 4 600/0FA/0.47/11.62G/6.1 630 630 665 665 5 580/12.2FA/0.493/12.54G/4.5 595 640 650 720 6 579/19.69FA/0.446/11.67G/5.5 615 600 620 730 1.20 7 622/26FA/0.422/12.14G/3.1 600 640 670 720 8 605/20.66FA/0.43/12.09D/5.0 615 630 660 765 9 590/18.64FA/0.438/10.87G/4.9 700 700 700 755 10 590/18.64FA/0.439/10.87D/5.9 615 645 635 765 11 600/20.16FA/0.47/11.42G/3.6 620 730 785 755 12 600/20.16FA/0.47/11.42G/4.7 650 640 715 740 NOTE: Mixture IDs signify: Cement Content/Fly Ash %/Water-Cement Ratio/CA Fraction/Air Content 8.4.5 Screen Shots for the PCC Properties: New Layers The following are screen shot examples that show the PCC material property inputs discussed within this section of Chapter 8. The drop-down arrows are used to access or select specific information and other input values for the project. 106 Overall Screen Shot for the PCC Material Properties 107 PCC Material Properties PCC Strength and Modulus 108 Cement Type Aggregate Type Curing Method 8.5 PORTLAND CEMENT CONCRETE (PCC) EXISTING FOR REHABILITATION DESIGNS 8.5.1 Existing Intact PCC Slabs Existing intact PCC properties are required for HMA overlay, unbonded PCC overlay and for concrete pavement restoration. Example screen shots showing the PCC material property inputs are included at the end of this section, primarily for the fractured slab condition. The PCC properties are the same as for new PCC mixes with the following exceptions. 109 The designer must assess the overall condition of the existing pavement PCC. Select typical modulus of elasticity values from the range of values given in Table 8.16 based on the amount of cracking (all types including longitudinal, transverse, corner, diagonal) of the existing PCC slabs. Table 8.16--Recommended Effective Modulus Values for Existing Intact PCC Slabs Qualitative Description of Pavement Condition Typical Modulus Ranges, psi Mean Modulus, psi Good/Adequate: (10 to 20 percent cracked slabs) 2 to 4 x 106 3.0 x 106 Marginal: (20 to 50 percent cracked slabs) 1 to 2 x 106 1.6 x 106 Poor/inadequate: (>50 percent cracked slabs) 0.2 to 1 x 106 0.65 x 106 NOTE: For backcalculation of PCC slab elastic modulus for uncracked slabs, the resulting modulus value is essentially a dynamic value that must be reduced by multiplying by 0.8 to obtain a static value to input into the Pavement ME. 8.5.2 Fractured PCC Slabs Existing fractured PCC properties are required for HMA or PCC overlays over fractured PCC pavements. GDOT does not routinely consider fracturing PCC slabs as part of their rehabilitation strategies. Guidance and the recommended input values for fractured PCC slabs are provided for future considerations. The two common methods of fracturing JPCP slabs include: crack and seat and rubblization. Of the two, the most effective to minimize reflection cracking is rubblization where the PCC slabs are broken into aggregate-sized pieces (less than 6 inches in diameter) that behave similar to a high-quality crushed aggregate layer. The PMED software can be used directly to design an HMA overlay of rubblized concrete similar to a flexible pavement design. Crack and seat involves cracking the slab into larger pieces (e.g., 3 to 6 ft. pieces) where the key design approach is to provide adequate HMA thickness to reduce deflections in the cracked JPCP 110 to prevent the pieces from becoming loose and rocking which leads to reflection cracking. The PMED software cannot be used to directly design a crack and seat project because HMA over a cracked and seated slab behaves totally different than a flexible pavement. Only the selection of a very conservative modulus of the cracked slab can obtain a reasonable design (the program does not model reflection cracking originating from crack and seated PCC pieces). Thus, it is recommended to assume conservative reflection cracking values to predicted transverse cracking values. The elastic modulus of the fractured PCC slabs should be selected in accordance with the values in Table 8.17. Table 8.17--Recommended Modulus Values for Fractured and Rubblized PCC Slabs Fractured PCC Type Elastic Modulus, psi Rubblized (into crushed granular like material) 50,000 Crack and seat 100,000 8.5.3 Screen Shots for the Fractured PCC Properties The following are screen shot examples that show the PCC material property inputs for the fractured slabs, as discussed within this section of Chapter 8. The drop-down arrows are used to access or select specific information and other input values for the project. 111 Overall Screen Shot for the JPCP Fractured Slabs Fractured JPCP Layer Properties 8.6 UNBOUND AGGREGATE BASE MATERIALS AND SOILS The material properties needed for the unbound aggregate base or subbase layer and embankment or subgrade soils are the same in the PMED software for flexible and rigid pavement 112 designs. Example screen shots showing the unbound aggregate base and subgrade soil or embankment material property inputs are included at the end of this section. The GDOT materials library includes one file for each of the different unbound base materials typically used in construction and one file for each of the major GDOT soil classifications found in Georgia. The following subsections simply describe the properties included in these files. 8.6.1 General Physical and Volumetric Properties The following unbound layer and embankment soil properties are site specific and easily determined from laboratory tests. Table 8.18 depicts the typical material properties for standard GDOT soil classifications. 1. Gradation of the material. 2. Atterberg limits tests. 3. Specific gravity. 4. Maximum dry density or the in-place density at the time of construction. 5. Optimum water content or the in-place water content at the time of construction. Material Name IA1 IA2 IA3 IIB1 IIB2 IIB3 IIB4 Table 8.18--Material Library Subgrade Properties Input Properties Percent Passing, % No. No. No. No. No. 4 10 40 60 200 Liquid Limit Plastic Limit Maximum Dry Density, pcf Optimum Water Content, % 100 99.5 70.1 46.2 13.1 25 9 118 10.7 100 99.7 70.7 48.0 14.7 23 7 116 12.6 100 99.5 75.4 55.5 12.7 25 9 106 14.5 100 100 73.9 52.2 23.9 25 9 122 9.9 100 99.3 72.8 55.0 29.0 28 9 118 11.5 100 98.8 75.9 59.9 34.6 23 7 112 14.4 100 99.1 80.2 66.8 41.4 39 13 100 19.1 113 For the GAB layers, all default layer properties included in the PMED software for a Crushed Stone Base should be assumed, except for resilient modulus, optimum water content, and maximum dry density. Predefined GAB material files have been developed for the GDOT library using the information found in Table 8.18 and Appendix C. These values represent the recommended values for different GAB materials used in Georgia. A subsurface investigation or soil survey should be planned to determine the above inputs for the project. If a soil survey and/or pavement investigation is not completed prior to design, the geotechnical engineer can provide values for these inputs based on historical information. The geotechnical engineer should be consulted to determine representative values for each design segment along the project. For the soils that are not disturbed during construction, the in-place moisture content and dry density should be entered. For the crushed gravel and other aggregate base materials used in Georgia or the embankment soils that are compacted, the mid-range of the specifications or construction data from previous projects can be used to determine the input values. The expected moisture content and dry density after compaction should be entered. 8.6.2 Resilient Modulus Kim (2013) conducted repeated load resilient modulus tests on typical aggregate base materials used in Georgia and on the more common soils encountered in Georgia through RP 12-07. Resilient modulus tests can also be determined from Dynamic Cone Penetrometer (DCP) tests and physical properties of the material/soil, which is input level 2. For new alignments or new designs, as well as rehabilitation designs, Tables 8.19 and 8.20 provide the suggested mean value and the range of those values for the different unbound 114 materials that were used in the calibration refinement for Georgia and derived from the repeated load resilient modulus tests for the granular aggregate base and subgrade soils, respectively. Table 8.19--Resilient Modulus Values for Granular Aggregate Base Materials in Georgia Group Type of Material or Soil Source Type Optimum Water Maximum Dry Content, % Density, pcf Typical Mean Resilient Modulus, psi II NA* Recycled Concrete 11.2 121.0 25,000 II Lithonia Granite Gneiss 5.7 II Stockbridge Granite Gneiss 5.9 II Columbus Granite Gneiss 6.0 II Dahlonega Granite Gneiss 5.6 II Gainesville Mylonitic Gneiss 6.0 II Hitchcock Mylonitic Gneiss 6.2 II Walton County Biotite Gneiss 6.4 Default Values All Gneiss GAB 6.0 133.9 134.2 137.6 135.2 136.6 141.2 135.0 136.5 25,000 21,000 20,000 17,000 20,000 22,000 22,000 23,000 I Dalton Limestone 6.6 II Demorest Meta Sandstone 5.3 I Mayo Mine Limerock 13.6 * Not Applicable. 142.5 137.4 112.6 22,000 18,000 25,000 Table 8.20--Resilient Modulus Values Derived for Selected Subgrade Soils in Georgia Type of Material or Soil Location or County GA Soil Class AASHTO Class Optimum Water Content, % Maximum Dry Density, pcf Typical Mean Resilient Modulus, psi Default A-1-a 7.4 127.2 18,000 Toombs IA1 A-1-b 11.9 119.3 13,000 Default A-1-b 9.1 123.7 18,000 Lowndes IIB2 A-2-4 4.7 113.1 17,000 Washington IIB2 A-2-4 11.0 117.8 18,000 Default A-2-4 9.0 124.0 16,500 Franklin IIB3 A-2-4 22.6 105.1 5,000 Default A-2-5 10.1 121.9 16,000 Default A-2-6 10.0 121.9 16,000 Coweta IIB3 A-2-7 16.7 105.3 9,000 Chatham IIB4 A-2-4 12.7 97.4 15,000 Default A-2-7 10.6 120.8 16,000 Default A-3 7.3 120.0 16,000 Default A-4 11.8 118.4 15,000 Lincoln IIB4 A-4 23.5 93.4 8,000 Default A-5 11.4 119.2 8,000 Default A-6 17.1 107.9 14,000 Default A-7-5 20.0 102.0 10,000 Walton IIB4 A-7-6 16.8 104.8 10,000 Default A-7-6 22.2 97.7 9,000 NOTE: The optimum water content and maximum dry density listed in this table were determined using the Modified Proctor compaction effort. 115 Where Table 8.20 is not applicable, Figure 8.3 may be used to determine an appropriate subgrade classification to use for input level 2 and 3 designs based on your project location. Subgrade material files of the same name in the GDOT library include a typical resilient modulus value for that region along with the particle size distribution, maximum dry density, and optimum moisture content. The properties for each material classification are summarized in Table 8.18. Figure 8.3--Subgrade Classification and Modulus Inputs by County 116 For rehabilitation/reconstruction designs, the resilient modulus of each unbound layer and embankment can be backcalculated from deflection basin data (input level 1) or estimated from DCP and other physical properties of the soil (input level 2). If the resilient modulus values are determined by backcalculating elastic layer modulus values from deflection basin tests, those values need to be adjusted to laboratory conditions. Table 8.21 lists the adjustment ratios that should be applied to the unbound layers for use in design. More importantly, the in-place water content and dry density need to be entered in the PMED software when the in place resilient modulus values are used. GDOT generally does not use the Dynamic Cone Penetrometer (DCP) for pavement evaluations and in estimating the resilient modulus of the unbound materials and soils. However, the DCP (ASTM D6951/D6951M-18) was used in the field investigation of all non-LTPP roadway segments included in the local calibration process. Equation 6 was used to calculate the resilient modulus from the penetration rate measured with a standard 17.6-lb (8-kg) DCP and may be applied to fine- and coarse-grained soils, granular construction materials, and weak stabilized or modified materials. It is suggested that the DCP be considered for future use for rehabilitation design for the unbound pavement layers and subgrade, especially when FWD deflection basin data are unavailable. 0.64 MR = 17.6 ( 292 ) DPI 1.12 (CDCP ) (6) Where: MR = Resilient modulus of unbound material, MPa. DPI = Penetration rate or index, mm/blow. 117 CDCP = Adjustment factor for converting the elastic modulus to a laboratory resilient modulus value. The resilient modulus values can be estimated from the DCP tests using equation 6, but those values need to be adjusted to laboratory conditions. Table 8.21 provides the adjustment factors recommended for use in estimating resilient modulus from the DCP penetration rate. (It should be noted and understood that the PMED does not adjust the resilient modulus values calculated from the DCP and the values in Table 8.21 have not been field verified for GDOT). Table 8.21--Resilient Modulus Values Derived for Subgrade Soil from DCP Tests for Use in Georgia Material/Soil Class Condition Adjustment Factor, CDCP Clay-Silt Above Optimum Water Content 1.90 Fine-Grained; Low Plasticity Soil Soil-Sand Mix At or Below Optimum Water Content 1.05 Soil-Aggregate Mix At or Below Optimum with Large Aggregate Water Content 0.60 Coarse-Grained Soil-Aggregate Mix At or Below Optimum Water Content 0.60 Material Crushed Aggregate At or Below Optimum Water Content 1.04 The resilient modulus of aggregate or granular base/subbase is dependent on the resilient modulus of the supporting layers. As a rule of thumb, the resilient modulus entered into PMED for a granular base layer should be less than three times the resilient modulus of the supporting layer to avoid decompaction of that layer. This layer modulus ratio is dependent on the type of base and thickness of the base layer. 