Research, Development, and Technology

Turner-Fairbank Highway Research Center

6300 Georgetown Pike

McLean, VA 22101-2296

Impact of Design Features on Pavement

Response and Performance in

Rehabilitated Flexible and Rigid 

Pavements

Publication No. FHWA-HRT-10-066 october 2011
FOREWORD

The primary focus of this research was to determine the effects of design and construction 

features, such as overlay thickness and mix type, presence of milling, and type of restoration, on 

pavement response and performance and to establish their importance in the prediction of future 

performance of rehabilitated pavements. Long-Term Pavement Performance program Specific

Pavement Study (SPS)-5 and SPS-6 experiments provided information to obtain a better

understanding of the effects of design and construction features on pavement response and 

performance of rehabilitated flexible and rigid pavements. The research findings provide 

guidance to identify appropriate features and rehabilitation alternatives for different pavement 

types and recommendations for improving data collection activities. The analyses results 

obtained in this study help determine the causes of distress and formulate models for predicting 

performance of rehabilitated pavements. Additionally, data from SPS-3 and SPS-4 experiments 

were used to determine the effectiveness and timing of preventive maintenance treatments. The 

findings suggest that it is possible to determine significant differences between treatment 

alternatives with respect to pavement performance and treatment timing. Performance of 

rehabilitated pavement sections from SPS-5 and SPS-6 were also examined using the 

Mechanistic Empirical Pavement Design Guide and compared with the field performance.(1)

The results provide useful information about rehabilitated pavement section performance 

predictions and recommendations for future model improvements.

Jorge E. Pagán-Ortiz

Director, Office of Infrastructure

Research and Development

Notice

This document is disseminated under the sponsorship of the U.S. Department of Transportation 

in the interest of information exchange. The U.S. Government assumes no liability for the use 

of the information contained in this document. This report does not constitute a standard, 

specification, or regulation.

The U.S. Government does not endorse products or manufacturers. Trademarks or 

manufacturers’ names appear in this report only because they are considered essential to the 

objective of the document.

Quality Assurance Statement

The Federal Highway Administration (FHWA) provides high-quality information to serve 

Government, industry, and the public in a manner that promotes public understanding. Standards 

and policies are used to ensure and maximize the quality, objectivity, utility, and integrity of its 

information. FHWA periodically reviews quality issues and adjusts its programs and processes to 

ensure continuous quality improvement.
TECHNICAL REPORT DOCUMENTATION PAGE

1. Report No.

FHWA-HRT-10-066

2. Government Accession No. 3. Recipient's Catalog No.

4. Title and Subtitle

Impact of Design Features on Pavement Response and 

Performance in Rehabilitated Flexible and Rigid Pavements

5. Report Date 

October 2011

6. Performing Organization Code

7. Author(s) 

R. Carvalho, M. Ayres, H. Shirazi, O. Selezneva, and M. Darter

8. Performing Organization Report No.

9. Performing Organization Name and Address

Applied Research Associates, Inc.

7184 Troy Hill Drive Suite N

Elkridge, MD 21075-7056

10. Work Unit No. (TRAIS)

11. Contract or Grant No.

DTFH61-02-C-00138

12. Sponsoring Agency Name and Address

Office of Infrastructure Research and Development

Federal Highway Administration

6300 Georgetown Pike

McLean, VA 22101-2296

13. Type of Report and Period Covered

Final Report

14. Sponsoring Agency Code

15. Supplementary Notes

The Contracting Officer’s Technical Representative (COTR) was Larry Wiser, HRDI-30, LTPP data analysis 

contract.

16. Abstract

The primary focus of this research was to determine the effects of design and construction features, such as overlay 

thickness and mix type, presence of milling, and type of restoration, on pavement response and performance and to

establish their importance in the prediction of future performances of rehabilitated pavements. Long-Term Pavement 

Performance program Specific Pavement Study (SPS)-5 and SPS-6 experiments provided information to obtain a 

better understanding of the effects of design and construction features on pavement response and performance of 

rehabilitated flexible and rigid pavements. The research findings provided guidance to identify appropriate features 

and rehabilitation alternatives for different pavement types and recommendations for improving data collection 

activities. The analyses results obtained in this study helped determine the causes of distress and helped formulate 

models for predicting performance of rehabilitated pavements. In addition, data from SPS-3 and SPS-4 experiments 

were used to determine effectiveness and timing of preventive maintenance treatments. The findings suggest that it is 

possible to determine significant differences between treatment alternatives with respect to pavement performance 

and treatment timing. Performance of rehabilitated pavement sections from SPS-5 and SPS-6 were also examined 

using the Mechanistic Empirical Pavement Design Guide and compared with the field performance.(1) The results 

provide useful information about rehabilitated pavement section performance predictions and recommendations for 

future model improvements.

17. Key Words

Pavement performance, Rehabilitation, Maintenance, 

Pavement design, Long-term performance, Flexible 

pavements, Rigid pavements

18. Distribution Statement

No restrictions. This document is available to the public 

through the National Technical Information Service, 

Springfield, VA 22161.

19. Security Classification (of this report)

Unclassified

20. Security Classification (of this page)

Unclassified

21. No. of Pages

261

22. Price

Form DOT F 1700.7 (8-72) Reproduction of completed page authorized
ii
iii

TABLE OF CONTENTS

EXECUTIVE SUMMARY .......................................................................................................... 1

PREVENTIVE MAINTENANCE TREATMENTS............................................................ 1

REHABILITATED FLEXIBLE PAVEMENTS ................................................................. 2

REHABILITATED RIGID PAVEMENTS.......................................................................... 3

FINDINGS FROM MEPDG ANALYSES ........................................................................... 4

CHAPTER 1. INTRODUCTION................................................................................................ 5

BACKGROUND ..................................................................................................................... 5

PROJECT OBJECTIVES...................................................................................................... 6

REPORT ORGANIZATION................................................................................................. 7

CHAPTER 2. LITERATURE REVIEW.................................................................................... 9

SUMMARY OF FINDINGS FROM PREVIOUS STUDIES............................................. 9

CHAPTER 3. OVERVIEW OF LTPP MAINTENANCE AND REHABILITATION 

EXPERIMENTS ......................................................................................................................... 21

INTRODUCTION................................................................................................................. 21

SPS-3 EXPERIMENT .......................................................................................................... 21

Experimental Design......................................................................................................... 21

SPS-3 Sections.................................................................................................................. 22

SPS-4 EXPERIMENT .......................................................................................................... 23

Experimental Design......................................................................................................... 23

SPS-5 EXPERIMENT .......................................................................................................... 25

Experiment Design............................................................................................................ 25

Final Factorial of SPS-5 Experiment................................................................................ 26

SPS-6 EXPERIMENT .......................................................................................................... 27

Experimental Design......................................................................................................... 27

Final Factorial of SPS-6 Experiment................................................................................ 28

OVERVIEW OF THE LTPP DATA RELEVANT TO THIS STUDY ........................... 29

Assessment of SPS-3 Data................................................................................................ 30

Assessment of SPS-4 Data................................................................................................ 33

Assessment of SPS-5 Data................................................................................................ 35

Assessment of SPS-6 Data................................................................................................ 40

CHAPTER 4. ASSESSMENT OF MAINTENANCE ALTERNATIVES............................. 49

PERFORMANCE INDICATORS USED IN PREVIOUS STUDIES ............................. 49

PERFORMANCE INDICATOR IMPLEMENTED IN THIS STUDY .......................... 50

STATISTICAL ANALYSIS APPROACH......................................................................... 51

FLEXIBLE PAVEMENTS MAINTENANCE................................................................... 52

Fatigue Cracking............................................................................................................... 56

Rutting............................................................................................................................... 56

IRI ..................................................................................................................................... 57

RIGID PAVEMENTS MAINTENANCE........................................................................... 58
iv

MAINTENANCE TREATMENT APPLICATION TIMING.......................................... 61

Flexible Pavement Maintenance Application Timing ...................................................... 61

Rigid Pavement Maintenance Application Timing........................................................... 65

CONCLUSIONS ................................................................................................................... 65

CHAPTER 5. REHABILITATED FLEXIBLE PAVEMENT ANALYSIS 

AND FINDINGS ......................................................................................................................... 67

INTRODUCTION................................................................................................................. 67

DATA ANALYSES............................................................................................................... 69

Statistical Approach and Tests.......................................................................................... 69

Performance Measures...................................................................................................... 70

EFFECT OF DESIGN, CONSTRUCTION FEATURES, AND SITE CONDITIONS 

ON PERFORMANCE OF REHABILITATED FLEXIBLE PAVEMENTS ................. 71

Example of Repeated Measures of ANOVA for Evaluation of SPS-5 Sites.................... 71

Summary of Findings........................................................................................................ 76

Conclusions from the Individual Analyses of SPS-5 Sites............................................... 76

Consolidated Analysis ...................................................................................................... 83

Influence of Site Condition............................................................................................... 96

EFFECT OF DESIGN AND CONTRUCTION FEATURES AND SITE 

CONDITIONS ON RESPONSE OF REHABILITATED FLEXIBLE 

PAVEMENTS ..................................................................................................................... 109

Individual Analysis of SPS-5 Sites................................................................................. 110

Consolidated Analysis .................................................................................................... 111

Influence of Site Condition............................................................................................. 113

RELATIONHIP BETWEEN STRUCTURAL RESPONES IMMEDIATELY 

AFTER REHABILITATION AND FUTURE PERFORMANCE ................................ 116

CHAPTER 6. REHABILITATED RIGID PAVEMENT ANALYSIS AND 

FINDINGS................................................................................................................................. 121

INTRODUCTION............................................................................................................... 121

STATISTICAL ANALYSIS APPROACH....................................................................... 121

Performance Measures.................................................................................................... 121

EFFECT OF DESIGN AND CONSTRUCTION FEATURES AND SITE 

CONDITIONS ON PERFORMANCE OF REHABILITATED RIGID 

PAVEMENTS ..................................................................................................................... 123

JPCP................................................................................................................................ 124

Influence of Site Conditions........................................................................................... 134

Influence of Site Conditions........................................................................................... 142

JRCP ............................................................................................................................... 147

EFFECT OF DESIGN AND CONSTRUCTION FEATURES AND SITE 

CONDITIONS ON RESPONSE OF REHABILITATED RIGID PAVEMENTS ....... 156

RELATIONSHIP BETWEEN STRUCTURAL RESPONSES IMMEDIATELY 

AFTER REHABILITATION AND FUTURE PERFORMANCE ................................ 158

LTE Versus Performance in JPCP.................................................................................. 159

Maximum Deflection at Center of Slab Versus JPCP Performance............................... 160

Maximum Deflection at Center of Lane Versus Performance of Overlaid JPCP........... 162

Response Versus Performance in JRCP ......................................................................... 165
v

CHAPTER 7. ANALYSIS OF REHABILITATED PAVEMENT STRUCTURES 

USING MEPDG........................................................................................................................ 167

INTRODUCTION............................................................................................................... 167

MEPDG OVERVIEW........................................................................................................ 167

Data Requirements.......................................................................................................... 167

Latest Calibration Efforts................................................................................................ 169

REHABILITATED FLEXIBLE PAVEMENTS ............................................................. 170

Roughness....................................................................................................................... 170

Rutting............................................................................................................................. 176

Cracking.......................................................................................................................... 177

REHABILITATED RIGID PAVEMENTS...................................................................... 180

Roughness....................................................................................................................... 180

Rutting............................................................................................................................. 184

Cracking.......................................................................................................................... 185

Faulting ........................................................................................................................... 187

Load Transfer Efficiency ................................................................................................ 189

SUMMARY AND CONCLUSIONS ................................................................................. 189

CHAPTER 8. STUDY FINDINGS, CONCLUSIONS, AND RECOMMENDATIONS.... 191

PREVENTIVE MAINTENANCE TREATMENTS........................................................ 191

Preventive Maintenance Effectiveness for Flexible Pavements..................................... 191

Preventive Maintenance Effectiveness for Rigid Pavements ......................................... 192

REHABILITATED FLEXIBLE PAVEMENTS ............................................................. 192

Evaluation of Rehabilitation Strategies with Respect to Performance ........................... 192

Evaluation of Rehabilitation Strategies with Respect to Structural Responses.............. 194

Evaluation of Structural Responses Immediately After Rehabilitation and Future 

Performance .................................................................................................................... 195

REHABILITATED RIGID PAVEMENTS...................................................................... 196

Evaluation of JPCP Rehabilitation Strategies with Respect to Performance ................. 196

Evaluation of JRCP Rehabilitation Strategies with Respect to Performance................. 198

Evaluation of Rehabilitation Strategies with Respect to Structural Responses.............. 200

Evaluation of Structural Responses Immediately After Rehabilitation and Future 

Performance .................................................................................................................... 200

FINDINGS FROM MEPDG ANALYSES ....................................................................... 202

RECOMMENDATIONS FOR FUTURE RESEARCH.................................................. 203

APPENDIX A. SUMMARY STATISTICAL ANALYSIS ................................................... 205

FLEXIBLE PAVEMENTS —SPS-5................................................................................. 205

APPENDIX B. PRACTICAL GUIDE: SELECTION OF PAVEMENT 

MAINTENANCE ALTERNATIVES ..................................................................................... 217

FLEXIBLE PAVEMENTS ................................................................................................ 217

Example .......................................................................................................................... 217

RIGID PAVEMENTS ........................................................................................................ 218
vi

APPENDIX C. PRACTICAL GUIDE: FACTORS AFFECTING PERFORMANCE 

OF REHABILITATED FEXIBLE PAVEMENTS ............................................................... 219

INTRODUCTION............................................................................................................... 219

SELECTION PROCESS.................................................................................................... 219

Selection Process Example ............................................................................................. 219

APPENDIX D. PRACTICAL GUIDE: FACTORS AFFECTING PERFORMANCE 

OF REHABILITATED RIGID PAVEMENTS..................................................................... 231

INTRODUCTION............................................................................................................... 231

SELECTION PROCESS.................................................................................................... 231

Selection Process Example ............................................................................................. 232

APPENDIX E. PERFORMANCE AND INPUT DATABASE FOR MEPDG 

ANALYSIS ................................................................................................................................ 237

PERFORMANCE DATA................................................................................................... 237

MEPDG INPUT DATA...................................................................................................... 241

REFERENCES.......................................................................................................................... 245
vii

LIST OF FIGURES

Figure 1. Equation. Weighted distress.......................................................................................... 50

Figure 2. Graph. Example of IRI trends to calculate WD-IRI...................................................... 51

Figure 3. Graph. Box-whisker plot for WD-fatigue of SPS-3 sections........................................ 53

Figure 4. Graph. Box-whisker plot for WD-rutting of SPS-3 sections......................................... 53

Figure 5. Graph. Box-whisker plot for WD-IRI of SPS-3 sections.............................................. 54

Figure 6. Graph. Box-whisker plot for WD-edge faulting of SPS-4 sections .............................. 59

Figure 7. Graph. Box-whisker plot for WD-wheel-path faulting of SPS-4 sections.................... 59

Figure 8. Graph. Box-whisker plot for WD-linear cracking of SPS-4 sections ........................... 60

Figure 9. Graph. Box-whisker plot for WD-IRI of SPS-4 sections.............................................. 60

Figure 10. Graph. Average rank of SPS-3 sites with respect to IRI............................................. 62

Figure 11. Graph. Average rank of SPS-3 sites with respect to rutting........................................ 63

Figure 12. Graph. Average rank of SPS-3 sites with respect to cracking based on 

application timing ......................................................................................................................... 64

Figure 13. Illustration. Statistical analysis flow chart................................................................... 69

Figure 14. Equation. Weighted distress........................................................................................ 70

Figure 15. Graph. Roughness from an SPS-5 site in Arizona ...................................................... 72

Figure 16. Graph. IRI versus overlay thickness (distribution) for an SPS-5 site in Arizona........ 73

Figure 17. Graph. IRI versus mix type (distribution) for an SPS-5 site in Arizona ..................... 74

Figure 18. Graph. IRI versus milling (distribution) for an SPS-5 site in Arizona........................ 75

Figure 19. Graph. Summary of SPS-5 sites by best-performing design feature for roughness 

according to repeated measures ANOVA results ......................................................................... 78

Figure 20. Graph. Summary of SPS-5 sites by best-performing design feature for rutting 

according to repeated measures ANOVA results ......................................................................... 79

Figure 21. Graph. Summary of SPS-5 sites by best-performing design feature for fatigue 

cracking according to repeated measures ANOVA results........................................................... 80

Figure 22. Graph. Summary of SPS-5 sites by best-performing design feature for transverse 

cracking according to repeated measures ANOVA results........................................................... 81

Figure 23. Graph. Summary of SPS-5 sites by best-performing design feature for longitudinal 

cracking according to repeated measures ANOVA results........................................................... 82

Figure 24. Graph. Example of WD-distress values in comparative performance analysis 

for IRI trend after rehab ................................................................................................................ 84

Figure 25. Graph. WD-IRI short-term values in SPS-5 sites........................................................ 88

Figure 26. Graph. WD-IRI long-term values in SPS-5 sites......................................................... 88

Figure 27. Graph. WD-rutting short-term values for SPS-5 sites................................................. 92

Figure 28. Graph. WD-rutting long-term values for SPS-5 sites.................................................. 92

Figure 29. Graph. Fatigue cracking WD values for long-term performance of SPS-5 sites........ 94

Figure 30. Graph. Transverse cracking WD values for long-term performance of 

SPS-5 sites .................................................................................................................................... 94

Figure 31. Graph. Longitudinal cracking WD values for long-term performance of 

SPS-5 sites .................................................................................................................................... 94

Figure 32. Graph. Percentage of SPS-5 sections with lower maximum deflection based on 

repeated measures ANOVA results............................................................................................ 110

Figure 33. Graph. Maximum deflection (wheel path of LTPP lane) WD values at 

SPS-5 sites .................................................................................................................................. 113
viii

Figure 34. Equation. Parameter subscript normalized................................................................ 117

Figure 35. Graph. Normalized long-term WD-roughness versus normalized maximum 

deflection measured after rehabilitation in SPS-5 sites .............................................................. 117

Figure 36. Graph. Normalized long-term WD-rutting versus normalized maximum 

deflection measured after rehabilitation in SPS-5 sections......................................................... 118

Figure 37. Graph. Normalized long-term WD-fatigue cracking versus normalized 

maximum deflection measured after rehabilitation in SPS-5 sections....................................... 118

Figure 38. Graph. Normalized long-term WD-transverse cracking versus normalized 

maximum deflection measured after rehabilitation in SPS-5 sections....................................... 119

Figure 39. Graph. Normalized long-term WD-longitudinal cracking versus normalized 

maximum deflection measured after rehabilitation in SPS-5 sections....................................... 119

Figure 40. Graph. WD-IRI short-term values for JPCP in SPS-6 sections................................. 127

Figure 41. Graph. WD-IRI long-term values for JPCP in SPS-6 sections ................................. 128

Figure 42. Graph. Average short-term WD-cracking for JPCP at SPS-6 sites........................... 132

Figure 43. Graph. Average long-term WD-cracking for JPCP at SPS-6 sites............................ 132

Figure 44. Graph. Average short-term WD-transverse cracking values for JPCP at 

SPS-6 sites .................................................................................................................................. 141

Figure 45. Graph. Average long-term WD-transverse cracking values for JPCP at 

SPS-6 sites .................................................................................................................................. 141

Figure 46. Graph. Long-term WD-roughness for JPCP at SPS-6 site........................................ 145

Figure 47. Graph. Long-term WD-longitudinal cracking for JPCP at SPS-6 sites..................... 146

Figure 48. Graph. Short-term WD-roughness values for JRCP at SPS-6 sites........................... 148

Figure 49. Graph. Long-term WD-roughness values for JRCP at SPS-6 sites........................... 149

Figure 50. Graph. Long-term WD-total cracking values for JRCP at SPS-6 sites..................... 149

Figure 51. Graph. Average short-term WD-transverse cracking values for JRCP at 

SPS-6 sites .................................................................................................................................. 152

Figure 52. Graph. Average long-term WD-transverse cracking values for JRCP at 

SPS-6 sites .................................................................................................................................. 152

Figure 53. Graph. Short-term average WD-transverse cracking values for JRCP at 

SPS-6 sites .................................................................................................................................. 154

Figure 54. Graph. Maximum deflection (center of lane) short-term WD values for JRCP 

at SPS-6 sites............................................................................................................................... 157

Figure 55. Graph. Maximum deflection (center of lane) long-term WD values for JRCP 

at SPS-6 sites............................................................................................................................... 157

Figure 56. Equation. Parameter subscript normalized................................................................ 159

Figure 57. Graph. Normalized long-term transverse cracking versus normalized LTE 

measured after rehabilitation of JPCP sites ................................................................................ 160

Figure 58. Graph. Normalized long-term roughness versus normalized deflection at the

center of the slab measured immediately after rehabilitation of JPCP sites............................... 160

Figure 59. Graph. Normalized long-term total cracking versus normalized deflection at 

the center of the slab measured immediately after rehabilitation of JPCP sites......................... 161

Figure 60. Graph. Normalized long-term longitudinal slab cracking versus normalized 

deflection at the center of slab measured after rehabilitation of JPCP sites............................... 161

Figure 61. Graph. Normalized long-term transverse cracking versus normalized deflection 

at the center of slab measured after rehabilitation of JPCP sites................................................ 162
ix

Figure 62. Graph. Normalized long-term faulting versus normalized deflection at the center 

of slab measured after rehabilitation of JPCP sites..................................................................... 162

Figure 63. Graph. Normalized long-term roughness versus normalized deflection at the 

center of the lane measured after rehabilitation of overlaid JPCP sites...................................... 163

Figure 64. Graph. Normalized long-term rutting versus normalized deflection at the 

center of the lane measured after rehabilitation of overlaid JPCP sites...................................... 164

Figure 65. Graph. Normalized long-term fatigue cracking versus normalized deflection 

at the center of the lane measured after rehabilitation of overlaid JPCP sites............................ 164

Figure 66. Graph. Normalized long-term longitudinal cracking versus normalized 

deflection at the center of the lane measured after rehabilitation of overlaid JPCP sites........... 165

Figure 67. Graph. LTPP-measured versus MEPDG-predicted IRI for all SPS-5 sections......... 171

Figure 68. Graph. LTPP-measured versus MEPDG-predicted IRI for SPS-5 

control sections ........................................................................................................................... 172

Figure 69. Graph. LTPP-measured versus MEPDG-predicted IRI for SPS-5 rehabilitated 

sections........................................................................................................................................ 172

Figure 70. Graph. LTPP-measured versus MEPDG-predicted IRI for SPS-5 control 

sections in wet and dry regions................................................................................................... 173

Figure 71. Graph. LTPP-measured versus MEPDG-predicted IRI for SPS-5 rehabilitated 

sections in wet and dry regions................................................................................................... 174

Figure 72. Graph. LTPP-measured versus MEPDG-predicted IRI for SPS-5 rehabilitated 

sections grouped by thickness..................................................................................................... 175

Figure 73. Graph. LTPP-measured versus MEPDG-predicted IRI for SPS-5 rehabilitated 

sections grouped by mix type ..................................................................................................... 175

Figure 74. Graph. LTPP-measured versus MEPDG-predicted IRI for SPS-5 rehabilitated 

sections grouped by milling........................................................................................................ 176

Figure 75. Graph. LTPP measured versus MEPDG predicted rutting for SPS-5 sections......... 177

Figure 76. Graph. LTPP-measured versus MEPDG-predicted longitudinal cracking for 

SPS-5 sections............................................................................................................................. 178

Figure 77. Graph. LTPP-measured versus MEPDG-predicted fatigue and reflective 

cracking for SPS-5 sections........................................................................................................ 179

Figure 78. Graph. LTPP-measured versus MEPDG-predicted fatigue cracking for SPS-5 

sections........................................................................................................................................ 179

Figure 79. Graph. LTPP-measured versus MEPDG-predicted IRI for SPS-6 sections 

without overlay ........................................................................................................................... 181

Figure 80. Graph. LTPP-measured versus MEPDG-predicted IRI for SPS-6 sections 

with overlay ................................................................................................................................ 181

Figure 81. Graph. LTPP-measured versus MEPDG-predicted IRI for SPS-6 sections in 

wet regions.................................................................................................................................. 182

Figure 82. Graph. LTPP-measured versus MEPDG-predicted IRI for SPS-6 sections in 

dry regions .................................................................................................................................. 183

Figure 83. Graph. LTPP-measured versus MEPDG-predicted IRI for SPS-6 sections in 

freeze regions.............................................................................................................................. 183

Figure 84. Graph. LTPP-measured versus MEPDG-predicted IRI for SPS-6 sections in 

no-freeze regions......................................................................................................................... 184

Figure 85. Graph. LTPP-measured versus MEPDG-predicted rutting for SPS-6 sections 

with overlays............................................................................................................................... 185
x

Figure 86. Graph. LTPP-measured versus MEPDG-predicted longitudinal cracking for 

HMA overlaid SPS-6 sections.................................................................................................... 186

Figure 87. Graph. LTPP-measured versus MEPDG-predicted fatigue and reflective 

cracking for HMA overlaid SPS-6 sections................................................................................ 186

Figure 88. Graph. LTPP-measured versus MEPDG-predicted faulting for SPS-6 sections 

without HMA overlay................................................................................................................. 187

Figure 89. Graph. LTPP-measured versus MEPDG-predicted faulting for SPS-6 sections 

without HMA overlay with fair pavement condition prior to rehabilitation .............................. 188

Figure 90. Graph. LTPP-measured versus MEPDG-predicted faulting for SPS-6 sections 

without HMA overlay with poor pavement condition prior to rehabilitation............................. 188

Figure 91. Graph. LTPP-measured versus MEPDG-predicted LTE for SPS-6 sections 

without HMA overlay................................................................................................................. 189
xi

LIST OF TABLES

Table 1. Rehabilitation of flexible pavements.............................................................................. 10

Table 2. Rehabilitation of rigid pavements................................................................................... 13

Table 3. Preventive maintenance of flexible pavements .............................................................. 15

Table 4. Preventive maintenance of rigid pavements................................................................... 17

Table 5. Optimal timing of preventive maintenance .................................................................... 18

Table 6. Data availability for SPS-3, SPS-4, SPS-5, and SPS-6 experiments.............................. 19

Table 7. SPS-3 categorization....................................................................................................... 23

Table 8. SPS-4 experimental design ............................................................................................. 25

Table 9. Core sections of SPS-5 experiment ................................................................................ 26

Table 10. Constructed SPS-5 sites for the experimental factorial ................................................ 27

Table 11. Core sections of the SPS-6 experiment......................................................................... 28

Table 12. As-built SPS-6 sites for the experimental factorial ...................................................... 29

Table 13. Data availability for SPS-3 sites................................................................................... 30

Table 14. Data availability for SPS-4 sites................................................................................... 34

Table 15. Original construction, traffic open, and major rehabilitation dates for 

SPS-5 projects............................................................................................................................... 36

Table 16. Traffic data for the SPS-5 experiment .......................................................................... 37

Table 17. Sample materials with project information for the SPS-5 experiment ......................... 38

Table 18. Available monitoring (distress) data............................................................................. 39

Table 19. Number of rutting and IRI surveys conducted at SPS-5 sites....................................... 40

Table 20. Original construction, traffic open, and major rehabilitation dates for SPS-6 sites ..... 42

Table 21. SPS-6 traffic growth ..................................................................................................... 43

Table 22. Sample materials with project information for the SPS-6 experiment ......................... 44

Table 23. SPS-6 available monitoring (distress) data..................................................................... 0

Table 24. Number of rutting and IRI surveys conducted at SPS-6 sites....................................... 47

Table 25. Example demonstrating WD-IRI concept..................................................................... 50

Table 26. Friedman results of fatigue cracking for treatments in wet climates............................ 52

Table 27. Summary of flexible pavement performance results based on Friedman test .............. 55

Table 28. Preferred flexible pavement treatments........................................................................ 58

Table 29. Friedman test results for SPS-3 sites with respect to IRI ............................................. 62

Table 30. Friedman test results of SPS-3 sites with respect to rutting ......................................... 64

Table 31. Friedman test results for SPS-3 sites with respect to cracking based on 

application timing ......................................................................................................................... 65

Table 32. Core sections of the SPS-5 experiment......................................................................... 68

Table 33. Constructed SPS-5 sites for the experimental factorial ................................................ 68

Table 34. Summary of statistical analysis results for SPS-5 site in Arizona................................ 76

Table 35. Long-term average WD-IRI values for SPS-5 sites...................................................... 85

Table 36. Long-term average WD-rutting values for SPS-5 sites................................................ 85

Table 37. Long-term average WD-fatigue cracking values for SPS-5 sites................................. 86

Table 38. Long-term average WD-transverse cracking values for SPS-5 sites............................ 86

Table 39. Long-term average WD-longitudinal cracking values for SPS-5 sites......................... 87

Table 40. Friedman test paired analysis of rehabilitation strategies for short-term 

roughness performance ranking for SPS-5 sites........................................................................... 89
xii

Table 41. Friedman test paired analysis of rehabilitation strategies for long-term 

roughness performance ranking for SPS-5 sites........................................................................... 90

Table 42. Ranking of rehabilitation strategies for roughness, SPS-5 sites................................... 91

Table 43. Ranking of rehabilitation strategies for rutting for SPS-5 sites.................................... 93

Table 44. Ranking of rehabilitation strategies for fatigue cracking at SPS-5 sites....................... 95

Table 45. Ranking of rehabilitation strategies for transverse cracking at SPS-5 sites ................. 95

Table 46. Ranking of rehabilitation strategies for longitudinal cracking at SPS-5 sites.............. 95

Table 47. Criteria for evaluating traffic characteristics of SPS-5 sites......................................... 97

Table 48. Summary of rankings for long-term roughness and rutting performance of SPS-5 

sites in fair surface condition prior to overlay .............................................................................. 98

Table 49. Summary of rankings for long-term roughness and rutting performance of 

SPS-5 sites in poor surface condition prior to overlay ................................................................. 98

Table 50. Summary based on short-term roughness performance of SPS-5 pavement 

structures..................................................................................................................................... 100

Table 51. Summary based on long-term roughness performance of SPS-5 pavement 

structures..................................................................................................................................... 101

Table 52. Summary based on short-term rutting performance of SPS-5 pavement structures... 102

Table 53. Summary based on long-term rutting performance of SPS-5 pavement structures.... 103

Table 54. Summary based on long-term fatigue cracking performance of SPS-5 pavement 

structures..................................................................................................................................... 104

Table 55. Summary based on short-term transverse cracking performance of SPS-5 

pavement structures .................................................................................................................... 105

Table 56. Summary based on long-term transverse cracking performance of SPS-5 

pavement structures .................................................................................................................... 106

Table 57. Summary based on long-term longitudinal cracking performance of SPS-5 

pavement structures .................................................................................................................... 107

Table 58. WD-deflection values at the center of the load for SPS-5 sites.................................. 112

Table 59. Ranking of rehabilitation strategies for structural response at SPS-5 sites................ 113

Table 60. Summary based on structural response (maximum deflection in the wheel path 

of the LTPP lane) of SPS-5 pavement structures....................................................................... 115

Table 61. Core sections of the SPS-6 experiment....................................................................... 122

Table 62. Description of independent studies and performance measures used in the 

analyses....................................................................................................................................... 123

Table 63. SPS-6 sites for the experimental factorial................................................................... 124

Table 64. Short-term average WD-IRI values for SPS-6 sites with JPCP.................................. 125

Table 65. Long-term average WD-IRI values for SPS-6 sites with JPCP.................................. 126

Table 66. Friedman test paired analysis of rehabilitation strategies by IRI short-term 

performance ranking for SPS-6 sites with JPCP......................................................................... 129

Table 67. Friedman test paired analysis of rehabilitation strategies by IRI long-term 

performance ranking for SPS-6 sites with JPCP......................................................................... 130

Table 68. Ranking of rehabilitation strategies for short-term roughness performance 

of SPS-6 sites with JPCP ............................................................................................................ 131

Table 69. Ranking of rehabilitation strategies for long-term roughness performance 

of SPS-6 sites with JPCP ............................................................................................................ 131

Table 70. Summary of rankings for short-term performance of JPCP structures at 

SPS-6 sites .................................................................................................................................. 133
xiii

Table 71. Summary of rankings for long-term performance of JPCP structures at 

SPS-6 sites .................................................................................................................................. 133

Table 72. Summary of rankings for long-term performance of JPCP structures at 

SPS-6 sites in poor surface condition prior to rehabilitation ...................................................... 135

Table 73. Summary of rankings for long-term performance of JPCP structures at 

SPS-6 sites in fair surface condition prior to rehabilitation........................................................ 135

Table 74. Summary of short-term roughness performance of JPCP structures.......................... 136

Table 75. Summary of long-term roughness performance of JPCP structures........................... 137

Table 76. Summary of short-term total cracking performance of JPCP structures.................... 138

Table 77. Summary for long-term total cracking performance of JPCP structures.................... 139

Table 78. Summary of rankings for short-term performance of JPCP composite structures at 

SPS-6 sites .................................................................................................................................. 141

Table 79. Summary of rankings for long-term performance of JPCP composite structures 

at SPS-6 sites............................................................................................................................... 142

Table 80. Performance for short-term roughness of overlaid JPCP structures........................... 143

Table 81. Performance for short-term transverse cracking of overlaid JPCP structures............ 143

Table 82. Performance for long-term transverse cracking of overlaid JPCP structures............. 144

Table 83. Rankings for long-term performance of JPCP structures at SPS-6 sites.................... 146

Table 84. Rankings for short-term performance of JRCP structures at SPS-6 sites................... 150

Table 85. Rankings for long-term performance of JRCP structures at SPS-6 sites.................... 150

Table 86. Rankings for short-term performance of JRCP composite structures at 

SPS-6 sites .................................................................................................................................. 153

Table 87. Rankings for long-term performance of JRCP composite structures at 

SPS-6 sites .................................................................................................................................. 153

Table 88. Rankings for short-term performance of JRCP structures at SPS-6 sites................... 154

Table 89. Rankings for short-term maximum deflection at the center of the lane of JRCP 

composite structures in SPS-6 sections....................................................................................... 158

Table 90. Rankings for long-term maximum deflection at the center of the lane of JRCP 

composite structures in SPS-6 sections....................................................................................... 158

Table 91. Predominant source of data used for preliminary statistical analysis and MEPDG 

performance models verification ................................................................................................ 168

Table 92. Conversion of MEPDG-predicted performance data to LTPP units .......................... 170

Table 93. Summary of individual statistical analysis results for SPS-5 site in Alabama (1) ..... 205

Table 94. Summary of individual statistical analysis results for SPS-5 site in Arizona (4)....... 205

Table 95. Summary of individual statistical analysis results for SPS-5 site in California (6).... 206

Table 96. Summary of individual statistical analysis results for SPS-5 site in Colorado (8)..... 206

Table 97. Summary of individual statistical analysis results for SPS-5 site in Florida (12) ...... 207

Table 98. Summary of individual statistical analysis results for SPS-5 site in Georgia (13)..... 207

Table 99. Summary of individual statistical analysis results for SPS-5 site in Maine (23)........ 207

Table 100. Summary of individual statistical analysis results for SPS-5 site in 

Maryland (24) ............................................................................................................................. 208

Table 101. Summary of individual statistical analysis results for SPS-5 site in 

Minnesota (27)............................................................................................................................ 208

Table 102. Summary of individual statistical analysis results for SPS-5 site in 

Mississipi (28)............................................................................................................................. 209
xiv

Table 103. Summary of individual statistical analysis results for SPS-5 site in 

Missouri (29)............................................................................................................................... 209

Table 104. Summary of individual statistical analysis results for SPS-5 site in 

Montana (30)............................................................................................................................... 210

Table 105. Summary of individual statistical analysis results for SPS-5 site in 

New Jersey (34) .......................................................................................................................... 210

Table 106. Summary of individual statistical analysis results for SPS-5 site in 

New Mexico (35)........................................................................................................................ 211

Table 107. Summary of individual statistical analysis results for SPS-5 site in 

Oklahoma (40) ............................................................................................................................ 211

Table 108. Summary of individual statistical analysis results for SPS-5 site in Texas (48) ...... 212

Table 109. Summary of individual statistical analysis results for SPS-5 site in Alberta (81).... 212

Table 110. Summary of individual statistical analysis results for SPS-5 site in 

Manitoba (83).............................................................................................................................. 212

Table 111. Long-term average WD-IRI values for SPS-5 sites.................................................. 213

Table 112. Long-term average WD-rutting values for SPS-5 sites............................................ 213

Table 113. Long-term average WD-fatigue cracking values for SPS-5 sites............................. 214

Table 114. Long-term average WD-transverse cracking values for SPS-5 sites........................ 214

Table 115. Long-term average WD-longitudinal cracking values for SPS-5 sites..................... 215

Table 116. Preferred flexible pavement treatments.................................................................... 217

Table 117. Flexible pavement example ...................................................................................... 218

Table 118. Selection of design features to improve performance of rehabilitated flexible 

pavements ................................................................................................................................... 220

Table 119. Summary of performance for all SPS-5 sections...................................................... 221

Table 120. Summary of performance for SPS-5 sections in wet zones...................................... 222

Table 121. Summary of performance for SPS-5 sections in dry zones...................................... 223

Table 122. Summary of performance for SPS-5 sections in freeze zones.................................. 224

Table 123. Summary of performance for SPS-5 sections in no-freeze zones ............................ 225

Table 124. Summary of performance for SPS-5 sections in fair surface condition prior to 

rehabilitation ............................................................................................................................... 226

Table 125. Summary of performance for SPS-5 sections in poor surface condition prior to 

rehabilitation ............................................................................................................................... 227

Table 126. Summary of performance for SPS-5 sections with low traffic levels....................... 228

Table 127. Summary of performance for SPS-5 sections with high traffic levels ..................... 229

Table 128. Selection of design features to improve performance of rehabilitated rigid 

pavements (JPCP)....................................................................................................................... 232

Table 129. Summary of performance for all JPCP SPS-6 sections............................................ 233

Table 130. Summary of performance for JPCP SPS-6 sections in wet zones............................ 234

Table 131. Summary of performance for JPCP SPS-6 sections in dry zones............................. 234

Table 132. Summary of performance for JPCP SPS-6 sections in no-freeze zones................... 235

Table 133. Summary of performance for JPCP SPS-6 sections in fair surface condition 

prior to rehabilitation .................................................................................................................. 236

Table 134. Summary of performance for JPCP SPS-6 sections in poor surface condition 

prior to rehabilitation .................................................................................................................. 236
1

EXECUTIVE SUMMARY

The main goal of this project was to use Long-Term Pavement Performance (LTPP) Specific

Pavement Study (SPS) experiment data to assess the impact of different design, construction, and 

rehabilitation features on pavement response and performance for specific site conditions. The 

analysis sought to identify which features could help achieve the best short-term and long-term 

performance and to evaluate the effectiveness of common maintenance practices used for 

flexible and rigid pavements.

