Innovative training modules for rapid and continuous deployment of MEPDG

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
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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
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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
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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

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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.

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Figure 2.1--Conceptual Flow Chart of the MEPDG Three-Stage Design/Analysis Process for AASHTOWare PMED (AASHTO, 2015, 2020)
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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.
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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.
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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

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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.
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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.
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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.

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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.

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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).
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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.

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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.

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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.
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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.
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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.
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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.
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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).
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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

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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
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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).
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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.
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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.

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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.
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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.
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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.
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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).

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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.
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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.
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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
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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).
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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.

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Overall Screen Shot for the CRCP Design Properties, Foundation Support, and JPCP Rehabilitation
Shoulder Type Crack Spacing
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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.
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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.

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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

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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

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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.
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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.
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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.
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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.
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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.
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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

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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.

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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.

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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

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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.
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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
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Asphalt Concrete

Dynamic Modulus; New AC Layer

Asphalt Binder; Superpave Performance Grade

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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.
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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

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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

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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.

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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.

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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

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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.
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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.
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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.
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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

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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.
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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.

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Overall Screen Shot for Bedrock Bedrock Layer Properties
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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

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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.

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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

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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

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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

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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.

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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.
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Flexible Pavement Calibration Coefficients
Rigid Pavement Calibration Coefficients
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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)
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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)
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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.
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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:
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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
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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.
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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:
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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.
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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.
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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

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185