118 Table 8.22--Summary of the Adjustment Factors Recommended for Use in Georgia to Convert Backcalculated Layer Modulus Values to Laboratory Equivalent Modulus Values Layer & Material Type Layer Description Adjustment Factor, (MR/E) FHWA Pamphlet Georgia Sites Granular base under a Portland Cement Concrete (PCC) surface 1.32 --- Aggregate Base Layers Granular base under a CAM layer, semi-rigid pavement Granular base above a stabilized material (a Sandwich Section) --1.43 0.75 --- Granular base under an HMA surface or base 0.62 0.60 Soil under a CAM layer, no granular base --- 1.00 Subgrade Soil/Foundation Soil under a semi-rigid pavement with a granular base/subbase Soil Under a Stabilized Subgrade Soil under a full-depth HMA pavement --- 0.50 0.75 --- 0.52 --- Soil under flexible pavement with a granular base/subbase 0.35 0.50 Cement Aggregate Base Layer Cement stabilized or treated aggregate layers --- 1.50 HMA surface and base layers, 41 F 1.00 0.9 HMA Mixtures HMA surface and base layers, 77 F 0.36 0.6 HMA surface and base layers, 104 F 0.25 0.5 Finally, the optimum water content is generally provided for the different unbound materials and soils encountered along a project and may also be used as a means to estimate resilient modulus. Figure 8.4 can be used to adjust the resilient modulus of the unbound aggregate base layer to ensure that it is in agreement with the above rule of thumb. Note that as the base comprises a single layer, only a single adjustment based on base layer thickness and subgrade resilient modulus is required. 119 Figure 8.4--Estimating the Resilient Modulus from the Optimum Water Content 8.6.3 Poisson's Ratio Poisson's ratio is another input parameter needed for the unbound materials and soils. Table 8.23 lists the values that were used during the regional calibration refinement effort and are recommended for use in future design runs. Table 8.23--Poisson's Ratio Suggested for Use for Unbound Layers GDOT Soil Class Description Poisson's Ratio IA1 to IA2 Medium to well-graded sand or clayey sand 0.40 IA3 Fine-grained, silty, or clayey sand 0.40 IIB4 High plasticity fine-grained soils (clays and silts). 0.45 IIB2 to IIB3 Low plasticity fine-grained soils (clays and silts). 0.40 IIB1 or Better Non-plastic or low plasticity fine-grained soil or coarse-grained soil with more than 35 percent fines or material passing the #200 sieve. 0.35 IIIC1 High plasticity and expansive clay soils. 0.45 I or Base Soil-Aggregate base materials which are predominately coarsegrained. 0.35 GAB Crushed gravel or crushed stone base materials used as a base or subbase layer. 0.30 120 8.6.4 Hydraulic Properties The other input parameters for the unbound layers are more difficult to measure and were not readily available for use in the regional calibration refinement effort. For these inputs, the default values recommended for use in the MOP Second Edition were used to predict the distresses. Therefore, the MOP default values are also recommended for use in Georgia for the following properties. 1. Soil saturated hydraulic conductivity. 2. Soil-water characteristic curves. 121 Note: For 12 inch GAB layers, simply use the 10 inch line in this graph. Figure 8.5--Limiting Layer Modulus Criterion of Unbound Aggregate Base Layers 8.6.5 Screen Shots for the Unbound Base and Subgrade Layer Properties The following are screen shot examples that show the unbound base and subgrade layer property inputs, as discussed within this section of Chapter 8. The material and layer properties are the same between the aggregate base and subgrade or embankment layers. The drop-down arrows are used to access or select specific information and other input values for the project. 122 Overall Screen Shot for the Unbound Layers 123 Resilient Modulus Drop Down Arrow Sieve; Gradation & Other Engineering Properties Drop Down Arrow 8.7 CEMENT AGGREGATE BASE MIXTURES The compressive strength (modulus of rupture), elastic modulus, and density are required inputs in the PMED software for any cementitious or pozzolonic stabilized material. The agency specific calibration factors are determined based on the quality of the CAM material. The LTPP database for test sections with cementitious layers did not contain material properties for these test sections. Table 8.24 provides the layer properties for interim use until the distress prediction models have been calibrated with more test sections. The minimum elastic modulus for all CAM layers is 100,000 psi. The other layer and material properties inputs for the cement aggregate base mixtures are the same as for the stabilized subgrade layers under Section 8.8. 124 Table 8.24--28-Day Strength and Elastic Moduli Suggested for Use for Cement Aggregate Base Layers Description of CAM Layer 28-Day Compressive 28-Day Elastic Density, Strength, psi Modulus, psi pcf High Strength CTB (intact cores recovered with cement content greater than 6 percent) 1,500 2,100,000 150 Moderate Strength CTB (intact cores recovered with cement contents greater than 600 1,350,000 150 4 percent but less than 6 percent) Low Strength CTB (intact cores cannot be Semi-Rigid Pavement Simulation not applicable; recovered with cement content generally less assume conventional flexible pavement with high than 4 percent) stiffness GAB layer. 8.8 STABILIZED SUBGRADE FOR STRUCTURAL LAYERS The compressive strength (modulus of rupture), elastic modulus, and density are required inputs to the PMED software for any cementitious or pozzolonic stabilized material. The agency specific calibration factors are determined based on the quality of the CAM material. The LTPP database for test sections with cementitious layers did not contain material properties for these test sections. Table 8.25 provides the layer properties for interim use until the distress prediction models have been calibrated with more test sections. The minimum elastic modulus for all CAM layers is 100,000 psi. The other layer and material properties inputs for the cement aggregate base mixtures are the same as for the stabilized subgrade layers under Section 8.8. Table 8.25--Resilient Modulus and Poisson's Ratio Values Suggested for Use for Stabilized Subgrade Layers Type of Stabilized Subgrade Recommended Representative Annual Resilient Modulus, psi Recommended Poisson's Ratio Soil Cement and Cement Stabilized Soils 100,000 0.2 Lime-Fly Ash Stabilized Soils 50,000 0.30 3 times the resilient modulus of the soil at Lime Stabilized Soils optimum water content and maximum dry 0.35 unit weight. For a full-depth flexible pavement when the HMA mixture is placed directly over the stabilized subgrade soil, this is considered a semi-rigid pavement. As noted in previous chapters, semirigid pavements were not calibrated during the original global calibration studies, as well as for 125 GDOT local calibration study. Example screen shots showing the stabilized layer material property inputs are included at the end of this section below. 8.8.1 Screen Shots for the Stabilized Base/Subgrade Layer Properties The following are screen shot examples that show the stabilized base or subgrade layer property inputs, as discussed within this section of Chapter 8. The material and layer properties are the same between the cement stabilized base layers and the cement or lime stabilized subgrade soil. The drop-down arrows are used to access or select specific information and other input values for the project. 126 Overall Screen Shot for the Stabilized Base/Subgrade Layers 127 8.9 BEDROCK Table 8.26 provides guidance on determining the inputs for a bedrock layer when it exists within the project limits. For locations where the depth to bedrock exceeds 100 inches or has more than 100 inches of soil above it, assume the subgrade is infinite and do not enter the bedrock layer. An example screen shot showing the bedrock material property inputs are included at the end of this section below. Table 8.26--Layer Properties for Bedrock Bedrock Parameters Recommended Input Value Depth to Bedrock Estimate based on the soil borings or topography. Elastic Modulus Severely Weathered Bedrock Highly Fractured Bedrock Massive and Continuous Bedrock 50,000 psi 500,0000 psi 1,000,000 psi Poisson's Ratio Severely Weathered Bedrock Highly Fractured Bedrock Massive and Continuous Bedrock 0.30 0.20 0.15 Unit Weight 140 pcf 8.9.1 Screen Shots for the Bedrock Properties The following are screen shot examples that show the bedrock layer property inputs, as discussed within this section of Chapter 8. The drop-down arrows are used to access or select specific information and other input values for the project. 128 Overall Screen Shot for Bedrock Bedrock Layer Properties 129 CHAPTER 9--GEORGIA CALIBRATION FACTORS Through the calibration efforts of RP 11-17 both LTPP and non-LTPP test sections were used to estimate the precision and bias of the transfer functions in the MOP for predicting the performance indicators (distress and roughness) of GDOT's pavements in PMED. The resulting distress prediction models, or transfer functions, can be used to optimize new pavement and rehabilitation design strategies, and used in forecasting of maintenance, repair, rehabilitation, and reconstruction costs. A summary of the input parameters and associated design level used to determine the calibration factors for v.2.3 of PMED is found in Table 9.1. Further details on the input library utilized for GDOT's local calibration are documented in the Task 2 interim report provided from RP 11-17 and are defined in the MOP. Table 9.1-- Input Levels used in Calibration of PMED Transfer Functions Calibration Input Input Group Performance Indicator Level 1 2 3 Axle Load Distributions (single, tandem, tridem) X Truck Volume Distribution X Truck Traffic Lane and Directional Truck Distributions Tire Pressure X X Axle Configuration, Tire Spacing X Truck Wander X Climate Temperature, Wind Speed, Cloud Cover, Precipitation, Relative Humidity X Material Properties Unbound Layers and Subgrade HMA Resilient Modulus- All Unbound Layers Classification and Volumetric Properties Moisture-Density Relationships Soil-Water Characteristic Relationships Saturated Hydraulic Conductivity HMA Dynamic Modulus HMA Creep Compliance and Indirect Tensile Strength Volumetric Properties X X X X X X X X X X X HMA Coefficient of Thermal Expansion X 130 PCC All Materials Existing Pavement PCC Elastic Modulus PCC Flexural Strength PCC Indirect Tensile Strength (CRCP Only) PCC Coefficient of Thermal Expansion Unit Weight Poisson's Ratio Other Thermal Properties; conductivity, heat capacity, surface absorptivity Condition of Existing Layers X X X X X X X X X X X X 9.1 BASELINE FILES FOR THE CALIBRATION FACTORS Some of the GDOT calibration factors for both flexible and rigid (JPCP) pavements are different than the global calibration factors. As such, 14 baseline files were created that include the GDOT calibration factors, so the designer does not have to manually enter these values for every design problem. The files listed in Table 9.2 contain the recommended calibration factors up to v.2.3 of PMED and the MOP Second Edition only. The most recent Edition of the MOP and subsequent software updates may contain different coefficients and require recalibration. The designer will need to open the appropriate PMED file listed above. These files are located along with the other available files from the GDOT materials library. Once the file is opened in the software, use the "Save As" function to rename the file under the appropriate convention. Once saved, make the appropriate revisions or changes to the baseline file using project specific features and layer properties. 