PREVENTIVE MAINTENANCE TREATMENTS

The findings of this study are based on the analysis of 81 SPS-3 flexible pavement sites and 

34 SPS-4 rigid pavement sites subjected to different preventive maintenance treatments. Most of 

the flexible pavement sites were monitored for at least 4 years, and approximately 22 percent of 

the sites were monitored for 10 years or more. Most of the rigid pavement sites were monitored 

for at least 4 years.

Of all SPS-3 treatments, thin overlay was the only effective alternative to mitigate and delay the 

progression of roughness; however, it was effective only for pavements in freeze zones, high 

traffic, or poor condition. It was found that thin overlays could only perform better relative to 

roughness compared to other treatments if the International Roughness Index (IRI) level was

higher than 7.34 ft/mi (1.39 m/km). For lower IRI levels, the sections performed similarly and

independent of the treatment, and there was no advantage of applying thin overlays.

Thin overlays slowed the progression of rutting under all circumstances. Chip seal was more 

effective than slurry seal in wet freeze zones but was only marginally more effective in dry 

freeze zones. There were no significant differences among slurry seal, crack seal, and the 

no treatment scenario with respect to rutting, as expected.

Thin overlays and chips seals were more effective than slurry seal and crack seal treatments in 

mitigating fatigue cracking. Thin overlays performed better than most other treatments if the 

pavement was in a freeze zone, in a wet climatic region, initially in poor condition as well as 

subjected to high traffic. For fatigue cracking, thin overlays and chip seals outperformed the 

other treatments, as well as the control section, when the initial cracking was lower than 

232.13 ft2

/mi (13.4 m

2

/km). For higher levels of cracking, every treatment outperformed the 

control section. Specifically, chip seals performed best, followed by thin overlays.

The data analysis from SPS-4 sites indicated that the joint/crack sealed sections and undersealed 

sections performed similarly to the control sections. Also, no meaningful differences were found 

between the two treatments. The analysis was based on a relatively small number of sites that 

had 4 years of performance history that included recorded surveys with undersealing treatment. 

While 34 sites were included in the survey measurements for joint/crack sealed sections, only 

10 had data for undersealed sections.
2

REHABILITATED FLEXIBLE PAVEMENTS

The findings are based on the analysis of 18 SPS-5 rehabilitated flexible pavement sites, with a 

total of 162 core test sections. Most of the sections were monitored for at least 9 years. 

Rehabilitation strategies with milling prior to overlay provided better performance relative to 

IRI levels for all site conditions. Moreover, strategies with thick overlays provided smoother 

pavements for all site conditions. Design alternatives with new or recycled asphalt mixes had 

equivalent performance when used under wet conditions; however, those with recycled asphalt 

mixes provided smoother pavements when used in dry conditions. Traffic level and freeze 

conditions did not affect pavement performance relative to roughness.

With respect to rutting, rehabilitation strategies with thin overlays performed better than thick 

overlays in the short term. The ranking of best strategies was evenly distributed between the two 

mix types (virgin and recycled asphalt). In the long term, the ranking of best strategies was more 

evenly distributed for both thick and thin overlays. Rehabilitation strategies with virgin mixes 

performed better in most of the sites, with the exception of pavements in fair surface condition

prior to rehabilitation and under freeze conditions, which corresponded to 33 percent of all sites. 

Strategies with milling did not improve rutting performance more than alternatives without 

milling. Surprisingly, the level of traffic did not affect rutting performance for the selected 

rehabilitation strategies.

Short-term fatigue cracking performance was not significantly affected by any design feature 

under any site conditions. This finding was expected because overlays are designed to minimize 

fatigue cracking in the short term. Rehabilitation strategies with thick overlays provided better 

performance for fatigue cracking for all site conditions that were evaluated. Strategies with 

milling prior to overlay performed better to mitigate development and propagation of fatigue 

cracking in all site conditions. In regions with a dry climate, alternatives without milling 

performed as well as solutions with milling. Strategies with recycled asphalt mixes were better 

ranked for sites with low traffic when evaluating fatigue cracking.

When comparing the alternatives evaluated and the overall performance for all types of loadassociated distress, overlay thickness was the most influential design feature. As expected, thick 

overlays consistently performed better. The impact of thickness on performance was more 

evident in the long term (more than 5 years) for most of the distresses. The exception was 

rutting, for which no evidence was found, suggesting that either thin or thick overlays provided

less rutted pavements. The analysis of milling prior to overlay suggests that replacing the 

distressed portion of the surface layer improved the performance for the majority of distresses 

commonly observed in flexible pavements. The majority of sites did not show significant 

differences in performance between sections overlaid with virgin and recycled asphalt mixes. 

However, when differences existed, they were mostly in favor of virgin mixes.

For evaluation of structural responses, a maximum falling weight deflectometer (FWD)

deflection measured under the center of the load was used as a structural response indicator. 

Rehabilitation strategies with thick overlays provided the lowest structural response independent 

of site conditions. Strategies with recycled asphalt mix overlays had the smallest structural 

deflections in freeze regions, while those with virgin mixes presented smaller deflections under 
3

no-freeze conditions. Milling prior to overlay did not further impact the structural response. In 

fact, in no-freeze zones, strategies without milling presented lower deflections. When comparing 

wet and dry climates, pavement surface conditions, and traffic levels, none had a significant 

impact on structural responses associated with each rehabilitation alternative.

As expected, rehabilitation strategies with thick overlays had lower maximum deflection values 

compared to alternatives with thin overlays. There were no differences in pavement response 

between strategies with virgin and recycled asphalt mix overlays. Strategies with milling prior 

to overlay did not affect the structural response more than alternatives without milling.

REHABILITATED RIGID PAVEMENTS

Findings for rehabilitated rigid pavements are based on the analysis of 14 SPS-6 rehabilitated 

rigid pavement sections, 8 jointed plain concrete pavement (JPCP) sections, and 6 jointed 

reinforced concrete pavement (JRCP) sections. Most of the sections were monitored for at least 

6 years. The results from the analysis are described separately for JPCP and JRCP sites.

With respect to JPCP structures, rehabilitation strategies with hot mix asphalt (HMA) overlays 

provided significantly smoother pavements than treatments without overlays in both the short 

term and long term. The best alternative to improve roughness performance was crack/break and 

seat with an 8-inch (203-mm) overlay. This same alternative and minimum restoration with a 

4-inch (102-mm) overlay (without crack/break) had statistically equivalent performances and 

were found to be the best alternatives for most of the scenarios evaluated when both short-term

and long-term roughness performance were considered. Crack/break and seat with a 4-inch 

(102-mm) overlay was among the worst alternatives to improve pavement performance relative 

to roughness. Saw and seal provided similar performance to other 4-inch (102-mm) overlays.

Rehabilitation strategies without overlays were the best to mitigate cracking development and 

propagation. HMA overlays over jointed concrete pavements exhibited more surface cracking 

than alternatives without overlays. Crack/break and seat the JPCP had no significant effect in 

reducing the amount of cracking because it performed similarly to the 4-inch (102-mm) overlays 

over noncracked JPCP (with both minimum and maximum restorations). The three alternatives 

without overlays, the no treatment scenario, minimum restoration, and maximum restoration, 

were found to be the best choices to mitigate surface cracking for both short-term and long-term 

performance. Crack/break and seat with 4-inch (102-mm) overlays was the best alternative 

among those that involved overlays. The sawed and sealed joints did not deteriorate significantly 

on these sections, and they effectively controlled reflection cracking.

When evaluating the impact of site conditions, different climate regions and surface conditions 

did not have a significant impact on roughness and total cracking performance for the 

rehabilitation strategies included in the SPS-6 JPCP experiment.

Similar to the findings for JPCP, JRCP strategies with HMA overlays improved roughness 

performance, while strategies without overlays were better at improving total cracking 

development and propagation. Rehabilitation strategies with overlays performed significantly 

better when compared to treatments without overlays. Minimum and maximum restorations with 
4

overlay were the best strategies to improve short-term performance for roughness. For long-term 

performance, the best alternative was the crack/break and seat and the 8-inch (203-mm) overlay.

Rehabilitation strategies without overlays were the best when considering total cracking. Saw 

and seal presented the highest surface cracking among all options evaluated; however, the 

sawing may have had an impact on the monitoring process because this alternative remained in 

reasonably good condition over time. Crack/break and seat the JRCP had no significant effect on 

reducing the amount of cracking because it performed similarly to the 4-inch (102-mm) overlay 

over noncracked JRCP (with minimum and maximum restoration). Sawing and sealing proved to 

effectively control reflective cracking.

Deflections at the center of the slab and at the transfer joints were evaluated in this study. JPCP 

and JRCP structures were evaluated independently. Sections that received HMA overlays were 

monitored like flexible pavements, and deflections at the center of the lane were used in the 

analysis. There were limitations due to the amount of data available, particularly after the data 

were grouped by pavement structure type and surface condition.

The only analysis that provided statistically meaningful results was the evaluation of maximum 

deflection at the center lane of overlaid JRCP structures. The results of that evaluation suggest 

that crack/break and seat significantly increased the overall deflections measured on the 

pavement surface. The remaining treatments provided equivalent maximum deflection 

magnitudes. This was expected since crack/break and seat was an alternative in which the 

concrete slab was reduced to smaller pieces, resulting in lower stiffness. This process increased

the maximum deflection at the center of the slab.

FINDINGS FROM MEPDG ANALYSES

The Mechanistic Empirical Pavement Design Guide (MEPDG) analysis was used to compare 

MEPDG-predicted performance of rehabilitated pavement sections with field measured data to 

verify current calibration for rehabilitated pavement structures.(1)

The roughness models for flexible and rigid pavements provided good estimates for rehabilitated 

sections with and without HMA overlays, and some bias was identified. The model has a 

tendency to underpredict roughness for rigid pavement sections with IRI values above 9.50 ft/mi 

(1.8 m/km). This bias is more characteristic of sections located in dry and freeze regions, and it 

could be addressed by calibrating the models for local conditions.

The rutting model needs further enhancement to more accurately predict permanent deformation 

for HMA overlays over flexible and rigid pavements. The model underpredicts rutting of HMA 

overlays over crack/break and seat restored rigid pavements and overpredicts for HMA overlays 

with saw and seal and for minimum and maximum restorations prior to overlays. 

The cracking models for HMA overlays, particularly the empirical reflection cracking, need 

further enhancement to provide more accurate estimates for rehabilitated sections. The models 

for fatigue cracking (new and reflective) and longitudinal cracking were very accurate for 

estimating consistent and comparable performance with measured values. MEPDG did not 

predict transverse cracking in any of the SPS-5 or SPS-6 sections, even though some transverse 

cracking was measured during surveys.
5

CHAPTER 1. INTRODUCTION

BACKGROUND

Rehabilitation represents the majority of pavement design and construction activity in the 

United States, and the importance of improving the rehabilitation process cannot be 

overemphasized. It is well known that in addition to site conditions (e.g., traffic level, climatic 

conditions, subgrade support, drainage, etc.), the performance of rehabilitated pavement sections 

depends on the condition and design of the existing pavement, including any prerehabilitation 

measures to improve the existing structure. 

Current pavement rehabilitation design procedures are based mainly on the American 

Association for State Highway and Transportation Officials (AASHTO) Guide for Design of 

Pavement Structures that uses limited performance models developed from the AASHTO road 

test in the late 1950s.

(2) The recently developed MEPDG reflects the state of the art in pavement 

design and is considered a significant improvement over the Guide for Design of Pavement 

Structures.

(1,2) However, gaps still exist in the knowledge base, particularly for rehabilitated 

pavements, and the mechanistic design methods still are supported by empirical relationships and 

judgments made by the designer (e.g., determining the representative response properties of a 

surface layer that exhibits a moderate level of distress).

One of the most critical aspects of MEPDG analysis for rehabilitated pavements is the 

characterization of existing pavement conditions prior to rehabilitation. Collection of reliable 

data is imperative because all major decisions regarding existing pavement problems and feasible 

rehabilitation alternatives depend on the accuracy and integrity of these data. 

More importantly, relatively few of the rehabilitation sections from the LTPP program were 

included in the calibration of MEPDG compared to what is currently available. Many of the test 

sections were missing data considered mandatory for the calibration process, and many sections 

in the SPS experiments exhibited little distress because those projects were less than 5 years old. 

Most of this missing data are now available on the LTPP database, and most of the SPS projects 

are at least 10 years old and are starting to exhibit moderate levels of distress. As a result, more 

data are now available and can be used to evaluate the empirical and subjective relationships. 

LTPP performance data can also be used to recommend improvements to the MEPDG 

rehabilitated pavement analysis and design procedures.

Because of continued data collection and improvements over time, LTPP collected information 

on test sections that included a variety of rehabilitation and preservation strategies. Because of

additional data available in the LTPP database, researchers have a better understanding of 

the effects of design and construction features on pavement response and performance of 

rehabilitated flexible and rigid pavements. These data were used in the analyses conducted in this 

study to examine the causes of distress. The information obtained in this study can be used to 

formulate improved models predicting performance of rehabilitated pavements for eventual use 

in MEPDG. In addition, the data collected and assembled during the study can be used to 

improve existing MEPDG calibration and validation. This project also offers a unique 

opportunity to evaluate MEPDG global calibration factors for rehabilitated pavements. 
6

The results of this research enhance existing knowledge related to rehabilitation design in three 

primary areas: (1) the relationship between pavement design and construction features and 

pavement response and performance, (2) guidance for identifying appropriate rehabilitation 

treatments and features for different pavement types, and (3) recommendations for improving 

LTPP data collection activities and future MEPDG model improvements. In addition, preventive 

maintenance alternatives were evaluated in this study, and guidance on selecting effective 

preventive maintenance treatments was developed based on findings from the SPS-3 and 

SPS-4 experiments. 

PROJECT OBJECTIVES

The objectives of this project were to use SPS experiment data to determine the following for 

specific site conditions:

• The impact of the different design, construction, and rehabilitation features on 

pavement response.

• The contributions of these features to achieve different levels of pavement performance.

• The effectiveness of specific maintenance options for new flexible and rigid pavements.

More specifically, these objectives translate into practical conclusions to respond to the 

following questions: 

• Which design/treatment alternative generally performs better for each type of 

existing pavement?

• Which design/treatment alternative performs better in the short term (5 years for SPS-5 

and SPS-6)? 

• Which design/treatment alternative performs better in the long term (10 years for SPS-5 

and SPS-6)? 

• Which design/treatment alternative performs better in each climatic region?

• Which design/treatment alternative performs better for low and high traffic volumes?

• Does preconstruction activity affect design/treatment alternative performance?

• Are MEPDG distress and roughness predictions biased for different traffic levels, 

climatic conditions, or pavement types? 

Practical findings obtained from this study will help highway engineers and managers make 

improved pavement design, construction, and rehabilitation decisions.
7

REPORT ORGANIZATION

This report documents findings from the investigation of the impact of design features on 

pavement response and performance in rehabilitated flexible and rigid pavements. The 

information presented in this report is organized into eight chapters and five appendices.

9

CHAPTER 2. LITERATURE REVIEW

SUMMARY OF FINDINGS FROM PREVIOUS STUDIES

The goal of the literature review was to identify available reports on the response and 

performance of rehabilitated flexible and rigid pavements and to summarize findings relevant to 

the objectives of the current study. 

The Federal Highway Administration (FHWA) and the National Cooperative Highway Research 

Program (NCHRP) have sponsored numerous studies to assess LTPP SPS experiment statuses, 

construction adequacies, and key data element availability (e.g., traffic, subgrade, materials, 

monitoring, etc.) and to conduct preliminary analyses of the collected data. This chapter contains 

a summary of findings from previous investigations related to the effect of key design and 

construction features and site conditions on performance of flexible and rigid rehabilitated 

pavements. The literature review findings are presented in table 1 through table 6.

The literature review findings provide information on the following topics:

• Key measures of pavement performance (distresses, roughness, etc.).

• Previously identified design factors affecting structural responses and 

pavement performance.

• Previously identified construction factors affecting structural responses and 

pavement performance.

• Previously identified site conditions affecting pavement performance.

• Effects of prerehabilitation pavement conditions and treatments on rehabilitated 

pavement responses and performance.

• Optimum timing of preventive maintenance treatments.
10

Table 1. Rehabilitation of flexible pavements.

Publication Major Findings

Current Study Relevance: Performance Measures

Performance of Rehabilitated 

Asphalt Concrete Pavements in the 

LTPP Experiments—Data 

Collected Through February 

1997(FHWA-RD-00-029)(3)

• Nonwheel-path longitudinal cracking was the most prevalent distress in the 

early period (SPS-5).

• Fatigue cracking was the least observed distress (SPS-5).

• Nonwheel-path longitudinal cracks exceeded wheel-path longitudinal cracks 

(general pavement study (GPS)-6).

• GPS-6 data showed that fatigue cracking and longitudinal cracking in the 

wheel path are related. Specifically, the longitudinal cracking in the wheel 

path will propagate or evolve into fatigue cracking with continued 

traffic loading.

Rehabilitation of Asphalt Concrete 

Pavements—Initial Evaluation of

the SPS-5 Experiment (FHWARD-01-168)(4)

• Four performance indicators were established: fatigue cracking, transverse 

cracking, rutting, and IRI.

• Fatigue cracking occurred most frequently on older sections.

• Transverse cracking occurred in all but four of the projects, all of which were 

less than 7 years old.

• Older sections showed moderate severity of transverse cracks even in a

no-freeze climate.

• Test sections with extensive transverse and fatigue cracking had high IRIs.

LTPP Data Analysis: Effectiveness 

of Maintenance and Rehabilitation 

Options Web Document 47 

(Project 20-50(3/4))(5)

• All SPS-5 overlay treatments reduced long-term roughness relative to the 

nonoverlaid sections.

• The rutting data from the SPS-5 and GPS-6B experiments indicated that on 

average, about 0.2 inches (6 mm) of rutting developed in the first year after 

placement of an asphalt overlay of an asphalt pavement.

Design Factors

Performance of Rehabilitated 

Asphalt Concrete Pavements in the 

LTPP Experiments—Data 

Collected Through February 1997

(FHWA-RD-00-029)(3)

• The nominal 5-inch (127-mm) overlays generally showed better performance 

than the nominal 2-inch (5l-mm) overlays, as expected (SPS-5).

• The thicker overlays generally exhibited less cracking distress than the thinner 

ones but had little effect on the occurrence of rutting and no apparent effect on 

roughness (SPS-5).

• The different type of mixtures (virgin or recycled asphalt concrete (AC)) 

appeared to have the least effect on performance of any of the factors included 

in this experiment (SPS-5).

• There was no advantage to using virgin versus recycled mixtures in reducing 

the number of transverse cracks.

• Compared to virgin mixes, recycled AC mixtures resisted longitudinal 

cracking outside the wheel path substantially better in at least five projects.

• Thicker pavement performed better (GPS-6).

• The thickness of the pavement was conversely correlated with the extent of 

nonwheel-path longitudinal cracks (GPS-6).

• Neither the age nor the condition of the pavement before the overlay seemed 

to be critical to cracking extent (GPS-6).

• Thicker overlays resisted rutting slightly better than thinner ones (GPS-6).

• AC mix properties were the most significant factors to limit rutting (GPS-6).

• Thicker overlays offered a slight advantage for roughness (GPS-6).

• GPS-6A (existing AC overlays on AC pavements) data showed that overlay 

designs that provided pavement structure consistent with traffic expectations 

can be expected to perform well for more than 10 years.
11

Rehabilitation of Asphalt Concrete 

Pavements—Initial Evaluation of 

the SPS-5 Experiment (FHWARD-01-168)(4)

• Overlay thickness did not appear to have a strong effect on the occurrence 

of longitudinal cracking in the wheel path and rutting (5 years after 

rehabilitation).

• There was no apparent effect of overlay thickness on roughness based on 

these early observations (5 years after rehabilitation).

• Age of overlay was found to be the leading contributing factor to four of the 

six distresses studied in the SPS-5 experiment (rehabilitation of AC 

pavements): fatigue cracking, rutting, transverse cracking, and initial 

pavement smoothness.

LTPP Data Analysis: Effectiveness 

of Maintenance and Rehabilitation 

Options (Project 20-50(3/4))(5)

• Overlay thickness and preoverlay roughness level were the two factors that 

most influenced the performance of asphalt overlays of asphalt pavements in 

the SPS-5 experiment with respect to roughness and fatigue cracking.

• No significant mean differences were detected in long-term roughness, 

cracking, and rutting between recycled mixes versus virgin mixes.

• No significant mean differences were detected in long-term rutting between 

minimal versus intensive preparation or thin versus thick overlays.

• Preoverlay cracking, age, and accumulated traffic loads significantly 

correlated to the difference in long-term cracking in nonoverlaid versus 

overlaid sections.

Reducing Flexible Pavement 

Distress in Colorado Through the 

Use of PMA Mixtures(6)

• Projects using modified HMA mixtures were found to have lower amounts of 

fatigue cracking, transverse cracking, and rutting.

• The use of modified HMA mixtures was found to extend the service life of 

HMA overlays by about 3 years, a 30 percent increase over the 10-year 

design life.

Construction Factors

Performance of Rehabilitated 

Asphalt Concrete Pavements in the 

LTPP Experiments—Data 

Collected Through February 1997

(FHWA-RD-00-029)(3)

• The test sections that had received intense surface preparation (patching and 

milling) prior to placement of the overlays generally performed better than test 

sections that had not. Reduced fatigue cracking, reduced longitudinal cracking 

in the wheel paths, and reduced transverse cracking were observed on 

intensely prepared sections.

• The amount of transverse cracking was dependent on the original pavement 

condition before overlay placement. The overlays placed on pavements 

classified in good condition exhibited less transverse cracking than on 

pavements classified in poor condition.

• No substantial difference was noted between longitudinal cracking outside the 

wheel paths, rutting, and roughness between the test sections with and without 

milling (SPS-5).

• Rutting was not affected by or related to the condition of the original 

pavement or age of the overlay (GPS-6).

• The condition of the original pavement prior to overlay appeared to have little 

effect on the occurrence of or increase in roughness (GPS-6).

• The amount of traffic affected the growth of roughness (GPS-6).

Rehabilitation of Asphalt Concrete 

Pavements—Initial Evaluation of 

the SPS-5 Experiment (FHWARD-01-168)(4)

• Fewer or shorter transverse cracks occurred on sections that had been milled.

• According to an analysis of variance (ANOVA), milling depth had an 

important effect on the length of transverse cracks.

• The IRI values of the overlay were lower for the overlays placed over 

pavements in the fair category and when the existing surface was milled 

before overlay.
12

LTPP Data Analysis: Effectiveness 

of Maintenance and Rehabilitation 

Options (Project 20-50(3/4))(5)

• Asphalt pavements overlaid when rougher tended to have somewhat 

more initial roughness after overlay than asphalt pavements overlaid 

when smoother.

• There was no significant mean difference in long-term roughness between 

overlays with minimal versus intensive preoverlay preparation.

• No significant mean differences were detected in long-term cracking between 

minimal versus intensive preparation.

Site Factors

Rehabilitation of Asphalt Concrete 

Pavements—Initial Evaluation of 

the SPS-5 Experiment(6)

• The age of the overlay and the climatic factors temperature and moisture had a 

significant effect on fatigue cracking.

• More fatigue cracking occurred on test sections in a climate with less 

precipitation but higher freeze indices.

• Longer transverse cracks occurred on the older pavements in areas with higher 

freeze indices.

• Freeze index had an effect on the length of transverse cracks.

• The age of the overlay and precipitation had an effect on rut depth. Sections 

with increased precipitation had larger rut depths.

• The age of the overlay, condition of the pavement before overlay placement, 

and surface preparation or milling depth were important factors relative to the 

IRI values.

• Milling offered no consistent advantage for resisting longitudinal cracking 

outside the wheel path during the early life of an overlay.

LTPP Data Analysis: Effectiveness 

of Maintenance and Rehabilitation 

Options (Project 20-50(3/4))(5)

• Overlay age and average annual precipitation had a significant effect on longterm rutting.

• A significant correlation was detected between average annual precipitation 

and the difference in long-term rutting in 2-inch (51-mm) versus 5-inch 

(127-mm) overlays.
13

Table 2. Rehabilitation of rigid pavements.

Publication Major Findings

Current Study Relevance: Design Factors

LTPP Data Analysis: Effectiveness 

of Maintenance and Rehabilitation 

Options (Project 20-50(3/4))(5)

• The effectiveness of the rigid pavement rehabilitation treatments in the 

SPS-6 experiment can be ranked from most to least effective with 

respect to IRI, rutting, and cracking as follows: (1) 8-inch (203-mm) 

overlay of cracked/broken and seated pavement, (2) 4-inch (102-mm) 

overlay of either intact or cracked/broken and seated pavement with or 

without sawing and sealing of transverse joints and with minimal or 

intensive preoverlay repair, (3) concrete pavement restoration with 

diamond grinding, full-depth repair, and joint and crack sealing, and 

(4) concrete pavement restoration without diamond grinding but with 

full-depth repair and joint and crack sealing.

• Subdrainage retrofitting, undersealing, and/or load transfer restoration 

techniques did not produce significantly lower long-term roughness 

levels compared to sections that received only diamond grinding, fulldepth repair, and joint and crack sealing.

Rehabilitation of Jointed Portland 

Cement Concrete Pavements: 

Initial Evaluation and Analysis

(FHWA-RD-01-169)(7)

• The rehabilitation techniques in exposed Portland cement concrete 

(PCC) involve restoration techniques other than overlay including fulldepth repair, diamond grinding, joint sealing, and addition of retrofitted 

edge drains.

• If the prerehabilitated section has significant roughness, diamond 

grinding should be considered or the section will retain its roughness. 

Full-depth repairs do not remove significant roughness from a 

jointed concrete pavement by themselves.

• Both routine and premium pavement preparation treatments reduce 

the amount of transverse cracking immediately after rehabilitation. 

Routine preparation treatment includes limited patching, crack repair 

and sealing, and stabilization of joints. Premium preparation 

treatment includes subsealing, subdrainage, joint repair and sealing, 

full-depth repairs with restoration of load transfer, diamond grinding, 

and shoulder rehabilitation.

• Premium pavement preparation with diamond grinding reduces the 

amount of faulting to zero immediately after rehabilitation.

• AC overlay of nonfractured PCC rehabilitation technique involves 

applying varying degrees of preoverlay repairs and placing an 

AC overlay.

• The AC overlay of nonfractured PCC reduces the roughness 

immediately after rehabilitation to a smooth level (5.28 ft/mi

(1.0 m/km)).

• The sections with AC overlay of nonfractured PCC exhibit a faster 

increase in IRI over time than does the fractured PCC.

• The sections with AC overlay of nonfractured PCC exhibit a lower 

increase in IRI over time than do premium preparation nonoverlaid 

PCC sections.

• The routine and premium preparation sections with 4-inch (102-mm)

AC overlays exhibited no reflective cracking within the first year 

after construction.
14

Design Versus Built Variations 

Rehabilitation of Jointed Portland 

Cement Concrete Pavements: 

Initial Evaluation and Analysis

(FHWA-RD-01-169)(7)

• Sites in South Dakota, Arizona, and California did not meet the annual 

precipitation requirement for the climate they were considered for.

• Sites in Tennessee, Oklahoma, and California did not meet the freeze 

index requirement for the climate they were considered for.

• Four sites fell short on the required age criteria.

• A total of 45 percent of sites did not have an AC overlay thickness 

within the designed range.

Performance Measures

LTPP Data Analysis: Effectiveness 

of Maintenance and Rehabilitation 

Options (Project 20-50(3/4))(5)

• The rutting data from the SPS-6 (rehabilitation of jointed PCC 

pavements) and GPS-7B (new AC overlays on PCC pavements) 

experiments indicate that on average, 0.24 inches (6 mm) of rutting 

developed in the first year after placement of an AC overlay of either an 

intact or a cracked/broken and seated concrete pavement. This may be 

due to compaction of the AC overlay by traffic and appears to be 

independent of the overlay thickness, mixture type, preoverlay 

preparation, and preoverlay rutting level.

• No significant differences were detected in cracking based on 8 years of 

data as follows:

• Between minimal (i.e., without milling) and intensive (i.e., with 

milling) preoverlay preparation.

• Between sections with and sections without sawed and sealed joints.

• Between 4-inch (102-mm) overlays with sawed and sealed joints 

versus those over cracked/broken and seated pavements.

• Between 4-inch (102-mm) and 8-inch (203 mm) overlays of 

cracked/broken and seated pavements.

• In 4-inch (102-mm) AC overlays of intact slabs, no significant 

differences were detected in roughness based on 6 years of data

as follows:

• Between minimal and intensive preoverlay preparation.

• Between sections with and without sawing and sealing of 

transverse joints.

• Between overlays with sawed and sealed joints and overlays of 

cracked/broken and seated slabs.

• Among overlays of cracked/broken and seated slabs, the 8-inch 

(203 mm) overlays had significantly lower long-term roughness than 

the 4-inch (102-mm) overlays, as expected.
15

Table 3. Preventive maintenance of flexible pavements.

Publication Major Findings

Current Study Relevance: Design Factors

The LTPP Experiment SPS-3 

5-Year Data Analysis

(FHWA-RD-97-102)(8)

• Structural adequacy did not have a significant effect on the performance of 

SPS-3 treatments.

• Thin overlay had a significant effect in rutting and roughness reduction, while 

other treatment options were either slightly effective or not effective.

LTPP Data Analysis: 

Effectiveness of Maintenance 

and Rehabilitation Options

(Project 20-50(3/4))(5)

• In the SPS-3 thin overlay sections, pavement age was the only factor studied 

that was found to be significantly correlated to the rate of rutting.

• In the SPS-3 crack sealed and chip sealed sections, average annual 

precipitation was the only factor studied found to significantly correlate to the 

rate of rutting.

Analysis Approach

The LTPP Experiment SPS-3 

5-Year Data Analysis

(FHWA-RD-97-102)(8)

• This report provides multiple regression models to develop prediction models 

for cracking, rutting, ride quality, friction, and pavement rating score.

Pavement Maintenance 

Effectiveness (SHRP-H358)(9)

• This study developed a damage modeling approach with an index varying 

between zero and 1. The index is dependent on accumulated traffic/age, 

expected traffic/age to failure, and the shape of the performance trend.

LTPP Maintenance and 

Rehabilitation Data Review

(FHWA-RD-01-019)(10)

• This report documents a survival analysis of SPS-3 sites in the Southern LTPP 

region in 1999 to obtain life expectancy of each treatment, effect of timing, and 

the benefit of treatment to the life span of the pavement.

Treatment Performance

LTPP Maintenance and 

Rehabilitation Data Review

(FHWA-RD-01-019)(10)

• After 6 years of service, sections that received maintenance when in poor 

condition had a probability of failure twice as much as sections initially in fair 

or good condition.

• Sections in fair and good condition had about the same probability of failure.

• The overall median survival times for thin overlay, slurry seal, and crack seal 

were 7, 5.5, and 5.1 years, respectively.

• A median survival time for chip seal could not be determined because fewer 

than 50 percent of these sections had failed at the time of the analysis. Chip 

seals outperformed thin overlay, slurry seal, and crack seal treatments with 

respect to controlling the reappearance of distress.

LTPP Data Analysis: 

Effectiveness of Maintenance 

and Rehabilitation Options

(Project 20-50(3/4))(5)

• In terms of roughness, rutting, and fatigue cracking, the most effective of the 

maintenance treatments was the thin overlay treatment, followed by the chip 

seal treatment, and then the slurry seal treatment.

• The thin overlay treatment was the only one of the four SPS-3 maintenance 

treatments to produce an initial small reduction in roughness, and the only one 

of the four to have a significant effect on long-term roughness, relative to the 

control sections.

• For the SPS-3 test sections, the thin AC overlay treatment was the only one of 

the four treatments (thin AC overlays, chip seals, slurry seals, and crack seals) 

that showed a significant initial effect on rutting. Thin AC overlays also had

the most significant effect on long-term rutting control.

• For rougher pavements, there was some evidence that chip seals and slurry 

seals also had some effect on long-term roughness, rutting, and cracking 

relative to the control sections.

• Crack seals did not have any significance on long-term roughness, rutting, or 

fatigue cracking.
16

Pavement Treatment 

Effectiveness, 1995 SPS-3 

and SPS-4 Site Evaluations 

National Report (FHWARD-96-208)(11)

• The thin AC overlay treatments performed best after 5 years.

• In general, chip seal treatments also performed well. Chip seal performance 

was best in the Southern region, which has a predominantly wet no-freeze 

environment.

• The crack seal treatment performed very well in wet freeze environments 

where the wide shallow sealant reservoir was routed. Crack seal performance 

in the other two regions was not as successful.

LTPP Pavement Maintenance 

Materials: SHRP Crack 

Treatment Experiment 

(FHWA-RD-99-143)(12)

• The most cost-effective treatments for crack seals are usually those consisting 

of rubberized asphalt placed in a standard or shallow-recessed band-aid 

configuration. The standard recessed band-aid method showed the longest 

estimated service life, followed very closely by the shallow recessed band-aid 

method.

• For long-term crack-seal performance (5 to 8 years) under the condition where 

0.1 to 0.2 inches (2.5 to 5.0 mm) of horizontal crack movement occurred, a 

modified rubberized asphalt sealant should be installed in either a standard or a 

shallow recessed band-aid configuration.

Design Versus Built Variations

LTPP Data Analysis: 

Effectiveness of Maintenance 

and Rehabilitation Options 

(Project 20-50(3/4))(5)

• The review of construction problems and deviations in the SPS-3 experiment 

illustrated that more than 40 percent of the sites had problems in the 

application of maintenance treatments, mostly chip seal.

Treatment Timing

Pavement Treatment 

Effectiveness, 1995 SPS-3 

and SPS-4 Site Evaluations 

National Report (FHWA-RD96-208 (11)

• The question of timing cannot be resolved completely from the visual 

observation of the SPS-3 sites, but indications are that earlier application of the 

preventive maintenance treatments provides greater benefits than later 

application.
17

Table 4. Preventive maintenance of rigid pavements.

Publication Major Findings

Current Study Relevance: Performance Measures

LTPP Data Analysis: 

Relative Performance of 

Jointed Plain Concrete 

Pavement with Sealed and 

Unsealed Joints (NCHRP 

Web Document 32 Project 

20-50(2))(13)

• Joint spalling was quantified by several measures, including percentage of 

joints spalled within a pavement section, total length of joint spalling, 

percentage of total joint length spalled, and percentage of individual joint 

length spalled. In addition, weighted measures were used that take into account 

the severity of joint spalling as characterized by low-, medium-, and highseverity joint spalling.

• The faulting measure employed in most previous analyses of LTPP concrete 

pavement performance is average joint faulting, as measured in the outer wheel 

path. In addition, average absolute faulting was introduced in the study to 

account for negative faulting (the approach slab edge being lower than the 

leave slab edge). Absolute average faulting is calculated as the arithmetic 

average of the absolute values of the individual joint faulting measurements.

• An index of weighted sealant damage was developed to quantify overall 

transverse joint sealant condition as a weighted average of the numbers of 

joints within the section with low, medium, and high sealant damage ratings.

Treatment Performance

LTPP Data Analysis: 

Relative Performance of 

Jointed Plain Concrete 

Pavement with Sealed and 

Unsealed Joints (NCHRP 

Web Document 32 Project 

20-50(2))(13)

• Based on 5 years of data collected at the five test sites built in Arizona, 

Colorado, and Utah (all in the dry region), the effects of sealed and unsealed 

joints on spalling were similar.

Pavement Treatment 

Effectiveness, 1995 SPS-3 

and SPS-4 Site Evaluations 

National Report (FHWA-RD96-208)(11)

• SPS-4 sealed joint sections performed better than unsealed sections.

• Unsealed joints also had significantly more joint spalling than the sealed joint 

sections.

• Unsealed joints in the control sections contained significantly more debris than 

sealed joint sections.

Concrete Pavement 

Maintenance Treatment 

Performance Review: SPS-4 

5-Year Data Analysis

(FHWA-RD-97-155)(14)

• No significant differences were identified between the control sections 

(unsealed) and the sealed-joint or undersealed (slab stabilization) sections. This 

observation was based on the 32 SPS-4 sites.

• Based on 5 years of data collected in Arizona, Colorado, Nevada, and Utah, no 

significant differences in initial pavement smoothness were identified among 

the three treatments consisting of sealed, undersealed, and unsealed joints in 

the SPS-4 experiment.

• In the analysis of SPS-4 performance through 1995, no significant differences 

were detected in IRI or joint faulting between sealed-joint and unsealed-joint 

sections.

Design and Construction of 

PCC Pavements, Volume 1: 

Summary of Design Features 

and Construction Practices 

that Influence the 

Performance of Pavements

(FHWA-RD-98-052)(15)

• Neither presence nor type of sealant was found to be significant in the 

regression analysis of JPCP joint faulting in the GPS-3 experiment.

Common Characteristics of 

Good and Poorly Performing 

Pavements (FHWA-RD-97-

131)(16)

• In statistical analyses of GPS-3 performance data, neither sealant presence or 

sealant type was found to be a significant variable in the prediction of dowelled 

or undowelled joint faulting in JPCP.
18

LTPP Pavement Maintenance 

Materials: SPS-4 

Supplemental Joint Seal 

Experiment (FHWA-RD-99-

151)(17)

• A comparison of joint sealant types among the SPS-4 supplemental test 

sections built in Arizona, Colorado, Nevada, and Utah between 1990 and 1995 

showed that silicone seals outperformed the other two treatments for transverse 

joint seals (compression seals and hot pours).

Table 5. Optimal timing of preventive maintenance.

Publication Major Findings

Current Study Relevance: Review of Previous Studies

Optimal Timing of Pavement 

Preventive Maintenance 

Treatment Applications

(NCHRP Report 523)(18)

• Several studies researched the issue of optimum timing of the preventive 

maintenance treatments to achieve best maintenance effectiveness. These 

included earlier studies of SPS-3 and SPS-4 experiments and State 

transportation department studies in Arizona, Iowa, Montana, Texas, and 

South Dakota. None of these studies was successful in identifying the optimum 

timing of preventive maintenance treatments.

Treatment Timing

Optimal Timing of Pavement 

Preventive Maintenance 

Treatment Applications

(NCHRP Report 523)(18)

• A methodology was developed to determine the optimal timing for the 

application of preventive maintenance treatments to flexible and rigid 

pavements. The methodology was based on the analysis of pavement 

performance and costs associated with maintenance treatment. It assessed the 

effectiveness of a particular preventive maintenance treatment in terms of both 

the benefit it provided and the cost required to obtain that benefit. The benefit 

was defined as the quantitative influence on pavement performance as 

measured by pavement condition factors. Condition indicators may be 

expressed by such measures as IRI, present serviceability index, or other 

custom-defined measure of pavement performance. The optimum application 

of a preventive maintenance treatment occurred at the point at which the 

benefit per unit cost was greatest.

SPS-3 and SPS-4 Data Applicability

Optimal Timing of Pavement 

Preventive Maintenance 

Treatment Applications

(NCHRP Report 523)(18)

• One of the case studies conducted under NCHRP Project 14-14 was a review 

of the data from LTPP SPS-3 and -4 experiments.(19) The conclusion from that 

case study was that LTPP data at that time could not be used to conduct the 

analysis of optimal timing. The reasons provided in the report include the 

counterintuitive performance trends, no improvement in performance as a 

result of treatment application, and not enough sections with treatments applied 

at different ages that exhibited the expected trends to support the analysis.
19

Table 6. Data availability for SPS-3, SPS-4, SPS-5, and SPS-6 experiments.

Publication Major Findings

Preliminary Evaluation and 

Analysis of LTPP Faulting 

Data— Final Report

(FHWA-RD-00-076)(20)

• Data analysis was performed to determine the usefulness of joint faulting and 

related data in identifying factors that affect joint faulting. As part of this study, 

an assessment of data availability and data quality was performed for the 

SPS-4 experiment. Data for a total of 422 jointed concrete pavement sections 

were available in the LTPP Information Management System (IMS) database 

at the time of the study. Of these, only 307 sections had records in the faulting 

data table MON_JPCC_FAULT, for a total of 24,108 records.

Rehabilitation of Asphalt 

Concrete Pavements: Initial 

Evaluation of the SPS-5 

Experiment (FHWA-RD-01-

168)(4)

• The data availability and completeness were good overall for the SPS-5 

experiment with two exceptions: traffic and materials test data. These data 

deficiencies should be addressed before a comprehensive analysis of the SPS-5 

experiment is conducted. Both of these data elements must be collected in 

order for the SPS-5 experiment to meet the expectations for calibrating and 

validating mechanistic models.

Rehabilitation of Jointed 

Portland Cement Concrete 

Pavements: SPS-6—

Initial Evaluation and 

Analysis (FHWA-RD-01-

169)(7)

• Data availability and completeness for the SPS-6 experiment are good overall, 

but some data, such as traffic, climatic, and materials data, were not yet 

available in the IMS database. Three of the 14 sites were still relatively new 

and, therefore, did not have much data available. It was believed that the 

information was collected and in the process of being entered into the IMS 

database.

LTPP Data Analysis: 

Effectiveness of Maintenance 

and Rehabilitation Options

(Project 20-50(3/4))(5)

• The data used in this research were the data available at all quality levels in 

LTPP data release 11.5 dated June 13, 2001.

• Efforts to analyze the SPS-3 experiment were hampered by data availability 

problems and the short times in which the treatments had been in service.

• In both the SPS-5 and -6 experiments, the long-term rutting data were so 

erratic that analysis of long-term trends was problematic.

LTPP Maintenance and 

Rehabilitation Data Review

(FHWA-RD-01-019)(10)

• This publication provides a review of maintenance and rehabilitation data 

elements across all the experiments for data completeness and anomalies. The 

test sections were divided into three categories based on surface type: HMA, 

jointed concrete pavement, and continuously reinforced concrete pavement. 

The study was based on the 1999 third quarter LTPP data release. There were a 

total of 757 type sections, including SPS and GPS, for which maintenance and 

rehabilitation techniques have been documented in the database.

21

CHAPTER 3. OVERVIEW OF LTPP MAINTENANCE AND REHABILITATION 

EXPERIMENTS

INTRODUCTION

Data from LTPP SPS-5 and SPS-6 experiments provided information to gain an understanding of 

the effects of design and construction features on pavement response and performance of 

rehabilitated flexible and rigid pavements. In addition, SPS-3 and SPS-4 experiments contain 

pavement performance data collected over the years for the sections subjected to different 

preventive maintenance treatments. The data from these experiments were used as primary data 

source for this study as follows:

• SPS-3: Maintenance treatments for flexible pavements.

• SPS-4: Maintenance treatments for rigid pavements.

• SPS-5: Rehabilitation of AC pavements.

• SPS-6: Rehabilitation of jointed concrete pavements.

SPS-3 and SPS-4 experiments were constructed in 1990 to evaluate the effectiveness of and to 

determine the optimum timing for applying preventive maintenance treatments for flexible and 

rigid pavements. SPS-5 and SPS-6 experiments provide critical information to support pavement 

rehabilitation decisions. The primary objective of these experiments was to develop conclusions 

concerning the effectiveness of rehabilitation techniques and strategies and their contribution to 

pavement performance and service life.

SPS-3 EXPERIMENT

Experimental Design

An experimental design for SPS-3 was developed to help determine the impact of important 

factors on the pavement performance changes caused by selected preventive maintenance 

treatments. Major factors included environment, traffic, subgrade type, structural capacity, and 

condition prior to treatment for the test sections applied to flexible pavements. 

At each site, SPS-3 examined the performance of four preventive maintenance treatments on 

flexible pavement sections: thin overlay, slurry seal, crack seal, and chip seal. The experiment 

design stipulated that the effectiveness of each of the four treatments be evaluated independently. 

The effectiveness of combinations of treatments was not considered; therefore, each test site 

included the following four treated test sections in addition to a control section:

• Thin overlay.

• Slurry seal.
22

• Crack seal.

• Chip seal.

SPS-3 Sections

SPS-3 experiments were initiated at 81 sites in the United States and Canada in 1990 and 1991. 

In many cases, these sites were linked to a GPS section that served as a control section. Most of 

these GPS control sections were from the GPS-1, GPS-2, and GPS-6 experiments.

The sections with thin overlays were nominally 1.5 inches (38.1 mm) thick and were placed 

by State and Provincial highway agencies using their own AC mixes. The slurry seals and chip 

seals were placed by four different contractors, one from each LTPP region. The material 

specifications were the same for all four regions. Crack sealing was executed by four different 

crews—one from each LTPP region. The material used for crack sealing was the same for all 

sites in all regions, but crack sealing application procedures varied.

A summary of SPS-3 sites and conditions is provided in table 7. The climate condition was 

defined based on the freeze index and average rainfall for each site. Sites with an average annual 

rainfall greater than 39 inches (1,000 mm) were classified as wet, and those with less than 

39 inches (1,000 mm) of rain were catalogued as dry. Similarly, the sites with a freeze index 

greater than 140 °F (60 °C) were classified as a freezing climate and those with a freeze index 

less than 140 °F (60 °C) were designated as a no-freeze climate. By March 1, 2006, all SPS-3 

sites were deassigned from the experiment, and data collection stopped. The LTPP database 

contains information for 370 core SPS-3 sections.
23

Table 7. SPS-3 categorization.

Condition at 

Beginning of 

Experiment

Wet

Freeze No-Freeze

Fine Subgrade Coarse Subgrade Fine Subgrade Coarse Subgrade

Low 

Traffic

High 

Traffic

Low 

Traffic

High 

Traffic

Low 

Traffic

High 

Traffic

Low 

Traffic

High 

Traffic

Good

21-A300 26-C300 5-A300 47-B300

24-A300 27-A300 48-F300 48-A300

42-B300 29-B300 48-I300

17-A300 36-B300 28-A300

Fair

19-A300 18-A300 47-A300 47-C300 1-A300

21-B300 26-B300 48-H300 40-C300 1-C300

26-D300 40-B300

48-G300

Poor

51-A300 17-B300 36-A300 48-B300 53-C300 1-B300

87-A300 27-B300 42-A300 12-B300

87-B300 27-D300 89-A300 12-C300

29-A300 26-A300

27-C300

Dry

Good

16-A300 16-B300 48-K300 48-J300 48-D300

49-C300 48-A300 48-M300

16-C300

83-A300

Fair 30-A300 56-A300 32-B300 48-Q300 4-D300

31-A300 6-A300 32-C300 48-E300 48-N300

Poor

20-B300 90-A300 56-B300 53-A300 40-A300 4-A300

8-A300 49-A300 90-B300 4-B300

20-A300 49-B300 4-C300

8-B300 32-A300 48-L300

53-B300

Note: The numbers in each cell represent the State code followed by the site ID. Blank cells indicate that data are not available.

SPS-4 EXPERIMENT

Experimental Design

The purpose of the SPS-4 experiment was to assess the effects of selected rigid pavement 

maintenance treatments, joint/crack sealing, and joint undersealing on performance relative to 

the performance of untreated control sections. The experiment design stipulated that the 

effectiveness of each of the two treatments be evaluated independently at each SPS-4 site. 

The experimental design for the main SPS-4 experiment incorporated the same primary 

experimental factors as in the GPS experiments: climatic zone, subgrade type, and traffic level. 

The original experimental design for SPS-4 included two second-level factors: type of subbase 
24

(granular or stabilized) and condition at the time of treatment (good, fair, or poor). The following 

maintenance treatments were considered:

• Joint and crack sealing.

• Joint undersealing. 

Both JPCP and JRCP were included in the study. The treatment sections on joint/crack 

sealing test sites consisted of one section in which all joints had no sealant and one in which a 

watertight seal was maintained on all cracks and joints. Undersealing was included as an optional 

experiment factor and was performed only on the sections in which the need for undersealing 

was indicated.

As originally designed, the matrix of cells for this experiment could not be filled out because 

some agencies were unwilling to provide sites for the SPS-4 study. A primary concern was the 

use of undersealing as a preventive maintenance treatment. Therefore, the SPS-4 study was 

modified to allow agencies to participate in installation of sections with joint/crack sealing and 

undersealing, joint/crack sealing only, or undersealing only. As a result, the standard experiment 

layout included a test section with silicone sealant and a control section with unsealed joints. In 

addition, separate undersealed test sections were constructed at eight test sites.

The final experiment design for SPS-4 was reduced to the following factors for JPCP:

• Climatic zone: Temperature and moisture.

• Subgrade type: Fine-grained and coarse-grained.

• Subbase type: Granular and stabilized.

For JRCP, only the wet moisture level was considered. 

The SPS-4 experiment included 35 sites in the United States and Canada during 1990 and 

1991 and 1 site in Colorado in 1995. Table 8 shows SPS-4 experimental factorials using 

as-built information.
25

Table 8. SPS-4 experimental design.

Experimental Factors

Freeze No-Freeze

Fine Subgrade Coarse Subgrade Fine Subgrade Coarse Subgrade

Plain

Wet Dense 19-A400 19-B400 40-A400

Stabilized 18-A400 21-A400 39-A400 39-B400 48-A400

Dry Dense

46-A400 6-B400 8-A400 4-A400 6-A400

31-B400 32-A400 48-C400

49-C400 49-D400

49-E400

Stabilized 31-A400 31-C400

Reinforced

Wet

Dense 29-A400 29-B400 5-A400 5-B400

42-A400 42-C400 48-E400

Stabilized 5-C400 28-A400

48-B400 48-D400

Dry Dense 20-B400

Stabilized 20-A400

Note: The numbers in each cell represent the State code followed by the site ID. Blank cells indicate that data are not available.

By March 1, 2006, all SPS-4 sites were deassigned from the experiment. The LTPP database 

contains information for 79 core SPS-4 sections.

SPS-5 EXPERIMENT

Experiment Design

The objective of the LTPP SPS-5 experiment was to help develop improved methodologies and 

strategies for the rehabilitation of flexible pavements. The experiment was designed to evaluate 

common rehabilitation techniques currently implemented in the United States and Canada. The 

factors considered in the experiment included the structural and functional condition of the 

pavement before overlay, the environmental and traffic loading of the test sections, and the 

various treatment applications. 

The SPS-5 experiment provides a means to compare rehabilitated HMA pavement performance 

using different surface preparation intensities, overlay thicknesses, and overlay mixtures. It also 

can be used to determine the appropriate timing of rehabilitation and to evaluate the life-cycle 

cost of different rehabilitation actions. 

The experiment was designed to compare the effect of the following variations on performance 

of rehabilitated pavements:

• Climatic zone: Wet versus dry and freeze versus no-freeze. 

• Existing pavement condition: Fair versus poor. 

• Surface preparation: Intense versus minimum. 
26

• Overlay material: Recycled versus virgin HMA.

• Overlay thickness: Thin 2 inches (51 mm) versus thick 5 inches (127 mm).

Variation of surface preparation alternatives, overlay material, and overlay thickness led to eight 

design combinations at each SPS-5 site (see table 9). One additional section was assigned as a 

control section and did not receive any overlay, except for routine maintenance, for a total of 

nine experimental sections. All test sections were designed to be 500 ft (152.4 m) long over a

fine-grained subgrade with minimum annual traffic over the test sections of 85,000 equivalent 

single axle loads (ESALs).

Table 9. Core sections of SPS-5 experiment.

LTPP ID Overlay Type

0501 Control: No treatment

0502 Thin overlay (2 inches): Recycled HMA mix

0503 Thick overlay (5 inches): Recycled HMA mix

0504 Thick overlay: Virgin mix

0505 Thin overlay: Virgin mix

0506 Thin overlay: Virgin mix with milling

0507 Thick overlay: Virgin mix with milling

0508 Thick overlay: Recycled mix with milling

0509 Thin overlay: Recycled mix with milling

1 inch = 25.4 mm

Final Factorial of SPS-5 Experiment

A total of 18 SPS-5 projects were constructed between 1989 and 1998. The as-built status of the 

SPS-5 design factorial is shown in table 10. All projects are located in the appropriate cells based 

on the actual environmental data. Additionally, all of the cells have at least two projects except 

for the wet no-freeze fair condition and the dry freeze poor condition. A total of 210 test sections 

(162 core test sections plus 48 supplemental sections) were built as part of the SPS-5 experiment.
27

Table 10. Constructed SPS-5 sites for the experimental factorial.

Pavement 

Condition

Soil 

Classification

Climate, Moisture/Temperature

Wet 

Freeze

Wet 

No-freeze

Dry 

Freeze

Dry 

No-freeze

Fair

Coarse/fine Georgia Colorado

Coarse New 

Jersey

Alberta, 

Canada New 

Montana Mexico

Fine Minnesota

Oklahoma

Texas

Poor

Coarse/fine Manitoba, 

Canada California

Coarse Maine

Florida

Alabama Arizona

Fine Maryland

Missouri Mississippi

Note: Blank cells indicate data are not available.

One major deviation from the original SPS-5 experimental plan was the subgrade soil type. 

Originally, the subgrade soils for all SPS-5 projects were supposed to be fine-grained soils. Only 

six of the SPS-5 projects actually had fine-grained soils. Four SPS-5 projects had soils that 

varied between fine and coarse grained. The subgrade soils for the remaining eight SPS-5 

projects were classified as coarse grained.

SPS-6 EXPERIMENT

Experimental Design

The goal of the SPS-6 experiment was to develop improved methodologies and strategies for the 

rehabilitation of concrete pavements. The experiment was designed to investigate the effects of 

the specific experimental rehabilitation design features on pavement performance.

The factors considered in the experiment were overlay thickness, various restoration activities, 

and site conditions such as existing pavement condition, subgrade soil, traffic, and climate. The 

interactions of these factors also were considered.

The SPS-6 experiment included both JPCP and JRCP. The experiment design examined the 

effects of the following factors: 

• Climatic zone: Wet versus dry and freeze versus no-freeze. 

• Pavement condition: Fair versus poor. 

• Type of concrete pavement: JPCP versus JRCP.

• Overlay thickness: 4 inches (102 mm) versus 8 inches (203 mm). 
28

The SPS-6 experimental plans were originally designed to incorporate project sites in all four 

LTPP climatic regions and on both fine- and coarse-grained subgrades. Every project constructed 

as part of the SPS-6 experiment had eight core pavement sections that represented eight different 

rehabilitation alternatives. These rehabilitation alternatives included variations in pavement 

preparation, restoration, AC overlay thickness, and additional treatments (saw and seal and crack 

and seat).

Table 11 lists the eight core experiment sections required for an SPS-6 project. Each section 

varies by a combination of the extent of pavement preparation, other treatments (saw and seal of 

the AC overlay and crack and seat), and the overlay thickness. It was also required that at least 

six of these core sections had 500-ft (152-m) nondestructive performance monitoring areas and 

that two had 1,000-ft (305-m) areas with an additional 49 ft (15 m) on each end for destructive 

testing. In addition, traffic in the test lane should have exceeded 200,000 ESALs per year.

Table 11. Core sections of the SPS-6 experiment.

Strategic Highway 

Research Program 

(SHRP) ID

Overlay 

Thickness (mm) PCC Preparation

0601 — Routine maintenance (control)

0602 — Minimum restoration

0603 102 Minimum restoration

0604 102

Minimum restoration (saw and 

seal AC over joints)

0605 — Maximum restoration

0606 102 Maximum restoration

0607 102 Crack/break and seat

0608 203 Crack/break and seat

1 inch = 25.4 mm

Note: The dashes indicate that the section did not receive an overlay.

Final Factorial of SPS-6 Experiment

The SPS-6 experiment contained 14 sites constructed between 1989 and 1998. Table 12 shows 

the constructed SPS-6 sites in relation to the experiment factorial. A total of 112 core sections 

and 58 State supplemental sections have been constructed for the SPS-6 experiment.
29

Table 12. As-built SPS-6 sites for the experimental factorial.

Pavement 

Type

Pavement 

Condition

Climate/Moisture/Temperature

Wet Freeze

Wet

No-freeze Dry Freeze

Dry 

No-freeze

JPCP Fair Missouri*

Alabama and 

Tennessee

South 

Dakota*

Poor Indiana* Arkansas*

Arizona and 

California

JRCP Fair

Iowa, 

Michigan, and

Pennsylvania Oklahoma* N/A

Poor

Illinois and 

Missouri N/A

* Represents a single additional site that is needed to complete the original design matrix. 

N/A indicates data are not available because there were no JRCP sections in that area of the country.

Note: Blank cells indicate that no section was available at the combination of climate and pavement conditions

for that particular pavement type.

OVERVIEW OF THE LTPP DATA RELEVANT TO THIS STUDY

Information in the LTPP database is divided into the following modules:

• Inventory: Section location, pavement characteristics, and material characteristics.

• Materials testing: Material properties and characteristics from field and laboratory tests.

• Climatic: Temperature, humidity, precipitation, cloud cover, and wind statistics.

• Maintenance: Activities performed since inclusion in the LTPP program.

• Rehabilitation: Major improvements since inclusion in the LTPP program.

• Traffic: Annual traffic summary statistics for a study lane since it was opened to traffic.

• Monitoring: FWD, profilometer, surface distress, skid, and transverse profile.

• Dynamic load response: Only available from the instrumented SPS-1 and SPS-2 test 

sections in Ohio and North Carolina. 

Each of these modules contains tables that provide information on the various design features 

and performance measurements of a particular pavement section. For the data elements 

identified, the LTPP data were examined to determine the extent of availability for all the data 

elements. The most current LTPP data release was used (23d released in January 2009).

Data extracted from the LTPP database were imported to a Microsoft Access® file and stored in 

relational databases so that they could be manipulated and linked together for different analyses.
30

Assessment of SPS-3 Data

Various tables containing data pertinent to the SPS-3 experiment were examined. Table 13

provides a summary of SPS-3 data availability including the location, number of surveys, 

number of treatments, and the observation period for each section. For example, all sections of 

the 1-A300 project were surveyed six times except for the control section, which was surveyed 

five times. The sections receiving thin overlay, slurry seal, and crack seal were treated twice, 

while chip seal and control section were treated once. The difference between the first and the 

last survey was 9 years for all sections except for the control section, which was 8 years. There 

were no data available for the cells left blank. The tables from the LTPP database used for this 

assessment were as follows:

• Inventory: INV_AGE:TRAFFIC_OPEN_DATE.

• IRI monitoring: MON_PROFILE_MASTER.

• AC distress survey monitoring: MON_DIS_AC_REV.

• AC rutting survey monitoring: MON_T_PRF_INDEX_SECTION.

The sample size for the SPS-3 experiment should allow for meaningful conclusions and should 

not just allow comparisons between treatments but also comparisons for the effectiveness of 

treatments for different conditions (e.g., environmental conditions).

Table 13. Data availability for SPS-3 sites.

State CodeSHRP ID

Number of Surveys Number of Treatments Number of Years

Thin OverlaySlurry SealCrack SealSectionControl Chip SealOThin 

verlay

SealSlurry Crack SealSectControl 

ion

Chip SealThin OverlaySlurry SealCrack SealControl SectionChip Seal

1 A300 6 6 6 5 6 2 2 2 1 1 9 9 9 8 9

1 B300 5 5 5 5 5 2 2 1 0 1 7 7 7 7 7

1 C300 8 8 8 8 5 1 1 7 0 3 12 12 12 12 7

4 A300 3 3 3 3 3 1 1 1 1 1 4 4 4 4 4

4 B300 1 1 5 1 2 1 4 2 0 0 9 0

4 C300 4 2 3 3 4 2 2 2 0 1 6 1 3 3 4

4 D300 3 1 2 5 1 1 2 2 2 1 6 0 3 12 0

5 A300 8 8 8 8 1 1 1 1 13 13 13 13

6 A300 6 7 7 7 7 2 3 1 0 1 12 13 13 13 13

8 A300 2 2 2 2 2 1 1 2 0 1 3 3 3 3 3

8 B300 2 2 2 3 2 1 1 1 0 2 0 0 0 3 0

12 A300 6 6 6 6 6 1 1 1 0 1 6 6 6 6 6

12 B300 4 4 4 6 4 1 1 1 1 1 4 4 4 9 4

12 C300 7 6 6 6 6 1 3 4 7 1 7 6 6 6 6

16 A300 5 5 5 6 5 1 1 1 1 1 14 14 14 14 14
31

State CodeSHRP ID

Number of Surveys Number of Treatments Number of Years

Thin OverlaySlurry SealCrack SealSectionControl Chip SealOThin 

verlay

SealSlurry Crack SealSectControl 

ion

Chip SealThin OverlaySlurry SealCrack SealControl SectionChip Seal

16 B300 6 6 6 7 6 1 1 1 0 1 14 14 14 14 14

16 C300 4 4 4 14 4 1 1 1 0 1 7 7 7 7 7

17 A300 8 8 8 8 8 1 1 2 0 1 14 14 14 14 14

17 B300 8 7 7 7 7 2 1 2 1 1 14 14 14 14 14

18 A300 6 7 6 6 6 1 1 1 0 1 4 5 4 4 4

19 A300 4 4 4 4 4 1 1 1 0 1 3 3 3 3 3

20 A300 6 6 6 5 6 2 2 2 0 2 10 10 10 9 10

20 B300 6 6 6 6 6 1 2 2 0 1 7 7 7 7 7

21 A300 4 4 5 4 4 1 1 1 0 1 3 3 4 2 3

21 B300 6 6 5 4 4 1 1 1 0 1 7 7 4 3 3

24 A300 7 7 7 7 7 1 1 1 0 1 8 8 8 8 8

26 A300 4 5 5 5 4 2 1 1 1 1 4 5 5 5 3

26 B300 5 5 5 5 5 1 1 1 1 2 5 5 5 5 5

26 C300 5 5 5 5 5 1 1 1 0 1 5 5 5 5 5

26 D300 5 5 5 5 5 1 1 1 0 1 5 5 5 5 5

27 A300 3 3 3 3 3 1 1 1 0 1 5 5 5 5 5

27 B300 4 4 4 4 4 1 1 1 0 1 5 5 5 5 5

27 C300 4 3 3 3 2 1 1 1 0 1 5 5 5 5 5

27 D300 4 3 1 3 4 2 1 1 0 1 2 4 0 4 5

28 A300 5 5 5 13 5 1 1 2 2 1 8 8 8 11 8

29 A300 8 8 8 8 8 2 2 2 0 1 14 14 14 14 15

29 B300 8 7 7 7 7 1 1 1 0 1 13 13 13 13 13

30 A300 5 5 5 5 5 1 1 1 0 1 8 8 8 8 8

31 A300 5 6 6 6 6 1 1 1 0 1 5 5 5 5 5

32 A300 4 3 3 3 4 1 3 3 1 2 6 6 6 6 6

32 B300 3 3 3 3 3 1 2 1 0 1 6 6 6 6 6

32 C300 2 2 2 4 2 1 1 1 2 1 1 1 1 6 1

36 A300 7 7 7 7 7 2 1 1 1 1 7 7 7 7 7

36 B300 6 6 6 6 6 1 1 1 0 1 7 7 7 7 7

40 A300 5 5 5 5 1 0 0 1 6 6 6 6

40 B300 6 6 6 7 6 1 1 2 0 1 8 8 8 13 8

40 C300 4 4 4 2 4 1 3 1 1 1 4 4 4 3 4

42 A300 7 7 7 7 7 1 1 1 1 1 6 6 6 6 6

42 B300 6 7 6 7 1 4 0 2 8 11 11 11

47 A300 3 3 3 10 1 2 2 3 2 1 4 4 4 16 0

47 B300 4 4 4 6 4 1 1 2 0 1 6 6 6 8 6

47 C300 4 4 4 9 4 1 1 2 4 3 4 4 4 15 4

48 A300 7 7 7 7 1 1 0 0 9 9 9 9
32

State CodeSHRP ID

Number of Surveys Number of Treatments Number of Years

Thin OverlaySlurry SealCrack SealSectionControl Chip SealOThin 

verlay

SealSlurry Crack SealSectControl 

ion

Chip SealThin OverlaySlurry SealCrack SealControl SectionChip Seal

48 B300 9 9 9 8 9 2 2 1 0 3 13 13 13 12 13

48 D300 5 5 4 5 5 2 2 3 3 2 5 5 3 5 5

48 E300 5 4 5 6 4 2 4 3 0 4 4 3 4 4 3

48 F300 7 6 6 5 5 1 2 3 0 3 7 5 5 5 4

48 G300 6 6 6 7 5 1 1 0 0 4 8 8 8 14 6

48 H300 5 5 5 5 5 1 1 2 0 1 6 6 6 6 6

48 I300 6 7 7 7 7 1 1 0 0 1 8 8 8 8 8

48 J300 9 9 9 9 9 2 2 1 1 2 11 11 11 11 11

48 K300 9 9 9 9 9 2 2 0 0 2 8 8 8 8 8

48 L300 8 8 8 8 8 2 2 1 0 2 12 12 12 12 12

48 M300 8 8 8 8 8 2 2 1 2 1 6 6 6 6 6

48 N300 5 5 5 5 5 1 2 5 1 1 2 2 2 2 2

48 Q300 8 8 8 8 8 1 1 0 0 2 11 11 11 11 11

49 A300 4 4 4 5 4 1 1 1 1 1 7 7 7 13 7

49 B300 6 2 6 5 6 2 1 2 2 2 10 2 10 10 10

49 C300 6 6 6 6 6 1 1 1 0 1 11 11 11 11 11

51 A300 7 7 7 7 7 1 1 1 0 1 7 7 7 7 7

53 A300 2 2 2 7 2 1 1 2 1 1 3 3 3 13 3

53 B300 5 5 5 5 5 1 1 2 0 1 9 9 9 9 9

53 C300 4 4 5 4 5 1 1 2 1 1 6 6 6 6 6

56 A300 3 3 3 20 3 1 1 1 2 1 7 7 7 13 7

56 B300 6 6 6 8 6 1 1 1 2 1 11 11 11 12 11

83 A300 7 7 7 8 7 3 3 4 2 2 14 13 13 14 14

87 A300 4 4 4 4 4 1 1 1 0 1 2 2 2 2 2

87 B300 6 6 6 6 1 2 1 0 7 7 7 7

89 A300 6 6 6 6 6 1 1 1 0 1 5 5 5 5 5

90 A300 5 6 4 6 7 1 2 1 5 2 4 5 3 5 5

90 B300 5 6 6 6 6 1 2 2 2 2 8 9 9 9 9

Note: Blank cells indicate data are not available.
33

Assessment of SPS-4 Data

Tables containing data relevant to the SPS-4 experiment were examined. Table 14 summarizes 

data availability for SPS-4 sections, including the location, number of surveys, number of 

treatments, and the observation period for each section. The sample size for SPS-4 was not as 

large as the sample size for the SPS-3 experiment. Moreover, the number of sections with 

undersealing treatment may not lead to statistically significant conclusions for this experiment. 

In this case, the research team will attempt to analyze the individual sections to draw some 

conclusions. The LTPP tables used for this assessment were as follows:

• Inventory: INV_AGE:TRAFFIC_OPEN_DATE.

• IRI monitoring: MON_PROFILE_MASTER, MON_T_PRF_INDEX_SECTION.

• PCC faulting monitoring: MON_DIS_JPCC_FAULT_SECT.

• PCC distress survey monitoring: MON_DIS_JPCC_REV, MON_DIS_

PADIAS42_JPCC.
34

Table 14. Data availability for SPS-4 sites.

State CodeSHRP ID

Number of 

Surveys

Number of 

Treatments

Number of 

Years

Sealing

UndersealingSControl 

ection

SealingUndersealingSectionControl SealingUndersealingSectionControl 

4 A400 4 4 1 0 7 7

5 A400 4 3 1 0 7 7

5 B400 3 3 1 0 6 6

5 C400 3 3 1 0 6 6

6 A400 5 4 5 1 1 0 12 12 12

6 B400 5 5 5 1 1 0 9 9 9

8 A400 4 4 1 1 7 7

18 A400 5 5 1 1 13 13

19 A400 1 1 1 0 0 0

19 B400 2 2 1 0 5 5

20 A400 2 2 1 0 2 2

20 B400 3 3 1 0 5 5

21 A400 3 3 6 0 7 7

28 A400 4 4 1 0 6 6

29 A400 3 3 2 2 4 4

29 B400 4 4 1 0 13 13

31 A400 4 4 1 0 9 9

31 B400 4 4 1 0 9 9

31 C400 4 4 2 0 9 9

32 A400 3 4 3 1 1 0 8 9 8

39 A400 4 4 1 0 11 11

39 B400 3 3 1 1 4 4

40 A400 5 5 5 1 1 0 8 8 8

42 A400 5 5 2 3 9 9

42 C400 6 6 2 1 12 12

46 A400 5 4 4 1 1 1 11 11 11

48 A400 4 4 4 1 1 0 7 7 7

48 B400 8 8 8 1 1 0 11 11 11

48 C400 7 7 7 4 7 4 9 9 9

48 D400 7 7 7 1 1 0 10 10 10

48 E400 7 7 7 1 2 1 10 10 10

49 C400 6 6 1 0 13 13

49 D400 4 4 2 1 9 9

49 E400 6 6 1 0 14 14

Note: Blank cells indicate data are not available.
35

Assessment of SPS-5 Data

The availability of SPS-5 experiment data was assessed in different modules of the LTPP 

database. Available data needed for the analysis of the experiment and the data needed for 

running MEPDG were extracted from different modules and stored in a new database. The 

tables from the LTPP database used to gather information are listed below.

Inventory data were as follows:

• Inventory: INV_AGE:TRAFFIC_OPEN_DATE.

• SPS: SPS5_PMA_CONSTRUCTION:DATE_COMPLETE.

Traffic data were as follows:

• Traffic: TRF_MONITOR_LTPP_LN:TRUCKS_LTPP_LN.

• Traffic: TRF_MON_EST_ESAL:AADT_TRUCK_COMBO.

• Traffic: TRF_MONITOR_LTPP_LN:TRUCKS_LTPP_LN.

Material data were as follows:

• Material_Test: TST_L05B: CONSTRUCTION_NO, LAYER_NO, LAYER_TYPE, 

REPR_THICKNESS.

• Material_Test: TST_L05B: MATL_CODE.

• Inventory: INV_SUBGRADE:AASHTO_SOIL_CLASS –

reference:CODES:AASHTO_SOIL_CLASS.

• Inventory:INV_UNBOUND:AASHTO_SOIL_ CLASS –

reference:CODES:AASHTO_SOIL_CLASS.

Monitoring data were as follows:

• IRI: MON_PROFILE_MASTER.

• Rutting surveys: MON_T_PRF_INDEX_SECTION.

• Cracking surveys: MON_DIS_AC_REV.

Inventory Data

Table 15 presents relevant data on the SPS-5 sites. The sites were constructed between 1965 

and 1982, and they were rehabilitated based on SPS-5 standard specifications between 1989

and 1998.
36

Table 15. Original construction, traffic open, and major rehabilitation dates for 

SPS-5 projects.