131 Pavement Type Table 9.2-- GDOT Baseline Files Baseline File Name Applicable Design Strategy New Pavement GA_Generic_NewFlexible_Neat Mixes GA_Generic_NewFlexible_PMA Mixes Conventional, deep-strength or fulldepth design strategy. The baseline file was setup as a conventional and deepstrength pavement without subgrade stabilization. If a full-depth pavement is considered, the granular aggregate base layer would need to be removed or deleted; and if a stabilized subgrade is needed, that layer would need to be added. The calibration factors for all transfer functions for these design strategies are the same. This baseline file is also applicable to the fractured PCC slab with an HMA/AC overlay strategy Rehabilitation/ Overlay GA_Generic_SemiRigid GA_Generic_Inverted Pavement New_JPCP New_CRCP GA_Generic_AC Overlay_Flexible_Neat Mixes GA_Generic_AC Overlay_Flexible_PMA Mixes GA_Generic_AC Over SemiRigid JPCP_over_AC CRCP_over_AC Unbonded_JPCP_over_JPCP Unbonded_CRCP_over_JPCP JPCP_Restore Semi-rigid pavement design Inverted pavement design JPCP design strategy; the new (2014) global calibration factors were validated CRCP design strategy; the global calibration factors were not changed because of insufficient sections and data HMA/AC overlay design strategy JPCP design strategy CRCP design strategy Unbonded JPCP overlay strategy Unbonded CRCP overlay strategy Diamond grinding, slab replacement, and retrofit dowels (if needed) strategy. 9.2 TRANSFER FUNCTION CALIBRATION COEFFICIENTS The remainder of this chapter simply lists the GDOT calibration factors for each transfer function for both flexible and rigid pavements. Tables 9.3 to 9.6 list the appropriate flexible pavement 132 calibration factors from the GDOT local calibration study, which are included in the above baseline files in the GDOT material library, and Tables 9.7 and 9.8 list the appropriate rigid pavement (JPCP) calibration factors. The values highlighted in these tables represent the GDOT calibration factors as determined through RP 11-17 that differ from the global calibration factors for Version 2.3 of the PMED software. The calibration coefficients for the IRI regression equation for both the flexible and rigid pavements are not included within this chapter because the local calibration factors are the same as for the global calibration factors they remained unchanged. In addition, the calibration coefficients for the reflection cracking regression equation for HMA/AC overlay of flexible and rigid pavements are the same as for the global calibration factors. Along with the Third Edition MOP that was published in 2020, PMED Version 2.6 released in July 2020 will contain an updated top down cracking model and transfer function. New validation and potentially additional data will be necessary in order to implement or use the top down cracking as a design criterion in future software iterations. Example screen shots showing the calibration factor inputs are included at the end of this section. Table 9.3-- HMA/AC Rutting: GDOT Calibration Factors Transfer Function Coefficient Global Value GDOT Value Neat Mixtures PMA Mixtures K1 -3.35412 -2.45 -2.55 K2 1.5606 1.5606 1.5606 K3 0.4791 0.30 0.30 Global Standard Deviation Equation: RutDepth,HMA = 0.24 * Pow(Rut,0.8026) + 0.001 GDOT Standard Deviation Equation: ( ) Georgia RutDepth, HMA = 0.20 * Pow Rut,0.550 + 0.001 133 Table 9.4-- Unbound Layer Rutting: GDOT Calibration Factors Transfer Function Coefficient Global Value GDOT Value Coarse-Grained, Bs1 1.0 0.50 Fine-Grained, Bs1 1.0 0.30 NOTE: The standard deviation equation for the unbound layer rutting was not changed from the local calibration process. Table 9.5-- HMA/AC Bottom-Up Fatigue Cracking: GDOT Calibration Factors Transfer Function Coefficient Global Value GDOT Value (Typical HMA Mixtures) K1 0.007566 0.00151 K2 3.9492 3.9492 K3 1.281 1.281 C1 1.0 2.2 C2 1.0 2.2 C3 6,000 6,000 Global Standard Deviation Equation: Bottom-Up = 1.13 + 1 + 13 e 7.57-15.5Log (DI +0.0001) GDOT Standard Deviation Equation: Georgia Bottom-Up = 1.0 + 1 + 10 e 7.5-6.5Log (DI +0.0001) Table 9.6--HMA/AC Thermal Transverse Cracking: GDOT Calibration Factors Transfer Function Coefficient Global Value GDOT Value (Typical HMA Mixtures) Bt1 1.5 35 Bt3 1.5 35 NOTE: The standard deviation equation was not revised from the local calibration process. However, 50 percent reliability is recommended for use in design so the standard deviation equation will have no impact (see Table 4.7 in Section 4 of this Guide). Table 9.7--JPCP Mid-Slab Cracking: GDOT Calibration Factors (Use for all JPCP Applications: Overlays and Restoration) Transfer Function Global Value GDOT Value Coefficient C1 2.0 2.0 C2 1.22 1.22 C4 0.52 0.52 C5 -2.17 -2.17 Standard Deviation 3.5522 * Pow(CRACK,0.3415) + 0.75 3.5522*Pow(CRACK,0.3415)+0.75 134 Table 9.8--JPCP Faulting: GDOT Calibration Factors (Use for all JPCP Applications: Overlays and Restoration) Transfer Function Global Value GDOT Value Coefficient C1 0.595 0.595 C2 1.636 1.636 C3 0.00217 0.00217 C4 0.00444 0.00444 C5 250 250 C6 0.47 0.47 C7 7.3 7.3 C8 400 400 Standard Deviation 0.07162*Pow(FAULT,0.368)+0.00806 0.07162*Pow(FAULT,0.368)+ 0.00806 Table 9.9--CRCP Punchout: GDOT Calibration Factors (All CRCP Applications) Transfer Function Global Value GDOT Value Coefficient C1 2 2 C2 1.22 1.22 C3 107.73 107.73 C4 2.475 2.475 C5 -0.785 -0.785 Standard Deviation 2.208*Pow(PO,0.5316) 2.208*Pow(PO,0.5316) 9.3 SCREEN SHOTS FOR THE CALIBRATION COEFFICIENTS The following are screen shot examples that show the calibration coefficient inputs, as presented within this section of Chapter 9. The purpose of the screenshots are to show the general location of the items and the details within the screenshot should not be used directly. It should be noted that the actual values for the calibration factors in the screenshots are not always equal to the values that should be used. 135 Overall Screen Shot for Calibration Coefficients Flexible Pavements Overall Screen Shot for Calibration Coefficients Rigid Pavements NOTE: The PCC cracking C4 and C5 values are different from the GDOT values. 136 Flexible Pavement Calibration Coefficients Rigid Pavement Calibration Coefficients 137 CHAPTER 10--CONCLUSIONS AND IMPLEMENTATION PLAN The foundation for implementation of the MEPDG and associated software for GDOT pavement design practices is well established as evident by the contents of this document. However, the transition to these practices still requires the completion of on-going and future research efforts regarding the PMED software and its inputs. This chapter serves to identify the remaining needs and tasks necessary for implementation and continual use of PMED and all future iterations of the software. Additional information on this topic may be found in the official GDOT Implementation Plan (Von Quintus et al., 2016). 10.1 IMPLEMENTATION ACTIVITIES GDOT has been preparing for the implementation of the MEPDG methodology for several years through its sponsorship of MEPDG-related activities. The following list highlights the major activities that may be considered implemented or recognized by the most recent calibration efforts and included in current PMED practices. 1. GDOT Project 10-09: GDOT Load Spectra Program. February 2011 February 2013 (Selezneva et al., 2014) 2. Report GDOT-TO-01-Task 1, Literature Search and Synthesis Verification and Local Calibration/Validation of the MEPDG Performance Models for use in Georgia, July 2013 (Von Quintus et al., 2013a) 3. Report GDOT-TO-01 Task 2, Validation of the MEPDG Transfer Functions using the LTPP Test Sections in Georgia, July 2013 (Von Quintus et al., 2013b) 138 4. GDOT Project 10-10: Georgia Concrete Pavement Performance and Longevity. May 2010 February 2012 (Tsai et al, 2014) 5. GDOT Project 10-04: Determination of Coefficient of Thermal Expansion for Portland Cement Concrete for MEPDG Implementation, October 2012 (Kim, 2012) 6. GDOT Project 05-19: Improving GDOT's Highway Pavement Preservation (Tsai et al., 2009) 7. GDOT Research Project 12-07: Measurements of Dynamic Modulus and Resilient Modulus of Roadway Test Sites, December 2013 (Kim, 2013) 8. Report GDOT-TO-02-Task 3, Calibration of the MEPDG Transfer Functions in Georgia, July 2014 (Von Quintus et al., 2014) 9. Report FHWA/GA-DOT-RD-014-1117: Georgia DOT Pavement ME Design User Input Guide, November 2014; and Georgia DOT Pavement ME Design Software Manual, 2015 (Von Quintus et al., 2015) Since the adoption of these efforts toward implementing the MEPDG methodology and development of the GDOT input libraries, more activities have been conducted that have not yet been integrated into the most recent calibration and PMED practices. These include both completed and ongoing GDOT research projects as well as other reports and activities. Three notable highlights from these efforts include (1) improvement of predicted pavement performance using MERRA climate data, (2) expansion of the existing HMA materials library, and (3) establishment of an extensive concrete material properties library. 1. GDOT Research Project 16-10: Improvement of Climate Data for use in MEPDG Calibration and other Pavement Analysis (Durham et al., 2019) 139 2. GDOT Research Project 16-19: Effects of Asphalt Mixture Characteristics on Dynamic Modulus and Fatigue Performance (Kim et al, 2019) 3. GDOT Research Project 18-03: Development of Concrete Material Property Database for Pavement ME Input. October 2018 Ongoing. 4. GDOT Research Project 18-04: Development of Equivalent Single Axle Load (ESAL) Factor for Georgia Pavement Design. October 2018 Ongoing. 5. GDOT Research Project 19-16: Improvement of Climate Data for use in MEPDG Calibration and other Pavement Analysis- Phase II. August 2019 Ongoing. 6. Continued performance monitoring and use in future updates to the local calibration coefficients of the transfer function. 7. Improved design manuals, workshop, and training materials on using the PMED software. The completion of these activities has provided GDOT with valuable information and data necessary for conducting concurrent pavement designs using PMED. Before these designs may be considered as a GDOT approved design strategy, further actions must be taken to verify and validate their effect on the PMED performance predictions. 10.2 REMAINING IMPLEMENTATION ITEMS While the existing resources have provided GDOT with the necessary tools to perform preliminary designs, several actions must be taken to ensure the continual operation of the PMED software. The following sections discuss the most pertinent actions required to reach full implementation. 140 10.2.1 Truck Traffic Input Library Expansion of the WIM database and continual developments under RP 18-04 will result in increased truck weight data for improving on the truck traffic default values. As a result, the traffic input libraries will need to be expanded and updated to include of the new WIM data. The analysis of the added WIM data should be used to determine if the existing traffic inputs need to be revised and/or expanded to cover the range of GDOT roadway classifications. It is strongly recommended that the WIM data be used to confirm whether the default input values (especially the normalized axle load spectra or distribution) need to be revised or additional default values be added to the truck traffic library. 10.2.2 Climate Data Updates to the PMED climate input process in v.2.5 of the software have not been evaluated for their effect on pavement performance using the GDOT calibration sections because the NARR and MERRA-2 hourly climate data were not available at the time the calibration was performed. Further, the improved MERRA data outlined in RP 16-10 as well as the custom climate files developed as part of the new climate study will have both direct and indirect effect on pavement design inputs. Upon completion of RP 16-19, the new climate data inputs should be verified and validated to see if the data show significant changes in the software analysis. Due to the impact of climate on the pavement performance models, it is likely that a recalibration of the transfer function coefficients will be necessary. 10.2.3. Materials/Layer Input Library 1. AC/HMA materials: 141 The further expansion of the GDOT HMA library under RP 16-19 has provided the dynamic modulus, dynamic shear modulus, and phase angle inputs for several standardized HMA mixtures. Presently, the transfer function coefficients for rutting and fatigue cracking represent general conditions that are not specific to these measured mixture characteristics. A reevaluation of these distress models is required before considering the additional inputs in current designs. Recent changes have been made to the indirect tensile and creep compliance inputs for HMA materials in PMED v.2.5 and the current edition of the MOP. These properties were not available for the latest calibration of GDOT transfer functions and remain undocumented in the GDOT materials library. Therefore, material testing is still required to determine laboratory derived fatigue cracking coefficients from flexural bending beam fatigue tests or the indirect tensile strength test. The flexural bending beam fatigue test should be performed in accordance with AASHTO T 321, and the indirect tensile test in accordance with ASTM D6931. The laboratory derived fatigue cracking coefficients must be used to determine the field-derived, mixture specific fracture coefficients that impact flexible pavement performance models in PMED. 2. PCC materials No testing data was available in the GDOT material library for local calibration of the PCC materials with the exception of the coefficient of thermal expansion (CTE). As a result, level 2 and 3 inputs were relied upon for all current rigid pavement transfer functions. Ongoing research efforts have provided extensive laboratory measurements on several standardize concrete mixtures to be added to this library. New measurements include fresh mixture, volume characteristic, thermal, and strength properties. Upon the 142 completion of this library, the new material properties will need to be verified, validated, and included in the latest recalibration before implemented in the PMED input process. 