State Code

Construction 

Date

Traffic 

Open Date

Rehabilitation

Date

1 06/1976 06/1976 12/1991

4 07/1968 09/1968 05/1990

6 06/1966 06/1966 04/1992

8 10/1974 10/1974 10/1991

12 04/1971 12/1971 04/1995

13 06/1978 06/1978 06/1993

23 11/1972 11/1972 06/1995

24 11/1971 11/1971 06/1992

27 07/1969 07/1969 06/1990

28 09/1973 09/1973 09/1990

29 10/1981 10/1981 09/1998

30 09/1982 09/1982 09/1991

34 11/1968 08/1972 08/1992

35 06/1965 07/1965 09/1996

40 07/1973 07/1973 07/1997

81 06/1977 06/1977 10/1990

83 09/1971 09/1971 09/1989

Traffic Data

Available traffic data for the SPS-5 experiment were reviewed and analyzed. The 

TRF_MON_EST_ESAL and TRF_HIST_EST_ESAL tables include the annual traffic counts 

and estimates of each site for a number of years. Using the data available from these tables, the 

average annual daily truck traffic (AADTT) at rehabilitation date, growth rate, and growth 

method were calculated as presented in table 16. These data are needed to run the 

MEPDG software.
37

Table 16. Traffic data for the SPS-5 experiment.

State

Code

Construction 

Year

Rehabilitation

Year

AADTT at 

Rehabilitation

Date

Growth 

Rate

Growth 

Method

1 1976 1991 500 5.06 Compound

4 1968 1990 530 8.27 Compound

6 1966 1992 2,478 0 —

8 1974 1991 781 12.7 Linear

12 1971 1995 131 14.9 Linear

13 1978 1993 3,689 21.9 Linear

23 1972 1995 600 4.9 Linear

24 1971 1992 615 7.37 Linear

27 1969 1990 188 7.9 Linear

28 1973 1990 1,155 5.65 Compound

29 1981 1998 630 0 —

30 1982 1991 751 3.9 Linear

34 1972 1992 1,530 28.9 Linear

35 1965 1996 3,483 14.4 Linear

40 1973 1997 — — —

81 1977 1990 270 18.6 Linear

83 1971 1989 207 7.6 Linear

— Indicates data are not available.

Some data are missing from the traffic module. For example, the database does not contain any 

traffic data for Oklahoma (State code 40). The axle distribution data are missing from Georgia 

(13) and Missouri (29), and monthly adjustment factors are not available for California (6) and 

Georgia (13).

Material Data

As shown in the sample in table 17, the State code, SHRP ID, layer number, layer type, and 

material description are obtained from the LTPP database. The construction number reveals if 

any major rehabilitation was applied to the site. For example, layer 5 was removed and was 

replaced with two layers of HMA with 1- and 2-inch (25.4- and 51-mm) thicknesses. As a 

result, the construction number is changed to 2. Construction 1 always refers to the original 

construction, and construction 2 is the rehabilitation work. Some sections have received several 

rehabilitation and maintenance treatments.
38

Table 17. Sample materials with project information for the SPS-5 experiment.

STATE_

CODE

SHRP

_

ID

CONSTRUCTION_NOLAYER_NOLAYER_TYPE

Material Description

REPRESENTATIVE

_

THICKNESS (inches)

1 506 1 1 SS Coarse-grained soil: silty sand

1 506 1 2 GS Other (specify, if possible) 5.4

1 506 1 3 GB Crushed gravel 10.6

1 506 1 4 AC

Hot mixed, hot laid AC, dense 

graded 2.2

1 506 1 5 AC

Hot mixed, hot laid AC, dense 

graded 1.5

1 506 2 5 AC

Hot mixed, hot laid AC, dense 

graded 0

1 506 2 6 AC

Hot mixed, hot laid AC, dense 

graded 1

1 506 2 7 AC

Hot mixed, hot laid AC, dense 

graded 2

1 inch = 25.4 mm

Note: The blank cell indicates that there is no thickness for subgrade.

Monitoring Data

Different monitoring data were collected from SPS-5 sites. Distress surveys were obtained and 

summarized from all experiment sections to compare performance. 

Table 18 depicts the number of surveys available for each experiment, the number of treatments 

applied to each experiment, and the number of years the section was under inspection. The table 

summarizes the data available from the MON_DIS_AC_REV table from the LTPP database. As 

shown, distress data have been collected for up to 17 years. Some sites have survey data for up to 

12 inspections.
39

Table 18. Available monitoring (distress) data.

State Code

501 502 503 504

SurveysNumber of TreatmentsNumber of YearsNumber of SurveysNumber of TreatmentsNumber of YearsNumber of SurveysNumber of TNumber of 

reatments

YearsNumber of SurveysNumber of TreatmentsNumber of YearsNumber of 

1 7 2 12 11 2 15 11 2 15 11 2 15

4 2 1 4 10 6 11 11 5 11 11 5 11

6 11 5 14 11 4 14 11 4 14 11 2 14

8 5 3 8 5 3 8 5 3 8 5 3 8

12 10 1 15 10 2 12 10 2 12 10 2 12

13 10 2 12 10 2 12 10 2 12

23 9 3 9 9 3 9 9 3 9 9 3 9

24 10 2 14 12 3 15 12 3 15 11 3 15

27 11 3 15 11 4 15 9 4 15 12 4 15

28 4 1 8 4 2 8 4 2 8 4 2 8

29 4 1 3 7 2 6 7 2 6 7 2 6

30 7 3 13 6 3 13 7 3 13 7 3 13

34 9 2 12 10 2 14 11 2 14 10 2 14

35 6 7 7 9 2 10 9 2 10 9 3 10

40 9 3 9 9 3 9 9 3 9 9 3 9

81 12 3 15 12 3 15 12 3 15 12 2 15

83 6 6 9 10 5 17 10 5 17 10 5 17

State Code

505 506 507 508 509

SurveysNumber of TreatmentsNumber of YearsNumber of SurveysNumber of TreatmentsNumber of yNumber of 

ears

SurveysNumber of TreatmentsNumber of yearsNumber of SurveysNumber of TreatmentsNumber of YearsNumber of SurveysNumber of TreatmentsNumber of YearsNumber of 

1 11 2 15 11 2 15 11 2 15 11 2 15 11 2 15

4 11 6 11 11 6 11 11 4 11 11 5 11 11 6 11

6 11 4 14 11 4 14 11 2 14 11 3 14 11 3 14

8 5 3 8 5 3 8 5 3 8 5 3 8 5 3 8

12 10 2 12 10 2 12 10 2 12 10 2 12 10 2 12

13 10 2 12 10 2 12 10 2 12 10 2 12 10 2 12

23 9 3 9 9 3 9 9 3 9 9 3 9 9 3 9

24 11 3 15 11 2 15 11 2 15 12 3 15 11 2 15

27 11 5 15 12 5 15 12 5 15 11 4 15 11 4 15

28 4 2 8 4 2 8 4 2 8 4 2 8 4 2 8

29 7 2 6 8 2 8 8 2 8 8 2 8 8 2 8

30 7 3 13 7 3 13 7 3 13 7 3 13 7 3 13

34 10 2 14 10 2 14 11 2 14 11 2 14 10 2 14
40

35 9 2 10 9 3 10 9 3 10 9 3 10 8 3 9

40 9 3 9 9 3 9 9 3 9 9 3 9 9 3 9

81 12 2 15 12 2 15 12 2 15 12 2 15 12 3 15

83 10 5 17 10 4 17 8 5 17 9 5 17 7 4 17

Note: Blank cells indicate data are not available.

Rutting data are recorded in the MON_T_PROF_INDEX_SECTION table from the LTPP 

database. Table 19 summarizes the number of rut measurements taken at each site. IRI is another 

monitoring index measured in SPS-5 sites. The IRI measurements are available from the 

MON_PROFILE_MASTER table from the LTPP database. The number of IRI measurements 

taken at each site is presented in table 19. For the sites where there is a considerable difference in 

available data for each experiment within the site, a range of available surveys is specified.

Table 19. Number of rutting and IRI surveys conducted at SPS-5 sites.

State Code Rutting IRI

1 13 11

4 17 14

6 18 15

8 8 10

12 13 9

13 14 9

23 13 10

24 17 15–19

27 12–18 14

28 6 6

29 10–12 5

30 12 16

34 18 17–20

35 12 7

40 13 9

81 14 17

83 13 15

Assessment of SPS-6 Data

Inventory Data

The SPS-6 experiment was conducted in 14 States throughout the United States. The sites were 

originally constructed between 1962 and 1978, and they were rehabilitated according to SPS-6

specifications between 1989 and 1998. 
41

Table 20 shows the States included in the study and their corresponding historic dates. The LTPP 

tables used to gather the information are as follows:

Inventory data include the following:

• Inventory: INV_AGE:TRAFFIC_OPEN_DATE.

• SPS: SPS6_PMA_CONSTRUCTION:DATE_COMPLETE.

Traffic data include the following:

• Traffic: TRF_MONITOR_LTPP_LN:TRUCKS_LTPP_LN.

• Traffic: TRF_MON_EST_ESAL:AADT_TRUCK_COMBO.

• Traffic: TRF_MONITOR_LTPP_LN:TRUCKS_LTPP_LN.

Material data include the following:

• Material_Test: TST_L05B: CONSTRUCTION_NO, LAYER_NO, LAYER_TYPE, 

REPR_THICKNESS.

• Material_Test: TST_L05B: MATL_CODE.

• Inventory: INV_SUBGRADE:AASHTO_SOIL_CLASS –

reference:CODES:AASHTO_SOIL_CLASS.

• Inventory: INV_UNBOUND:AASHTO_SOIL_ CLASS –

reference:CODES:AASHTO_SOIL_CLASS.

Monitoring data include the following:

• IRI: MON_PROFILE_MASTER.

• Rutting survey: MON_T_PRF_INDEX_SECTION (for sections with AC overlay).

• Faulting surveys: MON_DIS_JPCC_FAULT_SECT.

• PCC distress surveys: MON_DIS_JPCC_REV, MON_DIS_PADIAS42_JPCC.
42

Table 20. Original construction, traffic open, and major rehabilitation dates for 

SPS-6 sites.

State Code

Construction 

Date

Traffic 

Open Date Rehab Date

1 05/1966 06/1966 06/1998

4 09/1966 01/1967 10/1990

5 12/1978 01/1979 12/1996

6 08/1977 11/1977 09/1992

17 06/1964 04/1965 06/1990

18 01/1972 01/1974 08/1990

19 11/1965 11/1965 09/1989

26 06/1958 06/1958 05/1990

29 07/1975 10/1975 08/1992

29A 07/1969 08/1969 09/1998

40 11/1962 01/1963 08/1992

42 09/1968 09/1968 10/1992

46 04/1973 10/1973 09/1992

47 06/1964 07/1964 05/1996

Traffic Data

Similar to the SPS-5 experiment, available traffic data for the SPS-6 experiment were obtained 

from the TRF_MON_EST_ESAL and TRF_HIST_EST_ESAL tables, including the annual 

traffic counts and estimates of each site for a number of years. Using the data available from 

these tables, the AADTT at rehabilitation date was obtained. The growth model with a better fit 

and the growth rate are presented in table 21.
43

Table 21. SPS-6 traffic growth.

State

Construction 

Year

Rehab 

Year

AADTT at 

Rehab Date

Growth 

Rate

Growth 

Method

1 66 98 N/A

4 66 90 38 14.47 Compound

5A 78 96 N/A

6 77 92 1,436 0 No growth

17 64 90 391 11.25 Linear

18 72 90 110 59 Linear

19 65 89 441 11.11 Linear

26 58 90 476 1.2 Linear

29 75 92 637 4.35 Compound

29A 69 98 62 12.9 Linear

40 62 92 630 2.9 Compound

42 68 92 1,594 2.5 Linear

46 73 92 121 5 Linear

47 64 96 N/A

N/A indicates data are not available.

Note: Blank cells indicate missing traffic data.

Traffic data are missing from Alabama (1), Arkansas (5), and Tennessee (47). The axle 

distribution data were missing from Missouri (29), Oklahoma (40), and Pennsylvania (42). Also, 

Missouri (29) is missing axle per truck data from the database.

Material Data

Pavement structure information for SPS-6 sites and the sequence of the changes made to each 

site over time were extracted from the LTPP database. Table 22 provides a sample table with 

project information.
44

Table 22. Sample materials with project information for the SPS-6 experiment.

State 

Code

SHRP 

ID

Construction 

Number

Layer 

Number Layer Type

Material 

Description

Representative

Thickness 

(inches)

1 0606 1 1

Subgrade 

(untreated)

Coarse-grained soil: 

clayey gravel

1 0606 1 2

Unbound 

(granular) 

layer Crushed stone 6

1 0606 1 3

Portland 

cement 

concrete layer PCC (JPCP) 10.3

1 0606 2 1

Subgrade 

(untreated)

Coarse-grained soil: 

clayey gravel

1 0606 2 2

Unbound 

(granular) 

layer Crushed stone 6

1 0606 2 3

Portland 

cement 

concrete layer PCC (JPCP) 10.3

1 0606 2 4 AC

Hot mixed, hot laid 

AC, dense graded 2.2

1 0606 2 5 AC

Hot mixed, hot laid 

AC, dense graded 1.3

1 inch = 25.4 mm

Note: The blank cell indicates that there is no thickness for subgrade.

Monitoring Data

Table 23 summarizes the basic information about the monitoring data collected during the SPS-6 

study. Distress surveys were obtained and summarized from all experiment sections to compare 

performance. The table shows the number of surveys available for each experiment, the number 

of treatments applied to each experiment, and the number of years the section was inspected. 
Table 23. SPS-6 available monitoring (distress) data.

State 

Code

601 602 603 604

No. of 

Surveys

No. of 

Treatments

No. of 

Years

No. of 

Surveys

No. of 

Treatments

No. of 

Years

No. of 

Surveys

No. of 

Treatments

No. of 

Years

No. of 

Surveys

No. of 

Treatments

No. of 

Years

1 9 1 8 9 1 8 9 1 8 9 1 8

4 1 0 0 1 1 0 7 3 11 7 2 11

5 10 6 11 10 4 11 10 1 11 11 1 11

6 10 6 12 11 4 12 11 5 12

17 10 6 12 10 8 12 11 4 15 11 5 15

18 2 0 1 9 4 14 10 4 14 11 3 14

19 6 6 15 6 9 15 8 6 15 8 5 15

26 3 0 3 3 1 3 4 1 6 4 1 6

29 6 7 9 6 9 9 9 2 13 9 2 13

29A 8 3 8 8 2 8 8 2 8 7 2 6

40 13 5 15 13 2 15 13 3 15 13 3 15

42 11 2 15 11 1 15 11 2 15 11 2 15

46 10 7 14 9 3 14 9 3 14 9 3 14

47 8 3 8 8 4 8 8 1 8 8 1 8

State 

Code

605 606 607 608

No. of 

Surveys

No. of 

Treatments

No. of 

Years

No. of 

Surveys

No. of 

Treatments

No. of 

Years

No. of 

Surveys

No. of 

Treatments

No. of 

Years

No. of 

Surveys

No. of 

Treatments

No. of 

Years

1 9 1 8 9 1 8 9 5 8 9 1 8

4 2 1 0 7 2 11 7 3 11 7 3 11

5 10 4 11 10 1 11 10 1 11 10 1 11

6 8 7 12 11 4 12 11 4 12 11 3 12

17 10 7 12 11 9 15 11 6 15 11 3 15

18 8 4 13 10 4 14 11 4 14 10 4 14

19 6 10 15 8 4 15 9 5 15 10 4 18

26 3 1 3 4 1 6 4 1 6 4 1 6

29 6 9 9 9 1 13 2 2 3 9 3 13

29A 7 2 6 9 2 8 8 2 8 7 1 6

4

5
State 

Code

605 606 607 608

No. of 

Surveys

No. of 

Treatments

No. of 

Years

No. of 

Surveys

No. of 

Treatments

No. of 

Years

No. of 

Surveys

No. of 

Treatments

No. of 

Years

No. of 

Surveys

No. of 

Treatments

No. of 

Years

40 13 9 15 13 3 15 13 6 13 13 2 15

42 11 1 15 11 1 15 11 1 15 11 1 15

46 9 4 14 9 3 14 9 5 14 9 4 14

47 8 6 8 8 1 8 6 1 6 8 1 8

4

6
47

Rut measurements were collected several times from the SPS-6 sites. Table 24 summarizes the 

number of surveys conducted for each site. The number of surveys available from the database 

was not the same for all the sections of a site. Therefore, a range is presented for most of the 

sites. The number of IRI measurements available from the experiment also is provided.

Table 24. Number of rutting and IRI surveys conducted at SPS-6 sites.

State 

Code

Rutting 

Surveys

IRI 

Surveys

1 11 8

4 11 3–14

6 7–17 11

17 7–18 9–12

18 6–17 2–17

19 12–16 9–12

26 3–8 4–9

29 3–16 4–11

40 5–14 9–10

42 4–14 14–16

46 6–16 10–11

47 2–11 4–7

5A 1–12 8–10

29A 3–11 6

49

CHAPTER 4. ASSESSMENT OF MAINTENANCE ALTERNATIVES

To evaluate the effectiveness of preventive maintenance treatments, the performance of 

pavement sections with various treatments was compared to the performance of pavement 

sections with different treatments as well as to the control section. To make these comparisons 

possible, it was necessary to select parameters that reflected the actual performance of the 

pavement over the monitoring period of the experiment. Performance indicators were based on 

pavement distresses collected during the surveys, and this chapter describes the parameter 

selected for the analysis carried out in this study. 

PERFORMANCE INDICATORS USED IN PREVIOUS STUDIES

Several performance indicators have been utilized in past studies of LTPP experiments. The 

literature review conducted in this study identified the following list of indicators and the study 

where they were applied:

• Most recent survey measures of distress.(5)

• Expert task group field reviews of distress.(8)

• Evaluation of distress trends (distress versus time curves).(4,7,8)

• Distress regression models.(8)

• Area under/above condition indicators (rut, cracking, and friction).(18)

• Maximum distress at the latest age/survey.(21)

• Area under the performance curve.(21)

• Area under the performance curve normalized to the latest age.(21)

• Performance index.(21)

• Distress level immediately after rehabilitation/treatment.(7)

• Average distress over the survey period.(4,7)

• Joint deflection.(13)

• Weighted length of joint spalling.(13)

• Weighted sealant damage.(13)

• Average absolute faulting. (13)

• Mean area under the pavement profile.(5)
50

PERFORMANCE INDICATOR IMPLEMENTED IN THIS STUDY

Several parameters were evaluated, and the indicator selected for this study was the weighted 

distress (WD) or average distress value over the total survey period, as calculated using the 

following equation presented in figure 1:

∑

∑

=

+

−

=

+ + × +

= n

i

i

n

i

i i i

P

D D P

WD

0

1

1

0

1 1

2

( )

Figure 1. Equation. Weighted distress.

Where:

WD = Weighted distress average value over the total survey period.

Di = Distress value measured at the ith survey.

Pi + 1 = Period (in years) between survey i and survey i + 1 (i = 0 is the initial distress level 

immediately after the treatment).

n = Total number of surveys for the section. 

The weighted average represents the total normalized area (per year) under the distress versus 

time curve. As such, it is a measure of pavement performance relative to the specific distress 

over the entire monitoring period. The normalization to total time the section was in service 

provides a means for comparing survey periods that may be different, which allowed the 

comparison of performance for both the short term and long term. 

A hypothetic example of the calculations is provided below. Table 25 and figure 2 contain IRI 

measurements for a site surveyed for 8 years. The sections were surveyed five times. WD-IRI 

represents the weighted average value of IRI measured for five surveys conducted in different 

years. In an 8-year analysis period, thin overlay outperformed other treatments with a WD-IRI 

value of 4.80 ft/mi (0.91 m/km). Slurry seal presented the worst performance, with a WD-IRI of 

7.66 ft/mi (1.45 m/km) over the 8-year period. It can be noted that sections had similar IRI when 

the experiment was initiated.

Table 25. Example demonstrating WD-IRI concept.

Time

(years)

Control 

Section Thin Overlay Slurry Seal Crack Seal Chip Seal

IRI 

(m/km) WD

IRI 

(m/km) WD

IRI 

(m/km) WD

IRI 

(m/km) WD

IRI 

(m/km) WD

0 0.81 0.00 0.81 0.00 0.81 0.00 0.83 0.00 0.81 0.00

2 1.00 0.91 0.84 0.83 1.11 0.96 1.16 1.00 0.86 0.84

3 1.21 0.97 0.84 0.83 1.41 1.06 1.25 1.07 0.90 0.85

5 1.51 1.13 0.90 0.85 1.71 1.26 1.30 1.15 0.89 0.87

8 2.02 1.37 1.11 0.91 1.81 1.45 1.60 1.26 1.71 1.03

1 ft = 0.305 m

1 mi = 1.61 km
51

1 ft = 0.305 m

1 mi = 1.61 km

Figure 2. Graph. Example of IRI trends to calculate WD-IRI.

STATISTICAL ANALYSIS APPROACH

The statistical test selected for the analysis was the Friedman test, a nonparametric test 

(distribution-free) used to compare paired observations on a subject. It is also called a 

nonparametric randomized block analysis of variance. Unlike the parametric repeated measures 

ANOVA or paired t-test, this test makes no assumptions about the distribution of the data 

(e.g., normality). In addition, unlike the t-test, the Friedman test can be used for multiple 

comparisons, as is the case for the SPS-3 and SPS-4 experiments with four and two different 

types of treatments, respectively, in addition to the control section. The Friedman test, like many 

nonparametric tests, uses the ranks of data rather than their raw values. The test statistic for 

the Friedman test is a chi-square with n - 1 degrees of freedom, where n is the number of 

repeated measures. 

The performance of pavement sections with preventive maintenance treatments was compared to 

the performance of similar pavements without the treatment (control sections) as well as between 

the different treatment types. The Friedman test was applied for all design categories and for 

each distress. The values used were the WDs normalized for the analysis period. The results 

indicated whether a statistically significant difference existed between any pair of treatments. 

Table 26 provides an example of Friedman test results of the SPS-3 experiment for wet climates. 

A total of 41 sites were located in wet climatic regions with fatigue cracking measurements 

available for all treatments with 4 degrees of freedom. Based on the test results, thin overlay and 

chip seal sections had the lowest sum of ranks, and slurry seal and control sections had the 
52

highest sum of ranks. A lower sum of ranks indicated better performance because distresses were 

generally lower over the monitoring period. Analysis results indicated that the difference in 

performance of thin overlay and chip seal sections compared to slurry seal and the control 

sections was significant. Only chip seal performed significantly better than crack seal. The 

difference between other treatments was not significant. The Friedman test value was 49.12 

with p < 0.0001.

Table 26. Friedman results of fatigue cracking for treatments in wet climates.

Thin 

Overlay

Slurry 

Seal

Crack 

Seal

Control 

Section

Chip 

Seal

Sum of ranks 99.50 156.50 137.50 148.50 73.00

Median 2.30 20.40 5.80 12.70 0.00

Average of ranks 2.43 3.82 3.35 3.62 1.78

Standard deviation 22.64 54.15 63.26 103.31 8.04

Comparisons Difference p-Value

Thin overlay versus slurry seal 57 < 0.05

Thin overlay versus crack seal 38 not significant

Thin overlay versus control 

section 49 < 0.05

Thin overlay versus chip seal 26.5 not significant

Slurry seal versus crack seal 19 not significant

Slurry seal versus control section 8 not significant

Slurry seal versus chip seal 83.5 < 0.05

Crack seal versus control section 11 not significant

Crack seal versus chip seal 64.5 < 0.05

Control section versus chip seal 75.5 < 0.05 

FLEXIBLE PAVEMENTS MAINTENANCE

The effectiveness of treatments in prolonging flexible pavement life was evaluated using two 

load-associated distresses (fatigue cracking and rutting) and ride quality as measured in surveys 

conducted for the SPS-3 experiment. Performance was evaluated as the deterioration measured 

by fatigue cracking, rutting, and IRI.

Figure 3 through figure 5 illustrate box-whisker plots of WD index for fatigue cracking 

(WD-fatigue), rutting (WD-rutting), and IRI (WD-IRI). The boundaries of the box present lower 

and upper quartiles, and the middle line is the median. The whisker marks the minimum and 

maximum limits of WD. Only surveys providing distress measurements for all treatments were 

used to draw the graphs, and some outliers were excluded.

As shown in figure 3, thin overlay and chip seal sections exhibited lower fatigue cracking levels 

compared to slurry seal, crack seal, and the control section. Chip seal also presented the smallest 

minimum/maximum range. Sections that were treated with crack seal had lower WD-fatigue 

compared to slurry seal and the control section. The slurry seal alternative seemed to be less 

effective in mitigating the progression of fatigue cracking over the monitored period.
53

1 ft2 = 0.093 m2

Figure 3. Graph. Box-whisker plot for WD-fatigue of SPS-3 sections.

Rutting levels presented considerable differences between sections that were treated with thin 

overlay and other sections (see figure 4). Thin overlay was effective in reducing rutting 

immediately after the treatment, and, as a consequence, those sections presented a lower level of 

rutting over the analysis period. Although chip seal marginally outperformed the rest of the 

treatments, it provided little advantage over the remaining treatments.

1 inch = 2.54 cm

Figure 4. Graph. Box-whisker plot for WD-rutting of SPS-3 sections.

A similar conclusion was found in terms of IRI performance (see figure 5). As expected, thin 

overlay was the most effective maintenance option in mitigating IRI over the years. This type of 
54

treatment was the most effective in reducing initial roughness immediately after treatment rather 

than providing a significant structural improvement of the pavement section. 

1 ft = 0.305 m

1 mi = 1.61 km

Figure 5. Graph. Box-whisker plot for WD-IRI of SPS-3 sections.

Although the box-whisker plots showed some indication of which treatments performed best, the 

Friedman test was applied to the WD indexes to identify if the differences were statistically

significant. Results from the test runs for all design categories are summarized in table 27.

. 
55

Table 27. Summary of flexible pavement performance results based on Friedman test.

Condition

Fatigue Cracking Rutting IRI

TH SL CR CO TH SL CR CO TH SL CR CO

Temperature

Freeze

SL TH TH TH

CR TH TH

CO TH TH

CH CH CH CH TH CH TH

Nofreeze

SL TH

CR TH

CO TH

CH CH CH CH TH

Precipitation

Wet

SL TH TH

CR TH

CO TH TH

CH CH CH CH TH

Dry

SL TH

CR TH

CO TH

CH CH CH CH CH

Subgrade

Coarse

SL TH TH

CR TH

CO TH

CH CH CH CH TH TH

Fine

SL TH

CR TH

CO TH TH

CH CH CH CH TH

Traffic

High

SL TH TH

CR TH TH

CO TH TH TH

CH CH CH CH TH TH

Low

SL TH CO

CR TH

CO CO

CH CH CH CH TH

Pavement 

Condition

Poor

SL TH TH TH

CR TH TH TH

CO TH TH TH

CH CH CH CH TH

Fair

SL TH

CR TH

CO TH

CH CH TH

Good

SL TH

CR TH

CO

CH CH

TH = thin overlay, SL = slurry seal, CR = crack seal, CO = control, and CH = chip seal.

Note: Blank cells indicate that there is no significant difference between the two treatments being compared.
56

To compare the treatments, design conditions from the left side of the table and a distress from 

the top of the table should be selected. Then, one of the treatments from the third column and 

another one from the top are selected for comparison. If the intersecting cell is empty, there is no 

significant difference between the two treatments. Otherwise, the cell is filled with the treatment 

that performed better. For example, the first cell on the left is filled with “TH,” indicating that 

thin overlay is significantly superior to slurry seal with respect to fatigue cracking in 

freezing climates.

The main objective of the SPS-3 experiment was to provide data to identify the effects of major 

design factors on the performance of maintenance alternatives. Specifically, the experiment 

was intended to identify whether different climate conditions, subgrade material, traffic level, 

or initial pavement condition affect the choice of a preferred treatment. Therefore, the results 

from different design factors were compared for each type of distress and summarized in the 

following sections.

Fatigue Cracking

Temperature had a significant effect when comparing thin overlay with slurry seal and the 

control section. Thin overlays outperformed both treatments in freeze zones; however, 

temperature did not have an additional impact on the performance of other alternatives since chip 

seal outperformed slurry seal, crack seal, and the control section in both freeze and no-freeze 

zones. The same conclusion is valid for precipitation. Thin overlay outperformed slurry seal and 

the control section only in wet regions. There were no other significant differences in the 

performance of other treatments with respect to precipitation.

Subgrade type affected the performance of thin overlays relative to other treatments. Thin 

overlay generally performed better than slurry seal when the subgrade was comprised of coarse 

material. Traffic affected the performance of the thin overlay when compared to slurry seal and 

the control section. Under higher traffic levels, the performance of thin overlays prevailed over 

both the control and slurry seal sections; however, differences between thin overlays and chip 

seal or crack seal were not statistically significant. 

The performance of maintenance treatments with respect to the initial pavement condition was 

evaluated to identify the importance of timing. Timing of treatment application impacted

pavement performance. When the pavement was in poor condition, thin overlay performed better 

than slurry seal, crack seal, and the control section. Chip seal also outperformed crack seal,

with a significant statistical difference under such conditions. It is important to note that the 

comparisons were based on fatigue cracking surveys. In this case, chip seals in general may only 

mask the cracks and mislead survey measurements rather than actually correct the distress to 

improve performance.

Rutting

Generally, thin overlays performed better for rutting when compared to other treatment 

alternatives and the control section. Temperature was one of the factors that affected 

performance when comparing chip seal and slurry seal sections. In freezing zones, chip seal 

outperformed slurry seal. In addition to temperature, only precipitation was statistically 
57

influential in rutting when comparing chip seals with thin overlays and slurry seals. Under wet 

conditions, thin overlays outperformed chip seal, and under dry conditions, chip seal performed 

better than slurry seal. 

Under higher traffic levels, thin overlays performed better than the control section; however, in 

low traffic, the differences were not statistically significant. Surprisingly, slurry seal performed 

worse than the control section under low traffic level conditions with respect to rutting. No other 

design factor affected the performance of the pavement sections in a statistically significant way 

with respect to rutting.

IRI

Temperature condition was an important factor in defining maintenance activities concerning 

surface smoothness. Thin overlays performed significantly better than slurry seals, crack seals, 

and chip seals in freezing zones. In no-freeze zones, there were no significant differences among 

treatments and the control section with respect to IRI. Precipitation did not affect performance 

among the flexible pavement treatments evaluated. There was no significant difference among 

treatments under dry and wet conditions. 

In pavements with coarse subgrade, thin overlay was superior to chip seal. In pavements with 

fine subgrade, thin overlays outperformed the control section only. The comparison of the 

treatments did not show significant differences in any other combination.

Traffic also affected the performance of maintenance treatments when roughness was

considered. Thin overlays outperformed crack seals, chip seals, and the control section in roads 

under higher traffic levels. In low traffic roads, there were no significant differences among the 

treatments or the control section.

Pavement initial condition affected the performance of the treatments. Thin overlays performed 

better than crack seals, chip seals, and the control section if the condition of the pavement was 

poor. There was no significance difference identified when the pavement condition was good.

Table 28 summarizes the results of the statistical analysis for each distress type evaluated. All 

four treatments were considered. When pavement performance for the treatment was statistically 

significant compared to the control section, the treatment code was depicted in the cell. If no 

statistical significance was identified between the treatments and the control section, the cell was 

left empty. In some cases, two treatments significantly outperformed others, shown as 

“2d choice” in the table. For example, in freeze zones and with respect to fatigue cracking, 

chip seal is presented as the first choice and thin overlay is shown as the second choice.
58

Table 28. Preferred flexible pavement treatments.

Distress

Preferred 

Treatment

Temperature Precipitation Subgrade Traffic Pavement Condition

Freeze

Nofreeze Dry Wet Fine Coarse Low High Good Fair Poor

Fatigue 

Cracking

1st choice CH CH CH CH CH CH CH CH CH CH TH

2d choice TH — — TH — TH — TH — — CH

Rutting 1st choice TH TH TH TH TH TH TH TH TH TH TH

2d choice CH — CH — — — — — — — —

Roughness 1st choice TH None None None TH TH None TH None None TH

CH = chip seal and TH = thin overlay.

— Indicates that no data are available.

Note: None means that neither treatment alternative performed significantly better than the control section. CH is not included as an option for 

roughness because it was never the preferred treatment method.

RIGID PAVEMENTS MAINTENANCE

The effectiveness of the treatments in prolonging the pavement life of rigid pavements was 

evaluated using three types of distresses and the ride quality measurements available for the 

SPS-4 experiment. Edge faulting, wheel-path faulting, longitudinal cracking, and roughness 

measurements were chosen as the basis for the performance assessments. Figure 6 through 

figure 9 illustrate box-whisker plots of WD for these performance indicators.

As shown in figure 6 and figure 7, the experiment showed similar trends for both edge faulting 

and wheel-path faulting. Joint/crack sealing performed better by showing lower averages and 

minimum/maximum ranges as compared to the undersealing treatment and the control section. 

Undersealing treatments resulted in the highest WDs and greater performance variability with 

respect to edge faulting and wheel-path faulting.
59

1 inch = 25.4 mm

Figure 6. Graph. Box-whisker plot for WD-edge faulting of SPS-4 sections.

1 inch = 25.4 mm

Figure 7. Graph. Box-whisker plot for WD-wheel-path faulting of SPS-4 sections.

With respect to limiting the propagation of linear cracking, undersealing treatment performed 

better than the joint/crack sealing and the control section (see figure 8). Joint/crack seal was also 

better than the control section. Both treatments showed smaller variability as compared to the 

control section.
60

1 ft = 0.305 m

Figure 8. Graph. Box-whisker plot for WD-linear cracking of SPS-4 sections.

The performance of sections treated by joint/crack sealing was close to that for the control 

section with respect to IRI (see figure 9). However, the control sections presented lower 

variability in roughness performance. Sections that were undersealed performed worse than the 

sealed and control sections.

1 ft = 0.305 m

1 mi = 1.61 km

Figure 9. Graph. Box-whisker plot for WD-IRI of SPS-4 sections.

Although the box charts showed indications that joint/crack sealing may be a more effective 

treatment, the differences were not significant when running the consolidated analysis using the 
61

Friedman test. The analysis also was extended to evaluate the impact of specific site conditions. 

The SPS-4 test sites were grouped according to precipitation, temperature, structure, base 

material, and subgrade type. Only 10 sites contained measurements from sections treated by 

undersealing as compared to 34 sites for joint/crack sealed and control sections. As such, the 

Friedman test was performed in two stages. In the first stage, only the 10 sites with reported 

measurements for all 3 sections were considered. In the second stage, the undersealing treatment 

was excluded from the analysis. As a result, the existence of statistical differences between the 

crack/joint sealing and control sections was investigated using the data from 34 sites.

The results from both analyses showed no statistically significant differences in performance 

between the treatments and the control section, indicating that benefits from joint/crack sealing 

and undersealing may be relatively small; however, the sample size for sections with 

undersealing was small, which may affect the meaningfulness of the results.

MAINTENANCE TREATMENT APPLICATION TIMING 

Timing of treatment application is an important factor in achieving the best treatment 

performance. Optimum timing of treatment application can maximize treatment benefits

through improved pavement performance while minimizing the overall costs of maintaining the 

pavement. Performance of preventive maintenance treatments depends on the condition of the 

pavement at the time of treatment. Different types of treatments are likely to be most effective 

when applied at certain times in pavement life, providing a cost-effective solution to prolonging 

pavement life.

The LTPP database was used to obtain information on treatment dates, pretreatment 

pavement conditions, and post-treatment pavement condition changes over time. The analysis 

in this section of the report provides an indication for appropriate timing of different 

maintenance alternatives. 

The effects of initial pavement conditions on pavement performance for different treatment 

alternatives were evaluated by comparing the performances of two groups of pavements: sites 

with a WD lower than the median distress and sites with a WD higher than the median distress. 

The performance of the treated sections was evaluated in each group using the Friedman test to 

investigate the existence of statistically significant differences.

Flexible Pavement Maintenance Application Timing

IRI

Figure 10 presents the average rankings of the sites for different treatments. The figure illustrates 

the average ranking for all sites, including sites initially in poor condition and those initially in 

fair conditions. As explained earlier, a lower number for ranks indicates better performance. As 

such, thin overlay had better performance when all sites were included and when the sites were 

initially in poor conditions. However, the performance of the control section was statistically 

similar to all treatments with respect to IRI when the sites were initially in better conditions.
62

Figure 10. Graph. Average rank of SPS-3 sites with respect to IRI.

Table 29 presents the Friedman test results based on application timing. As shown in the 

table, the median roughness of the SPS-3 sites was 7.34 ft/mi (1.39 m/km). When considering all 

the sites collectively for the analysis, thin overlay significantly outperformed the control section, 

crack seal, and chip seal sections. However, when the analysis was run for those sites with IRIs 

higher than 7.34 ft/mi (1.39 m/km) (higher levels of roughness), the thin overlay treatment 

significantly outperformed other treatment types and the control section. No statistically 

significant differences were observed in the performance of treatments when the existing 

pavement sections had IRI levels lower than 7.34 ft/mi (1.39 m/km). It was concluded that 

treatments had little effect on the IRI performance if the pavement had a low initial IRI. 

Conversely, for sections with higher IRIs prior to the treatment, only thin overlays provided 

significant improvements to IRI performance over the service life of pavements.

Table 29. Friedman test results for SPS-3 sites with respect to IRI.

All Initial Conditions

IRIinitial >

1.39 m/km

IRIinitial <

1.39 m/km

Thin overlay 

outperformed the control 

section

Thin overlay 

outperformed the control 

section —

—

Thin overlay 

outperformed slurry seal —

Thin overlay 

outperformed crack seal

Thin overlay 

outperformed crack seal —

Thin overlay 

outperformed chip seal

Thin overlay 

outperformed chip seal —

1 ft = 0.305 m

1 mi = 1.61 km

— Indicates that the Friedman test was not significant for the specific condition.
63

Rutting

Figure 11 presents the average performance rankings of treatment types related to rutting. The 

sites were separated in two groups using the median (0.25 inches (6.4 mm)) for initial rutting of 

all sites. Using the median helped maximize the power of the comparisons using two groups with 

the same sample size. Thin overlay had better performance whether the sites were in fair or poor 

conditions. For both groups (low and high levels of initial rutting), the performance of the sites 

that were treated by crack sealing and slurry sealing was not any better than the control section 

that received no treatment. However, the average ranking remained consistent with respect to the 

application timing. There was not a significant difference in performance of the sites with thin 

overlays with either low or high levels of initial rutting. This was also true for other treatments.

Figure 11. Graph. Average rank of SPS-3 sites with respect to rutting.

Table 30 presents the Friedman test results based on application timing for rutting. Thin overlay 

significantly outperformed slurry seal, crack seal, and chip seal for both levels of rutting. 

Surprisingly, when the pavements had initial rutting lower than 0.25 inches (6.4 mm), the 

differences in rankings between the control section and the thin overlay were not statistically 

significant. Also, chip seal was significantly better than the slurry seal when the sites had initial 

rutting lower than 0.25 inches (6.4 mm); however, the differences were not identified when the 

pavement sections had higher levels of rutting prior to the treatments.
64

Table 30. Friedman test results of SPS-3 sites with respect to rutting.

Any Initial Condition Ruttinginitial > 0.25 inches Ruttinginitial < 0.25 inches

Thin overlay outperformed 

the control section

Thin overlay outperformed 

the control section —

Control section outperformed 

slurry seal —

Control section outperformed 

slurry seal

Thin overlay outperformed 

slurry seal

Thin overlay outperformed 

slurry seal

Thin overlay outperformed 

slurry seal

Thin overlay outperformed 

crack seal

Thin overlay outperformed 

crack seal

Thin overlay outperformed 

crack seal

Thin overlay outperformed 

chip seal

Thin overlay outperformed 

chip seal

Thin overlay outperformed 

chip seal

Chip seal outperformed 

slurry seal —

Chip seal outperformed slurry 

seal

1 inch = 25.4 mm

— Indicates that the Friedman test was not significant for the specific condition.

Cracking

Figure 12 presents the average performance rankings of sections with different maintenance 

treatments and varying levels of fatigue cracking prior to receiving those treatments. Similar to 

the previous analyses, the sites were grouped according to the median level of cracking prior to 

treatment for all sites. Chip seal had better cracking performance whether the sections had initial 

lower or higher levels of cracking. The cracking performance of sections that were treated with 

crack sealing, slurry sealing, and thin overlay was poorer than the control section when the sites 

had a level of cracking lower than 21.96 ft2 (2.04 m2). All treatments performed relatively better 

than the control section when the pavement had cracking higher than 21.96 ft2 (2.04 m2).

Figure 12. Graph. Average rank of SPS-3 sites with respect to cracking based on 

application timing.
65

Table 31 presents the Friedman test results based on application timing for cracking. The median 

level of existing cracking prior to the application of maintenance treatments for all of the sites in 

initial condition was 21.96 ft2 (2.04 m2

). Thin overlay and chip seal significantly outperformed 

slurry seal, crack seal, and the control section when the existing pavement had more than 

21.96 ft2 (2.04 m2) of cracking. Chip seal outperformed slurry seal and crack seal for pavements 

that had an initial level of cracking lower than 21.96 ft2 (2.04 m2). Under this condition, the 

control section performed better than slurry seal. 

Table 31. Friedman test results for SPS-3 sites with respect to cracking based on 

application timing.

Any Initial Condition Crackinginitial > 21.96 ft2 Crackinginitial < 21.96 ft2

Thin overlay outperformed 

the control section

Thin overlay outperformed 

the control section —

Chip seal outperformed the 

control section

Chip seal outperformed the

control section —

Thin overlay outperformed 

slurry seal

Thin overlay outperformed 

slurry seal —

Thin overlay outperformed 

crack seal

Thin overlay outperformed 

crack seal —

Chip seal outperformed 

slurry seal

Chip seal outperformed 

slurry seal

Chip seal outperformed 

slurry seal

Chip seal outperformed 

crack seal

Chip seal outperformed 

crack seal

Chip seal outperformed 

crack seal

— —

Control section 

outperformed slurry seal

1 ft2 = 0.093 m2

— Indicates that the Friedman test was not significant for the specific condition.

Rigid Pavement Maintenance Application Timing

The same analysis was conducted for rigid pavement sites in the SPS-4 experiment. The number 

of sites with undersealing treatments and reported distress measurements were limited to 10 or 

less. As a result, this treatment was excluded from further analysis to achieve meaningful 

conclusions due to the small sample size.

A Friedman test was applied to joint/crack sealed sections and the control sections to investigate 

significant differences in performance with respect to the application timing. Roughness, edge 

faulting, wheel-path faulting, and longitudinal cracking distress measurements were considered. 

No statistically significant differences were identified between the joint/crack sealing and control 

sections for any of the measured distresses under fair or poor initial pavement conditions.

CONCLUSIONS

Based on the analysis of SPS-3 sites, the following conclusions were made:

• Thin overlays and chips seals were more effective than slurry seal and crack seal 

treatments in mitigating fatigue cracking.
66

• As expected, thin overlay was the most effective option with respect to rutting. Chip seal 

was more effective than slurry seal in freeze zones and in wet regions. There were no 

significant differences between slurry seal, crack seal, and the no treatment scenario with 

respect to rutting.

• As expected, thin overlay was the most effective treatment with respect to IRI.

• With respect to fatigue cracking, thin overlay performed better than most other treatments 

if the pavement was in a freeze zone, in a wet climatic region, subject to high traffic 

conditions, or initially in poor condition.

• When the pavement was in a freeze zone, subject to high traffic, or in an initially poor 

condition, thin overlay was the best choice with respect to IRI.

• Thin overlays were more effective in wet regions compared to other treatments only with 

respect to fatigue cracking.

• Chip seal performance compared to other treatments was not affected by most design 

factors with respect to fatigue cracking. Specifically, chip seal performed better than 

slurry seal, crack seal, and the control section in freeze and no-freeze zones, in wet and 

dry climatic conditions, with fine and coarse subgrade materials, and under high and 

low traffic loads. Although chip seal was better than the mentioned treatments in 

initially poor condition pavements, it outperformed only slurry seal in initially fair 

condition pavements and outperformed only the control section in initially good 

condition pavements.

• Design factors had little or no influence on treatments with respect to rutting. Chip seal 

was only marginally more effective in the freeze zones and in dry climates.

The study of SPS-4 sites showed that the performance of the joint/crack sealed sections and 

undersealed sections was not significantly different than that of the control sections. No 

meaningful difference between the two treatments was found. The strength of the analysis was 

weakened by the number of sites that included recorded surveys with undersealing treatments. 

While there were 34 sites included in the survey measurements for joint/crack sealed sections, 

only 10 sites had recorded data for undersealed sections. 
67

CHAPTER 5. REHABILITATED FLEXIBLE PAVEMENT ANALYSIS AND FINDINGS

INTRODUCTION

This chapter describes the analysis of rehabilitation alternatives for flexible pavements. The 

LTPP SPS-5 experiment was the main source of information for this study. The objective of the 

SPS-5 experiment, “Rehabilitation of Asphalt Concrete Pavements,” was to help develop 

improved methodologies and strategies for the rehabilitation of flexible pavements. Specifically, 

the experiment evaluated common rehabilitation techniques implemented in the United States 

and Canada, and it evaluated the effects of climate, structural condition, and material variations 

on performance of rehabilitated flexible pavements. The design factorial is documented in 

Rehabilitation of Asphalt Concrete Pavements—Initial Evaluation of the SPS-5 Experiment, and 

included the following evaluation parameters:(4)

• Climate: Wet versus dry and freeze versus non-freeze.

• Existing pavement condition: Fair versus poor.

• Surface preparation: Milling versus no milling.

• Overlay material: Recycled versus virgin HMA.

• Overlay thickness: Thin (2 inches (51 mm)) versus thick (5 inches (127 mm)).

Variation of surface preparation alternatives, overlay material, and overlay thickness led to eight

combinations at each SPS-5 project site (see table 32). In addition, one section was assigned as 

the control and did not receive any overlay, except for routine maintenance, creating nine 

experimental sections at each SPS-5 project site. As a result, each individual SPS-5 project 

provided a means for directly comparing rehabilitated HMA pavement performance using 

different surface preparation intensity, overlay thickness, and type of overlay mixture. 

The initial SPS-5 sampling matrix was supposed to include only one subgrade type (fine-grained 

soil) with a minimum annual traffic of over 85,000 ESALs. Other factors considered in the 

sampling matrix included structural and functional condition of the pavement before overlay and 

climate. A total of 18 SPS-5 projects were constructed between 1989 and 1998. Table 33

presents the site location of each experiment according to their experimental design classification 

and as-built data. As shown, there were at least two projects for each condition except for the wet

no-freeze fair condition cell and the dry freeze poor condition cell. A total of 162 test sections 

were built as part of the core SPS-5 experiment.
68

Table 32. Core sections of the SPS-5 experiment.

SHRP ID Overlay Type

0501 Control: No treatment

0502 Thin overlay (1.99 inches (51 mm)): Recycled 

HMA mix

0503 Thick overlay (4.95 inches (127 mm)): 

Recycled HMA mix

0504 Thick overlay: Virgin mix

0505 Thin overlay: Virgin mix

0506 Thin overlay: Virgin mix with milling

0507 Thick overlay: Virgin mix with milling

0508 Thick overlay: Recycled mix with milling

0509 Thin overlay: Recycled mix with milling

Table 33. Constructed SPS-5 sites for the experimental factorial.

Pavement 

Condition

Soil 

Classification

Climate, Moisture Temperature

Wet Freeze

Wet 

No-freeze Dry Freeze

Dry 

No-freeze

Fair

Coarse/fine Georgia Colorado

Coarse New Jersey

Alberta, Canada

Montana New Mexico

Fine Minnesota

Oklahoma

Texas

Poor

Coarse/fine

Manitoba, 

Canada California

Coarse Maine

Florida

Alabama Arizona

Fine

Maryland

Missouri Mississippi

Note: Blank cells indicate data are not available.

One major deviation from the original SPS-5 experimental plan was the subgrade soil type. 

Originally, the subgrade soils for all SPS-5 projects were supposed to be fine-grained soils; 

however, only five of the SPS-5 projects actually had fine-grained soils. Four SPS-5 projects had

soils that varied between fine- and coarse-grained soils. The subgrade soils for the remaining 

eight SPS-5 projects were classified as coarse-grained soils.

Additionally, one major deviation from the original SPS-5 sampling matrix was subgrade soil 

type. Originally, the subgrade soils for all SPS-5 projects were supposed to be fine-grained soils. 

However, only six of the SPS-5 projects actually had fine-grained soils. Four SPS-5 projects had

soils that varied between fine- and coarse-grained soils, while the remaining eight projects were

classified as coarse-grained soils. Another deviation from the experimental plan for only a few of 

the SPS-5 projects was that no control section was left in place. For example, section 0501 for 

the Colorado project included the placement of a thin overlay during rehabilitation. 
69

DATA ANALYSES

The impact of design features and site conditions on performance and response can be evaluated 

by looking at the trends in the survey data over time. Statistical tests can be used to verify if there 

are differences in these trends and if they can be associated with any of the design features in the 

experiment. Moreover, it is important to establish if any information on performance or response 

is reproduced in other sites or if they are associated with a particular site characteristic (e.g., 

climate, traffic, etc.). The best approach to achieve this objective is to consider every site and 

section available to statistically compare performance and response.

The SPS-5 experimental designed was balanced between design features intended for 

investigation. With few exceptions, out of 9 sections in each one of the 18 sites, there was

1 control section and 8 sections that combined equally thin and thick overlays with virgin and 

reclaimed asphalt pavement (RAP) mixes and milling and not milling prior to overlay. This 

provided an opportunity for a gradual statistical analysis in which information was gained by 

sequentially analyzing the data from each site first and complemented with a consolidated 

analysis. The consolidated analysis involved evaluating all sites and sections simultaneously in 

search of general trends and conclusions about pavement performance and its dependency on 

design features and site conditions. Figure 13 illustrates the statistical analysis process.

Figure 13. Illustration. Statistical analysis flow chart.

Statistical Approach and Tests

The approach consisted of analyzing each site individually to initially check its construction 

history to address possible problems during that phase. ANOVA was then used for repeated 

measures. ANOVA can be used to explain if different trends in performance exist because of a 

particular choice of design feature (e.g., milling versus no milling). The repeated measures are 

the surveys conducted throughout the duration of the experiment. Each section that is part of one 

site has the same site conditions and traffic volume. The surveys were performed within a short 

period for sections, which made ANOVA with repeated measures the best option for the 

statistical analysis of individual sites.
70

The consolidated analysis was performed using the Friedman test. This is a nonparametric test 

(distribution-free) used to compare repeated observations on similar subjects. Unlike the more 

common parametric repeated measures such as ANOVA or a paired t-test, the Friedman test 

makes no assumptions about the distribution of the data (e.g., normality), and it can be used for 

multiple comparisons. The Friedman test uses the ranks of the data rather than their raw values to 

calculate the statistic. The test statistic for the Friedman test is a chi-square with n - 1 degrees of 

freedom, where n is the number of repeated measures (i.e., the number of sections in each site 

of the experiment). Statistical significance was defined at 95 percent (p ≤ 0.05 for the 

chi-square test). 

The Friedman test also permits the evaluation of paired statistical significance between two 

rehabilitation strategies. In some instances, the result of one analysis may indicate that 

significant differences exist between the rankings of sections (i.e., the performances of these 

sections are statistically different). However, there might be groups within the sorted ranking 

with similar performance. The paired statistical analysis feature is important to identify groups of

strategies with equivalent performance.

Performance Measures

The analysis of individual sites used distress and response data collected throughout the 

experiment duration. The data were checked for consistency and reasonableness prior to use in 

the analysis. Roughness, rutting, and fatigue, longitudinal, and transverse cracking were selected 

as indicative of performance and maximum deflection as indicative of response.

As described in the previous chapter, the consolidated analysis used WD as a performance 

measure of various distresses and the pavement response. It is calculated using the equation in

figure 14.

∑

∑

=

+

−

=

+ + × +

= n

i

i

n

i

i i i

P

D D P

WD

0

1

1

0

1 1

2

( )

Figure 14. Equation. Weighted distress.

The weighted average, in reality, represents the total normalized area (per year) under the 

distress versus time curve. As such, it is a measure of pavement performance relative to the 

specific distress over the entire monitoring period. The normalization to total time the section 

was in service provides means for comparing survey periods that may be different, which 

allowed the comparison of performance for both short term and long term. 

The WD parameter is related to pavement performance over the whole analysis period. This 

concept is comparable to performance originally defined as the area under the serviceability 

curve.

(2) The effect of variability from measurements by different surveyors is reduced when 

using this procedure and provided a parameter that could be used to compare sections with 

different survey periods. The WD performance measure proved a viable alternative to access the 

performance of different sections with individual in situ conditions and in-service ages. WD 
71

values were computed for the short term to evaluate performance in less than or equal to 5 years 

after rehabilitation was executed. Additionally, WD values were computed for the long term to 

compare performance for a period greater than 5 years.

EFFECT OF DESIGN, CONSTRUCTION FEATURES, AND SITE CONDITIONS ON 

PERFORMANCE OF REHABILITATED FLEXIBLE PAVEMENTS

The first task was to analyze the impact of design features on performance for each site 

separately. The objective of this initial step was to identify trends in performance that could be 

associated with each design feature in the experiment (thin versus thick overlay, RAP versus 

virgin mix, and milling versus no milling). ANOVA with repeated measures was the statistical 

test used for this task. This statistical analysis took advantage of the fact that all sections at each 

SPS-5 site had the same underlying pavement structure, traffic, and climate. The distress surveys 

and profile measurements were taken on the same day in all sections within each site. The survey 

dates were used as the repeated measures for the ANOVA.

The following section provides a complete example of the ANOVA tests used for the

individual evaluation of SPS-5 sites. Each site in the experiment was evaluated following this 

sequential approach.

Example of Repeated Measures of ANOVA for Evaluation of SPS-5 Sites

Site Description and Data Availability

This site was assigned to LTPP in 1987, marking the initial data collection for the LTPP 

database. It is located at I-8 eastbound 17 mi (27.37 km) west of the I-10/I-8 interchange in 

Pinal County, AZ. The subgrade is a silty gravel soil with sand. The base course is a 14-inch

(355-mm) soil aggregate mixture. The surface course is 5 inches (127 mm) of HMA. Traffic data 

are available since 1994, and AADTT for the LTPP lane is approximately 800 trucks. The 

average growth rate during the period is 8.5 percent. FHWA class 9 trucks account for 

80 percent of the total truck traffic.

Data were available for all nine sections of this LTPP site. After being extracted from the 

LTPP database, performance data were evaluated for completeness and reasonableness. If any 

outliers were identified, they were removed from the analysis and recorded for reporting. In 

some instances, there were surveys performed on different days to cover all test sections in one 

specific date. When this happened, the missing survey was complemented with an interpolation 

of distresses measured during the previous and next survey dates. The reason for this was the 

need for equal numbers of surveys required to run ANOVA analysis with repeated measures.

All eight sections were rehabilitated in April 1990 following the selected SPS-5 experimental 

design. Section 0501 was used as the control section and was left without any rehabilitation. 

Data collection started after the rehabilitation and continued for 16 years until 2006. Data 

collection for the control section ended in 1993 probably as a result of the need to rehabilitate 

this section.
72

Analysis Approach

The analysis was performed for each type of distress previously described as well as for the 

maximum deflection. ANOVA with repeated measures was indicated in this case because the 

evaluation was carried out through a series of performance measurements taken throughout the 

duration of the experiment. The number of measurements in each section must be equal, and the 

experiment factorial must be balanced. The core sections of the SPS-5 experiment were

balanced within each one of the three design features (overlay thickness, mix type, and surface 

preparation) and were independent. Without the control section, the eight remaining core 

sections provided an equal combination of all options in the design features. Therefore, the 

control section was not used for the statistical analysis of individual sites.

Repeated measures ANOVA is a technique used to test the equality of means. The null 

hypothesis has no differences between population means. The F-test in ANOVA evaluates the 

significance of the differences between means. A large F-value yields a correspondingly small 

p-value. The p-value is the observed significance level, or probability, of a type I error (alpha), 

which shows that the difference between population means exists when in fact there is no 

difference. In this study, an acceptable level of significance and probability of a type I error 

was defined as 0.05. The null hypothesis was rejected if the p-value was less than 0.05.

Analysis of Performance

Roughness was measured by the IRI. Figure 15 presents an example showing IRI values for all 

sections in the site. The vertical dotted line indicates the year the sections were rehabilitated, as 

the measured roughness drops from the first to the second measurement. When the data were 

tested with the repeated measures ANOVA, they were grouped by different design features in 

the experiment.

1 inch = 25.4 mm

1 mi = 1.61 km

Figure 15. Graph. Roughness from an SPS-5 site in Arizona.
73

Figure 16 shows IRI over time for both thin and thick overlay sections. The marks are the 

average IRI for all sections grouped by overlay thickness. The bars represent the range of values 

with one standard deviation from the average. The p-value in the top of the chart is zero and 

indicates that there is a significant statistical difference in IRI values over time between sections 

with thin and thick overlays. The plot also indicates that sections with thick overlay performed 

better than those with thin overlays, as expected.

Statistically significant differences were also found when comparing sections overlaid with 

virgin versus recycled mixtures. Figure 17 shows IRI values over time for both mixture types, 

and the p-value was close to zero. The plot indicates that sections overlaid with virgin mix had 

better performance than those with recycled asphalt mix. It is interesting to note that soon after 

rehabilitation, IRI average values were not different between the two types of sections. The great 

significant difference in performance was more evident later in the pavements’ service life.

Surface preparation prior to overlay did not have an impact on roughness performance. 

Figure 18 shows IRI values over time for sections that were milled versus not milled prior to 

receiving the overlay. The p-value was close to 1.0 and indicated that both distributions were

statistically similar. 

SURVEY*overlay; LS Means

Current effect: F(12, 48)=10.795, p=.00000

 overlay

 thin

 overlay

 thick s1 s2 s3 s4 s5 s6 s7 s8 s9 s10 s11 s12 s13

SURVEY

20

40

60

80

100

120

140

160

180

200

220

IRI (in/mi)

1 inch = 25.4 mm

1 mi = 1.61 km

Figure 16. Graph. IRI versus overlay thickness (distribution) for an SPS-5 site in Arizona.
74

SURVEY*mix; LS Means

Current effect: F(12, 48)=13.512, p=.00000

 mix

 RAP

 mix

 Virgin s1 s2 s3 s4 s5 s6 s7 s8 s9 s10 s11 s12 s13

SURVEY

40

60

80

100

120

140

160

180

200

220

IRI (in/mi)

1 inch = 25.4 mm

1 mi = 1.61 km

Figure 17. Graph. IRI versus mix type (distribution) for an SPS-5 site in Arizona.
75

SURVEY*milling; LS Means

Current effect: F(12, 48)=.03921, p=1.0000

 milling

 no

 milling

 yes

s1 s2 s3 s4 s5 s6 s7 s8 s9 s10 s11 s12 s13

SURVEY

0

20

40

60

80

100

120

140

160

180

200

220

240

260

IRI (in/mi)

1 inch = 25.4 mm

1 mi = 1.61 km

Figure 18. Graph. IRI versus milling (distribution) for an SPS-5 site in Arizona.

The analysis of pavement performance associated with roughness described previously was 

repeated for rutting, fatigue, longitudinal cracking, and transverse cracking. The results are 

summarized in table 34. If a statistically significant difference in performance existed, it is

marked with a “Y,” and the corresponding design feature with the best performance was

indicated. When no difference was justified statistically, it is marked with an “N” in the table.

In this case, a qualitative assessment was made of which design feature provided the best 

performance. Blank cells indicate that no design feature had predominant performance. For 

example, the first line (roughness) in table 34 indicates statistical differences in performance 

when evaluating the effect of overlay thickness. In this case, for both short-term and long-term

performances, the performance for thick overlays (5-inch (127-mm)) was found to be better than 

thin overlays (2-inch (51-mm)).
76

Table 34. Summary of statistical analysis results for SPS-5 site in Arizona.

Distress

Overlay Thickness Mix Type Milling

Statistical 

Difference

Best 

Performance Statistical 

Difference

Best 

Performance Statistical 

Difference

Best 

Performance

Short Long Short Long Short Long

Roughness

Y

(p = 0) Thick Thick

Y

(p = 0) Virgin N Mill Mill

Rutting

Y

(p = 0.004) Thin Thick

Y

(p = 0.0004) Virgin Virgin N

No 

mill

Fatigue N Thick Thick N

Y

(p = 0.005) Mill Mill

Transverse N N Virgin Virgin N

Longitudinal N Thin

Y

(p = 0.01) Virgin Virgin N

Note: Blank cells indicate that no design feature had predominant performance.

Summary of Findings

The repeated measures ANOVA results for this SPS-5 site suggest the following:

• Thick overlays provided smoother pavements after rehabilitation when compared to 

thin overlays.

• Rehabilitation alternatives with virgin mix overlays were smoother over the long term

(5 years or more after rehabilitation) than sections overlaid with recycled asphalt mixes. 

There was no statistical difference for short-term performance.

• Thin overlays provided better rutting performance for the short term, but thick overlays 

were statistically better for the long term.

• Virgin mix overlays demonstrated better rutting performance than recycled asphalt 

mix overlays. 

• Milling the existing surface prior to overlay improved fatigue cracking performance 

when compared to sections that were not milled.

• Neither of the design features investigated had a significant impact on transverse 

cracking performance. 

• Virgin mix overlays provided better longitudinal cracking performance than recycled 

asphalt mix overlays.

Conclusions from the Individual Analyses of SPS-5 Sites

The example presented in the previous section illustrates the approach taken to individually 

evaluate each site in the SPS-5 experiment. The summary tables for each site containing the 
77

results of the statistical analysis on performance for roughness, rutting, fatigue cracking, 

longitudinal cracking, and transverse cracking are presented in appendix A of this report.

The individual analysis of each site provided good qualitative information about the impact of 

design features on the performance of rehabilitated flexible pavement sections. The differences 

in performance are best visualized when compiled in plots that explore each design feature 

investigated in the SPS-5 experiment. These plots and key findings from the individual analyses 

of SPS-5 sites are presented in this section.

The compilation of results was created by identifying the number of sites in which various

design features provided different performance throughout the site’s service life. For example, if 

sections with thick overlays performed better than thin overlaid sections in one site, thick overlay 

was marked for the site. The process was repeated for all sites and distresses. The plots presented 

in this section summarize the percentage of sites in which differences in performance were 

identified. The number of sites with statistically justified differences from the ANOVA repeated 

measures test was also noted.

Results for roughness are provided in figure 19, suggesting that thick overlays provided the 

best performance in more than 50 percent of the sites. No differences in short-term performance 

were found in the majority of sites when comparing the two mix types. When long-term 

performance was evaluated, virgin mixes were found to perform better than recycled mixes, 

but no differences were found in 44 percent of sites. Milling improved performance in the 

majority of sites; however, one-third of sites had no differences in performance between 

milled and nonmilled sections.

The results in figure 19 were obtained from statistical analysis and engineering judgment when 

statistically significant differences were not found (p-values higher than 0.05) but differences in 

trends were clearly visible. The choice to consider both statistically-based and engineering 

judgment-based results was justified by the expansion of data analysis the two approaches 

provided combined. In the analysis of thickness, five sites (28 percent of all SPS-5 sites) had 

statistically significant differences in roughness performance. Four sites (22 percent) had 

statistically significant differences in the analysis of mix type, and three sites (17 percent) had 

statistically significant differences in the analysis of milling.
78

Figure 19. Graph. Summary of SPS-5 sites by best-performing design feature for roughness 

according to repeated measures ANOVA results.

Results for rutting are provided in figure 20, suggesting that the overlay thickness did not impact 

performance in the majority of sites. Mix type was also a design feature in which the impact on 

performance was not observed in the majority of sites. It is important to note that when 

differences were found, they were observed more in favor of sections overlaid with virgin mixes. 

The results also suggested that milling did not have an impact on rutting performance, and the 

majority of sites had milled and nonmilled sections performing similarly.

The results in figure 20 were obtained from statistical analysis and engineering judgment.

Statistical significant differences were not found (p-values greater than 0.05), but differences in 

trends were clearly visible. In the analysis of thickness, five sites (28 percent of all SPS-5 sites) 

had statistically significant differences in rutting performance. Four sites (22 percent) had 

statistically significant differences in the analysis of mix type, and only two sites (12 percent) 

had statistically significant differences in the analysis of milling.
79

Figure 20. Graph. Summary of SPS-5 sites by best-performing design feature for rutting 

according to repeated measures ANOVA results.

Results for fatigue cracking are summarized in figure 21. None of the design features evaluated 

had an impact on short-term fatigue cracking performance. Sections with thick overlays had 

better long-term performances than thin overlays, although there were still 44 percent of sites in 

which no differences were found. Sections with virgin mix overlay had better long-term 

performances in half of the sites. Surprisingly, milled and nonmilled sections had equivalent 

long-term performances in the majority of sites.

The results in figure 21 were obtained from statistical analysis and engineering judgment. 

Statistically significant differences were not found (p-values higher than 0.05), but differences in 

trends were clearly visible. In the thickness analysis, four sites (22 percent of all SPS-5 sites) had 

statistically significant differences in fatigue cracking performance. Five sites (28 percent) had 

statistically significant differences in the analysis of mix type, and two sites (12 percent) had 

statistically significant differences in the analysis of milling.
80

Figure 21. Graph. Summary of SPS-5 sites by best-performing design feature for fatigue 

cracking according to repeated measures ANOVA results.

Results for transverse cracking in figure 22 suggest that none of the design features evaluated in 

the SPS-5 experiment had any impact on performance in the majority of sites. It is worth noting 

that thick overlays had better transverse cracking long-term performance in 22 percent of sites, 

and milling prior to overlay had better transverse cracking long-term performance in 39 percent 

of sites.

The results in figure 22 were obtained from statistical analysis and engineering judgment.

Statistically significant differences were not found (p-values greater than 0.05), but differences in 

trends were visible. In the thickness analysis, five sites (28 percent of all SPS-5 sites) had 

statistically significant differences in transverse cracking performance. Five sites (28 percent) 

had statistically significant differences in the analysis of mix type, and three sites (18 percent)

had statistically significant differences in the analysis of milling.
81

Figure 22. Graph. Summary of SPS-5 sites by best-performing design feature for 

transverse cracking according to repeated measures ANOVA results.

Results for longitudinal cracking are provided in figure 23 and suggest that for the majority 

of sites, none of the design features evaluated in the SPS-5 experiment had an impact on 

performance. It is worth noting that thin overlays had better longitudinal cracking long-term 

performance in 22 percent of sites, and milling prior to overlay had better longitudinal cracking 

long-term performance in 39 percent of sites.

The results in figure 23 were obtained from statistical analysis and engineering judgment.

Statistically significant differences were not found (p-values greater than 0.05), but differences 

in trends were visible. In the thickness analysis, three sites (18 percent of all SPS-5 sites) had 

statistically significant differences in longitudinal cracking performance. Three sites (18 percent) 

had statistically significant differences in the mix type analysis, and four sites (22 percent) had 

statistically significant differences in the milling analysis.
82

Figure 23. Graph. Summary of SPS-5 sites by best-performing design feature for 

longitudinal cracking according to repeated measures ANOVA results.

The key findings from the assessment of individual sites are listed below.

Roughness results were as follows:

• Thick overlays provided smother pavements in the majority of SPS-5 sites, as expected.

• There were no differences in short-term performance between virgin mix and recycled 

asphalt overlays for the majority of sites. Although this number dropped when long-term 

performance was evaluated, it was still higher than the number of sites in which one mix 

had better performance than the other. When differences were identified, virgin mix 

overlays performed better in twice as many sites as RAP overlays.

• Milling improved roughness performance, particularly in the long term.

Rutting results were as follows:

• There were no differences in performance between thin and thick overlays.

• Virgin mixes and mixes containing up to 30 percent RAP presented equivalent 

performance in the majority of sites. When differences were noted, virgin mixes 

performed better in a slightly higher number of sites.

• Milling did not improve rutting performance.
83

Fatigue cracking results were as follows:

• There were no differences in short-term performance between thin and thick overlays. 

However, thick overlays provided better long-term performance.

• Virgin mixes and mixes containing RAP performed equivalently in the majority of sites 

in the short term. When differences were noted, virgin mixes performed better in half of 

the SPS-5 sites.

• Milling did not improve fatigue cracking performance, and the number of sites with 

statistically significant differences was small.

Transverse cracking results were as follows:

• There were no differences in performance between thin and thick overlays in the short

term. However, thick overlays provided better long-term performance.

• Virgin mixes and mixes containing RAP performed equivalently in the majority of sites 

in the short term and long term.

• Milling improved transverse cracking performance; however, in the majority of sites, no 

differences were noted.

Longitudinal cracking results were as follows:

• Performance was not significantly affected by any of the design features.

• The majority of sites had equivalent performance on all three design features (overlay 

thickness, mix type, and milling).

Consolidated Analysis

The consolidated analysis involved compiling all sites in the SPS-5 experiment and 

simultaneously evaluating the impact of design features and site conditions for short-term and 

long-term performance. WD was the parameter selected for the comparisons, and it allowed the 

analysis to be carried across different conditions observed in each site of the experiment (more 

specifically, the different periods of monitoring data).

After the data were processed and verified for quality and existing outliers were corrected after 

LTPP analysis or removed, WD was computed for short-term and long-term performance. For 

simplicity, only the values for long-term performance are shown in table 35 through table 39. 

The remaining results are available in appendix A of this report. The Friedman test used the 

distress-associated WD to create a ranking of performance from the lowest value of WD (best 

performance) to the highest value (worst performance) for each site in the dataset. Ranking 

statistics for each type of section were then used to calculate the Friedman chi-square value used 

to determine if statistical differences existed among the performance rankings of the sections.
84

The WD-distress represents the overall performance of the section. It is better understood as an 

index computed based on the entire performance at a given period, as illustrated in figure 24.

Therefore, it is intended for comparative analyses. The higher the WD value, the more distressed 

the pavement section is compared to sections with lower WD values.

1 inch = 25.4 mm

1 mi = 1.61 km

Figure 24. Graph. Example of WD-distress values in comparative performance analysis for 

IRI trend after rehab.
Table 35. Long-term average WD-IRI values for SPS-5 sites.

Section

Experimental Design Sites (State Codes)/Average WD-IRI Values (m/km)

Mill Mix

Thickness 

(mm) 1 4 6 8 12 13 23 24 27 28 29 30 34 35 40 48 81 83

0501 No None 80 108 70 92 97 193 88 130 134 39 113 127 98

0502 No RAP 51 55 134 130 65 49 40 42 80 90 96 72 74 70 44 86 82 93 104

0503 No RAP 127 53 77 75 50 49 40 54 71 87 114 62 62 45 33 66 76 89 69

0504 No Virgin 127 57 82 74 56 42 40 56 86 95 87 71 48 51 37 70 93 101 71

0505 No Virgin 51 58 92 102 55 36 40 45 90 101 110 69 57 57 39 64 95 83 107

0506 Yes Virgin 51 48 71 81 87 32 36 52 59 92 101 69 56 51 37 66 90 72 117

0507 Yes Virgin 127 56 88 73 65 37 39 55 63 72 83 83 61 52 42 62 83 93 59

0508 Yes RAP 127 65 64 64 52 46 49 48 53 80 92 62 48 48 35 61 74 78 63

0509 Yes RAP 51 55 115 142 62 37 40 60 76 87 108 84 62 49 37 64 78 94 84

1 inch = 25.4 mm

1 ft = 0.305 m

1 mi = 1.61 km

Note: Higher WD values indicate rougher pavement over time. The blank cells indicate data are not available

Table 36. Long-term average WD-rutting values for SPS-5 sites.

Section

Experimental Design Sites (State Codes)/Average WD-Rutting Values (mm)

Mill Mix

Thickness 

(mm) 1 4 6 8 12 13 23 24 27 28 29 30 34 35 40 48 81 83

0501 No None 0.36 0.15 0.33 0.56 0.36 0.27 0.55 0.33 0.31 0.14 0.41 0.36 0.36

0502 No RAP 51 0.10 0.19 0.16 0.13 0.16 0.13 0.27 0.17 0.10 0.36 0.14 0.17 0.11 0.12 0.11 0.23 0.25 0.14

0503 No RAP 127 0.13 0.15 0.10 0.11 0.17 0.13 0.27 0.25 0.08 0.43 0.19 0.12 0.09 0.15 0.17 0.16 0.33 0.17

0504 No Virgin 127 0.14 0.11 0.16 0.09 0.15 0.14 0.31 0.21 0.07 0.60 0.12 0.17 0.11 0.15 0.12 0.21 0.28 0.13

0505 No Virgin 51 0.12 0.12 0.15 0.12 0.13 0.12 0.25 0.15 0.09 0.33 0.12 0.13 0.10 0.12 0.16 0.18 0.18 0.16

0506 Yes Virgin 51 0.09 0.11 0.12 0.14 0.11 0.12 0.35 0.12 0.09 0.36 0.12 0.20 0.13 0.15 0.15 0.25 0.25 0.18

0507 Yes Virgin 127 0.13 0.21 0.20 0.17 0.14 0.13 0.33 0.22 0.09 0.59 0.08 0.17 0.12 0.18 0.15 0.25 0.22 0.21

0508 Yes RAP 127 0.21 0.14 0.11 0.13 0.16 0.12 0.32 0.19 0.08 0.56 0.17 0.11 0.10 0.16 0.11 0.18 0.23 0.22

0509 Yes RAP 51 0.13 0.16 0.13 0.09 0.13 0.13 0.30 0.43 0.11 0.33 0.11 0.17 0.13 0.15 0.09 0.16 0.26 0.15

1 inch = 25.4 mm

Note: Higher WD values indicate the pavement is more rutted over time. The blank cells indicate data are not available.