3. Unbound/Base materials: Resilient modulus testing of both unbound granular aggregate base (GAB) materials and subgrade soils is already included in the GDOT material library. Although the resilient modulus testing of GAB materials is fairly complete, the resilient modulus of subgrade soils should be expanded to include all major soil types or classes throughout the state. Additionally, extensive laboratory testing on cement stabilized base materials is still omitted from the input library. 10.2.4. Recalibration and Verification Global calibration of the PMED transfer functions was completed under NCHRP Projects 1-37A and 1-40, and as a part of the annual software updates in 2018, primarily using data extracted from the Long Term Pavement Performance (LTPP) database over a wide range of pavement sections from across the United States, including some in Canada. Under RP 11-17, the transfer functions were initially verified and calibrated using performance data from Georgia LTPP and non-LTPP roadway segments with current design and materials and construction standards, as part of the early MEPDG implementation process in Georgia. However, the verification-calibration effort is not a one-time activity and should be conducted periodically to verify if the accuracy and bias of existing transfer functions with consideration to new materials, techniques, and design strategies have changed. Additionally, future versions of the software will continue to introduce new or improved prediction models that must be validated. For example, a new top-down cracking transfer function is expected to release in v.2.6 of PMED. 143 This distress model will require validation and potentially new data before being considered as a design criterion. As a result of these changes and recent additions to the GDOT input library, recalibration is required to establish more accurate relationships between the computed structural responses, accumulated damage, and observed pavement distresses. In October 2019, the web-based Calibration Assistance Tool (CAT, v1.0) was made available to help agencies conduct comparisons between versions and perform local calibrations of the PMED performance models. The tool was developed in accordance with the 11-step procedure given in the AASHTO Local Calibration Guide and is a full-factor web application, consisting of a calibration database with a subset of LTPP sections used in the global calibration and userdefined test sections. While more convenient than previous calibration methods, this tool requires significant user engagement and engineering decisions. In order to utilize the CAT for current and future iterations of the PMED design practices, GDOT must continue monitoring existing test sections and establish additional sections with newer mixtures, design strategies, and materials. These activities will provide long term performance data and ensure the transfer functions are producing reliable results. 10.3 CONCLUSIONS The contents of this report provide GDOT with the means to develop pavement designs and evaluate certain performance criteria in accordance with the MEPDG MOP Second and Third Editions. Recent additions to the PMED input library also included in this report are available, but not yet used to calibrate the performance prediction models, and can be used in current and future software versions. In order to ensure the long-term success of implementing the MEPDG, the remaining services outlined in this chapter will greatly help current and future pavement design engineers: 144 1. Select the most appropriate design strategies for specific conditions, 2. Easily identify the most representative materials, traffic, and climate data that are specific to Georgia conditions, 3. Streamline the design process to focus on making engineering decisions instead of manually entering input data, and 4. Use designs and models that are calibrated to Georgia specific field conditions These services must be procured through either outsourced contracts or Research Needs Statements (RNS). Once completed, GDOT can fully endorse and complete the transition from the existing pavement design methodologies to the ME-based approach. 145 CHAPTER 11--INPUT WORKSHEET This chapter of the Input User Guide provides a series of worksheets or checklists for the designer to use, at least in the beginning, for setting up a design problem and selecting the inputs. One worksheet is provided for flexible pavements and one for rigid pavements. Each worksheet includes the recommended default values for those input parameters that should remain unchanged, and references the sections and/or appropriate tables in this User Input Guide. Multiple example problems are included in a separate document, defined as Volume 2, to the Input User Guide. All appropriate worksheets have been completed for each example design problem and are included in Volume 2. 146 CHECK LIST OF INPUTS FOR NEW AND REHABILITATED FLEXIBLE PAVEMENT DESIGNS Input Parameter GDOT Input Value Comment General Design Type Pavement Type New Pavement or Overlay Flexible Pavement or AC over AC Section 3.1.1 Information Design Life, years (20)* Section 3.3 Base/Subgrade Construction Date Pavement Construction Date Section 3.4; Table 3.2 Traffic Opening Date Initial IRI, in./mi. Section 4.1, Table 4.1 Terminal IRI, in./mi. Section 4.2.1, Table 4.6 Top-Down Fatigue Cracking, ft./mi. (5,000)** Not considered in design. Bottom-Up Fatigue Cracking, % Performance Thermal (Transverse) Cracking, Criteria ft./mi. Permanent Deformation (Rut Depth)- Total Pavement, inches Section 4.2, Tables 4.2 and 4.5 Permanent Deformation (Rut Depth)- AC Only, inches AC Total Cracking (Overlays), % Section 4.2, Table 4.5 Reliability Level, percent Section 4.3, Table 4.7 Two-Way Average Annual Daily Truck Traffic Number of Lanes in Design Direction Section 5.1 Traffic, Site Features Percent Trucks in Design Direction (DDF) (50)* Percent of Trucks in Design Lane (LDF) Section 5.1; Table 5.1 Operational Speed Section 5.1 Traffic Capacity Cap (Not Enforced)* Section 5.2 Avg. Axle Width (8.5)* General Traffic, Axle Configuration Dual Tire Spacing Tire Pressure Tandem Axle Spacing Tridem Axle Spacing (12)* (120)* (51.6)* (49.2)* Section 5.3; use global default values Quad Axle Spacing (49.2)* * - Default values should be used. ** - Excessively high value used so that top-down cracking does not control design when the optimization tool is being used. 147 Mean Wheel Location Traffic; Lateral Wander Traffic Wander, Standard Deviation Design Lane Width Traffic, Wheelbase Traffic; Volume Average Axle Spacing (short/medium/long) Percent trucks within each axle spacing (short/medium/long) Normalized Vehicle Class Distribution (TTC Group) Growth Rate & Function Monthly Adjustment Factors Number of Axles per Truck Type Traffic; Axle Loads Climate Hourly Distribution Factors Single Axles Tandem Axles Tridem Axles Quad Axles Longitude Location: Latitude Elevation, ft. Depth to Water Table, ft. Climate Station Multi-Layer Rutting Parameters Shortwave Absorptivity Endurance Limit Applied AC (HMA) Layer Properties: New and Existing Layers Bedrock Layer Interface (Interface Friction) Milled Thickness Fatigue Cracking; input level 2 Rehabilitation Pavement Rating; (Condition of input level 3 existing flexible pavement) Rut Depth in existing layers; input levels 1 & 2 Total Rut Depth, input level 3 Elastic Modulus, psi Poisson's Ratio Unit Weight, pcf 148 (18)* (10)* (12)** Section 5.4; not used for flexible design. Section 5.4; use global default values Section 5.4; not used for flexible design. 12/15/18* Section 5.5; not used 17/22/61* for flexible design, Section 5.6, Table 5.2 (GDOT Defaults)* (GDOT Defaults)* (Defaults) Section 5.6 Section 5.7: Tables 5.3 or 5.4 Section 5.9, Table 5.6 Section 5.8; not used. Section 5.10; Table 5.7 Section 6.1 False (0.85)* False (1)* Section 6.2; Table 6.1 Section 6.3, 6.5 Table 6.2-6.3 Section 7.1.1; not used Section 7.1.2; use global default value Section 7.1.3; not used Section 7.1.4; use global default value for all layers Section 7.1.6 Section 7.1.5, Figure 7.1 Section 7.1.5, Table 7.2 Section 7.1.5, use global default values; Table 7.1 Section 7.1.5, use global default values Section 8.9, Table 8.26, (140)* Section 8.9, Table 8.26; used only when subgrade thickness is less than 100 inches. Thickness, inches (if applicable) Poisson's Ratio Resilient Modulus Coefficient of Lateral Pressure Subgrade (embankment and natural soil layers) Stabilized Subgrade Layer; Soil Cement and Lime Stabilized Soil (Assumed to be a coarsegrained soil; A-1-b) Is Layer Compacted? Specific Gravity Saturated Hydraulic Conductivity Soil-Water Characteristic Curve Water Content Dry Unit Weight Gradation Plasticity Index Liquid Limit Thickness, inches Poisson's Ratio Coefficient of Lateral Earth Pressure Resilient Modulus AASHTO Soil Classification Specific Gravity Saturated Hydraulic Conductivity Soil-Water Characteristic Curve Water Content; Optimum Dry Unit Weight; Modified Proctor Gradation Plasticity Index Liquid Limit Thickness, inches Poisson's Ratio Coefficient of Lateral Earth Pressure Classification Unbound Granular Aggregate Base (GAB) Layer Resilient Modulus Is Layer Compacted? Specific Gravity Saturated Hydraulic Conductivity Soil-Water Characteristic Curve Water Content; Optimum Dry Unit Weight; Modified Proctor Gradation Plasticity Index Liquid Limit (0.50)* (2.7)* (5.051e-02) Calculated Section 8.6 Section 8.6.3, Table 8.23 Section 8.6.2, Table 8.20 Not used. Always check this box for the upper subgrade layer, if used. Section 8.6.1 Section 8.6.4 Section 8.6.1, Table 8.18, and Figure 8.3 (0.50)* (A-1-b)* (2.7)* (1.803e-03)* Calculated (9.3)* (124.0)* Section 8.8 Section 8.8, Table 8.25 Not used. Section 8.8, Use annual representative modulus value; Table 8.25 Section 8.8 Section 8.8, use default values for an A-1-b soil (1)* (6)* (0.50)* (Crushed Stone)* Yes (2.7)* (5.054e-02)* Calculated Section 8.6 Section 8.6.3, Table 8.23 Not used. Section 8.6.2, Table 8.19; software calculates monthly resilient modulus Always check this box when the layer is compacted. Section 8.6.1; Use global default values for a Crushed Stone Section 8.6.1, Table 8.19 (1)* Section 8.6.1 (6)* 149 Asphalt Stabilized or Treated Base Cement Stabilized or Treated Base Layer AC/HMA (Existing) Layer(s) The inputs for an asphalt stabilized or treated base layer are the same as for an AC/HMA layer Thickness, inches Unit Weight, pcf Poisson's Ratio Minimum Elastic Modulus, psi 28-day Compressive Strength, psi 28-day Elastic/Resilient Modulus, psi Thermal Conductivity Heat Capacity Same inputs as for new AC/HMA layers, except for modulus or condition of existing layer. Number of existing HMA/AC layers Thickness after milling Existing HMA Backcalculated Modulus Thickness, inches Unit Weight, pcf Effective Asphalt Content by Volume, % Air Voids, % Poisson's Ratio New AC/HMA Layers Base Layer; if present Dynamic Modulus Gradation Estar Predictive Model; G*-based model Reference Temp., F Asphalt Binder Grade Tensile Strength, psi Creep Compliance Thermal Conductivity Heat Capacity Thermal Contraction See AC/HMA layer inputs. (150)* (0.20)* (100,000)* Section 8.1 & 8.7 Section 8.7 Section 8.7, Table 8.24 (1.25)* (0.28)* Section 8.1 & 8.7 Section 8.1 and 8.3 No more than 2 layers. Section 7.1.6 and 8.1 Section 8.3 (input level 1) Section 8.1, Table 8.1 Section 8.3.1, Table 8.3 Section 8.3.1, Table 8.3 True (Calculated)* False (Calculated)* (70)* (Calculated)* (Calculated)* (0.67)* (0.23)* (Calculated)* Section 8.3.1, Table 8.3 Section 8.3.1, use global default values Section 8.3.3. Section 8.3.2, Table 8.6 Section 8.3.2, use global default equation Section 8.3.2, use global default value Section 8.3.2, Table 8.5 Section 8.3.3, use global default value Section 8.3.2, use global default value Section 8.3.4, use global default value 150 New AC/HMA Layers Binder Layer; if present Thickness, inches Unit Weight, pcf Effective Asphalt Content by Volume, % Air Voids, % Poisson's Ratio Dynamic Modulus Gradation Estar Predictive Model; G*-based model Reference Temp., F Asphalt Binder Grade Tensile Strength, psi New AC/HMA Layers Wearing Surface or Surface Layer Creep Compliance Thermal Conductivity Heat Capacity Thermal Contraction Thickness, inches Unit Weight, pcf Effective Asphalt Content by Volume, % Air Voids, % Poisson's Ratio Dynamic Modulus Gradation Estar Predictive Model; G*-based model Reference Temp., F Asphalt Binder Grade Tensile Strength, psi Georgia Calibration Factors Creep Compliance Thermal Conductivity Heat Capacity Thermal Contraction Bottom-Up Fatigue Cracking Permanent Deformation (AC Rut Depth) Permanent Deformation (Rut Depth); Coarse-Grained Soil Permanent Deformation (Rut Depth); Fine-Grained Soil HMA IRI Regression Equation Reflection Cracking Section 8.1, Table 8.1 Section 8.3.1, Table 8.3 Section 8.3.1, Table 8.3 True (Calculated)* Section 8.3.1, Table 8.3 Section 8.3.1, use global default values Section 8.3.3. False (Calculated)* (70)* (Calculated)* (Calculated)* (0.67)* (0.23)* (Calculated)* Section 8.3.2, Table 8.6 Section 8.3.2, use global default equation Section 8.3.2, use global default value Section 8.3.2, Table 8.5 Section 8.3.3, use global default value Section 8.3.2, use global default value Section 8.3.4, use global default value True (Calculated)* False (Calculated)* (70)* (Calculated)* (Calculated)* (0.67)* (0.23)* (Calculated)* Section 8.1, Table 8.1 Section 8.3.1, Table 8.3 Section 8.3.1, Table 8.3 Section 8.3.1, Table 8.3 Section 8.3.1, use global default values Section 8.3.3. Section 8.3.2, Table 8.6 Section 8.3.2, use global default equation Section 8.3.2, use global default value Section 8.3.2, Table 8.5 Section 8.3.3, use global default value Section 8.3.2, use global default value Section 8.3.4, use global default value Section 9; Table 9.5 Section 9; Table 9.3 Section 9; Table 9.4 Section 9, use global calibration factors. Section 9, use global calibration factors. 