8

5
Table 37. Long-term average WD-fatigue cracking values for SPS-5 sites.

Section

Experimental Design Sites (State Codes)/Average WD-Fatigue Cracking Values (m2)

Mill Mix

Thickness 

(mm) 1 4 6 8 12 13 23 24 27 28 29 30 34 35 40 48 81 83

0501 No None 2,305 692 13 810 1 51 1,927 2,475 11 0 46 377 2,305 692

0502 No RAP 51 2,566 966 38 0 0 25 0 458 0 1,263 463 1 1 3 1,480 916 2,566 966

0503 No RAP 127 513 137 1 0 0 5 0 46 0 993 151 0 10 8 1,052 734 513 137

0504 No Virgin 127 475 111 0 0 0 96 0 4 2 0 178 2 1 0 384 544 475 111

0505 No Virgin 51 1,467 674 1 0 0 183 0 94 0 16 165 1 4 0 700 681 1,467 674

0506 Yes Virgin 51 474 1,261 0 0 0 9 0 198 3 1 7 6 1 0 765 822 474 1261

0507 Yes Virgin 127 528 840 0 1 0 0 0 0 108 0 45 4 1 5 273 489 528 840

0508 Yes RAP 127 85 180 0 0 0 84 0 258 0 725 47 0 1 8 399 498 85 180

0509 Yes RAP 51 2,204 16 0 1 0 0 0 705 2 1,511 650 2 0 29 1,272 1068 2,204 16

1 ft = 0.305 m

1 inch = 25.4 mm

Note: Higher WD values indicate increased cracking in the pavement over time. The blank cells indicate data are not available.

Table 38. Long-term average WD-transverse cracking values for SPS-5 sites.

Section

Experimental Design Sites (State Codes)/Average WD-Transverse Cracking Values (m)

Mill Mix

Thickness 

(mm) 1 4 6 8 12 13 23 24 27 28 29 30 34 35 40 48 81 83

0501 No None 0 154 63 38 140 245 201 32 270 33 91 30 32

0502 No RAP 51 110 87 153 69 5 0 0 134 262 96 0 26 199 47 62 220 96 188

0503 No RAP 127 4 339 194 11 0 0 0 54 196 136 0 14 69 44 24 98 88 151

0504 No Virgin 127 0 40 83 43 0 0 0 32 200 3 0 35 50 3 5 4 61 250

0505 No Virgin 51 54 216 197 64 8 0 0 152 327 50 0 57 155 56 52 186 288 81

0506 Yes Virgin 51 1 50 152 90 2 0 0 129 294 65 1 51 9 2 33 4 130 39

0507 Yes Virgin 127 1 2 100 10 0 0 0 4 149 1 4 10 11 0 0 2 143 208

0508 Yes RAP 127 1 207 257 9 0 0 0 59 217 80 0 10 51 2 0 73 54 225

0509 Yes RAP 51 13 339 209 40 0 0 0 5 230 32 1 0 47 9 30 155 19 110

1 ft = 0.305 m

1 inch = 25.4 mm

Note: Higher WD values indicate increased cracking in the pavement over time. The blank cells indicate data are not available.

8

6
Table 39. Long-term average WD-longitudinal cracking values for SPS-5 sites.

Section

Experimental Design Sites (State Codes)/Average WD-Longitudinal Cracking Values (m) 

Mill Mix

Thickness 

(mm) 1 4 6 8 12 13 23 24 27 28 29 30 34 35 40 48 81 83

0501 No None 0 364 842 1,039 939 894 239 563 670 380 53 170 250

0502 No RAP 51 95 47 268 722 2 304 277 795 843 209 52 377 862 405 252 797 575 741

0503 No RAP 127 143 337 430 552 2 209 292 624 549 101 96 186 949 508 113 646 579 848

0504 No Virgin 127 86 26 362 715 9 132 302 429 677 52 33 176 827 103 83 80 704 669

0505 No Virgin 51 92 130 342 996 27 293 277 486 894 47 465 270 585 268 28 797 319 932

0506 Yes Virgin 51 0 78 485 673 0 144 214 627 737 52 88 205 599 158 36 337 84 574

0507 Yes Virgin 127 19 3 459 410 0 129 277 651 649 17 74 89 753 60 65 19 456 578

0508 Yes RAP 127 69 285 497 152 73 135 218 745 369 170 116 266 926 559 0 631 578 921

0509 Yes RAP 51 100 329 492 152 8 206 138 99 572 146 54 322 826 411 48 639 544 392

1 ft = 0.305 m

1 inch = 25.4 mm

Note: Higher WD values indicate increased cracking in the pavement over time. The blank cells indicate data are not available.

8

7
88

As noted earlier, the Friedman null hypothesis states that there are no differences between the 

ranking of sections (i.e., all sections have similar performances). The null hypothesis is rejected 

if the p-value is lower than 0.05, which represents a 95 percent confidence level that at least two 

sections have statistically different rankings. Examples of Friedman test outputs are provided 

in figure 25 and figure 26. In the figures, the average WD value for IRI found for each 

rehabilitation strategy among all sites was analyzed. The vertical bars represent the interval 

between the mean value ±1 standard deviation as an illustration of the variability of the 

measurements. The results in figure 25 indicate that for short-term roughness performance, 

there were at least two sections with statistically different performance (p < 0.0001, ANOVA 

chi-square = 48.8889). A similar result was found for long-term performance, as shown in 

figure 26 (p < 0.0001, ANOVA chi-square = 44.5667).

1 ft = 0.305 m

1 mi = 1.61 km

Figure 25. Graph. WD-IRI short-term values in SPS-5 sites.

1 ft = 0.305 m

1 mi = 1.61 km

Figure 26. Graph. WD-IRI long-term values in SPS-5 sites.

When the result of the Friedman test indicated the existence of at least two strategies with 

statistically different rankings, the next step was to identify which sections were different and to 
89

build the rankings of best-performing strategies based on the statistical analysis. Table 40 and 

table 41 provide the p-values for each Friedman test paired analysis for short-term and long-term 

roughness performance rankings.

Table 40. Friedman test paired analysis of rehabilitation strategies for short-term 

roughness performance ranking for SPS-5 sites.

Paired Analysis p-Value

0501 and 0502 —

0501 and 0503 < 0.05

0501 and 0504 < 0.05

0501 and 0505 —

0501 and 0506 < 0.05

0501 and 0507 < 0.05

0501 and 0508 < 0.05

0501 and 0509 < 0.05

0502 and 0503 —

0502 and 0504 —

0502 and 0505 —

0502 and 0506 —

0502 and 0507 < 0.05

0502 and 0508 < 0.05

0502 and 0509 —

0503 and 0504 —

0503 and 0505 —

0503 and 0506 —

0503 and 0507 —

0503 and 0508 —

0503 and 0509 —

0504 and 0505 —

0504 and 0506 —

0504 and 0507 —

0504 and 0508 —

0504 and 0509 —

0505 and 0506 —

0505 and 0507 —

0505 and 0508 < 0.05

0505 and 0509 —

0506 and 0507 —

0506 and 0508 —

0506 and 0509 —

0507 and 0508 —

0507 and 0509 —

0508 and 0509 —

— Indicates pair analysis with no 

statistical significance.
90

Table 41. Friedman test paired analysis of rehabilitation strategies for long-term roughness 

performance ranking for SPS-5 sites.

Paired Analysis p-Value

0501 and 0502 —

0501 and 0503 < 0.05

0501 and 0504 —

0501 and 0505 —

0501 and 0506 < 0.05

0501 and 0507 < 0.05

0501 and 0508 < 0.05

0501 and 0509 —

0502 and 0503 —

0502 and 0504 —

0502 and 0505 —

0502 and 0506 —

0502 and 0507 —

0502 and 0508 < 0.05

0502 and 0509 —

0503 and 0504 —

0503 and 0505 —

0503 and 0506 —

0503 and 0507 —

0503 and 0508 —

0503 and 0509 —

0504 and 0505 —

0504 and 0506 —

0504 and 0507 —

0504 and 0508 —

0504 and 0509 —

0505 and 0506 —

0505 and 0507 —

0505 and 0508 —

0505 and 0509 —

0506 and 0507 —

0506 and 0508 —

0506 and 0509 —

0507 and 0508 —

0507 and 0509 —

0508 and 0509 —

— Indicates pair analysis with no 

statistical significance.
91

The paired analysis results were used to create a practical ranking of roughness performance 

based on the statistical differences that were identified. The tables were intended to help users 

select the best alternatives given the specific conditions that they may want to evaluate. Based 

on the results presented in table 40 and table 41, the final ranking for evaluating roughness 

performance was created for the short term and long term (see table 42). Sections were ordered 

from best to worst performance, and sections with equivalent performance were grouped under 

the same rank.

Table 42. Ranking of rehabilitation strategies for roughness, SPS-5 sites.

Statistical 

Relevance (Y/N)

Roughness

Short-Term Long-Term

Y (p < 0.0001) Y (p < 0.0001)

Ranking

(if relevant)

Ranking Strategy Ranking Strategy

1 Mill, thick, RAP 1 Mill, thick, RAP

2 Mill, thick, virgin 2 No mill, thick, RAP

3 No mill, thick, RAP 2 Mill, thin, virgin

3 No mill, thick, virgin 2 Mill, thick, virgin

3 Mill, thin, virgin 5 No mill, thick, virgin

3 Mill, thin, RAP 5 Mill, thin, RAP

3 No mill, thin, virgin 5 No mill, thin, virgin

8 No mill, thin, RAP 8 No mill, thin, RAP

9 Control 9 Control

The results in table 42 suggest that rehabilitations with milling and thick recycled overlays 

provided smoother pavements in both the short-term and long-term performance. Strategies with 

milling and virgin thick overlay were the second best for short-term performance. For long-term 

roughness performance, three strategies had equivalent second best performances. A broader 

analysis of both rankings suggests that thick overlays provided better performance over the short 

term and long term. Overall, differences between performance of recycled asphalt and virgin 

overlays were difficult to identify, suggesting that roughness performance was not significantly 

affected by the overlay mix type. Both rankings also suggested that strategies with milling were

more likely to provide better short-term and long-term roughness performance. These results 

agree with the conclusions drawn from the analysis of individual sites.

The same approach described for the analysis of roughness was applied to all distresses (rutting, 

fatigue, transverse, and longitudinal cracking). Figure 27 and figure 28 describe the Friedman 

test for rutting. Based on the same test statistics, the ranking of best-performing rehabilitation 

strategies for rutting was created (see table 43). The results suggest that thin overlays performed 

better at early stages for short-term performance (see figure 27, p < 0.0001, ANOVA chi-square 

= 40.2), while no significant differences were identified for long-term performance (see 

figure 28, p < 0.0001, ANOVA chi-square = 38.9778). The top rankings also were equally 

distributed among sections overlaid with virgin and RAP mixes and among sections previously 

milled and not milled. These findings agree with the observations from the analysis of 

individual sites.
92

1 inch = 25.4 mm

Figure 27. Graph. WD-rutting short-term values for SPS-5 sites.

1 inch = 25.4 mm

Figure 28. Graph. WD-rutting long-term values for SPS-5 sites.
93

Table 43. Ranking of rehabilitation strategies for rutting for SPS-5 sites.

Statistical 

Relevance (Y/N)

Rutting

Short-Term Long-Term

Y (p < 0.0001) Y (p < 0.0001)

Ranking 

(if relevant)

Ranking Strategy Ranking Strategy

1 No mill, thin, virgin 1 No mill, thin, virgin

1 No mill, thin, RAP 1 Mill, thick, RAP

1 Mill, thin, RAP 1 No mill, thin, RAP

1 Mill, thick, RAP 1 Mill, thin, virgin

1 Mill, thin, virgin 1 No mill, thick, RAP

1 No mill, thick, RAP 1 Mill, thin, RAP

1 No mill, thick, virgin 1 No mill, thick, virgin

8 Mill, thick, virgin 8 Mill, thick, virgin

9 Control 9 Control

Design features were found to have an impact on only long-term performance associated with 

fatigue, longitudinal, and transverse cracking. Figure 29 through figure 31 present descriptive 

statistics for performance rankings among all sites. Based on the Friedman test, the ranking of 

best-performing rehabilitation strategies for cracking was created (see table 44 through table 46). 

Figure 29 (p = 0.0009, ANOVA chi-square = 26.5074) and table 44 suggest that thick overlays 

performed better in the long term for fatigue cracking. As expected, it was evident from the 

figure that the no treatment control alternative performed the poorest in regards to fatigue 

cracking. The ranking of alternatives was more equally distributed when comparing mix types; 

however, out of the top three alternatives, two were virgin mix overlays. Overall, mix type had 

limited influence on long-term fatigue cracking performance. The results also suggested that 

milling prior to overlay improved performance. Two of the top three alternatives included 

milling prior to the overlay.

The results described in figure 30 (p < 0.0001, ANOVA chi-square = 33.6741) and table 45

suggested that thick overlays were better to mitigate transverse cracking. The two best-ranked 

sections had virgin mix overlays, but overall the performances of virgin and RAP mix overlays 

were similar. Sections that were milled prior to overlay consistently performed better than 

nonmilled ones.

The results for longitudinal cracking in figure 31 (p = 0.0011, ANOVA chi-square = 25.8407) 

and table 46 suggested that none of the design features had a significant influence on 

performance. Although the best alternative was milling and overlaying with a thick virgin mix, 

the remaining alternatives that ranked second consisted of different combinations of design 

features with no clear trend to which one provided better performance associated with 

longitudinal cracking.
94

1 ft2 = 0.093 m2

Figure 29. Graph. Fatigue cracking WD values for long-term performance of SPS-5 sites.

1 ft = 0.305 m

Figure 30. Graph. Transverse cracking WD values for long-term performance of 

SPS-5 sites.

1 ft = 0.305 m

Figure 31. Graph. Longitudinal cracking WD values for long-term performance of 

SPS-5 sites.
95

Table 44. Ranking of rehabilitation strategies for fatigue cracking at SPS-5 sites.

Statistical 

Relevance (Y/N)

Long-Term

Y p = 0.0009

Ranking

(if relevant)

Ranking Strategy

1 No mill, thick, virgin

1 Mill, thick, RAP

1 Mill, thick, virgin

4 Mill, thin, virgin

4 No mill, thick, RAP

4 No mill, thin, virgin

4 Mill, thin, RAP

4 No mill, thin, RAP

9 Control

Table 45. Ranking of rehabilitation strategies for transverse cracking at SPS-5 sites.

Statistical 

Relevance (Y/N)

Long-Term

Y p < 0.0001

Ranking

(if relevant)

Ranking Strategy

1 Mill, thick, virgin

2 No mill, thick, virgin

3 Mill, thick, RAP

3 Mill, thin, RAP

3 Mill, thin, virgin

3 No mill, thick, RAP

7 No mill, thin, RAP

8 No mill, thin, virgin

8 Control

Table 46. Ranking of rehabilitation strategies for longitudinal cracking at SPS-5 sites.

Statistical 

Relevance (Y/N)

Long-Term

Y p = 0.0011

Ranking

(if relevant)

Ranking Strategy

1 Mill, thick, virgin

2 Mill, thin, virgin

2 No mill, thick, virgin

2 Mill, thin, RAP

2 No mill, thin, virgin

2 Mill, thick, RAP

7 No mill, thick, RAP

7 Control

7 No mill, thin, RAP
96

The results obtained in the consolidated analysis agreed for the most part with the results found 

in the individual site analysis. Overlay thickness was the most influential design feature. Thick 

overlays consistently performed better, as expected. The impact of thickness on performance was

more evident in the long term (more than 5 years) rather than the short term for most of the 

distresses used as performance measures. The exception was rutting, for which no evidence was 

found suggesting that either thin or thick overlays provided less rutted pavements.

The majority of sites did not show significant differences in performance between sections 

overlaid with virgin and RAP mixes. However, when differences existed, they were mostly in 

favor of virgin mixes.

The analysis of milling prior to overlay suggested that replacing the distressed portion of the 

surface layer improved the performance for the majority of distresses commonly observed in 

flexible pavements.

Influence of Site Condition

The influence of site condition was determined by three variables: (1) pavement surface 

condition prior to rehabilitation, (2) climate, and (3) traffic levels. These three conditions were 

determined for each site, and the Friedman test was repeated by grouping the sites according to 

each of the following variables:

• Pavement condition: Fair versus poor.

• Climate condition: Wet versus dry and freeze versus no-freeze.

• Traffic: Low versus high.

The designation of fair versus poor was assigned by the owner agency nominating the SPS-5 

project. These ratings were purely subjective and not based on the actual level of existing 

distresses prior to rehabilitation. They were used only to ensure a range of surface conditions of 

the original pavement before rehabilitation. However, the assessment of distresses prior to 

overlay indicated that, on average, fair pavements had IRI values of 9.50 ft/mi (1.8 m/km) with

0.39 inches (10 mm) or less of rutting and up to 1,237.86 ft2 (115 m

2

) of fatigue cracking per 

section. Poor pavements had roughness of 8.71 ft/mi (1.65 m/km) with 0.59 inches (15 mm) of 

rutting and up to 1,937.52 ft2 (180 m

2

) of fatigue cracking per section.

Climate condition was defined based on the freeze index and average rainfall for each site. Sites 

with an average annual rainfall greater than 39 inches (1,000 mm) were classified as wet, and 

sites with less than 39 inches (1,000 mm) of rain were classified as dry. Similarly, sites with a 

freeze index greater than 140 °F (60 °C) were classified as a freezing climate, and sites with less 

than 140 °F (60 °C) were designated as a no-freeze climate. These classifications are part of the 

LTPP experiment definition.

The classification of traffic was defined based on volume and commercial vehicle distribution. 

These characteristics were simple to evaluate and, at the same time, most influential on pavement 

performance predictions estimated with MEPDG. The combination of criteria generated two 
97

groups of sites: low traffic and high traffic. Table 47 describes the characteristics of both groups 

used in this study. Georgia and Texas did not have any traffic information.

Table 47. Criteria for evaluating traffic characteristics of SPS-5 sites.

Traffic Characteristics Low Traffic High Traffic

AADTT 340–950 750–2,750

Vehicle class 5 

(percent in volume) 25–75 5–20

Vehicle class 9 

(percent in volume) 10–50 40–85

SPS-5 sites

Alabama, Florida, Maine,

Maryland, Minnesota, 

Missouri, and Oklahoma

Arizona, California, Colorado, 

Mississippi, Montana, New 

Jersey, New Mexico, Alberta,

and Manitoba

The analysis followed the same steps presented in the previous section. Rankings of 

rehabilitation strategies were developed for each group of sites using descriptive statistics and 

the paired analyses from the Friedman test when statistical differences in performance were 

found. The results are summarized in the tables presented in appendix C. 

Table 48 and table 49 provide examples of how the data were summarized. These tables show 

the ranking of best-performing sections based on long-term performance for roughness and 

rutting in sections with fair and poor surface conditions prior to rehabilitation.

The examples illustrate the impact of site conditions on performance of rehabilitated 

flexible pavements. They suggest that rehabilitation strategies with milling and virgin 

mix overlays were better to improve roughness performance in pavements with poor surface

condition. If surface condition was fair, RAP mixes provided a slight advantage in terms of 

roughness performance.

According to the ranking for rutting performance, rehabilitation strategies with milling and thin 

overlays with virgin mixes were the best alternatives when pavements had poor surface condition 

before the overlay. When surface conditions were fair, the impact of design features was not as 

significant. In fact, rehabilitation strategies with milling prior to overlay were among the worst

ranked for rutting performance.
98

Table 48. Summary of rankings for long-term roughness and rutting performance of SPS-5 

sites in fair surface condition prior to overlay.

Statistical 

Relevance (Y/N)

Distress

Roughness Rutting

Y p = 0.0001 Y p = 0.0044

Ranking

(if relevant)

Ranking Strategy Ranking Strategy

1 (Best) Mill, thick, RAP 1 (Best) Mill, thick, RAP

2 No mill, thick, RAP 1 No mill, thin, virgin

2 Mill, thin, virgin 1 No mill, thick, RAP

2 Mill, thin, RAP 4 No mill, thick, virgin

5 Mill, thick, virgin 4 No mill, thin, RAP

5 No mill, thick, virgin 4 Mill, thin, RAP

5 No mill, thin, virgin 4 Mill, thin, virgin

8 No mill, thin, RAP 4 Mill, thick, virgin

9 (Worst) Control 9 (Worst) Control

Table 49. Summary of rankings for long-term roughness and rutting performance of SPS-5 

sites in poor surface condition prior to overlay.

Statistical 

Relevance (Y/N)

Distress

Roughness Rutting

Y p = 0.019 Y p = 0.0015

Ranking

(if relevant)

Ranking Strategy Ranking Strategy

1 Mill, thick, RAP 1 No mill, thin, virgin

2 Mill, thin, virgin 1 Mill, thin, virgin

2 Mill, thick, virgin 3 Mill, thin, RAP

2 No mill, thick, RAP 3 No mill, thin, RAP

2 No mill, thick, virgin 3 No mill, thick, virgin

2 No mill, thin, virgin 3 No mill, thick, RAP

2 No mill, thin, RAP 3 Mill, thick, RAP

2 Mill, thin, RAP 3 Mill, thick, virgin

9 None 9 None

A detailed assessment of the combined results for each of the analyses performed was assembled 

in tables for better visualization and interpretation of results. These tables were created for each 

distress and performance period (short-term and long-term performance) with the exception of 

fatigue and longitudinal cracking, which only presented statistically significant differences for 

long-term performance data . Table 50 and table 51 present the results for short-term and longterm roughness performance. 

Table 52 and table 53 summarize the results for rutting. Table 54 shows the results for long-term 

fatigue cracking, and table 55 and table 56 present the results for short-term and long-term 

transverse cracking performance. Finally, table 57 summarizes the results for long-term 

longitudinal cracking. The best alternatives with statistical relevance are shown in each cell. 

The number before the treatment indicates its ranking among all alternatives.
99

The summary of best-performing strategies can be used as a practical guide to help select the 

best rehabilitation option based on performance. For example, if the section is located in a wet 

freeze region, and the pavement is in fair surface condition with low traffic levels, based on longterm roughness performance, three alternatives in table 51 provide equivalent best performance 

(mill, thick, and RAP; mill, thin, and virgin; and no mill, thick, and RAP). This performancebased selection can be further improved by evaluating material availability, costs, and other 

relevant issues.

These summary tables provide clear information for choosing the best rehabilitation treatment 

based on distress type and site condition. Moreover, the influence of different site conditions can 

be determined by observing the best treatments for each condition.
Table 50. Summary based on short-term roughness performance of SPS-5 pavement structures.

Climate

Traffic/Surface Condition

High Low

Poor Fair Poor Fair

Wet

Freeze

1: Mill, thick, virgin 1: Mill, thick, virgin 1: Mill, thick, virgin 1: Mill, thick, virgin

2: Mill, thick, RAP 2: Mill, thick, RAP 2: Mill thick, RAP 2: Mill, thick, RAP

3: No mill, thick, RAP 3: No mill, thick, RAP 3: No mill, thick, RAP 2: No mill, thick, RAP

4: Mill, thin, virgin 4: Mill, thin, RAP 4: Mill, thin, virgin 4: Mill, thin, RAP

Nofreeze

1: Mill, thick, virgin 1: Mill, thick, virgin 1: Mill, thick, virgin 1: Mill, thick, virgin

2: Mill, thick, RAP 2: Mill thick, RAP 2: Mill, thick, RAP 2: Mill, thick, RAP

3: Mill, thin, virgin 3: No mill, thick, RAP 3: No mill, thick, RAP 3: No mill, thick, RAP

3: No mill, thick, RAP 4: Mill, thin, RAP 4: Mill, thin, virgin 4: Mill, thin, RAP

Dry

Freeze

1: Mill, thick, RAP 1: Mill, thick, RAP 1: Mill, thick, RAP 1: Mill, thick, RAP

1: Mill, thick, virgin 1: Mill, thick, virgin 1: Mill, thick, virgin 1: Mill, thick, virgin

3: No mill, thick, RAP 3: No mill, thick RAP 3: No mill, thick, RAP 3: No mill, thick, RAP

— 4: Mill, thin, RAP — 4: Mill, thin, RAP

Nofreeze

1: Mill, thick RAP 1: Mill, thick, RAP 1: Mill, thick, RAP 1: Mill, thick, RAP

1: Mill, thick, virgin 1: Mill thick, virgin 1: Mill, thick, virgin 1: Mill, thick, virgin

— 3: Mill thin, RAP 3: No mill, thick, RAP 3: No mill, thick, RAP

— 3: No mill, thick, RAP — 4: Mill, thin, RAP

— Indicates that no preferred treatment was statistically found.

100
Table 51. Summary based on long-term roughness performance of SPS-5 pavement structures.

Climate

Traffic Surface/Condition

High Low

Poor Fair Poor Fair

Wet

Freeze

1: Mill, thick, RAP 1: Mill, thick, RAP 1: Mill, thick, RAP 1: Mill, thick, RAP

1: Mill, thick, virgin 1: Mill, thin, virgin 1: Mill, thick, virgin 1: Mill, thin, virgin

1: Mill, thin, virgin 1: No mill, thick, RAP 1: Mill, thin, virgin 1: No mill, thick, RAP

1: No mill, thick, RAP 4: Mill, thick, virgin 1: No mill, thick, RAP 4: Mill, thick, virgin

No-freeze

1: Mill, thick, RAP 1: Mill, thick, RAP 1: Mill, thick, RAP 1: Mill, thick, RAP

1: Mill, thick, virgin 1: Mill, thin, virgin 1: Mill, thick, virgin 1: Mill, thin, virgin

1: Mill, thin, virgin 1: No mill, thick, RAP 1: Mill, thin, virgin 1: No mill, thick, RAP

1: No mill, thick, RAP 4: Mill, thick, virgin 1: No mill, thick, RAP 4: Mill, thick, virgin

Dry

Freeze

1: Mill, thick, RAP 1: Mill, thick, RAP 1: Mill, thick, RAP 1: Mill, thick, RAP

1: No mill, thick, RAP 1: No mill, thick, RAP 1: No mill, thick, RAP 1: No mill, thick, RAP

3: Mill, thick, virgin 3: Mill, thin, virgin 3: Mill, thick, virgin 3: Mill, thin, virgin

3: Mill, thin, virgin 4: Mill, thick, virgin 3: Mill, thin, virgin 4: Mill, thick, virgin

No-freeze

1: Mill, thick, RAP 1: Mill, thick, RAP 1: Mill, thick, RAP 1: Mill, thick, RAP

1: No mill, thick, RAP 1: No mill, thick, RAP 1: No mill, thick, RAP 1: No mill, thick, RAP

3: Mill, thick, virgin 3: Mill, thin, virgin 3:Mill, thick, virgin 3: Mill, thin, virgin

3: Mill, thin, virgin 4: Mill, thick, virgin 3: Mill, thin, virgin 4: Mill, thick, virgin

101
Table 52. Summary based on short-term rutting performance of SPS-5 pavement structures.

Climate

Traffic Surface/Condition

High Low

Poor Fair Poor Fair

Wet

Freeze

1: No mill, thin, virgin 1:No mill, thin, RAP 1: No mill, thin, virgin 1: No mill, thin, virgin

2: No mill, thin, RAP 1: No mill, thin, virgin 2: Mill, thin, virgin 2: No mill, thin, RAP

3: Mill, thick, RAP 3: Mill, thick, RAP 3: No mill, thin, RAP 3: Mill, thick, RAP

3: Mill, thin, virgin 4: Mill, thin, RAP 4: Mill, thick, RAP 3: Mill, thin, RAP

Nofreeze

1: No mill, thin, virgin 1: No mill, thin, virgin 1: Mill, thin, virgin 1: No mill, thin, virgin

2: Mill, thin, virgin 2: No mill, thin, RAP 1: No mill, thin, virgin 2: Mill, thin, virgin

3: No mill, thin, RAP 3: Mill, thick, RAP 3: Mill, thin, RAP 3: Mill, thin, RAP

4: Mill, thick, RAP 3: Mill, thin, RAP 3: No mill, thin, RAP 3: No mill, thin, RAP

Dry

Freeze

1: No mill, thin, virgin 1: Mill, thick, RAP 1: No mill, thin, virgin 1: No mill, thin, virgin

2: Mill, thick, RAP 1: No mill, thin, RAP 2: Mill, thick, RAP 2: Mill, thick, RAP

2: No mill, thin, RAP 1: No mill, thin, virgin 2: Mill, thin, RAP 2: Mill, thin, RAP

4: Mill, thin, RAP 4: Mill, thin, RAP 2: Mill, thin, virgin 2: No mill, thick, RAP

Nofreeze

1: No mill, thin, virgin 1: No mill, thin, virgin 1: No mill, thin, virgin 1: No mill, thin, virgin

2: Mill, thick, RAP 2: Mill, thick, RAP 2: Mill, thin, virgin 2: Mill, thin, RAP

2: Mill, thin, RAP 2: Mill, thin, RAP 3: Mill, thin, RAP 3: Mill, thick, RAP

2: Mill, thin, virgin 2: No mill, thin, RAP 4: Mill, thick, RAP 3: Mill, thin, virgin

10

2
Table 53. Summary based on long-term rutting performance of SPS-5 pavement structures.

Climate

Traffic/Surface Condition

High Low

Poor Fair Poor Fair

Wet

Freeze

1: No mill, thin, virgin 1: No mill, thin, virgin 1: No mill, thin, virgin 1: No mill, thin, virgin

2: Mill, thin, virgin 2: Mill, thick, RAP 2: Mill, thin, virgin 2: Mill, thick, RAP

3: Mill, thick, RAP 2: No mill, thick, RAP 3: Mill, thick, RAP 2: Mill, thin, virgin

3: No mill, thick, RAP 4: Mill, thin, virgin 3: No mill, thick, RAP 2: No mill, thick, RAP

Nofreeze

1: Mill, thin, virgin 1: No mill, thin, virgin 1: Mill, thin, virgin 1: No mill, thin, virgin

1: No mill, thin, virgin 2: Mill, thin, virgin 1: No mill, thin, virgin 2: Mill, thin, virgin

3: Mill, thin, RAP 3: Mill, thick, RAP 3: Mill, thin, RAP 3: Mill, thick, RAP

4: Mill, thick, RAP 3: Mill, thin, RAP 4: Mill, thick, RAP 3: Mill, thin, RAP

Dry

Freeze

1: No mill, thin, virgin 1: Mill, thick, RAP 1: No mill, thin, virgin 1: No mill, thin, virgin

2: Mill, thick, RAP 1: No mill, thin, virgin 2: Mill, thick, RAP 2: Mill, thick, RAP

2: No mill, thick, virgin 3: No mill, thick, RAP 2: Mill, thin, virgin 3: No mill, thick, RAP

4: Mill, thin, virgin 3: No mill, thick, virgin 2: No mill, thick, virgin 3: No mill, thick, virgin

Nofreeze

1: No mill, thin, virgin 1:No mill, thin, virgin 1: No mill, thin, virgin 1: No mill, thin, virgin

2: Mill, thin, virgin 2: Mill, thick, RAP 2: Mill, thin, virgin 2: Mill, thick, RAP

3: Mill, thick, RAP 3: Mill, thin, RAP 3: Mill, thick, RAP 2: Mill, thin, virgin

3: Mill, thin, RAP 3: Mill, thin, virgin 3: Mill, thin, RAP 4: Mill, thin, RAP

10

3
Table 54. Summary based on long-term fatigue cracking performance of SPS-5 pavement structures.

Climate

Traffic Surface/Condition

High Low

Poor Fair Poor Fair

Wet

Freeze

1: Mill, thick, virgin 1: Mill, thick, virgin 1: Mill, thick, virgin 1: Mill, thick, virgin

2: Mill, thick, RAP 2: Mill, thick, RAP 2: Mill, thick, RAP 2: Mill, thick, RAP

2: No mill, thick, virgin 2: No mill, thick, virgin 2: Mill, thin, virgin 2: Mill, thin, virgin

4: Mill, thin, virgin 4: Mill, thin, virgin 2: No mill, thick, RAP 2: No mill, thick, RAP

Nofreeze

1: Mill, thick, virgin 1: Mill, thick, virgin 1: Mill, thick, virgin 1: Mill, thick, virgin

2: Mill, thick, RAP 2: Mill, thick, RAP 2: Mill, thick, RAP 2: Mill, thick, RAP

2: No mill, thick, virgin 2: No mill, thick, virgin 2: Mill, thin, virgin 2: Mill, thin, virgin

4: Mill, thin, virgin 4: Mill, thin, virgin 2: No mill, thick, RAP 2: No mill, thick, RAP

Dry

Freeze

1: Mill, thick, RAP 1: Mill, thick, RAP 1: Mill, thick, RAP 1: Mill, thick, RAP

1: Mill, thick, virgin 1: Mill, thick, virgin 1: Mill, thick, virgin 1: Mill, thick, virgin

1: No mill, thick, virgin 1: No mill, thick, virgin 1: No mill, thick, virgin 1: No mill, thick, virgin

— — — —

Nofreeze

1: Mill, thick, RAP 1: Mill, thick, RAP 1: Mill, thick, RAP 1: Mill, thick, RAP

1: Mill, thick, virgin 1: Mill, thick, virgin 1: Mill, thick, virgin 1: Mill, thick, virgin

1: No mill, thick, virgin 1: No mill, thick, virgin 1: No mill, thick, virgin 1: No mill, thick, virgin

4: Mill, thin, RAP 4: Mill, thin, RAP 4: Mill, thin, RAP 4: Mill, thin, RAP

— Indicates that no preferred treatment was statistically found.

10

4
Table 55. Summary based on short-term transverse cracking performance of SPS-5 pavement structures.

Climate

Traffic/Surface Condition

High Low

Poor Fair Poor Fair

Wet

Freeze

— — — —

— — — —

— — — —

— — — —

Nofreeze

1: Mill, thick, virgin 1: Mill, thick, virgin 1: Mill, thick, virgin 1: Mill, thick, virgin

1: No mill, thick, virgin 1: No mill, thick, virgin 1: No mill, thick, virgin 1: No mill, thick, virgin

— — — —

— — — —

Dry

Freeze

— — — —

— — — —

— — — —

— — — —

Nofreeze

1: Mill, thick, virgin 1: Mill, thick, virgin 1: Mill, thick, virgin 1: Mill, thick, virgin

1: No mill, thick, virgin 1: No mill, thick, virgin 1: No mill, thick, virgin 1: No mill, thick, virgin

— — — —

— — — —

— Indicates that no preferred treatment was statistically found.

10

5
Table 56. Summary based on long-term transverse cracking performance of SPS-5 pavement structures.

Climate

Traffic/Surface Condition

High Low

Poor Fair Poor Fair

Wet

Freeze

1: Mill, thick, virgin 1: Mill, thick, virgin 1: Mill, thick, virgin 1: Mill, thick, virgin

1: No mill, thick, virgin 2: No mill, thick, virgin 1: No mill, thick, virgin 2: No mill, thick, virgin

— 3: Mill, thick, RAP 3: Mill, thick, RAP 3: Mill, thick, RAP

— — 3: No mill, thick, RAP 4: No mill, thick, RAP

Nofreeze

1: Mill, thick, virgin 1: Mill, thick, virgin 1: Mill, thick, virgin 1: Mill, thick, virgin

1: No mill, thick, virgin 2: No mill, thick, virgin 1: No mill, thick, virgin 2: No mill, thick, virgin

— 3: Mill, thick, RAP 3: Mill, thick, RAP 3: Mill, thick, RAP

— — 3: No mill, thick, RAP 4: No mill, thick, RAP

Dry

Freeze

1: Mill, thick, virgin 1: Mill, thick, virgin 1: Mill, thick, virgin 1: Mill, thick, virgin

1: No mill, thick, virgin 2: Mill, thick, RAP 1: No mill, thick, virgin 2: Mill, thick, RAP

3: Mill, thick, RAP 2: No mill, thick, virgin 3: Mill, thick, RAP 2: No mill, thick, virgin

3: Mill, thin, RAP 4: Mill, thin, RAP 3: No mill, thick, RAP 4: No mill, thick, RAP

Nofreeze

1: Mill, thick, virgin 1: Mill, thick, virgin 1: Mill, thick, virgin 1: Mill, thick, virgin

1: No mill, thick, virgin 2: No mill, thick, virgin 1: No mill, thick, virgin 2: No mill, thick, virgin

3: Mill, thick, RAP 3: Mill, thick, RAP 3: Mill, thick, RAP 3: Mill, thick, RAP

3: Mill, thin, RAP 4: Mill, thin, RAP 3: No mill, thick, RAP 4: No mill, thick, RAP

— Indicates that no preferred treatment was statistically found.

10

6
Table 57. Summary based on long-term longitudinal cracking performance of SPS-5 pavement structures.

Climate

Traffic/Surface Condition

High Low

Poor Fair Poor Fair

Wet

Freeze

1: Mill, thick, virgin 1: Mill, thick, virgin 1: Mill, thick, virgin 1: Mill, thick, virgin

1: Mill, thin, virgin 1: Mill, thin, virgin 1: Mill, thin, virgin 1: Mill, thin, virgin

3: Mill, thick, RAP 3: Mill, thick, RAP 3: Mill, thick, RAP 3: Mill, thick, RAP

3: Mill, thin, RAP 3: Mill, thin, RAP 3: Mill, thin, RAP 3: Mill, thin, RAP

Nofreeze

1: Mill, thick, virgin 1: Mill, thick, virgin 1: Mill, thick, virgin 1: Mill, thick, virgin

1: Mill, thin, virgin 1: Mill, thin, virgin 1: Mill, thin, virgin 1: Mill, thin, virgin

3: Mill, thick, RAP 3: Mill, thick, RAP 3: Mill, thick, RAP 3: Mill, thick, RAP

3: Mill, thin, RAP 3: Mill, thin, RAP 3: Mill, thin, RAP 3: Mill, thin, RAP

Dry

Freeze

1: Mill, thick, RAP 1: Mill, thick, virgin 1: Mill, thick, RAP 1: Mill, thick, virgin

1: Mill, thick, virgin 1: Mill, thin, virgin 1: Mill, thick, virgin 1: Mill, thin, virgin

1: Mill, thin, RAP 3: Mill, thick, RAP 1: Mill, thin, RAP 3: Mill, thick, RAP

1: Mill, thin, virgin 3: Mill, thin, RAP 1: Mill, thin, virgin 3: Mill, thin, RAP

Nofreeze

1: Mill, thick, RAP 1: Mill, thick, virgin 1: Mill, thick, RAP 1: Mill, thick, virgin

1: Mill, thick, virgin 1: Mill, thin, virgin 1: Mill, thick, virgin 1: Mill, thin, virgin

1: Mill, thin, RAP 3: Mill, thick, RAP 1: Mill, thin, RAP 3: Mill, thick, RAP

1: Mill, thin, virgin 3: Mill, thin, RAP 1: Mill, thin, virgin 3: Mill, thin, RAP

10

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108

The summary tables show only alternatives in which statistically significant differences in 

performance were identified with the Friedman test analysis. They were created by considering 

the best alternatives from each analysis performed in the dataset. These selected rehabilitation 

alternatives were then grouped for each combination of site conditions.

According to the summary tables, the following conclusions were made when roughness 

performance was considered:

• Rehabilitation strategies with milling prior to overlay provided better roughness 

performance for all site conditions.

• Strategies with thick overlays provided smoother pavements for all site conditions, 

as expected.

• Strategies with virgin or RAP mixes had equivalent performances when used under 

wet conditions.

• Strategies with RAP mixes ranked better when used in dry conditions.

• Traffic level and freeze conditions did not impact roughness performance ranking.

The analysis of rutting indicated the following:

• Rehabilitation strategies with thin overlays performed better than thick overlays in the 

short term. In the long term, the ranking of best strategies was more evenly distributed for 

both thick and thin overlays.

• The ranking of best strategies was evenly distributed among the two mix types in the 

short term. In the long term, rehabilitation strategies with virgin mixes were in the top 

ranking of performance more frequently, with the exception of fair pavement surface 

under freeze conditions, which corresponded to 33 percent of all sites.

• Strategies with milling did not improve rutting performance more than alternatives 

without milling.

• The level of traffic did not impact the rutting performance of selected 

rehabilitation strategies.

The analysis of fatigue cracking indicated the following:

• Short-term fatigue cracking performance was not significantly affected by any design 

features under any site conditions.

• Rehabilitation strategies with thick overlays provided better performance for fatigue 

cracking under all site conditions that were evaluated.

• Strategies with milling prior to overlay performed better to mitigate development and 

propagation of fatigue cracking in all site conditions.
109

• Alternatives without milling performed as well as solutions with milling in regions with 

dry climates.

• Strategies with RAP mixes were better ranked for sites with low traffic.

The analysis of transverse cracking indicated the following:

• There were no differences identified in short-term performance among the rehabilitation 

strategies in freezing zones.

• Among the sites located in no-freeze zones, the remaining site conditions did not have 

any impact on short-term performance.

• Strategies with virgin mixes and thick overlays ranked best for long-term transverse 

cracking performance.

• Strategies with RAP mixes performed better than virgin mixes when the site had low 

traffic and when it had high traffic and dry climate.

• Milling prior to overlay did not improve performance more than alternatives 

without milling.

The analysis of longitudinal cracking indicated the following:

• Rehabilitation strategies with milling prior to overlay were consistently better for 

improving performance than alternatives without milling.

• Strategies with virgin mixes were consistently better than alternatives with RAP in sites 

located in wet climates.

• There was no difference in ranking between strategies with virgin and RAP mixes in 

dry conditions.

• Overlay thickness was not a significant factor affecting performance associated with 

longitudinal cracking.

The summary tables presented in this section, along with a complete set of tables with 

descriptive statistics for all the analyses conducted, are provided in appendix C.

EFFECT OF DESIGN AND CONTRUCTION FEATURES AND SITE CONDITIONS ON 

RESPONSE OF REHABILITATED FLEXIBLE PAVEMENTS

The study to evaluate the impact of design features and site conditions on response of 

rehabilitated flexible pavements followed the same approach used in the analysis of 

performance. FWD deflection data are available in the LTPP database and used as the response 

measure of the pavement structure. Deflections in the wheel path of the LTPP lane were used as 

indicators of structural response.
110

The same analysis sequence applied to the study of performance was applied to the study of 

response. The first task was to evaluate individual sites and how the pavement structural 

responses were affected by each rehabilitation strategy and its design features. Since the analysis 

was carried out for each site separately, the deflection values were not adjusted for temperature, 

and the FWD survey was assumed to take place under similar conditions for all sections of a 

given site. There were small variations in surface temperature throughout the day, but they were 

considered minor and unlikely to significantly affect the total pavement stiffness. The variation 

of deflections over time and over the seasons throughout the year was used as input for the 

repeated ANOVA.

Individual Analysis of SPS-5 Sites

Summary tables containing the results of the statistical analysis for pavement response for each 

site are presented in appendix A. 

A compilation of results was created by identifying the number of sites in which design features 

had provided differences in response throughout the site’s service life. For example, if sections 

with thick overlays had lower deflection measurements than thin overlay sections in one site, the 

thick overlay was marked for this site, and the process was repeated for all sites. Figure 32

summarizes the percentage of sites in which differences in response were identified.

Figure 32. Graph. Percentage of SPS-5 sections with lower maximum deflection based on 

repeated measures ANOVA results.

The key findings from the assessment of individual sites were as follows:

• As expected, rehabilitation strategies with thick overlays had lower maximum deflection 

values compared to alternatives with thin overlays.

• There were no differences in pavement response between strategies using virgin and RAP

mix overlays.
111

• Strategies with milling prior to overlay did not affect the structural response more than 

alternatives without milling.

Consolidated Analysis

The consolidated analysis involved the simultaneous analysis of all sites in the SPS-5 experiment 

using the Friedman test. A follow-up analysis was performed by grouping the data by site 

condition to evaluate the impact of design features and site conditions for short-term and 

long-term performance. WD was the parameter used for this analysis.

After the data were processed and verified for quality, WD was computed for each section in 

each SPS-5 site. The values are shown in table 58. The Friedman test used WD to create the 

ranking of performance from the lowest to the highest value for each site in the dataset. Ranking 

statistics for each type of section were then used to calculate the chi-square value, and this 

parameter was used to determine if statistical differences existed among the performance 

rankings of the sections.

The Friedman test output for maximum deflection in the wheel path is provided in figure 33, and

it presents the average and standard deviation values for the WD maximum deflection for each 

type of rehabilitation strategy among all sites analyzed. The results indicate that there were at 

least two sections with statistically different structural responses (p < 0.0001, ANOVA chisquare = 78.737). Therefore, the ranking of sections (i.e., rehabilitation strategies) for structural 

response can be created using Friedman paired analyses. The results of the paired analyses were 

used to define a practical ranking for structural response (see table 59).
Table 58. WD-deflection values at the center of the load for SPS-5 sites.

Section

Experiment Design Sites (State Codes)/Average Deflection WD Values (microns)

Mill Mix

Thickness 

(mm) 1 4 6 8 12 13 23 24 27 28 29 30 34 35 40 48 81 83

0501 No None 374 271 249 174 164 323 202 285 198 333 213 394 374

0502 No RAP 51 264 292 319 260 190 102 134 218 250 270 207 465 214 241 168 139 465 257

0503 No RAP 127 115 196 151 197 144 62 107 157 189 209 112 383 33 139 158 149 272 182

0504 No Virgin 127 130 77 131 155 134 69 106 164 197 143 109 317 104 175 203 148 272 186

0505 No Virgin 51 286 256 348 275 186 85 132 265 261 198 139 389 131 271 205 112 273 304

0506 Yes Virgin 51 156 112 271 319 182 75 141 161 243 209 144 420 37 294 259 134 384 293

0507 Yes Virgin 127 168 56 167 288 125 63 106 162 177 126 116 292 36 222 145 110 292 180

0508 Yes RAP 127 162 99 164 205 128 58 108 168 177 179 84 321 30 157 232 122 217 207

0509 Yes RAP 51 179 202 330 240 166 90 145 190 255 212 153 540 35 217 245 138 324 320

1 μm = 0.039 mil

1 inch = 25.4 mm

Note: Higher WD values indicate higher maximum deflection for FWD measurements for pavements. Blank cells indicate data are not available.

11

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113

1μm = 0.039 mil

Figure 33. Graph. Maximum deflection (wheel path of LTPP lane) WD values at 

SPS-5 sites.

Table 59. Ranking of rehabilitation strategies for structural response at SPS-5 sites.

Statistical 

Relevance (Y/N)

Deflection

Y p < 0.0001

Ranking

(if relevant)

Ranking Strategy

1 (Lowest) Mill, thick, virgin

2 Mill, thick, RAP

2 No mill, thick, RAP

2 No mill, thick, virgin

5 Mill, thin, virgin

6 No mill, thin, virgin

6 Mill, thin, RAP

6 No mill, thin, RAP

6 None

The results in table 59 and figure 29 support the findings from the analysis of individual sites 

that suggest that thick overlays provided lower maximum deflections compared to alternatives 

with thin overlays. The ranking also shows that there were no significant differences in response 

for strategies using either virgin or RAP mix overlays, and they are intertwined in the ranking. 

The results further suggest that milling prior to overlay may reduce the level of pavement 

response, as strategies with this design feature were ranked among those with lower deflections 

for FWD measurements.

Influence of Site Condition

Similar to the pavement performance analysis, the influence of site conditions was determined by 

three variables: (1) pavement surface condition prior to rehabilitation, (2) climate, and (3) traffic 

levels. The analysis followed the same steps described in the previous section. Rankings of 
114

rehabilitation strategies were developed for each group of sites using descriptive statistics and 

the paired analyses from the Friedman test when statistical differences in performance were 

found in the first step. The results were summarized in tables and are presented in appendix C. 

After a careful assessment of the results from the analyses performed for each group, summary 

tables including all possible combinations of site conditions were assembled. Table 60 presents 

the results, and the alternatives with lower deflections with statistical relevance are shown in 

each cell. The number before the treatment indicates its ranking among all alternatives.

Table 60 can be used as a practical guide to help select rehabilitations strategies that provide low 

deflection values. For example, if the section is located in a wet freeze region and the pavement 

is in fair surface condition with low traffic levels, an alternative with a thick RAP overlay 

without milling is indicated. However, if the same section is in poor condition, the alternative 

indicated is one with milling and a thick virgin overlay.

These summary tables provide clear information to identify the rehabilitation treatment with the 

lowest and highest pavement responses based on site conditions, and the influence of different 

site condition can be determined by observing the ranking of treatments for each condition.
Table 60. Summary based on structural response (maximum deflection in the wheel path of the LTPP lane) of SPS-5 

pavement structures.

Climate

Traffic/Surface Condition

High Low

Poor Fair Poor Fair

Wet

Freeze

1: Mill, thick, RAP 1: Mill, thick, RAP 1: Mill, thick, virgin 1: No mill, thick, RAP

1: No mill, thick, RAP 1: No mill, thick, RAP 1: No mill, thick, RAP 2: Mill, thick, RAP

1: No mill, thick, virgin 3: No mill, thick, virgin 1: No mill, thick, virgin 2: Mill, thick, virgin

4: Mill, thick, virgin 4: Mill, thick, virgin 4: Mill, thick, RAP 2: No mill, thick, virgin

Nofreeze

1: No mill, thick, virgin 1: No mill, thick, virgin 1: Mill, thick, virgin 1: Mill, thick, virgin

2: Mill, thick, virgin 2: Mill, thick, RAP 1: No mill, thick, virgin 1: No mill, thick, virgin

3: Mill, thick, RAP 2: Mill, thick, virgin 3: No mill, thick, RAP 3: No mill, thick, RAP

3: No mill, thick, RAP 2: No mill, thick, RAP 4: Mill, thick, RAP 4: Mill, thick, RAP

Dry

Freeze

1: Mill, thick, RAP 1: Mill, thick, RAP 1: Mill, thick, virgin 1: No mill, thick, RAP

1: No mill, thick, RAP 1: No mill, thick, RAP 1: No mill, thick, RAP 2: Mill, thick, RAP

1: No mill, thick, virgin 3: No mill, thick, virgin 1: No mill, thick, virgin 2: Mill, thick, virgin

4: Mill, thick, virgin 4: Mill, thick, virgin 4: Mill, thick, RAP 2: No mill, thick, virgin

Nofreeze

1: No mill, thick, virgin 1: No mill, thick, virgin 1: Mill, thick, virgin 1: Mill, thick, virgin

2: Mill, thick, virgin 2: Mill, thick, RAP 1: No mill, thick, virgin 1: No mill, thick, virgin

3: Mill, thick, RAP 2: Mill, thick, virgin 3: No mill, thick, RAP 3: No mill, thick, RAP

3: No mill, thick, RAP 2: No mill, thick, RAP 4: Mill, thick, RAP 4: Mill, thick, RAP

11

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116

Table 60 shows only alternatives in which statistically significant differences in WD-maximum

deflection were found. The table was created by considering the alternatives with the lowest 

responses for each analysis performed with the dataset. These selected rehabilitation alternatives 

were then grouped for each combination of site conditions. According to the summary table, the 

following conclusions were made with respect to structural response: 

• Rehabilitation strategies with thick overlays provided the lowest structural response 

independent of site conditions.

• Strategies with RAP mix overlays had the lowest structural response in freeze regions, 

while those with virgin mixes presented lower deflections under no-freeze conditions.

• Milling prior to overlay did not further impact structural response. In no-freeze zones, 

strategies without milling presented lower deflections.

• When comparing wet and dry pavement surface condition and traffic level, neither had a 

significant impact on structural responses associated with each rehabilitation alternative.

The summary table presented in this section, along with a complete set of tables with descriptive 

statistics for all the analyses performed, is provided in appendix C.

RELATIONHIP BETWEEN STRUCTURAL RESPONES IMMEDIATELY AFTER 

REHABILITATION AND FUTURE PERFORMANCE

There have been many attempts to find direct relationships or models to predict performance 

based on the structural response of the pavement to loading immediately after construction 

or rehabilitation. These relationships are not completely straightforward, and deriving them 

accurately using mechanistic theory can be difficult. The objective of this study was to identify 

trends in the relationship between response measured after the rehabilitation and the observed 

performance in subsequent years of the pavement’s service life. If these trends can be 

identified, they will provide important information and guidance on what to expect for a 

pavement’s performance as a result of rehabilitation strategies that yield to a certain level of 

structural response.

This study concentrated on evaluating FWD maximum deflections measured under the center of 

the load against the average pavement performance during the service life of SPS-5 sites. WD 

was once again used as the performance measure. Each response was evaluated against all 

distresses previously used in this study. Only long-term performance was used for this analysis, 

indicating performance data of 5 years or more.

The SPS-5 experiment had sites across the United States under different climatic zones, subgrade 

types, and traffic loads. Consequently, the results from this study could be impacted by in situ

conditions. The alternative to circumvent this problem was to normalize the data in each site by a 

common factor. The rehabilitation strategy selected as the normalization factor had a thin virgin 

mix overlay without milling, and it was selected because the control section was not available or 

was eliminated from the surveys for some of the SPS-5 sites. Response and performance 
117

measured for thin virgin mix overlaid sections were used to normalize the data of the remaining 

sections in each site. Normalized values were computed according to the equation in figure 34.

PPPPPPPPPPPPPPPPPPNNNN NNNNNN NN = PPPPPPPPPPPPPPPPPPss ss ss

PPPPPPPPPPPPPPPPPP0602

Figure 34. Equation. Parameter subscript normalized.

The relationship between performance and deflection was verified using Pearson’s linear 

coefficient, r. The t-Student’s test was used to test the null hypothesis stating that no correlation 

existed between performance and deflection (r = 0). A potential relationship between 

performance and deflection was confirmed if the null hypothesis was rejected with 95 percent 

confidence (p ≤ 0.05).

The trend between roughness and maximum deflection is shown in figure 35. It suggests that 

roughness, measured by IRI, is poorly related to the deflection values measured after the 

rehabilitation of the pavement structure (p = 0.029).

0.5

0.7

0.9

1.1

1.3

1.5

1.7

0 0.5 1 1.5 2 2.5 3

Normalized Roughness

Normalized Max Defl

Figure 35. Graph. Normalized long-term WD-roughness versus normalized maximum 

deflection measured after rehabilitation in SPS-5 sites.

Similarly, the results in figure 36 suggest that maximum deflection after the pavement’s 

rehabilitation cannot provide good qualitative information about the rutting performance 

predictions (p = 0.296). This observation may be contrary to what is expected. Rutting is a loadrelated distress, and because deflection measures the pavement’s response to load applications, it 

seems intuitive that a positive trend might exist. However, instant deflections as measured by 

FWD tests were more likely to capture instantaneous elastic response of the pavement structure. 

Rutting is a plastic deformation more likely to occur in unbound aggregate layers and AC at 

warm temperatures. In rehabilitated flexible pavements, most of the permanent deformation 

occurred in the overlay. As temperature increases, AC behaves less like a time-dependent elastic 

material and more like a time-dependent plastic material. The instantaneous FWD deflections 

cannot be associated with the material’s behavior impacting rutting performance.
118

0

0.5

1

1.5

2

2.5

3

3.5

0 0.5 1 1.5 2 2.5 3

Normalized Rutting

Normalized Max Defl

Figure 36. Graph. Normalized long-term WD-rutting versus normalized maximum 

deflection measured after rehabilitation in SPS-5 sections.

Contrary to expectations, the data in figure 37 indicate that no statistically significant trend was 

found between fatigue cracking performance and maximum deflection (p = 0.565). Conversely, 

the data in figure 38 suggest that higher values of transverse cracking are expected when the 

pavement has higher deflections (p = 0.001). The trend in figure 39 suggests that longitudinal 

cracking is not related to deflections measured under the center of the load on FWD tests but just 

marginally (p = 0.058).

0

1

2

3

4

5

6

0 0.5 1 1.5 2 2.5 3

Normalized Fatigue 

cracking

Normalized Max Defl

Figure 37. Graph. Normalized long-term WD-fatigue cracking versus normalized 

maximum deflection measured after rehabilitation in SPS-5 sections.
119

0

0.5

1

1.5

2

2.5

3

3.5

4

0 0.5 1 1.5 2 2.5 3

Normalized Transverse 

cracking

Normalized Max Defl

Figure 38. Graph. Normalized long-term WD-transverse cracking versus normalized 

maximum deflection measured after rehabilitation in SPS-5 sections.

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

0 0.5 1 1.5 2 2.5

Normalized Longitudinal 

cracking

Normalized Max Defl

Figure 39. Graph. Normalized long-term WD-longitudinal cracking versus normalized 

maximum deflection measured after rehabilitation in SPS-5 sections.

Some of the distresses had clear trends with responses that agreed with the conventional wisdom 

and expectations of relationships between performance and response. However, none of the 

trends were strong enough to suggest a direct correlation between performance and response as 

measured by maximum deflection. These plots only suggested that deflection could be used to 

infer qualitative assessments of future performance of some distresses but not to quantitatively 

predict performance.

121

CHAPTER 6. REHABILITATED RIGID PAVEMENT ANALYSIS AND FINDINGS

INTRODUCTION

This chapter describes the rehabilitation of rigid pavements. Data from the SPS-6 sites were used 

to assess the impact of rehabilitation effort with and without HMA overlay on performance and 

response of JPCP and JRCP. The impact of design features (i.e., different rehabilitation 

procedures and the presence or absence of an HMA overlay) on performance and response was 

statistically evaluated for major distresses commonly recorded in the LTPP database for rigid 

pavements and reported in the MEPDG.

STATISTICAL ANALYSIS APPROACH

The core sections of the SPS-6 experiment consisted of independent rehabilitation strategies. 

The experiment did not evenly combine all restoration and overlay options. Additionally, it was

unbalanced for statistical purposes. As a result, ANOVA of individual sites was not possible. 

Therefore, the statistical analysis of SPS-6 was performed by simultaneously considering all of 

the sites in the experiment using the Friedman test.

The Friedman test is a nonparametric test (distribution-free) used to compare repeated 

observations on the same subjects. Unlike the more common parametric repeated measures 

ANOVA or paired t-test, the Friedman test makes no assumptions about the distribution of the 

data (e.g., normality). In addition, it can be used for multiple comparisons, as is the case of the 

SPS-6 experiment which had multiple rehabilitation alternatives. The Friedman test uses the 

ranks of the data rather than their raw values to calculate the statistic. The test statistic for the 

Friedman test is a chi-square with n - 1 degrees of freedom, where n is the number of repeated 

measures (i.e., the number of sections in each site of the experiment). Statistical significance was 

defined at 95 percent (p ≤ 0.05 for the chi-square test). 

The Friedman test also permits the evaluation of paired statistical significance between two 

rehabilitation strategies. In some instances, the result of one analysis may indicate that 

significant differences exist between the rankings of sections (i.e., the performances of these 

sections are statistically different). However, there might be groups within the sorted ranking 

with similar performances. The paired statistical analysis feature is important to identify groups 

of strategies with equivalent performance.

Performance Measures

The WD average (i.e., the unit area under the distress performance curve) over the survey period 

was selected as a performance measure of various distresses and roughness. It was calculated as 

described in the previous chapter.

Different distresses were used to evaluate the performance of rehabilitated rigid pavements. The 

decision was based on the importance and frequency of occurrence, but most notably, it was 

based on distresses that were visible during the surveys (i.e., present in the surface layer). The 

SPS-6 experiment consisted of rigid pavement sections that had been rehabilitated with or 

without HMA overlay. The core sections of the experiment are described in table 61. Sections 
122

that were rehabilitated through an HMA overlay were monitored after rehabilitation, and typical 

flexible pavement distresses (e.g., rutting, fatigue cracking, transverse cracking, etc.) were 

recorded throughout the service life of the experiment. Sections that were rehabilitated and did 

not receive an HMA overlay were monitored, and typical rigid pavement distress surveys 

(e.g., faulting, slab cracking, etc.) were recorded.

This particular characteristic of SPS-6 sites required multiple analyses in which individual 

sections were grouped based on their surface layer type and, consequently, their monitoring 

distresses. Roughness was measured in all sections, and it was chosen as the performance 

measure associated with all sections independent of their surface type as an indication of 

functional performance of the rehabilitation strategies. Different cracking performance 

measurements were taken according to the surface layer type. The sum of all cracking area was 

also an important performance measure used to evaluate all sections simultaneously, especially 

for decisionmaking on crack preventive maintenance. Therefore, roughness and total cracking 

were used to simultaneously compare the performance of all rehabilitation strategies.

Table 61. Core sections of the SPS-6 experiment.

SHRP 

ID

Overlay 

Thickness 

(mm) PCC Preparation Code

0601 —

Routine maintenance 

(control) —

0602 — Minimum restoration min-no

0603 102 Minimum restoration min-ov

0604 102 Saw and seal AC over joints ss-ov

0605 — Maximum restoration max-no

0606 102 Maximum restoration max-ov

0607 102 Crack/break and seat cb-4 inches

0608 203 Crack/break and seat cb-8 inches

1 inch = 25.4 mm

— Indicates that the section did not have an overlay and/or code.

There were four sections in each SPS-6 site with distinct restoration treatments executed prior to 

or just after the 4-inch (102-mm) overlays. The restoration treatments were minimum and 

maximum restoration, saw and seal over joints, and crack/break and seat. The impact of these 

treatments on performance was analyzed by grouping these sections into a new dataset, 

excluding all others. Roughness and typical flexible pavement distresses were used as 

performance measures. Sections with different restoration treatments but without overlays were 

used to evaluate the performance of these treatments when they were the main component of the 

rehabilitation strategy. The no treatment control section was also analyzed in this group dataset, 

and roughness and distresses typical of rigid pavement were used as performance measures. 

Table 62 summarizes all datasets and provides the purpose of the study and the distresses and 

responses used in each analysis.

The analysis of the SPS-6 sites was intended to assess the impact of rehabilitation strategies on 

performance and response as well as the influence of climate and pavement surface conditions 

prior to rehabilitation. Therefore, each dataset defined in table 62 was analyzed in four ways: 
123

(1) all sites in the study, (2) sites grouped by wet/dry condition, (3) sites grouped by freeze/nofreeze condition, and (4) sites grouped by fair/poor condition prior to rehabilitation. By 

comparing results from different conditions, it was possible to investigate the influence of 

climate conditions and pavement deterioration prior to rehabilitation on performance. Separate 

analyses were conducted for JPCP and JRCP.

In addition to performance measures, mechanistic responses were analyzed. Sections with HMA 

overlays were evaluated using maximum deflection measured at the center of the lane, while 

sections without overlays were analyzed using the load transfer efficiency between joints and the 

maximum deflection at the center of the slab.

Table 62. Description of independent studies and performance measures used 

in the analyses.

Study Type/Dataset Purpose Distress

All rehabilitation strategies

and all sections

To compare performance of 

all rehabilitation options

Roughness

Total cracking

PCC restoration prior to 

overlay: sections 0603, 0604, 

0606, and 0607

To evaluate the impact of 

different preoverlay treatments 

on performance

Roughness

Rutting

Fatigue cracking

Longitudinal cracking

Transverse cracking

Maximum deflection

PCC restoration: sections 

0601, 0602, and 0605

To evaluate the impact on 

performance of PCC 

restoration without HMA 

overlay

Roughness

PCC faulting

Slab corner breaks

Durability

Longitudinal slab cracking

Transverse slab cracking

Load transfer efficiency (LTE)

Maximum deflection

EFFECT OF DESIGN AND CONSTRUCTION FEATURES AND SITE CONDITIONS 

ON PERFORMANCE OF REHABILITATED RIGID PAVEMENTS

There were 14 sites in the SPS-6 experiment. Eight of them were JPCP, and six were JRCP. 

The sites and their characteristics in the experimental factorial are presented in table 63. Their 

behavior was different, and the level of distresses typically varied. The analysis of the impact 

of different rehabilitation strategies on performance was performed separately for JPCP and 

JRCP sites.
124

Table 63. SPS-6 sites for the experimental factorial.

Pavement 

Type

Pavement 

Condition

Climate, Moisture/Temperature

Wet Freeze

Wet 

No-freeze Dry Freeze

Dry 

No-freeze

JPCP

Fair Missouri (29)

Alabama (1)

and

Tennessee

(47)

South Dakota

(46)

Poor Indiana (18) Arakansas (5)

Arizona (4)

and

California (6)

JRCP

Fair

Iowa (19), 

Michigan (26), and

Pennsylvania (42)

Oklahoma

(40)

Poor

Illinois (17) and

Missouri (29)

Note: State codes are provided in parentheses. Blank cells indicate that there are no sites with those sets of conditions.

JPCP

This section describes the results of the study on JPCP sites in the SPS-6 experiment. JPCP sites 

were located throughout the United States and had a balanced distribution between climate and 

pavement condition. Only the dry, no-freeze climatic zone did not have a representative site. 

Four out of eight sites were reported to have fair pavement conditions prior to rehabilitation. Five 

sites were located in wet regions, and five were located in freeze regions. Traffic was similar in 

all sites in terms of daily truck volume and class distributions.

Analysis of All Rehabilitation Strategies

Roughness and total cracking were used to evaluate all rehabilitation alternatives simultaneously. 

Roughness was the only performance indicator measured in all sections within each site. The 

surveys were independent from surface type and were performed systematically during the 

experiment. The surveys provided a uniform way of comparing the impact of all of the 

rehabilitation strategies used in the experiment. In addition to roughness, total cracking was 

used as an indicator of performance. In this case, the measurements were not obtained directly. 

Cracking was measured depending on the surface layer type after the rehabilitation strategy 

was completed. 

After the data were processed and verified for quality and existing outliers were removed, WD 

was computed for short-term and long-term performance (see table 64 and table 65). The 

Friedman test used the calculated WD to create a ranking of performance, from lowest WD (best 

performance) to highest (worst performance) for each site in the dataset. Descriptive statistics of 

the ranking (i.e., average, standard deviation, sum of rankings, etc.) for each type of section were

used to calculate the chi-square value to determine if statistical differences existed among the 

performance rankings.
Table 64. Short-term average WD-IRI values for SPS-6 sites with JPCP. 

Section

Experiment Design Sites (State Codes)/Average IRI WD Values (m/km) 

Restoration Overlay (mm) 1 4 5 6 18 29 46 47

0601 No no 1.57 1.64 2.02 1.83 1.50 0.40 1.49

0602 Minimum no 0.69 2.43 2.01 1.89 1.02 0.69 0.47 0.86

0603 Minimum 102 0.74 1.29 0.48 0.96 0.68 0.67 0.89 0.43

0604 Saw and seal 102 0.64 0.99 0.50 0.91 0.75 0.78 0.83 0.79

0605 Maximum no 0.69 1.51 0.97 1.95 1.18 0.73 0.41 0.89

0606 Maximum 102 0.85 1.04 0.54 1.02 0.72 0.60 0.71 0.45

0607

Crack/break and 

seat 102 1.07 1.56 0.55 0.86 0.78 0.72 0.90 0.90

0608

Crack/break and 

seat 203 0.47 0.93 0.45 0.83 0.54 0.46 0.66 0.40

1 ft = 0.305 m

1 mi = 1.61 km

1 inch = 25.4 mm

12

Note: Higher WD values indicate rougher pavement over time. The blank cell indicates data are not available.

5
Table 65. Long-term average WD-IRI values for SPS-6 sites with JPCP.

Section

Experiment Design Sites (State Codes)/Average IRI WD Values (m/km)

Restoration Overlay (mm) 1 4 5 6 18 29 46 47

0601 No no 3.09 2.48 3.15 2.72 3.15 3.03 1.86

0602 Minimum no 1.30 3.65 2.18 2.24 2.21 1.31 1.56 1.19

0603 Minimum 102 1.32 1.74 0.94 1.39 1.07 1.26 1.36 0.78

0604 Saw and seal 102 1.23 1.20 0.97 1.55 1.19 1.41 1.50 0.98

0605 Maximum no 1.25 1.81 1.38 1.90 2.14 1.28 1.28 1.19

0606 Maximum 102 1.48 1.37 1.01 1.84 1.13 1.13 1.25 0.80

0607

Crack/break and 

seat 102 2.43 1.43 1.07 1.58 1.09 1.46 1.38 1.19

0608

Crack/break and 

seat 203 0.93 1.14 0.90 1.09 1.00 0.95 1.11 0.78

1 ft = 0.305 m

1 mi = 1.61 km

1 inch = 25.4 mm

Note: The blank cell indicates data are not available.

12

6
127

The Friedman null hypothesis stated that there was no difference between the section rankings

(i.e., all sections had identical performances). The null hypothesis was rejected if the p-value was 

lower than 0.05, which represents a 95 percent confidence that at least two sections have 

statistically different rankings. Examples of Friedman test outputs are provided in figure 40 and 

figure 41. In the figures, the average WD value for IRI found for each rehabilitation strategy 

among all sites was analyzed. The vertical bars represent the interval between the mean value

±1 standard deviation as an illustration of the variability of the measurements. The results 

indicate that for short-term roughness performance, there were at least two sections with 

statistically different performances (see figure 40, p = 0.0004, ANOVA chi-square = 26.5938). 

A similar result was found for long-term performance in figure 41 (p < 0.0001, ANOVA 

chi-square = 40.2188).

When the result from the Friedman test indicated the existence of at least two strategies with 

statistically different rankings, the next steps were to identify those sections and build the 

rankings of best-performing strategies based on the statistical analysis. The paired analyses from 

the Friedman test were used for this purpose. The significance (p-value) of these paired analyses 

indicated the presence or absense of statistical differences between their rankings. Table 66 and 

table 67 provide the statistical p-values for each paired analysis for short-term and long-term 

roughness rankings.

The paired analysis results were used to create a practical ranking of roughness performance 

based on the statistical significance. Based on results presented in table 66 and table 67, the final 

ranking of evaluating roughness performance was created for the short term and the long term 

and are described in table 68 and table 69, respectively. Sections were ordered from best to worst

performance, and sections with equivalent performance were grouped under the same rank.

1 ft = 0.305 m

1 mi = 1.61 km

Figure 40. Graph. WD-IRI short-term values for JPCP in SPS-6 sections.
128

1 ft = 0.305 m

1 mi = 1.61 km

Figure 41. Graph. WD-IRI long-term values for JPCP in SPS-6 sections.
129

Table 66. Friedman test paired analysis of rehabilitation strategies by IRI short-term 

performance ranking for SPS-6 sites with JPCP.

Paired Analysis p-Value

0601 and 0602 —

0601 and 0603 —

0601 and 0604 —

0601 and 0605 —

0601 and 0606 —

0601 and 0607 —

0601 and 0608 < 0.05

0602 and 0603 —

0602 and 0604 —

0602 and 0605 —

0602 and 0606 —

0602 and 0607 —

0602 and 0608 < 0.05

0603 and 0604 —

0603 and 0605 —

0603 and 0606 —

0603 and 0607 —

0603 and 0608 —

0604 and 0605 —

0604 and 0606 —

0604 and 0607 —

0604 and 0608 —

0605 and 0606 —

0605 and 0607 —

0605 and 0608 < 0.05

0606 and 0607 —

0606 and 0608 —

0607 and 0608 < 0.05

— Indicates a pair analysis with no 

statistical significance.
130

Table 67. Friedman test paired analysis of rehabilitation strategies by IRI long-term 

performance ranking for SPS-6 sites with JPCP.

Paired Analysis p-Value

0601 and 0602 —

0601 and 0603 < 0.05

0601 and 0604 < 0.05

0601 and 0605 —

0601 and 0606 < 0.05

0601 and 0607 —

0601 and 0608 < 0.05

0602 and 0603 —

0602 and 0604 —

0602 and 0605 —

0602 and 0606 —

0602 and 0607 —

0602 and 0608 < 0.05

0603 and 0604 —

0603 and 0605 —

0603 and 0606 —

0603 and 0607 —

0603 and 0608 —

0604 and 0605 —

0604 and 0606 —

0604 and 0607 —

0604 and 0608 —

0605 and 0606 —

0605 and 0607 —

0605 and 0608 < 0.05

0606 and 0607 —

0606 and 0608 —

0607 and 0608 < 0.05

— Indicates a pair analysis with no 

statistical significance.
131

Table 68. Ranking of rehabilitation strategies for short-term roughness performance of 

SPS-6 sites with JPCP.

Section Ranking Restoration

Overlay 

(mm)

0608 1

Crack/break and 

seat 203

0603 2 Minimum 102

0604 2 Saw and seal 102

0606 2 Maximum 102

0602 5 Minimum No

0605 5 Maximum No

0607 5

Crack/break and 

seat 102

0601 5 Control No

1 inch = 25.4 mm

Table 69. Ranking of rehabilitation strategies for long-term roughness performance of 

SPS-6 sites with JPCP.