151 CHECK LIST OF INPUTS FOR NEW AND REHABILITATED RIGID PAVEMENT DESIGNS: JPCP Input Parameter Design Type General Information Pavement Type Performance Criteria Traffic, Site Features General Traffic, Axle Configuration Traffic; Lateral Wander Design Life, years Base/Subgrade Construction Date Pavement Construction Date Traffic Opening Date Initial IRI, in./mi. Terminal IRI, in./mi. JPCP Transverse (Mid-Slab) Cracking, % JPCP Joint Faulting, inches Reliability Level, percent Two-Way Average Annual Daily Truck Traffic Number of Lanes in Design Direction Percent Trucks in Design Direction (DDF) Percent of Trucks in Design Lane (LDF) Operational Speed Traffic Capacity Cap Avg. Axle Width Dual Tire Spacing Dual Tire Pressure Tandem Axle Spacing Tridem Axle Spacing Quad Axle Spacing Mean Wheel Location Wander, Standard Deviation Design Lane Width Average Axle Spacing Traffic, (short/medium/long) Wheelbase Percent Trucks within each axle spacing (short/medium/long) * - Default values should be used. GDOT Input Value New Pavement, Overlay, or Restoration AC over JPCP; JPCP over JPCP or CRCP (bonded & unbonded) (20)* Comment Section 3.1.2 Section 3.3 Section 3.4; Table 3.2 Section 4.1, Table 4.1 Section 4.2, Table 4.6 Section 4.2, Table 4.3 Section 4.3, Table 4.7 Section 5.1 (50)* Section 5.1, Table 5.1 (Not Enforced)* (8.5)* (12)* (120)* (51.6)* (49.2)* (49.2)* (18)* (10)* (12)* Section 5.1 Section 5.2; not used Section 5.3; use global default values. Section 5.4; use global default values. (12/15/18)* Section 5.5; use (17/22/61)* global default values. 152 Traffic; Volume Normalized Vehicle Class Distribution (TTC Group) Growth Rate & Function Monthly Adjustment Factors Hourly Distribution Factors Traffic; Axle Loads Climate Number of Axles per Truck Type Single Axles Tandem Axles Tridem Axles Quad Axles Longitude Location: Latitude Elevation, ft. Depth to Water Table, ft. Climate Station Shortwave Absorptivity JPCP Design Properties Foundation Support JPCP (Existing) Rehabilitation PCC Joint Spacing, ft. Sealant Type Dowelled Joints Widened Slabs Tied Shoulders Erodibility Index PCC Base Contact Friction Permanent Curl/Warp Effective Temperature Difference Modulus of Subgrade Reaction or Resilient Modulus Same inputs as for new JPCP except for modulus or condition of existing layer. Slabs cracked or replaced before restoration Slabs repaired or replaced after restoration Resilient Modulus, psi Bedrock Poisson's Ratio Unit Weight, pcf Section 5.6, Table 5.2 (Use GDOT Defaults)* (Use GDOT Defaults)* (Use GDOT Defaults)* Section 5.6 Section 5.7; Tables 5.3 or 5.4 Section 5.8, Table 5.5 Section 5.9, Table 5.6 Section 5.10; Table 5.7 Section 6.1 (0.85)* Section 6.2; Table 6.1 Section 6.3, 6.5 Table 6.2-6.3 Section 7.2.1; use global default value Section 7.2.2 Section 7.2.3 Section 7.2.4 Section 7.2.5 Section 7.2.6 Section 7.2.7, Table 7.4 Section 7.2.8 (-10F)* Section 7.2.9 (Calculated)* Section 7.2.10 See PCC Layer Section 7.2.11 Section 7.2.11 (140)* Section 8.9, Table 8.26, default values are bedrock condition dependent; used only when subgrade thickness is less than 100 inches. Section 8.9, Table 8.26; used only when subgrade thickness is less than 100 inches. 153 Thickness, inches (if applicable) Poisson's Ratio Resilient Modulus Coefficient of Lateral Pressure Subgrade (embankment and natural soil layers) Stabilized Subgrade Layer; Soil Cement and Lime Stabilized Soil (Assumed to be a coarsegrained soil; A-1-b) Unbound Granular Aggregate Base (GAB) Layer Is Layer Compacted? Specific Gravity Saturated Hydraulic Conductivity Soil-Water Characteristic Curve Water Content Dry Unit Weight Gradation Plasticity Index Liquid Limit Thickness, inches Poisson's Ratio Coefficient of Lateral Earth Pressure Resilient Modulus AASHTO Soil Classification Specific Gravity Saturated Hydraulic Conductivity Soil-Water Characteristic Curve Water Content; Optimum Dry Unit Weight; Modified Proctor Gradation Plasticity Index Liquid Limit Thickness, inches Poisson's Ratio Coefficient of Lateral Earth Pressure Classification Resilient Modulus Is Layer Compacted? Specific Gravity Saturated Hydraulic Conductivity Soil-Water Characteristic Curve Water Content; Optimum Dry Unit Weight; Modified Proctor Gradation Plasticity Index Liquid Limit (0.50)* (2.7)* (5.051e-02) Calculated Section 8.6 Section 8.6.3, Table 8.23 Section 8.6.2, Table 8.20 Not used. Always check this box for the upper subgrade layer, if used. Section 8.6.1 Section 8.6.4 Section 8.6.1, Table 8.18, and Figure 8.3 Section 8.6.1 (0.50)* (A-1-b)* (2.7)* (1.803e-03)* Calculated (9.3)* (124.0)* Section 8.8 Section 8.8, Table 8.25 Not used. Section 8.8, Use annual representative modulus value; Table 8.25 Section 8.8 Section 8.8, use default values for an A-1-b soil (1)* (6)* (0.50)** (Crushed Stone)* (Yes)* (2.7)* (5.054e-02)* Calculated Section 8.6 Section 8.6.3, Table 8.23 Not used. Section 8.6.2, Table 8.19; software calculates monthly resilient modulus Always check this box when the layer is compacted. Section 8.6.1; Use global default values for a Crushed Stone Section 8.6.1, Table 8.19 (1)* Section 8.6.1 (6)* 154 Cement Stabilized or Treated Base Layer AC/HMA Layer or Interlayer Thickness, inches Unit Weight, pcf Poisson's Ratio Minimum Elastic Modulus, psi 28-Day Compressive Strength, psi 28-Day Elastic/Resilient Modulus, psi Thermal Conductivity Heat Capacity Thickness, inches Unit Weight, pcf Effective Asphalt Content by Volume, % Air Voids, % Poisson's Ratio Dynamic Modulus Gradation Estar Predictive Model; G*-based model Reference Temp., F Asphalt Binder Grade Tensile Strength, psi Creep Compliance Thermal Conductivity Heat Capacity Thermal Contraction (150)* (0.20)* (100,000) Section 8.1 & 8.7 Section 8.7 Section 8.7, Table 8.24 (1.25)* (0.28)* True (Calculated)* False (Calculated)* (70)* (Calculated)* (Calculated)* (0.67)* (0.23)* (Calculated)* Section 8.1 & 8.7 Section 8.1, Table 8.1 Section 8.3.1, Table 8.3 Section 8.3.1, Table 8.3 Section 8.3.1, Table 8.3 Section 8.3.1, use global default values Section 8.3.3. Section 8.3.2, Table 8.6 Section 8.3.2, use global default equation Section 8.3.2, use global default value Section 8.3.2, Table 8.5 Section 8.3.3, use global default value Section 8.3.2, use global default value Section 8.3.4, use global default value 155 PCC Layer Georgia Calibration Factors Thickness, inches Unit Weight, pcf Poisson's Ratio Coefficient of Thermal Expansion Thermal Conductivity Heat Capacity Cement Type Cementitious Material Content Water to cement ratio Aggregate Type PCC Zero-stress temperature Ultimate shrinkage Reversible shrinkage Time to develop 50% ultimate shrinkage, days Curing Method Flexural PCC Strength, psi Compressive Elastic Modulus, ksi Mid-Slab Cracking, % Joint Faulting, inches IRI, in./mi. (150)* (0.2)* (0.67)* (0.23)* (Type I)* (660)* (0.45)* (Calculated)* (Calculated)* (50)* (35)* Section 8.2, Table 8.1 Section 8.4.1, Table 8.8 Section 8.4.1, Table 8.9 Section 8.4.2, Tables 8.10 - 8.11 Section 8.4.2 Section 8.4.3, Table 8.7 Section 8.4.3, Tables 8.11 - 8.12 Section 8.4.3, Use global default value (705)* (6097)* (4,500)* Section 8.4.3 Section 8.4.4, Tables 8.13 8.15 Section 9; Table 9.7 Section 9; Table 9.8 Section 9; use global calibration factors. 156 CHECK LIST OF INPUTS FOR NEW AND REHABILITATED RIGID PAVEMENT DESIGNS: CRCP Input Parameter Design Type General Information Pavement Type Design Life, years Base/Subgrade Construction Date Pavement Construction Date Traffic Opening Date Initial IRI, in./mi. Performance Terminal IRI, in./mi. Criteria CRCP Punchouts per mile Reliability Level, percent Two-Way Average Annual Daily Truck Traffic Number of Lanes in Design Direction Traffic, Site Features Percent Trucks in Design Direction (DDF) Percent of Trucks in Design Lane (LDF) Operational Speed Traffic Capacity Cap Avg. Axle Width General Traffic, Axle Configuration Dual Tire Spacing Dual Tire Pressure Tandem Axle Spacing Tridem Axle Spacing Quad Axle Spacing Traffic; Mean Wheel Location Lateral Wander, Standard Deviation Wander Design Lane Width Average Axle Spacing Traffic, (short/medium/long) Wheelbase Percent Trucks within each axle spacing (short/medium/long) * - Default values should be used. GDOT Input Value New Pavement, Overlay, or Restoration AC over CRCP; CRCP over JPCP or CRCP (bonded & unbonded) (20)* (50)* (Not Enforced)* (8.5)* (12)* (120)* (51.6)* (49.2)* (49.2)* (18)* (10)* (12)* (12/15/18)* (17/22/61)* Comment Section 3.1.2 Section 3.3 Section 3.4; Table 3.2 Section 4.1, Table 4.1 Section 4.2, Table 4.6 Section 4.2, Table 4.4 Section 4.3, Table 4.7 Section 5.1 Section 5.1, Table 5.1 Section 5.1 Section 5.2; not used Section 5.3; use global default values Section 5.4 Section 5.4; use global default values Section 5.4 Section 5.5 157 Traffic; Volume Normalized Vehicle Class Distribution (TTC Group) Growth Rate & Function Monthly Adjustment Factors Hourly Distribution Factors Number of Axles per Truck Type Traffic; Axle Loads Climate Single Axles Tandem Axles Tridem Axles Quad Axles Longitude Location: Latitude Elevation, ft. Depth to Water Table, ft. Climate Station Foundation Support Modulus of Subgrade Reaction or Resilient Modulus Shortwave Absorptivity CRCP Design Properties Shoulder Type Permanent Curl/Warp Effective Temperature Difference Steel, percent reinforcement Bar Diameter, in. Steel Depth, in. Base/Slab Friction Coefficient Generate Crack Spacing CPCP (Existing) Rehabilitation Same inputs as for new CRCP except for modulus or condition of existing layer. Number of Punchouts per mile Resilient Modulus, psi Bedrock Poisson's Ratio Unit Weight, pcf Section 5.6, Table 5.2 (Use GDOT Defaults)* (Use GDOT Defaults)* (Use GDOT Defaults)* Section 5.6 Section 5.7; Tables 5.3 or 5.4 Section 5.8, Table 5.6 Section 5.9, Table 5.5 Section 5.10; Table 5.7 Section 6.1 Section 6.2; Table 6.1 Section 6.3, 6.5 Table 6.2-6.3 (Calculated)* Section 7.2.10 (0.85)* Section 7.2.1; use global default value Section 7.3 (-10F)* Section 7.2.9 Section 7.3 Section 7.3, Table 7.5 (True)* Software calculates crack spacing. See PCC Layer for CRCP (140)* Section 7.3 Section 8.9, Table 8.26, default values are bedrock condition dependent; used only when subgrade thickness is less than 100 inches. Section 8.9, Table 8.26; used only when subgrade thickness is less than 100 inches. 158 Thickness, inches (if applicable) Poisson's Ratio Resilient Modulus Coefficient of Lateral Pressure Subgrade (embankment and natural soil layers) Is Layer Compacted? Specific Gravity Saturated Hydraulic Conductivity Soil-Water Characteristic Curve Water Content Dry Unit Weight Gradation Plasticity Index Liquid Limit Thickness, inches Poisson's Ratio Coefficient of Lateral Earth Pressure Stabilized Subgrade Layer; Soil Cement and Lime Stabilized Soil Unbound Granular Aggregate Base (GAB) Layer Resilient Modulus AASHTO Soil Classification Specific Gravity Saturated Hydraulic Conductivity Soil-Water Characteristic Curve Water Content; Optimum Dry Unit Weight; Modified Proctor Gradation Plasticity Index Liquid Limit Thickness, inches Poisson's Ratio Coefficient of Lateral Earth Pressure Classification Resilient Modulus Is Layer Compacted? Specific Gravity Saturated Hydraulic Conductivity Soil-Water Characteristic Curve Water Content; Optimum Dry Unit Weight; Modified Proctor Gradation Plasticity Index Liquid Limit (0.50)* (2.7)* (5.051e-02) Calculated Section 8.6 Section 8.6.3, Table 8.23 Section 8.6.2, Table 8.20 Not used. Always check this box for the upper subgrade layer, if used. Section 8.6.1 Section 8.6.4 Section 8.6.1, Table 8.18, and Figure 8.3 Section 8.6.1 (0.50)* (A-1-b)* (2.7)* (1.803e-03)* Calculated (9.3)* (124.0)* Section 8.8 Section 8.8, Table 8.25 Not used. Section 8.8, Use annual representative modulus value; Table 8.25 Section 8.8 Section 8.8, use default values for an A-1-b soil (1)* (6)* (0.50)** (Crushed Stone)* (Yes)* (2.7)* (5.054e-02)* Calculated (7.4)* (127.2)* Section 8.6 Section 8.6.3, Table 8.23 Not used. Section 8.6.2, Table 8.19; software calculates monthly resilient modulus Always check this box when the layer is compacted. Section 8.6.1; Use global default values for a Crushed Stone Section 8.6.1, Table 8.19 (1)* Section 8.6.1 (6)* 159 Cement Stabilized or Treated Base Layer AC/HMA Layer or Interlayer Thickness, inches Unit Weight, pcf Poisson's Ratio Minimum Elastic Modulus, psi 28-Day Compressive Strength, psi 28-Day Elastic/Resilient Modulus, psi Thermal Conductivity Heat Capacity Thickness, inches Unit Weight, pcf Effective Asphalt Content by Volume, % Air Voids, % Poisson's Ratio Dynamic Modulus Gradation Estar Predictive Model; G*-based model Reference Temp., F Asphalt Binder Grade Tensile Strength, psi Creep Compliance Thermal Conductivity Heat Capacity Thermal Contraction (150)* (0.20)* (100,000) Section 8.1 & 8.7 Section 8.7 Section 8.7, Table 8.24 (1.25)* (0.28)* Section 8.1 & 8.7 Section 8.1, Table 8.1 Section 8.3.1, Table 8.3 Section 8.3.1, Table 8.3 True (Calculated)* False (Calculated)* (70)* (Calculated)* (Calculated)* (0.67)* (0.23)* (Calculated)* Section 8.3.1, Table 8.3 Section 8.3.1, use global default values Section 8.3.3. Section 8.3.2, Table 8.6 Section 8.3.2, use global default equation Section 8.3.2, use global default value Section 8.3.2, Table 8.5 Section 8.3.3, use global default value Section 8.3.2, use global default value Section 8.3.4, use global default value 160 Thickness, inches Unit Weight, pcf Poisson's Ratio Coefficient of Thermal Expansion Thermal Conductivity Heat Capacity Cement Type Cementitious Material Content Water to cement ratio PCC Layer Aggregate Type Georgia CRCP Calibration Factors PCC Zero-stress temperature Ultimate shrinkage Reversible shrinkage Time to develop 50% ultimate shrinkage, days Curing Method Flexural PCC Strength, psi Compressive Elastic Modulus, ksi Number of Punchouts per mile IRI, in./mi. (150)* (0.2)* (0.67)* (0.23)* (Type I)* (660)* (0.45)* (Calculated)* (Calculated)* (50)* (35)* Section 8.2, Table 8.1 Section 8.4.1, Table 8.8 Section 8.4.1, Table 8.9 Section 8.4.2, Tables 8.10 - 8.11 Section 8.4.2 Section 8.4.3, Table 8.7 Section 8.4.3, Tables 8.11 - 8.12 Section 8.4.3, Use global default value (705)* (6097)* (4,500)* Section 8.4.3 Section 8.4.4, Tables 8.13 8.15 Section 9; Table 9.9 Section 9; Use global calibration factors. 161 APPENDIX A--HMA DATABASE (KIM ET AL., 2019) Mixture Type: A 12.5_64_M1 Asphalt Mix: Dynamic Modulus Table Temperature (F) Mixture |E*|, psi 0.1 Hz 0.5 Hz 39.2 740,802 1,082,794 68 150,334 278,518 104 24,296 46,335 130 11,119 19,491 1 Hz 1,202,705 336,268 58,625 24,290 Table A.1 Level 1 5 Hz 1,586,888 564,559 113,719 46,322 10 Hz 1,706,096 658,669 142,644 58,611 XML File: 25 Hz 1,924,615 818,440 198,566 83,996 L*_PG64_12.5_A_R3-LG Asphalt Binder: Superpave Binder Test Data Temperature (F) Angular Freq. = 10 rad/sec G* (Pa) Delta (degree) 147.2 8850 79.1 158 4220 82 168.8 2070 84.1 Asphalt Mix: Aggregate Gradation Cumulative % Retained 3/4 Inch Sieve 0 3/8 Inch Sieve 14 #4 Sieve 26 #200 Sieve 94.2 Percent Passing 100 86 74 5.8 Level 2 Asphalt General: Volumetric Properties as Built Effective Binder Content (%) 12.5 Air Voids (%) 5.5 Total Unit Weight (pcf) 145 Asphalt Binder: Superpave Binder Test Data Temperature (F) Angular Freq. = 10 rad/sec G* (Pa) Delta (degree) 147.2 8850 79.1 158 4220 82 168.8 2070 84.1 Asphalt Mix: Aggregate Gradation Level 3 3/4 Inch Sieve 3/8 Inch Sieve #4 Sieve #200 Sieve Cumulative % Retained 0 14 26 94.2 Percent Passing 100 86 74 5.8 Asphalt General: Volumetric Properties as Built Effective Binder Content (%) 12.5 Air Voids (%) 5.5 Total Unit Weight (pcf) 145 Asphalt General: Volumetric Properties as Built Effective Binder Content (%) 12.5 Air Voids (%) 5.5 Total Unit Weight (pcf) 145 Asphalt Binder: Superpave Binder Grading: PG 64-22 Note: The table summarizes the test data using extracted asphalt binder from asphalt plant mix. 162 Mixture Type: A.12.5_64_M2 Asphalt Mix: Dynamic Modulus Table Mixture |E*|, psi Temperature (F) 0.1 Hz 0.5 Hz 1 Hz Table A.2 Level 1 XML File: 5 Hz 10 Hz 25 Hz 39.2 913,266 1,203,332 1,342,315 1,646,168 1,775,603 1,961,809 68 196,746 348,622 411,796 649,274 741,030 894,448 104 33,991 70,120 89,932 173,205 212,727 301,364 130 19,970 39,240 55,296 102,271 139,928 188,459 L*_PG64_12.5_A_R3-FP Asphalt Binder: Superpave Binder Test Data Angular Freq. = 10 rad/sec Temperature (F) G* (Pa) Delta (degree) 147.2 158 168.8 27500 73.7 10800 76.8 6600 79.2 Asphalt Mix: Aggregate Gradation Cumulative % Retained 3/4 Inch Sieve 0 3/8 Inch Sieve 12 #4 Sieve 27 #200 Sieve 94.1 Percent Passing 100 88 73 5.9 Asphalt General: Volumetric Properties as Built Effective Binder Content (%) 12.2 Air Voids (%) 5.5 Total Unit Weight (pcf) 145 Level 2 Asphalt Binder: Superpave Binder Test Data Angular Freq. = 10 rad/sec Temperature (F) G* (Pa) Delta (degree) 147.2 158 168.8 27500 73.7 10800 76.8 6600 79.2 Asphalt General: Volumetric Properties as Built Effective Binder Content (%) 12.2 Air Voids (%) 5.5 Total Unit Weight (pcf) 145 Level 3 Asphalt Mix: Aggregate Gradation 3/4 Inch Sieve Cumulative % Retained 0 3/8 Inch Sieve 12 #4 Sieve 27 #200 Sieve 5.9 Percent Passing 100 88 61 55.1 Asphalt General: Volumetric Properties as Built Effective Binder Content (%) 12.2 Air Voids (%) 5.5 Total Unit Weight (pcf) 145 Asphalt Binder: Superpave Binder Grading: PG 64-22 Note: The table summarizes the test data using extracted asphalt binder from asphalt plant mix. 163 Mixture Type: A 12.5_67_N Asphalt Mix: Dynamic Modulus Table Temperature (F) 39.2 68 104 130 Mixture |E*|, psi 0.1 Hz 787,225 192,088 38,301 18,543 0.5 Hz 1,089,505 325,597 66,256 29,902 1 Hz 1,207,067 382,568 82,046 37,036 Table A.3 Level 1 5 Hz 1,545,325 599,750 142,791 63,196 10 Hz 1,661,798 686,073 175,827 79,242 XML File: 25 Hz 1,870,709 833,912 228,559 104,091 L*_PG67_12.5_A_R2 Asphalt Binder: Superpave Binder Test Data Angular Freq. = 10 rad/sec Temperature (F) G* (Pa) Delta (degree) 147.2 147.2 26600 158 168.8 158 168.8 12400 5780 Asphalt Mix: Aggregate Gradation Cumulative % Retained 3/4 Inch Sieve 0 3/8 Inch Sieve 13 #4 Sieve 25 #200 Sieve 93.7 Percent Passing 100 87 75 6.3 Asphalt General: Volumetric Properties as Built Effective Binder Content (%) 11.8 Air Voids (%) 6.3 Total Unit Weight (pcf) 145 Level 2 Asphalt Binder: Superpave Binder Test Data Angular Freq. = 10 rad/sec Temperature (F) G* (Pa) Delta (degree) 147 26600 72.1 158 12400 75.3 169 5780 78.5 Asphalt General: Volumetric Properties as Built Effective Binder Content (%) 11.8 Air Voids (%) 6.3 Total Unit Weight (pcf) 145 Level 3 Asphalt Mix: Aggregate Gradation Asphalt General: Volumetric Properties as Built 3/4 Inch Sieve 3/8 Inch Sieve #4 Sieve #200 Sieve Cumulative % Retained 0 13 25 6.3 Percent Passing 100 87 62 55.7 Effective Binder Content (%) 11.8 Air Voids (%) 6.3 Total Unit Weight (pcf) 145 Asphalt Binder: Superpave Binder Grading: PG 67-22 Note: The table summarizes the test data using extracted asphalt binder from asphalt plant mix. 164 Mixture Type: A 12.5_76_N Asphalt Mix: Dynamic Modulus Table Temperature (F) 39.2 68 104 130 Mixture |E*|, psi 0.1 Hz 829,119 177,587 35,227 18,567 0.5 Hz 1,118,111 304,657 59,261 29,167 Table A.4 Level 1 1 Hz 1,264,046 359,764 73,824 35,573 5 Hz 1,585,167 573,195 127,260 60,107 10 Hz 1,726,851 658,991 158,583 74,603 XML File: 25 Hz 1,930,605 807,522 205,713 98,547 L*_PG76_12.5_A_R2 Asphalt Binder: Superpave Binder Test Data Angular Freq. = 10 rad/sec Temperature (F) G* (Pa) Delta (degree) 158 168.8 179.6 14100 65.8 6770 67.2 8140 67.8 Asphalt Mix: Aggregate Gradation Cumulative % Retained 3/4 Inch Sieve 0 3/8 Inch Sieve 10 #4 Sieve 27 #200 Sieve 93.7 Level 2 Percent Passing 100 90 73 6.3 Asphalt General: Volumetric Properties as Built Effective Binder Content (%) 12.6 Air Voids (%) 5.7 Total Unit Weight (pcf) 145 Asphalt Binder: Superpave Binder Test Data Angular Freq. = 10 rad/sec Temperature (F) G* (Pa) Delta (degree) 158 168.8 179.6 14100 65.8 6770 67.2 8140 67.8 Asphalt Mix: Aggregate Gradation Level 3 3/4 Inch Sieve 3/8 Inch Sieve #4 Sieve #200 Sieve Cumulative % Retained Percent Passing 0 100 10 90 27 63 6.3 56.7 Asphalt General: Volumetric Properties as Built Effective Binder Content (%) 12.6 Air Voids (%) 5.7 Total Unit Weight (pcf) 145 Asphalt General: Volumetric Properties as Built Effective Binder 12.6 Content (%) Air Voids (%) 5.7 Total Unit Weight (pcf) 145 Asphalt Binder: Superpave Binder Grading: PG 76-22 Notes: The table summarizes the test data using extracted asphalt binder from asphalt plant mix. 165 Mixture Type: A 19_64_N Asphalt Mix: Dynamic Modulus Table Temperature (F) 39.2 68 104 130 Mixture |E*|, psi 0.1 Hz 1,080,201 259,963 49,660 24,494 0.5 Hz 1,378,093 430,811 86,728 41,822 Table A.5 Level 1 1 Hz 1,534,188 501,396 108,870 51,610 5 Hz 1,835,810 759,378 187,266 91,408 10 Hz 1,977,396 859,191 232,492 113,125 XML File: 25 Hz 2,154,776 1,021,609 296,430 150,931 L*_PG64_19_A_R2 Asphalt Binder: Superpave Binder Test Data Angular Freq. = 10 rad/sec Temperature (F) G* (Pa) Delta (degree) 147.2 158 168.8 49700 60.4 31300 62.2 16500 63.7 Asphalt Mix: Aggregate Gradation Cumulative % Retained 3/4 Inch Sieve 5 3/8 Inch Sieve 11 #4 Sieve 27 #200 Sieve 94.2 Level 2 Percent Passing 95 89 73 5.8 Asphalt General: Volumetric Properties as Built Effective Binder Content (%) 11.6 Air Voids (%) 5.5 Total Unit Weight (pcf) 145 Asphalt Binder: Superpave Binder Test Data Angular Freq. = 10 rad/sec Temperature (F) G* (Pa) Delta (degree) 147.2 49700 60.4 158 31300 62.2 168.8 16500 63.7 Asphalt Mix: Aggregate Gradation Level 3 3/4 Inch Sieve 3/8 Inch Sieve #4 Sieve #200 Sieve Cumulative % Retained 5 11 27 5.8 Percent Passing 95 84 57 51.2 Asphalt General: Volumetric Properties as Built Effective Binder Content (%) 11.6 Air Voids (%) 5.5 Total Unit Weight (pcf) 145 Asphalt General: Volumetric Properties as Built Effective Binder Content (%) 11.6 Air Voids (%) 5.5 Total Unit Weight (pcf) 145 Asphalt Binder: Superpave Binder Grading: PG 64-22 Notes: The table summarizes the test data using extracted asphalt binder from asphalt plant mix. 166 Mixture Type: A 19_64_N2 Asphalt Mix: Dynamic Modulus Table Temperature (F) 39.2 68 104 130 Mixture |E*|, psi 0.1 Hz 1,604,374 419,108 88,175 54,060 0.5 Hz 1,905,957 668,293 155,884 91,967 Table A.6 Level 1 1 Hz 2,067,163 765,958 191,065 115,782 5 Hz 2,321,134 1,100,487 327,445 198,940 10 Hz 2,449,785 1,223,621 394,311 247,199 XML File: 25 Hz 2,560,126 1,409,156 500,186 343,452 L*_PG64_19_A_R1 Asphalt Binder: Superpave Binder Test Data Angular Freq. = 10 rad/sec Temperature (F) G* (Pa) Delta (degree) 147.2 158 168.8 Asphalt Mix: Aggregate Gradation Cumulative % Retained 3/4 Inch Sieve 1 3/8 Inch Sieve 9 #4 Sieve 19 #200 Sieve 94.7 Level 2 Percent Passing 99 91 81 5.3 Asphalt General: Volumetric Properties as Built Effective Binder Content (%) 10.1 Air Voids (%) 5.0 Total Unit Weight (pcf) 145 Asphalt Binder: Superpave Binder Test Data Angular Freq. = 10 rad/sec Temperature (F) G* (Pa) Delta (degree) 147.2 158 168.8 49700 60.4 31300 62.2 16500 63.7 Asphalt Mix: Aggregate Gradation Level 3 3/4 Inch Sieve 3/8 Inch Sieve #4 Sieve #200 Sieve Cumulative % Retained 1 9 19 5.3 Percent Passing 95 84 57 51.2 Asphalt General: Volumetric Properties as Built Effective Binder Content (%) 10.1 Air Voids (%) 5.0 Total Unit Weight (pcf) 145 Asphalt General: Volumetric Properties as Built Effective Binder Content (%) 11.6 Air Voids (%) 5.5 Total Unit Weight (pcf) 145 Asphalt Binder: Superpave Binder Grading: PG 64-22 Notes: The table summarizes the test data using extracted asphalt binder from asphalt plant mix. 167 Mixture Type: A 25_64_N Asphalt Mix: Dynamic Modulus Table Temperature (F) 39.2 68 104 130 Mixture |E*|, psi 0.1 Hz 1,491,958 518,414 112,825 112,825 0.5 Hz 1,756,555 718,035 181,733 181,733 Table A.7 Level 1 1 Hz 1,875,438 814,243 218,814 218,814 5 Hz 2,161,550 1,085,754 359,743 359,743 10 Hz 2,283,430 1,212,228 438,885 438,885 XML File: 25 Hz 2,438,814 1,390,576 573,577 573,577 Asphalt Binder: Superpave Binder Test Data Angular Freq. = 10 rad/sec Temperature (F) G* (Pa) Delta (degree) 147.2 158 168.8 37100 72.6 17500 75.6 7890 78.4 Asphalt Mix: Aggregate Gradation Cumulative % Retained 3/4 Inch Sieve 12 3/8 Inch Sieve 9 #4 Sieve 20 #200 Sieve 94.3 Level 2 Percent Passing 88 91 80 5.7 Asphalt General: Volumetric Properties as Built Effective Binder Content (%) 11.2 Air Voids (%) 5.5 Total Unit Weight (pcf) 145 Asphalt Binder: Superpave Binder Test Data Angular Freq. = 10 rad/sec Temperature (F) G* (Pa) Delta (degree) 147.2 158 168.8 37100 72.6 17500 75.6 7890 78.4 Asphalt Mix: Aggregate Gradation Level 3 3/4 Inch Sieve 3/8 Inch Sieve #4 Sieve #200 Sieve Cumulative % Retained 12 9 20 5.7 Percent Passing 88 79 59 53.3 Asphalt General: Volumetric Properties as Built Effective Binder Content (%) 11.2 Air Voids (%) 5.5 Total Unit Weight (pcf) 145 Asphalt General: Volumetric Properties as Built Effective Binder Content (%) 11.2 Air Voids (%) 5.5 Total Unit Weight (pcf) 145 Asphalt Binder: Superpave Binder Grading: PG 64-22 Notes: The table summarizes the test data using extracted asphalt binder from asphalt plant mix. 168 Mixture Type: A 25_64_N2 Asphalt Mix: Dynamic Modulus Table Temperature (F) 39.2 68 104 130 Mixture |E*|, psi 0.1 Hz 1,556,596 381,566 68,568 34,913 0.5 Hz 1,890,369 628,307 108,719 50,039 Table A.8 Level 1 1 Hz 2,066,300 729,361 140,700 62,015 5 Hz 2,351,759 1,081,872 229,344 97,443 10 Hz 2,486,870 1,216,166 297,634 125,624 XML File: 25 Hz 2,625,608 1,414,382 381,114 167,944 L*_PG64_25_A_R1 Asphalt Binder: Superpave Binder Test Data Angular Freq. = 10 rad/sec Temperature (F) G* (Pa) Delta (degree) Asphalt General: Volumetric Properties as Built Effective Binder Content (%) 9.8 Air Voids (%) 5.2 Total Unit Weight (pcf) 145 Asphalt Mix: Aggregate Gradation Cumulative % Retained 3/4 Inch Sieve 7 3/8 Inch Sieve 9 #4 Sieve 15 #200 Sieve 94.5 Level 2 Percent Passing 93 91 85 5.5 Asphalt Binder: Superpave Binder Test Data Angular Freq. = 10 rad/sec Temperature (F) G* (Pa) Delta (degree) 147.2 158 168.8 37100 72.6 17500 75.6 7890 78.4 Asphalt General: Volumetric Properties as Built Effective Binder Content (%) 9.8 Air Voids (%) 5.2 Total Unit Weight (pcf) 145 Level 3 Asphalt Mix: Aggregate Gradation 3/4 Inch Sieve 3/8 Inch Sieve #4 Sieve #200 Sieve Cumulative % Retained 9 7 15 5.5 Percent Passing 91 84 69 63.5 Asphalt General: Volumetric Properties as Built Effective Binder Content (%) 9.8 Air Voids (%) 5.2 Total Unit Weight (pcf) 145 Asphalt Binder: Superpave Binder Grading: PG 64-22 Notes: The table summarizes the test data using extracted asphalt binder from asphalt plant mix. 169 Mixture Type: B 9.5_64_M1 Asphalt Mix: Dynamic Modulus Table Temperature (F) 39.2 68 104 130 Mixture |E*|, psi 0.1 Hz 707,903 135,249 26,470 14,879 0.5 Hz 1,004,842 244,567 47,501 24,650 1 Hz 1,143,469 293,579 58,462 30,313 Table A.9 Level 1 5 Hz 1,491,896 492,606 108,497 54,053 10 Hz 1,631,093 573,874 133,205 67,772 XML File: 25 Hz 1,857,805 723,054 186,318 98,849 L*_PG64_9.5_B_R3-A Asphalt Binder: Superpave Binder Test Data Angular Freq. = 10 rad/sec Temperature (F) G* (Pa) Delta (degree) 147.2 24300 73.6 158 1170 76.6 168.8 6800 79.2 Asphalt Mix: Aggregate Gradation Cumulative % Retained 3/4 Inch Sieve 0 3/8 Inch Sieve 1 #4 Sieve 28 #200 Sieve 94 Percent Passing 100 99 72 6 Asphalt General: Volumetric Properties as Built Effective Binder Content (%) 12.6 Air Voids (%) 6.5 Total Unit Weight (pcf) 145 Level 2 Asphalt Binder: Superpave Binder Test Data Angular Freq. = 10 rad/sec Temperature (F) G* (Pa) Delta (degree) 147.2 158 168.8 24300 73.6 1170 76.6 6800 79.2 Asphalt General: Volumetric Properties as Built Effective Binder Content (%) 12.6 Air Voids (%) 6.5 Total Unit Weight (pcf) 145 Level 3 Asphalt Mix: Aggregate Gradation Asphalt General: Volumetric Properties as Built 3/4 Inch Sieve 3/8 Inch Sieve #4 Sieve #200 Sieve Cumulative % Retained Percent Passing 100 0 1 99 28 71 6 65 Effective Binder Content (%) 12.6 Air Voids (%) 6.5 Total Unit Weight (pcf) 145 Asphalt Binder: Superpave Binder Grading: PG 64-22 Notes: The table summarizes the test data using extracted asphalt binder from asphalt plant mix. 170 Mixture Type: B 9.5_64_M2 Asphalt Mix: Dynamic Modulus Table Temperature (F) 39.2 68 104 130 Mixture |E*|, psi 0.1 Hz 726,463 151,093 29,619 15,871 0.5 Hz 1,059,151 273,425 52,882 26,004 1 Hz 1,180,868 328,405 65,149 31,375 Table A.10 Level 1 5 Hz 1,560,876 548,293 121,003 56,328 10 Hz 1,682,118 638,450 148,834 69,451 XML File: 25 Hz 1,905,371 796,580 207,462 100,315 L*_PG64_9.5_B_R3-V Asphalt Binder: Superpave Binder Test Data Angular Freq. = 10 rad/sec Temperature (F) G* (Pa) Delta (degree) 147.2 158 168.8 5780 80.8 11500 78.4 19600 75.4 Asphalt Mix: Aggregate Gradation Cumulative % Retained 3/4 Inch Sieve 0 3/8 Inch Sieve 6 #4 Sieve 27 #200 Sieve 93.5 Percent Passing 100 94 73 6.5 Asphalt General: Volumetric Properties as Built Effective Binder Content (%) 11.6 Air Voids (%) 6.5 Total Unit Weight (pcf) 145 Level 2 Asphalt Binder: Superpave Binder Test Data Angular Freq. = 10 rad/sec Temperature (F) G* (Pa) Delta (degree) 147.2 158 168.8 5780 80.8 11500 78.4 19600 75.4 Asphalt General: Volumetric Properties as Built Effective Binder Content (%) 11.6 Air Voids (%) 6.5 Total Unit Weight (pcf) 145 Level 3 Asphalt Mix: Aggregate Gradation Asphalt General: Volumetric Properties as Built 3/4 Inch Sieve 3/8 Inch Sieve #4 Sieve #200 Sieve Cumulative % Retained Percent Passing 100 0 6 94 27 67 6.5 60.5 Effective Binder Content (%) 11.6 Air Voids (%) 6.5 Total Unit Weight (pcf) 145 Asphalt Binder: Superpave Binder Grading: PG 64-22 Notes: The table summarizes the test data using extracted asphalt binder from asphalt plant mix. 171 Mixture Type: B 9.5_67_S Asphalt Mix: Dynamic Modulus Table Temperature (F) 39.2 68 104 130 Mixture |E*|, psi 0.1 Hz 778,386 154,455 24,939 11,980 0.5 Hz 1,050,892 275,617 49,370 23,189 1 Hz 1,189,409 328,315 62,359 29,765 Table A.11 Level 1 5 Hz 1,493,084 530,523 119,532 58,146 10 Hz 1,629,393 612,484 148,018 73,784 XML File: 25 Hz 1,824,386 750,601 202,299 109,831 L*_PG67_9.5_B_R4 Asphalt Binder: Superpave Binder Test Data Angular Freq. = 10 rad/sec Temperature (F) G* (Pa) Delta (degree) 147.2 158 168.8 23600 72.2 10600 75.6 4910 78.6 Asphalt Mix: Aggregate Gradation Cumulative % Retained 3/4 Inch Sieve 0 3/8 Inch Sieve 3 #4 Sieve 28 #200 Sieve 94.7 Percent Passing 100 97 72 5.3 Asphalt General: Volumetric Properties as Built Effective Binder Content (%) 12.8 Air Voids (%) 5.5 Total Unit Weight (pcf) 145 Level 2 Asphalt Binder: Superpave Binder Test Data Angular Freq. = 10 rad/sec Temperature (F) G* (Pa) Delta (degree) 147.2 158 168.8 23600 72.2 10600 75.6 4910 78.6 Asphalt General: Volumetric Properties as Built Effective Binder Content (%) 12.8 Air Voids (%) 5.5 Total Unit Weight (pcf) 145 Level 3 Asphalt Mix: Aggregate Gradation Asphalt General: Volumetric Properties as Built 3/4 Inch Sieve 3/8 Inch Sieve #4 Sieve #200 Sieve Cumulative % Retained Percent Passing 100 0 3 97 28 69 5.3 63.7 Effective Binder Content (%) 12.8 Air Voids (%) 5.5 Total Unit Weight (pcf) 145 Asphalt Binder: Superpave Binder Grading: PG 67-22 Notes: The table summarizes the test data using extracted asphalt binder from asphalt plant mix. 172 Mixture Type: B 12.5_64_M Asphalt Mix: Dynamic Modulus Table Temperature (F) 39.2 68 104 130 Mixture |E*|, psi 0.1 Hz 713,383 139,056 24,366 12,516 0.5 Hz 1,077,654 263,348 43,769 19,494 1 Hz 1,200,054 321,364 54,864 23,735 Table A.12 Level 1 5 Hz 1,606,245 555,823 105,353 42,183 10 Hz 1,729,371 654,698 132,701 53,201 XML File: 25 Hz 1,937,672 822,028 187,020 74,579 L*_PG64_12.5_B_R3 Asphalt Binder: Superpave Binder Test Data Angular Freq. = 10 rad/sec Temperature (F) G* (Pa) Delta (degree) 147.2 158 168.8 14300 76.7 9440 79.6 5170 81.9 Asphalt Mix: Aggregate Gradation Cumulative % Retained 3/4 Inch Sieve 0 3/8 Inch Sieve 13 #4 Sieve 25 #200 Sieve 94 Percent Passing 100 87 75 6 Asphalt General: Volumetric Properties as Built Effective Binder Content (%) 12.5 Air Voids (%) 5.6 Total Unit Weight (pcf) 145 Level 2 Asphalt Binder: Superpave Binder Test Data Angular Freq. = 10 rad/sec Temperature (F) G* (Pa) Delta (degree) 147.2 158 168.8 14300 76.7 9440 79.6 5170 81.9 Asphalt General: Volumetric Properties as Built Effective Binder Content (%) 12.5 Air Voids (%) 5.6 Total Unit Weight (pcf) 145 Level 3 Asphalt Mix: Aggregate Gradation Asphalt General: Volumetric Properties as Built 3/4 Inch Sieve 3/8 Inch Sieve #4 Sieve #200 Sieve Cumulative % Retained 0 13 25 6 Percent Passing 100 97 69 63.7 Effective Binder Content (%) 12.5 Air Voids (%) 5.6 Total Unit Weight (pcf) 145 Asphalt Binder: Superpave Binder Grading: PG 64-22 Notes: The table summarizes the test data using extracted asphalt binder from asphalt plant mix. 173 Mixture Type: B 12.5_67_S Asphalt Mix: Dynamic Modulus Table Temperature (F) 39.2 68 104 130 Mixture |E*|, psi 0.1 Hz 799,436 178,701 40,797 26,760 0.5 Hz 1,098,798 307,743 72,786 43,528 1 Hz 1,226,957 364,226 89,099 57,073 Table A.13 Level 1 5 Hz 1,560,258 578,586 159,438 95,217 10 Hz 1,685,026 666,209 192,590 125,372 XML File: 25 Hz 1,894,083 811,324 267,258 167,782 L*_PG67_12.5_B_R4 Asphalt Binder: Superpave Binder Test Data Angular Freq. = 10 rad/sec Temperature (F) G* (Pa) Delta (degree) 147.2 158 168.8 26800 73.8 10800 77.3 5270 80.3 Asphalt Mix: Aggregate Gradation Cumulative % Retained 3/4 Inch Sieve 0 3/8 Inch Sieve 14 #4 Sieve 25 #200 Sieve 95 Percent Passing 100 86 75 5 Asphalt General: Volumetric Properties as Built Effective Binder Content (%) 12.1 Air Voids (%) 6.0 Total Unit Weight (pcf) 145 Level 2 Asphalt Binder: Superpave Binder Test Data Angular Freq. = 10 rad/sec Temperature (F) G* (Pa) Delta (degree) 147.2 26800 73.8 158 10800 77.3 168.8 5270 80.3 Asphalt General: Volumetric Properties as Built Effective Binder Content (%) 12.1 Air Voids (%) 6.0 Total Unit Weight (pcf) 145 Level 3 Asphalt Mix: Aggregate Gradation Asphalt General: Volumetric Properties as Built 3/4 Inch Sieve 3/8 Inch Sieve #4 Sieve #200 Sieve Cumulative % Retained Percent Passing 0 0 14 14 25 25 5 5 Effective Binder Content (%) 12.1 Air Voids (%) 6.0 Total Unit Weight (pcf) 145 Asphalt Binder: Superpave Binder Grading: PG 67-22 Notes: The table summarizes the test data using extracted asphalt binder from asphalt plant mix. 174 Mixture Type: B 19_64_M Asphalt Mix: Dynamic Modulus Table Temperature (F) 39.2 68 104 130 Mixture |E*|, psi 0.1 Hz 1,328,492 280,235 21,279 5,605 0.5 Hz 1,666,382 496,408 41,131 8,689 Table A.14 Level 1 1 Hz 1,844,406 584,651 54,178 11,188 5 Hz 2,154,559 912,001 106,296 19,543 10 Hz 2,300,147 1,034,218 137,938 26,533 XML File: 25 Hz 2,463,630 1,232,022 206,862 38,301 L*_PG64_19_B_R3 Asphalt Binder: Superpave Binder Test Data Angular Freq. = 10 rad/sec Temperature (F) G* (Pa) Delta (degree) 147.2 158 168.8 Asphalt Mix: Aggregate Gradation Cumulative % Retained 3/4 Inch Sieve 1 3/8 Inch Sieve 14 #4 Sieve 25 #200 Sieve 94 Level 2 Percent Passing 99 86 75 6 Asphalt General: Volumetric Properties as Built Effective Binder Content (%) 10.5 Air Voids (%) 5.5 Total Unit Weight (pcf) 145 Asphalt Binder: Superpave Binder Test Data Angular Freq. = 10 rad/sec Temperature (F) G* (Pa) Delta (degree) Asphalt General: Volumetric Properties as Built Effective Binder Content (%) 10.5 Air Voids (%) 5.5 Total Unit Weight (pcf) 145 Asphalt Mix: Aggregate Gradation Level 3 3/4 Inch Sieve 3/8 Inch Sieve #4 Sieve #200 Sieve Cumulative % Retained Percent Passing 1 0 14 14 25 25 6 5 Asphalt Binder: Superpave Binder Grading: PG 64-22 Asphalt General: Volumetric Properties as Built Effective Binder Content (%) 10.5 Air Voids (%) 5.5 Total Unit Weight (pcf) 145 175 Mixture Type: B 25_64_M Asphalt Mix: Dynamic Modulus Table Temperature (F) 39.2 68 104 130 Mixture |E*|, psi 0.1 Hz 1,155,865 312,972 65,957 33,987 0.5 Hz 1,551,697 521,710 113,107 53,689 Table A.15 Level 1 1 Hz 1,677,457 611,119 139,266 65,279 5 Hz 2,059,318 924,418 241,927 111,491 10 Hz 2,169,615 1,050,408 295,964 137,751 XML File: 25 Hz 2,361,791 1,234,732 383,009 182,596 L*_PG64_25_B_R3 Asphalt Binder: Superpave Binder Test Data Angular Freq. = 10 rad/sec Temperature (F) G* (Pa) Delta (degree) 147.2 158 168.8 33500 72.6 17200 75.4 17700 76.1 Asphalt Mix: Aggregate Gradation Cumulative % Retained 3/4 Inch Sieve 8 3/8 Inch Sieve 10 #4 Sieve 17 #200 Sieve 95 Level 2 Percent Passing 92 90 83 5 Asphalt General: Volumetric Properties as Built Effective Binder Content (%) 9.4 Air Voids (%) 5.9 Total Unit Weight (pcf) 145 Asphalt Binder: Superpave Binder Test Data Angular Freq. = 10 rad/sec Temperature (F) G* (Pa) Delta (degree) 147.2 158 168.8 33500 72.6 17200 75.4 17700 76.1 Asphalt General: Volumetric Properties as Built Effective Binder Content (%) 9.4 Air Voids (%) 5.9 Total Unit Weight (pcf) 145 Level 3 Asphalt Mix: Aggregate Gradation 3/4 Inch Sieve 3/8 Inch Sieve #4 Sieve #200 Sieve Cumulative % Retained Percent Passing 10 90 8 82 17 65 5 60 Asphalt General: Volumetric Properties as Built Effective Binder Content (%) 9.4 Air Voids (%) 5.9 Total Unit Weight (pcf) 145 Asphalt Binder: Superpave Binder Grading: PG 64-22 Notes: The table summarizes the test data using extracted asphalt binder from asphalt plant mix. 176 Mixture Type: C 9.5_67_M Asphalt Mix: Dynamic Modulus Table Temperature (F) 39.2 68 104 130 Mixture |E*|, psi 0.1 Hz 1,042,729 252,870 47,958 22,643 0.5 Hz 1,338,882 416,779 78,495 34,356 Table A.16 Level 1 1 Hz 1,493,116 484,584 100,325 43,766 5 Hz 1,797,075 735,545 164,872 70,134 10 Hz 1,938,251 832,459 209,851 91,120 XML File: 25 Hz 2,119,050 993,556 264,927 118,701 L*_PG67_9.5_C_R3 Asphalt Binder: Superpave Binder Test Data Angular Freq. = 10 rad/sec Temperature (F) G* (Pa) Delta (degree) 147.2 158 168.8 15900 77.7 7850 80.2 3240 82.7 Asphalt Mix: Aggregate Gradation Cumulative % Retained 3/4 Inch Sieve 0 3/8 Inch Sieve 5 #4 Sieve 32 #200 Sieve 94.5 Level 2 Percent Passing 100 95 68 5.5 Asphalt General: Volumetric Properties as Built Effective Binder Content (%) 12.9 Air Voids (%) 5.0 Total Unit Weight (pcf) 145 Asphalt Binder: Superpave Binder Test Data Angular Freq. = 10 rad/sec Temperature (F) G* (Pa) Delta (degree) 147.2 158 168.8 15900 77.7 7850 80.2 3240 82.7 Asphalt General: Volumetric Properties as Built Effective Binder Content (%) 12.9 Air Voids (%) 5.0 Total Unit Weight (pcf) 145 Level 3 Asphalt Mix: Aggregate Gradation Asphalt General: Volumetric Properties as Built 3/4 Inch Sieve 3/8 Inch Sieve #4 Sieve #200 Sieve Cumulative % Retained Percent Passing 0 100 5 95 32 63 5.5 57.5 Effective Binder Content (%) 12.9 Air Voids (%) 5.0 Total Unit Weight (pcf) 145 Asphalt Binder: Superpave Binder Grading: PG 67-22 Notes: The table summarizes the test data using extracted asphalt binder from asphalt plant mix. 177 Mixture Type: C 12.5_67_M Asphalt Mix: Dynamic Modulus Table Temperature (F) 39.2 68 104 130 Mixture |E*|, psi 0.1 Hz 869,851 192,115 34,875 17,203 0.5 Hz 1,189,925 337,801 64,822 30,483 1 Hz 1,322,964 400,017 80,557 37,530 Table A.17 Level 1 5 Hz 1,667,244 639,995 149,572 70,132 10 Hz 1,791,974 734,224 183,594 86,785 XML File: 25 Hz 2,000,302 895,946 249,302 125,192 Asphalt Binder: Superpave Binder Test Data Angular Freq. = 10 rad/sec Temperature (F) G* (Pa) Delta (degree) 147.2 158 168.8 Asphalt Mix: Aggregate Gradation Cumulative % Retained 3/4 Inch Sieve 0 3/8 Inch Sieve 12 #4 Sieve 27 #200 Sieve 93.9 Percent Passing 100 88 73 6.1 Asphalt General: Volumetric Properties as Built Effective Binder Content (%) 11.5 Air Voids (%) 5.8 Total Unit Weight (pcf) 145 Level 2 Asphalt Binder: Superpave Binder Test Data Angular Freq. = 10 rad/sec Temperature (F) G* (Pa) Delta (degree) 147.2 158 168.8 Asphalt General: Volumetric Properties as Built Effective Binder Content (%) 11.5 Air Voids (%) 5.8 Total Unit Weight (pcf) 145 Level 3 Asphalt Mix: Aggregate Gradation Asphalt General: Volumetric Properties as Built 3/4 Inch Sieve 3/8 Inch Sieve #4 Sieve #200 Sieve Cumulative % Retained Percent Passing 0 100 12 88 27 61 6.1 54.9 Effective Binder Content (%) 11.5 Air Voids (%) 5.8 Total Unit Weight (pcf) 145 Asphalt Binder: Superpave Binder Grading: PG 67-22 178 Mixture Type: C 12.5_76_M Asphalt Mix: Dynamic Modulus Table Temperature (F) 39.2 68 104 130 Mixture |E*|, psi 0.1 Hz 565,772 133,118 27,968 14,093 0.5 Hz 851,214 233,060 46,100 20,212 Table A.18 Level 1 XML File: 1 Hz 953,092 278,933 56,895 24,970 5 Hz 1,301,342 459,431 98,431 39,117 10 Hz 1,417,104 536,563 122,377 50,048 25 Hz 1,608,734 668,467 161,150 64,680 L*_PG76_12.5_C_R3 Asphalt Binder: Superpave Binder Test Data Angular Freq. = 10 rad/sec Temperature (F) G* (Pa) Delta (degree) 147.2 158 168.8 Asphalt Mix: Aggregate Gradation Cumulative % Retained 3/4 Inch Sieve 0 3/8 Inch Sieve 12 #4 Sieve 27 #200 Sieve 93.9 Percent Passing 100 88 73 6.1 Asphalt General: Volumetric Properties as Built Effective Binder Content (%) 11.5 Air Voids (%) 5.8 Total Unit Weight (pcf) 145 Level 2 Asphalt Binder: Superpave Binder Test Data Angular Freq. = 10 rad/sec Temperature (F) G* (Pa) Delta (degree) 147.2 158 168.8 Asphalt General: Volumetric Properties as Built Effective Binder Content (%) 11.5 Air Voids (%) 5.8 Total Unit Weight (pcf) 145 Level 3 Asphalt Mix: Aggregate Gradation Asphalt General: Volumetric Properties as Built 3/4 Inch Sieve 3/8 Inch Sieve #4 Sieve #200 Sieve Cumulative % Retained Percent Passing 0 100 12 88 27 61 6.1 54.9 Effective Binder Content (%) 11.5 Air Voids (%) 5.8 Total Unit Weight (pcf) 145 Asphalt Binder: Superpave Binder Grading: PG 76-22 179 APPENDIX B--UNBOUND LAYER MATERIAL PROPERTIES (KIM ET AL., 2013) Source Lincoln Washington Coweta Walton Chatham Lowndes Franklin Cook Toombs Table C.1- Subgrade Soil Properties Percent Passing (%) #10 #40 #60 #200 % Clay % Volum e Chang e % Swel l % Shrink Max. Dry Density (pcf) 99.3 96.8 93.8 48.9 40.7 24.5 20.5 4.0 93.4 99.8 84.6 56.1 23.8 20.6 4.7 4.5 0.2 117.8 89.5 64.6 48.9 28.3 24.0 12.2 11.2 1.0 105.3 89.4 61.5 50.5 36.3 28.3 4.0 1.0 3.0 104.8 99.9 97.4 93.5 3.6 1.8 0.0 3.6 0.0 99.0 74.9 52.9 12.2 4.5 0.0 0.0 0.0 97.4 113.1 97.3 89.4 70.9 31.1 19.6 5.2 3.0 2.2 105.1 79.9 66.4 46.6 25.0 18.4 0.6 0.6 0.0 84.2 37.8 17.6 6.2 4.6 1.1 0.1 1.0 113.1 119.3 Opt. Moistur e Content LL (%) PI (%) Eros Inde x (%) 23.5 39. 9 8.6 4.23 11.0 23. 0 6.6 7.30 16.7 42. 5 11. 0 6.69 16.8 40. 5 12. 7 5.71 12.7 0.0 0.0 9.76 4.7 0.0 0.0 8.65 22.6 39. 3 9.8 6.32 9.9 0.0 0.0 7.06 11.9 0.0 0.0 9.39 180 Table C.2- GAB Material Characteristics QPL Aggregate Source GAB wopt ID Group Location Character (%) Max. d (pcf) wactual (%) Actual d (pcf) Percent Compaction LA Abrasion (%) Bulk Specify Gravity 011C II Lithonia Granite Gneiss 5.7 133.9 4.3 133 013C I Dalton Limestone 6.6 142.5 4.7 139 024C II Gainsville Mylonitic Gneiss 6 136.6 6.7 134 028C II Hitchcock Mylonitic Gneiss 6.2 141.2 5.6 138 050C II Stockbridge Granite Gneiss 5.9 134.2 5.9 134 101C II Demorest Metasandstone 5.3 137.4 5 137 108T I Mayo Mine Limerock 13.6 112.6 11.5 110 118C II Columbus Granite Gneiss 6 137.2 6.5 135 141C II Dahlonega Granite Gneiss 5.6 135.2 4 132 158C II Walton County Biotite Gneiss 6.4 135 4.5 132 165T II I-75 Unadilla Recycled Concrete 7 134 8.5 131 99 50 2.614 98 25 2.702 98 39 2.605 98 18 2.697 100 42 2.611 100 32 2.642 98 N/A N/A 98 33 2.677 98 34 2.646 98 41 2.64 98 N/A N/A 181 % Passing Table C.3- GAB Aggregate Gradations Sieve 2" 1 1/2" 3/4 in No. 10 mm 50 37.5 19 2 MIN 100 97 60 25 MAX 100 100 90 45 011C 100 100 70 33 013C 100 100 90 38 024C 100 100 74 26 028C 100 100 71 30 050C 100 100 85 43 101C 100 100 87 26 118C 100 100 71 31 141C 100 100 82 36 158C 100 100 77 29 165T 100 100 72 29 No. 60 0.25 5 30 16 10 10 14 20 14 14 18 13 7 No. 200 0.075 4 11 5 7 4 6 6 7 6 6 5 4 182 REFERENCES American Association of State Highway and Transportation Officials, AASHTO Guide for Design of Pavement Structures, Washington, DC, 1986. American Association of State Highway and Transportation Officials, AASHTO Guide for Design of Pavement Structures, Washington, DC, 1993. American Association of State Highway and Transportation Officials, Mechanistic-Empirical Pavement Design Guide--A Manual of Practice, Publication Code: MEPDG-1, ISBN: 978-156051-423-7, AASHTO, Washington, DC, 2008. American Association of State Highway and Transportation Officials, Mechanistic-Empirical Pavement Design Guide--A Manual of Practice, Second Edition, Publication Code: MEPDG2, ISBN: 978-1-56051-597-5, AASHTO, Washington, DC, 2015. Applied Research Associates, Inc, Guide for Mechanistic-Empirical Design of New and Rehabilitated Pavement Structures: Part 1-Introduction and Part 2-Design Inputs, Final Report, NCHRP Project 1-37A, National Cooperative Highway Research Program, Transportation Research Board, National Research Council, Washington, DC, 2004a. Applied Research Associates, Guide for Mechanistic-Empirical Design of New and Rehabilitated Pavement Structures: Part 3-Design Analysis and Part 4-Low Volume Roads, Final Report, NCHRP Project 1-37A, National Cooperative Highway Research Program, Transportation Research Board, National Research Council, Washington, DC, 2004b. Applied Research Associates, Inc, Guide for Mechanistic-Empirical Design of New and Rehabilitated Pavement Structures: Appendices A to C, Final Report, NCHRP Project 1-37A, National Cooperative Highway Research Program, Transportation Research Board, National Research Council, Washington, DC, 2004c. Applied Research Associates, Inc, Guide for Mechanistic-Empirical Design of New and Rehabilitated Pavement Structures: Appendix D User's Guide, Final Report, NCHRP Project 1-37A, National Cooperative Highway Research Program, Transportation Research Board, National Research Council, Washington, DC, 2004d. Durham, S., Cetin, B., Schwartz, C., Forman, B., and Gopisetti, L.S.P., Improvement of Climate Data for use in MEPDG Calibration and Other Pavement Analysis, Final Report, Research Project Number 16-10, Georgia Department of Transportation, Office of Performance-Based Management and Research, Forest Park, Georgia, January 2019. Federal Highway Administration, Distress Identification Manual for Long Term Pavement Performance Program (Fourth Revised Edition), Publication No. FHWA-RD-03-031, Federal Highway Administration, Washington, DC, 2003. Kim, S., Measurements of Dynamic and Resilient Moduli of Roadway Test Sites, Final Report, Research Project Number 12-07, Georgia Department of Transportation, Office of Materials and Research, Research and Development Branch, Forest Park, Georgia, December 2013. 183 Kim, S., Determination of Coefficient of Thermal Expansion for Portland Cement Concrete Pavements for MEPDG Implementation, Final Report, Research Project Number 10-04, Georgia Department of Transportation, Office of Materials and Research, Research and Development Branch, Forest Park, Georgia, October 2012. Kim, S., Etheridge, A., Chorzepa, M., Kim, Y.R., Effects of Asphalt Mixture Characteristics of Dynamic Modulus and Fatigue Performance, Final Report, Research Project Number 16-19, Georgia Department of Transportation. Office of Materials and Research, Research and Development Branch, Forest Park, Georgia, April 2019. National Cooperative Highway Research Program, Changes to the Mechanistic-Empirical Pavement Design Guide Software Through Version 0.900, NCHRP Research Results Digest 308, NCHRP Project 1-40D, Transportation Research Board, National Research Council, Washington, DC, 2006. Selezneva, Olga, and Von Quintus, H., Traffic Load Spectra for Implementing and Using the Mechanistic Empirical Pavement Design Guide in Georgia, Final Report, Research Project Number 10-09, PI Number 0010110, Georgia Department of Transportation, Office of Materials and Research, Research and Development Branch, Forest Park, Georgia, January 2014. Tsai, Y., Wang, Z., Purcell, R., Improving GDOT's Highway Pavement Preservation, Final Report, Research Project Number 05-19, Georgia Department of Transportation, Office of Materials and Research, Research and Development Branch, Forest Park, Georgia, 2009 Tsai, J., Wu Y., Wang, C., Georgia Concrete Pavement Performance and Longevity, Final Report, Research Project Number 10-10, Georgia Department of Transportation, Office of Materials and Research, Research and Development Branch, Forest Park, Georgia, January 2014. Von Quintus, Harold L. and Chetana Rao, Long-Term Pavement Performance Program Determination of In-Place Elastic Layer Modulus: Backcalculation Methodology and Procedures, Publication Number FHWA-HRT-15-036, Federal Highway Administration, Turner-Fairbanks Highway Research Center, McLean, Virginia, March 2015. Von Quintus, H.L., Darter, M.I., Bhattacharya, B., and Sadasivam, S. Implementation of the Mechanistic Empirical Pavement Design Guide in Georgia, Research Project Number 11-17, Georgia Department of Transportation, Office of Performance Based-Management and Research, Forest Park, Georgia, 2015. Von Quintus, H.L., Darter, M., Mallela J., Bhattacharya, B., Sadasivam, S. Validation of the MEPDG Transfer Functions Using the LTPP Test Sections in Georgia, Research Project Number 11-17, Georgia Department of Transportation, Office of Performance BasedManagement and Research, Forest Park, Georgia, 2013b. Von Quintus, H.L., Darter, M.I., Bhattacharya, B., and Titus-Glover, L., Calibration of the MEPDG Transfer Functions in Georgia, Research Project Number 11-17, Georgia Department of Transportation, Office of Performance Based-Management and Research, Forest Park, Georgia, 2014. 184 Von Quintus, H.L., Darter, M.I., Bhattacharya, B., and Titus-Glover, L., Implementation and Calibration of the Mechanistic Empirical Pavement Design Guide in Georgia, Research Project Number 11-17, Georgia Department of Transportation, Office of Performance BasedManagement and Research, Forest Park, Georgia, 2016. Von Quintus, H., Mallela J., Sadasivam, S., Darter, M. Verification and Local Calibration/Validation of the MEPDG Performance Models for Use in Georgia, Research Project Number 11-17, Georgia Department of Transportation, Office of Performance BasedManagement and Research, Forest Park, Georgia, 2013a. Von Quintus, H.L. and J.S. Moulthrop, Performance Prediction Models: Volume I Executive Research Summary, Publication Number FHWA/MT-07-008/8158-1, Montana Department of Transportation, Research Programs, Helena, MT, 2007a. Von Quintus, H.L. and J.S. Moulthrop, Performance Prediction Models: Volume II Reference Manual, Publication Number FHWA/MT-07-008/8158-2, Montana Department of Transportation, Research Programs, Helena, MT, 2007b. 185