Section Ranking Restoration

Overlay 

(mm)

0608 1

Crack/break and 

seat 203

0603 2 Minimum 102

0606 2 Maximum 102

0604 2 Saw and seal 102

0605 5 Maximum No

0607 5

Crack/break and 

seat 102

0602 5 Minimum No

0601 8 Control No

1 inch = 25.4 mm

Results from table 68 and table 69 suggest that the rehabilitation alternative for section 0608

(crack/break and seat with an 8-inch (203-mm) overlay) was the best performing treatment for 

roughness in both the short term and long term. The statistical analysis also suggests that there 

was practically no difference in performance between sections overlaid with 4-inch (102-mm) 

HMA regardless of the restoration treatment performed prior to the overlay, except the 

alternative crack/break and seat with a 4-inch (102-mm) overlay, which was the poorer 

alternative with overlays. Roughness performance for this rehabilitation alternative was 

equivalent to not having an overlay after restoration.

The same approach described for the analysis of roughness was applied to total cracking, which

was computed as the sum of fatigue, longitudinal, and transverse cracking measured in sections 

overlaid with HMA and the sum of transverse and longitudinal slab cracking measured in 

sections without HMA overlays. Figure 42 (p < 0.0001, ANOVA chi-square = 38.4896) and 
132

figure 43 (p < 0.0001, ANOVA chi-square = 31.7919) describe the Friedman ANOVA test for 

this type of distress. Based on the same test statistics, the ranking of best performing 

rehabilitation strategies for total cracking was created. 

1 ft = 0.305 m

Figure 42. Graph. Average short-term WD-cracking for JPCP at SPS-6 sites.

1 ft = 0.305 m

Figure 43. Graph. Average long-term WD-cracking for JPCP at SPS-6 sites.

table 70 show a compilation of the rankings for roughness and total cracking performances for

short-term performance, and table 71 presents the results for long-term performance.
133

Table 70. Summary of rankings for short-term performance of JPCP structures at 

SPS-6 sites.

Statistical 

Relevance

(Y/N)

Distress

Roughness Total Cracking

Y p = 0.0004 Y p = 0.0004

Ranking 

(if relevant)

Ranking Strategy

Overlay 

(mm) Ranking Strategy

Overlay 

(mm)

1

Crack/break

and seat 203 1 Minimum None

2 Minimum 102 2 Maximum None

2 Saw and seal 102 2 None None

2 Maximum 102 4

Crack/break

and seat 102

5 Minimum None 5 Minimum 102

5 Maximum None 5

Crack/break

and seat 203

5

Crack/break

and seat 102 5 Maximum 102

5 Control 8 Saw and seal 102

1 inch = 25.4 mm

Note: The blank cell indicates that there was no overlay for the control.

Table 71. Summary of rankings for long-term performance of JPCP structures at 

SPS-6 sites.

Statistical 

Relevance

(Y/N)

Distress

Roughness Total Cracking

Y p < 0.0001 Y p < 0.0001

Ranking 

(if 

relevant)

Ranking Strategy

Overlay 

(mm) Ranking Strategy

Overlay 

(mm)

1 Crack/break and 

seat 203 1 None None

2 Minimum 102 1 Minimum None

2 Maximum 102 1 Maximum None

2 Saw and seal 102 4 Crack/break

and seat 203

5 Maximum None 4 Crack/break

and seat 102

5 Crack/break and 

seat 102 4 Maximum 102

5 Minimum None 4 Minimum 102

8 Control 8 Saw/seal 102

1 inch = 25.4 mm

Note: The blank cell indicates that there was no overlay for the control.

The impact of rehabilitation strategies on roughness and total cracking performance was 

investigated for all sections in the JPCP sites of the SPS-6 experiment. Results from the 
134

statistical analysis suggest that rehabilitation treatments with HMA overlay provided smoother 

pavement sections. The best alternatives to mitigate the progression of total cracking were those 

without overlays. This result was influenced by the fact that, when combining all cracking from 

HMA overlays on PCC (including saw and seal joints), reflective cracking at joints was surveyed 

as longitudinal and transverse cracks, which significantly increased the amount of cracking 

observed in HMA overlaid sections. The main conclusions from table 70 and table 71 are

as follows:

• Rehabilitation strategies with overlays were significantly smoother than treatments 

without overlays.

• The best alternative to improve roughness performance was to use the thicker overlay 

alternative (crack/break and seat with 7.9-inch (203-mm) overlay).

• Crack/break and seat with a 4-inch (102-mm) overlay was among the worst alternatives 

to improve roughness performance.

• Rehabilitation strategies without overlays were the best to mitigate crack development 

and propagation.

• Saw and seal was rated as the worst alternative to prevent cracking; however, the design 

goal of this alternative was control of reflection cracks. This alternative provided similar 

smoothness to other 4-inch (102-mm) overlays. 

• Crack/break and seat of JPCP had no significant effect on reducing the amount of 

cracking, and it performed similarly to the 4-inch (102-mm) overlay over noncracked 

JPCP (with both minimum and maximum restorations).

Influence of Site Conditions

The influence of site conditions was determined by two variables: pavement surface condition 

prior to rehabilitation (fair versus poor) and climate (wet versus dry and freeze versus no-freeze). 

These conditions were determined for each site, and the Friedman test was applied to each group.

Additionally, traffic was investigated, and AADTT volumes were computed from 2000 to 2007. 

No significant variation in daily truck traffic was found among the sites in the SPS-6 experiment. 

All sites had AADTT values close to 800 trucks except for Missouri (1,700 average daily trucks)

and South Dakota (292 daily trucks). Therefore, there were not enough sites with significant 

variations in traffic level that resulted in meaningful statistical results.

The analysis followed the same steps described in the previous section. Rehabilitation strategy 

rankings were developed for each group of sites using the paired analyses from the Friedman test 

if statistical differences in performance were found. 

Table 72 and table 73 provide the rankings for roughness and total cracking for long-term 

performance in sections with poor and fair surface conditions prior to rehabilitation. For both 

tables, four sites were used in the analysis of poor surface condition. Despite grouping the data 

according to similar characteristics in respect to surface condition, the strategy rankings
135

remained unaltered from the ranking considering all sites. One result was that the maximum 

restoration effort provided a smoother pavement in the long term than the minimum effort when 

neither received a HMA overlay.

Table 72. Summary of rankings for long-term performance of JPCP structures at SPS-6 

sites in poor surface condition prior to rehabilitation.

Statistical 

Relevance

(Y/N)

Distress

Roughness Total Cracking

Y p = 0.0007 N

Ranking 

(if relevant)

Ranking Strategy

Overlay 

(mm) Ranking Strategy

Overlay 

(mm)

1

Crack/break and 

seat 203

2 Minimum 102

2 Saw/seal 102

2 Maximum 102

2

Crack/break and 

seat 102

2 Maximum None

7 Minimum None

7 Control

1 inch = 25.4 mm

Note: Blank cells indicate that no data are available because cracking did not have statistical relevance.

Table 73. Summary of rankings for long-term performance of JPCP structures at SPS-6 

sites in fair surface condition prior to rehabilitation.

Statistical 

Relevance

(Y/N)

Distress

Roughness Total Cracking

Y p = 0.0052 Y p = 0.0009

Ranking 

(if relevant)

Ranking Strategy

Overlay 

(mm) Ranking Strategy

Overlay 

(mm)

1

Crack/break and 

seat 203 1 Maximum None

2 Maximum 102 1 Minimum None

2 Minimum 102 3 Control

2 Maximum None 3

Crack/break and 

seat 203

2 Saw/seal 102 3

Crack/break and 

seat 102

2 Minimum None 3 Minimum 102

2

Crack/break and 

seat 102 3 Maximum 102

8 None None 8 Saw/seal 102

1 inch = 25.4 mm

Note: The blank cell indicates that there was no overlay for the control.
136

The influence of other site conditions was evaluated, and tables containing the statistical results 

and rankings are presented in appendix D.

After a careful assessment of the results from all the analyses performed, summary tables were 

assembled for better visualization and interpretation of results. These tables were created for 

each distress and analysis period (short-term and long-term performance). Table 74 and table 75

present the results for short-term and long-term roughness, while table 76 and table 77 describe 

the results for short-term and long-term total cracking. The best alternatives with statistical 

relevance are shown in each cell. The number before the treatment indicates its ranking among 

all the alternatives.

These summary tables provide information for selecting the best rehabilitation alternative among 

those evaluated in this study based on distress type and site conditions. Moreover, the influence 

of different site conditions can be determined by observing the best treatments for each 

condition. The analysis of sites in different climate regions and with different surface conditions 

resulted in rankings that are similar to each other. Therefore, the study suggests that site 

conditions did not have a significant impact on roughness and total cracking performance for the 

rehabilitation strategies included in the SPS-6 JPCP experiment.

Table 74. Summary of short-term roughness performance of JPCP structures.

Climate

Surface Condition

Poor

Overlay 

(mm) Fair

Overlay 

(mm)

Wet

Freeze

1: Crack/break

and seat 203

1: Crack/break

and seat 203

1:Minimum 102 1: Minimum 102

3: Maximum 102 3: Maximum 102

3: Saw/seal 102 3: Saw/seal 102

Nofreeze

1: Crack/break

and seat 203

1: Crack/break

and seat 203

1: Minimum 102 1: Minimum 102

3:Maximum 102 3: Maximum 102

3: Saw/seal 102 3: Saw/seal 102

Dry

Freeze

1: Crack/break

and seat 203

1: Crack/break

and seat 203

1: Maximum 102 1: Maximum 102

1: Minimum 102 1: Minimum 102

1: Saw/seal 102 1: Saw/seal 102

Nofreeze

1: Crack/break

and seat 203

1: Crack/break

and seat 203

1: Maximum 102 1: Maximum 102

1: Minimum 102 1: Minimum 102

1: Saw/seal 102 1: Saw/seal 102

1 inch = 25.4 mm
137

Table 75. Summary of long-term roughness performance of JPCP structures.

Climate

Surface Condition

Poor

Overlay 

(mm) Fair

Overlay 

(mm)

Wet

Freeze

1 : Crack/break and 

seat 203

1: Crack/break and 

seat 203

1: Minimum 102 1: Minimum 102

3:Maximum 102 3: Maximum 102

3:Saw/seal 102 3: Saw/seal 102

Nofreeze

1: Crack/break and 

seat 203

1: Crack/break and 

seat 203

1: Minimum 102 1: Minimum 102

3: Saw/seal 102 3: Saw/seal 102

4: Maximum 102 4: Maximum 102

Dry

Freeze

1: Crack/break and 

seat 203

1: Crack/break and 

seat 203

1: Maximum 102 1: Maximum 102

1: Minimum 102 1: Minimum 102

1: Saw/seal 102 1: Saw/seal 102

Nofreeze

1: Crack/break and 

seat 203

1: Crack/break and 

seat 203

1: Minimum 102 1: Minimum 102

1: Saw/seal 102 1: Saw/seal 102

4: Maximum 102 4: Maximum 102

1 inch = 25.4 mm
138

Table 76. Summary of short-term total cracking performance of JPCP structures.

Climate

Surface Condition

Poor

Overlay 

(mm) Fair

Overlay 

(mm)

Wet

Freeze

1: Maximum None 1: Maximum None

1: Minimum None 1: Minimum None

3: Control 3: Control

4: Crack/break and 

seat 102

4: Crack/break and 

seat 102

Nofreeze

1: Maximum None 1: Maximum None

1: Minimum None 1: Minimum None

3: Control 3: Control

4: Crack/break and 

seat 102

4: Crack/break and 

seat 102

Dry

Freeze

1: Maximum None 1: Maximum None

1: Minimum None 1: Minimum None

1: Control 3: Control

4: Crack/break and 

seat 102

4: Crack/break and 

seat 102

Nofreeze

1: Maximum None 1: Maximum None

1: Minimum None 1: Minimum None

1: Control 3: Control

4: Crack/break and 

seat 102

4: Crack/break and 

seat 102

1 inch = 25.4 mm

Note: Blank cells indicate that there was no overlay for the control.
139

Table 77. Summary for long-term total cracking performance of JPCP structures.

Climate

Surface Condition

Poor

Overlay 

(mm) Fair

Overlay 

(mm)

Wet

Freeze

1: Maximum None 1: Maximum None

1: Minimum None 1: Minimum None

1: Control 3: Control

4: Crack/break and 

seat 102

4: Crack/break and 

seat 102

Nofreeze

1: Maximum None 1: Maximum None

1: Minimum None 1: Minimum None

1: Control 3: Control

4: Crack/break and 

seat 102

4: Crack/break and 

seat 102

Dry

Freeze

1: Maximum None 1: Maximum None

1: Minimum None 1: Minimum None

1: Control 3: Control

4: Crack/break and 

seat 102

4: Crack/break and 

seat 102

Nofreeze

1: Maximum None 1: Maximum None

1: Minimum None 1: Minimum None

1: Control 3: Control

4: Crack/beak and 

seat 102

4: Crack/break and 

seat 102

1 inch = 25.4 mm

Note: Blank cells indicate that there was no overlay for the control.

The summary tables show only alternatives in which statistically significant differences in 

performance were found. The tables were developed to identify the best alternatives for each 

type of analysis performed. The selected rehabilitation alternatives were then grouped for each 

combination of site conditions. Although these may be the best performance alternatives, they 

may not be the lowest cost alternatives, and selection of a rehabilitation alternative must also 

consider the cost.

From the summary tables, the following conclusion was made: crack/break and seat with 8-inch

(203-mm) overlays and minimum restoration with 4-inch (102-mm) overlays were statistically 

equivalent and were found to be the best alternatives for most of the scenarios evaluated when 

short-term and long-term roughness performance was considered. Additionally, these alternative 

would be the highest cost alternative.

The analysis of total cracking indicated the following:

• The three alternatives without overlays (no treatment control scenario, minimum 

restoration, and maximum restoration) were found to be the best choices for short-term

and long-term performance.
140

• Crack/break and seat with 4-inch (102-mm) overlays was the best alternative among 

options involving overlays.

The sawed and sealed joints did not deteriorate significantly on these sections, and they became 

an effective control of reflection cracking. If they were removed from total cracking, the saw and 

sealed sections would have shown similar performance to other HMA overlays.

PCC Restoration Prior to Overlay

Different restoration treatments were applied prior to the installation of a 4-inch (102-mm) 

overlay in four sections as part of the rehabilitation strategy. The impact on performance of these 

PCC restoration treatments was evaluated by analyzing a subset of the data that included only 

four sections: 0603, 0604, 0606, and 0607 (see table 62). The same approach used in the analysis 

of the entire dataset and described in the previous section was applied in this investigation.

The surface layer after the rehabilitation that was completed was HMA, and the monitoring 

program to survey these sections was typically used for flexible pavements. Rutting, fatigue, 

and longitudinal and transverse cracking were used as performance measures. The subset of data 

was too small to provide results with statistical significance for the majority of distresses 

observed. Within the availability of data, only short-term and long-term transverse cracking 

performance was found to be statistically significant, and the results provided insight on 

expected performance.

Figure 44 (p = 0.0027, ANOVA chi-square = 14.175) and figure 45 (p < 0.0001, ANOVA 

chi-square = 21.75) present the average transverse cracking values computed as WD for both 

short-term and long-term performance. The vertical bars represent the variability among all sites 

represented by 1 standard deviation from the average. Both plots indicate that saw and seal after 

overlay (section 0604) was the least effective treatment to prevent transverse cracking, while 

crack/break and seat (section 0607) was the most effective. It could be argued that the sawed and 

sealed joints should be excluded from the analysis. This would result in saw and seal being 

similar to or better than any other overlay. The complete rankings of best-performing 

rehabilitation treatments with overlay are provided in table 78 and table 79 for short-term and 

long-term performance.
141

1 ft = 0.305 m

Figure 44. Graph. Average short-term WD-transverse cracking values for JPCP at 

SPS-6 sites.

1 ft = 0.305 m

Figure 45. Graph. Average long-term WD-transverse cracking values for JPCP at 

SPS-6 sites.

Table 78. Summary of rankings for short-term performance of JPCP composite structures 

at SPS-6 sites.

Transverse Cracking

Statistical 

Relevance 

(Y/N) Y p = 0.0027

Ranking

(if relevant)

Ranking Strategy

Overlay 

(mm)

1 Crack/break and seat 102

2 Minimum 102

2 Maximum 102

4 Saw/seal 102

1 inch = 25.4 mm
142

Table 79. Summary of rankings for long-term performance of JPCP composite structures 

at SPS-6 sites.

Transverse Cracking

Statistical 

Relevance 

(Y/N) Y p < 0.0001

Ranking 

(if relevant)

Ranking Strategy

Overlay 

(mm)

1 Crack/break and seat 102

2 Minimum 102

3 Maximum 102

4 Saw/seal 102

1 inch = 25.4 mm

The impact of PCC restoration treatments on performance of overlaid sections was investigated 

in the JPCP sites of the SPS-6 experiment. Transverse cracking was the only distress for which 

statistical differences were found between the four treatments. The conclusions from this study 

were as follows:

• The best alternative to limit the development and propagation of transverse cracking 

among all options with 4-inch (102-mm) overlays was crack/break and seat.

• Minimum and maximum restorations had an equivalent impact on short-term transverse 

cracking performance.

Influence of Site Conditions

The analysis of impact of site conditions had additional constraints on data availability. 

Statistical differences in performance were identified for short-term roughness and short-term

and long-term transverse cracking only. The results are presented in summary tables in 

appendix D.

Summary tables combine the results for all site conditions and provide a better visualization and 

interpretation of the outcome. They present the alternatives in which statistical significant 

differences in performance were found in the analysis. Blank cells indicate no statistical 

differences in performance of the selected alternatives. The rankings of best alternatives are 

shown in each cell. The number before the alternative indicates its ranking among all eight 

alternatives. When one or more alternatives were found to perform better than other sections but 

no difference was found between the selected ones, the same ranking was assigned to the group 

of alternatives. Table 80 presents the best restoration treatments prior to overlay for short-term 

roughness performance.
143

Table 80. Performance for short-term roughness of overlaid JPCP structures.

Climate

Surface Condition

Poor

Overlay 

(mm) Fair

Overlay 

(mm)

Wet

Freeze

1: Maximum 102 1: Maximum 102

1: Minimum 102 1: Minimum 102

1: Saw/seal 102 1: Saw/seal 102

Nofreeze

1: Maximum 102 1: Maximum 102

1: Minimum 102 1: Minimum 102

1: Saw/seal 102 1: Saw/seal 102

Dry

Freeze

Nofreeze

1 inch = 25.4 mm

Note: Blank cells indicate that all alternatives have statistically equal performances.

Table 81and table 82 present the results for short-term and long-term transverse cracking 

performance.

Table 81. Performance for short-term transverse cracking of overlaid JPCP structures.

Climate

Surface Condition

Poor

Overlay 

(mm) Fair

Overlay 

(mm)

Wet

Freeze

1: Crack/break

and seat 102

1: Crack/break

and seat 102

1: Maximum 102 1: Maximum 102

1: Minimum 102 1: Minimum 102

Nofreeze

1: Crack/break

and seat 102

1: Crack/break

and seat 102

1: Maximum 102 1: Maximum 102

1: Minimum 102 1: Minimum 102

Dry

Freeze

1: Crack/break

and seat 102

1: Crack/break

and seat 102

1: Maximum 102 1: Maximum 102

1: Minimum 102 1: Minimum 102

Nofreeze

1: Crack/break

and seat 102

1: Crack/break

and seat 102

1: Maximum 102 1: Maximum 102

1: Minimum 102 1: Minimum 102

1 inch = 25.4 mm
144

Table 82. Performance for long-term transverse cracking of overlaid JPCP structures.

Climate

Surface Condition

Poor

Overlay 

(mm) Fair

Overlay 

(mm)

Wet

Freeze

1: Crack/break

and seat 102

1: Crack/break

and seat 102

1: Minimum 102 1: Minimum 102

3: Maximum 102 3: Maximum 102

Nofreeze

1: Crack/break

and seat 102

1: Crack/break

and seat 102

1: Minimum 102 1: Minimum 102

3:Maximum 102 3: Maximum 102

Dry

Freeze

1: Crack/break

and seat 102

1: Crack/break

and seat 102

1: Minimum 102 1: Minimum 102

3: Maximum 102 3: Maximum 102

Nofreeze

1: Crack/break

and seat 102

1: Crack/break

and seat 102

1: Minimum 102 1: Minimum 102

3: Maximum 102 3: Maximum 102

1 inch = 25.4 mm

The summary tables only present alternatives for which statistically significant differences in 

performance were found. The tables were created by considering the best alternatives for each 

analysis performed in the dataset. These selected rehabilitation alternatives were then grouped 

for each combination of site conditions.

Based on the summary tables, the following conclusions were made:

• Statistical differences in performance of overlaid sections were observed only for 

transverse cracking and short-term roughness when individual site characteristics 

were considered.

• There was no impact on performance due to variations in surface condition prior to 

rehabilitation or the climatic region where the LTPP site was located. 

• Minimum, maximum, and saw and seal restorations provided the best short-term 

roughness performance, but there was no difference between the rehabilitation 

alternatives for long-term performance.

• Crack/break and seat and minimum restoration were the best alternatives to mitigate the 

development and propagation of transverse cracking for long-term performance.
145

PCC Restoration

Three sections in each SPS-6 site did not receive overlays as part of their rehabilitation 

strategies, and they were used to evaluate the impact of PCC restoration on performance. These 

sections were 0601 (control), 0602 (minimum restoration), and 0605 (maximum restoration). The 

same approach using the Friedman test was applied. Distresses that were common to rigid 

pavements were used as performance measures.

The small number of sections available for this study significantly reduced the power of the 

analysis and the chances of finding statistical differences among the treatment alternatives that 

were evaluated. No statistical differences in performance were found for short-term performance. 

The only performance indicator that showed statistical differences between the treatments was 

long-term roughness. Average WD values for long-term roughness are provided in figure 46

along with the variability of measures in the vertical bars representing one standard deviation 

from the average (p = 0.002, ANOVA chi-square = 12.4375). The ranking of best-performing 

alternatives is presented in table 83. Longitudinal slab cracking provides an example of 

performance data that were statistically equivalent (see figure 47 (p = 0.0582, ANOVA 

chi-square = 5.6875)). From the long-term roughness analysis, the findings supported by the 

statistical analysis can be summarized as follows:

• The maximum restoration treatment produced the smoothest pavement over the long 

term. The weighted roughness for section 0605 was the lowest.

• The minimum restoration treatment produced the next smoothest pavement over the 

long term.

• The control section was the roughest pavement over the long-term, as expected, while the 

weighted roughness for section 0601 was the highest.

1 ft = 0.305 m

1 mi = 1.61 km

Figure 46. Graph. Long-term WD-roughness for JPCP at SPS-6 site.
146

Table 83. Rankings for long-term performance of JPCP structures at SPS-6 sites.

Roughness

Statistical 

Relevance (Y/N) Y p = 0.002

Ranking 

(if relevant)

Ranking Strategy

Overlay 

(mm)

1 Maximum None

2 Minimum None

3 Control None

1 inch = 25.4 mm

1 ft = 0.305 m

Figure 47. Graph. Long-term WD-longitudinal cracking for JPCP at SPS-6 sites.

An attempt was made to evaluate the impact of site conditions on performance, but the results 

were not statistically significant. In part, this study remains mostly inconclusive, particularly due 

to the small sample size and consequent minimal power of the statistical analysis. Additional 

sections with rehabilitation treatments without overlays would provide a more robust 

characterization of performance differences among the rehabilitation treatments evaluated 

in this study.

Summary of Findings for JPCP Sites

When all sections in each site were evaluated simultaneously for roughness and total cracking 

performance, the following findings were observed:

• Rehabilitation strategies with overlays were significantly smoother than treatments 

without overlays.

• The best alternative to improve roughness performance was the thicker overlay 

alternative crack/break and seat with 8-inch (203-mm) overlays.

• Conversely, crack/break and seat with 4-inch (102-mm) overlays was among the worst

alternatives to improve roughness performance.
147

• Rehabilitation strategies without overlays were the best to mitigate cracking development 

and propagation.

• Saw and seal was rated as the worst alternative to prevent cracking; however, control of 

reflection cracks was the design goal of this alternative, which was difficult to measure 

directly. This alternative provided similar smoothness to other 4-inch (102-mm) overlays. 

• Crack/break and seat of JPCP had no significant effect in reducing the amount of 

cracking, and it performed similarly to the 4-inch (102-mm) overlay over noncracked 

JPCP (with both minimum and maximum restorations).

The results of independent evaluation of sections with HMA overlays suggested the following:

• Based on the available data, only short-term and long-term transverse cracking exhibited 

statistically meaningful results.

• The best alternative to limit the development and propagation of transverse cracking 

among all options with 4-inch (102-mm) overlays was crack/break and seat.

• Minimum and maximum restorations had equivalent impacts on short-term transverse 

cracking performance.

The analysis of rehabilitation treatments without HMA overlays suggested the following:

• Based on the available data, only long-term roughness exhibited statistically

meaningful results.

• The maximum restoration treatment produced the smoothest pavement over the 

long term. 

• The minimum restoration treatment produced the next smoothest pavement over the 

long term.

• The control section was the roughest pavement over the long term, as expected.

JRCP

This section describes the analysis results for JRCP sites in the SPS-6 experiment. There were

six sites with JRCP structures in the experiment (see table 63). Similar to the study of JPCP sites, 

the analysis of SPS-6 sites with JRCP structures was originally intended to consider the impact 

of rehabilitation strategies on performance as well as the influence of climate and pavement 

surface conditions prior to rehabilitation. Unfortunately, the number of sites evaluated for each 

climatic region and surface condition was too small for any meaningful statistical analysis. 

Therefore, only the analysis considering all sites simultaneously was conducted. The study was 

divided in three parts: (1) all rehabilitation strategies, (2) PCC restoration prior to overlay, and 

(3) PCC restoration without overlay.
148

Analysis of All Rehabilitation Strategies

Roughness and total cracking were used to characterize performance and simultaneously

evaluate all alternatives. Roughness was the only performance indicator measured for all sections 

within each site. The surveys were independent from surface type and were performed

systematically during the experiment. They provided a uniform way of comparing the impact of 

different rehabilitation strategies used in the experiment. In addition to roughness, total cracking 

was used as an indicator of performance for the analysis of all sections. In this case, the 

measurements were not obtained directly. Cracking was measured depending on the surface 

layer type after the rehabilitation strategy was completed. For this study, total cracking was 

computed as the sum of fatigue, longitudinal cracking, and transverse cracking measured in 

sections overlaid with HMA and the sum of transverse and longitudinal slab cracking measured 

in sections without HMA overlays.

The same analysis approach described in previous sections using WD and the Friedman test was 

used to evaluate the impact of rehabilitation strategies of JRCP structures. After the data were 

processed and verified for quality, WD was computed for short-term and long-term performance. 

The Friedman test used WD to create a ranking of performance from the lowest value of WD 

(best performance) to the highest value (worst performance) for each site in the dataset. WD 

results for the entire set were then used in to determine the chi-square statistics to evaluate if 

differences existed among the performance rankings of the sections.

Roughness and long-term total cracking performances were statistically different among the 

rehabilitation strategies investigated. The results of the statistical analysis are presented in 

figure 48 (p = 0.0027, ANOVA chi-square = 21.8889), figure 49 (p < 0.0001, ANOVA 

chi-square = 30.7361), and figure 50 (p = 0.0047, ANOVA chi-square = 20.4444). Similar to the 

results for the JPCP sites, the results suggested that rehabilitation strategies with HMA overlays

improved roughness performance, while strategies without overlays were better for improving 

total cracking development and propagation. The complete ranking of best-performing 

rehabilitation treatments with overlays is provided in table 84 for short-term performance 

and in table 85 for long-term performance.

1 ft = 0.305 m

1 mi = 1.61 km

Figure 48. Graph. Short-term WD-roughness values for JRCP at SPS-6 sites.
149

1 ft = 0.305 m

1 mi = 1.61 km

Figure 49. Graph. Long-term WD-roughness values for JRCP at SPS-6 sites.

1 ft2 = 0.093 m2

Figure 50. Graph. Long-term WD-total cracking values for JRCP at SPS-6 sites.
150

Table 84. Rankings for short-term performance of JRCP structures at SPS-6 sites.

Distress

Statistical 

Relevance 

(Y/N)

Roughness Total Cracking

Y p = 0.0027 N

Ranking 

(if 

relevant)

Ranking Strategy

Overlay 

(mm) Ranking Strategy

Overlay 

(mm)

1 Minimum 102

1 Maximum 102

3

Crack/break and 

seat 203

3 Saw/seal 102

3

Crack/ break and 

seat 102

3 Maximum None

3 Minimum None

8 Control

1 inch = 24.5 mm

Note: The blank cells indicate that no differences were found in short-term total cracking performance among 

all treatments.

Table 85. Rankings for long-term performance of JRCP structures at SPS-6 sites.

Distress

Statistical 

Relevance 

(Y/N)

Roughness Total Cracking

Y p < 0.0001 Y p = 0.0047

Ranking

(if relevant)

Ranking Strategy

Overlay 

(mm) Ranking Strategy

Overlay 

(mm)

1

Crack/break and 

seat 203 1 None

2 Maximum 102 1 Maximum None

2 Minimum 102 3 Minimum None

4

Crack/break and

seat 102 3

Crack/break

and seat 102

4 Saw/seal 102 3 Minimum 102

6 Maximum None 3 Maximum 102

6 Minimum None 3

Crack/break

and seat 203

8 None None 8 Saw/seal 102

1 inch = 24.5 mm

Note: The blank cell indicates that there was no overlay for the control.

The results from table 84 and table 85 suggest that rehabilitation strategies with overlays were

better for improving roughness performance for both short-term and long-term performance 

when compared to strategies without overlays. No difference was found in short-term total 
151

cracking performance among all treatments, while the control section (no treatment) and 

maximum restoration without overlays were identified as the best strategies in the long term.

The impact of rehabilitation strategies on roughness and total cracking performance was 

investigated for all sections in the JRCP sites. Results from the statistical analysis suggest that 

rehabilitation treatments with HMA overlays provided smoother pavement sections, as expected. 

The best alternatives to mitigate the progression of total cracking were the ones without overlays. 

This result was probably influenced by the fact that, when combining all cracking from HMA 

overlays on PCC, reflective cracking at joints were surveyed as longitudinal and transverse 

cracks. Additionally, for nonoverlaid sections, the joints were not counted as cracks, which 

significantly increased the amount of cracking observed during the surveys of HMA overlaid 

sections. The main conclusions from table 84 and table 85 were as follows:

• Rehabilitation strategies with overlays had significantly better roughness performance 

than treatments without overlays.

• Minimum and maximum restorations with overlays were the best strategies to improve 

short-term performance for roughness.

• The best alternative for long-term performance was the thick overlay alternative 

crack/break and seat with 8-inch (203-mm) overlays.

• Rehabilitation strategies without overlays were the best treatments when considering 

total cracking.

• Saw and seal was the worst treatment to prevent cracking among all of the options that 

were evaluated.

• Crack/break and seat of JRCP had no significant effect on reducing the amount of 

cracking, and it performed similarly to the 4-inch (102-mm) overlay over noncracked 

JRCP (with minimum and maximum restoration).

The sawed and sealed joints did not deteriorate significantly on these sections, and they became 

an effective control of reflection cracking. If they were removed from total cracking, the saw and 

sealed sections would have shown similar performance to other HMA overlays.

PCC Restoration Prior to Overlay

The impact on performance of PCC restoration prior to overlaying the structure with HMA was 

evaluated by analyzing a subset of the data that included sections 0603, 0604, 0606, and 0607 

(see table 62). The sample size was too small to identify statistical differences for the majority of 

distresses evaluated. Only short-term and long-term transverse cracking performances were 

found to be statistically different when comparing the rehabilitation alternatives. 

Figure 51 (p = 0.0041, ANOVA chi-square = 13.25) and figure 52 (p = 0.0012, ANOVA 

chi-square = 15.8) summarize the average WD results with associated standard deviations 

for short-term and long-term values. Both figures indicate that saw and seal prior to overlay 

(section 0604) was the worst treatment to prevent transverse cracking when the sawed joints 
152

were considered cracks, while crack/break and seat (section 0607) was the best treatment. The 

complete rankings of best-performing rehabilitation treatments with overlays are provided in 

table 86 for short-term performance and in table 87 for long-term performance.

1 ft = 0.305 m

Figure 51. Graph. Average short-term WD-transverse cracking values for JRCP at 

SPS-6 sites.

1 ft = 0.305 m

Figure 52. Graph. Average long-term WD-transverse cracking values for JRCP at 

SPS-6 sites.
153

Table 86. Rankings for short-term performance of JRCP composite structures at 

SPS-6 sites.

Transverse Cracking

Statistical 

Relevance 

(Y/N) Y p = 0.0041

Ranking 

(if relevant)

Ranking Strategy

Overlay 

(mm)

1 Crack/break and seat 102

2 Maximum 102

2 Minimum 102

4 Saw/seal 102

1 inch = 25.4 mm

Table 87. Rankings for long-term performance of JRCP composite structures at 

SPS-6 sites.

Transverse Cracking

Statistical 

Relevance 

(Y/N) Y p = 0.0012

Ranking 

(if relevant)

Ranking Strategy

Overlay 

(mm)

1 Crack/break and seat 102

1 Minimum 102

3 Maximum 102

4 Saw/seal 102

1 inch = 25.4 mm

The impact of PCC restoration treatments on performance of overlaid sections was investigated 

for JRCP sites of the SPS-6 experiment. Transverse cracking was the only distress for which 

statistical differences were found between the four treatments. The conclusions from this study 

were as follows:

• Crack/break and seat was the best alternative for short-term performance.

• Minimum and maximum restorations had equivalent impacts on short-term performance.

• The best alternatives to limit the development and propagation of transverse cracking in 

the long term were crack/break and seat and minimum restoration.

• Saw and seal prior to overlay was the worst treatment among all options evaluated in the 

SPS-6 experiment.

The sawed and sealed joints did not significantly deteriorate on these sections, and they became 

an effective control of reflection cracking. If they were removed from total cracking, the sawed

and sealed sections would have shown similar performance to other HMA overlays.
154

PCC Restoration

Three sections in each SPS-6 site did not receive overlays as part of their rehabilitation 

strategies, and they were used to evaluate the impact of PCC restoration on performance. The 

sections included 0601 (control), 0602 (minimum restoration), and 0605 (maximum restoration). 

Distresses common to rigid pavements were used as performance measures.

The only performance indicator that showed statistical differences between the treatments was 

short-term transverse slab cracking. Average WD values for short-term transverse slab cracking 

are provided in figure 53 (p = 0.0111, ANOVA chi-square = 9) along with the variability of 

measures in the vertical bars represented by one standard deviation from the average. From this 

figure, the ranking of best-performing alternatives was created and is presented in table 88.

The maximum restoration treatment and the control section had statistically equivalent 

performances for short-term transverse slab cracking. The minimum restoration treatment 

provided the worst transverse slab cracking performance. The small number of sites limited the 

statistical findings.

1 inch = 25.4 mm

Figure 53. Graph. Short-term average WD-transverse cracking values for JRCP at 

SPS-6 sites.

Table 88. Rankings for short-term performance of JRCP structures at SPS-6 sites.

Transverse Cracking

Statistical 

Relevance 

(Y/N) Y p = 0.0111

Ranking 

(if relevant)

Ranking Strategy

Overlay 

(mm)

1 Maximum None

1 None None

3 Minimum None

1 inch = 25.4 mm
155

Summary of Findings for JRCP Sites

When all sections in each site were evaluated simultaneously for roughness and total cracking 

performance, the following were observed:

• Rehabilitation strategies with overlays had significantly better roughness performance 

than treatments without overlays.

• Minimum and maximum restorations with overlays were the best strategies to improve 

short-term performance for roughness.

• The best alternative for long-term performance was the thick overlay alternative 

crack/break and seat with 8-inch (203-mm) overlays.

• Rehabilitation strategies without overlays were the best treatments when considering 

total cracking.

• Saw and seal was the worst treatment to prevent cracking among all options evaluated.

• Crack/break and seat of JRCP had no significant effect on reducing the amount of 

cracking, and it performed similarly to the 4-inch (102-mm) overlay over noncracked 

JRCP (with minimum and maximum restoration).

The results of independent evaluation of sections with HMA overlays suggested the following:

• Crack/break and seat was the best alternative for short-term performance.

• Minimum and maximum restorations had equivalent impacts on short-term performance.

• The best alternatives to limit the development and propagation of transverse cracking on 

the long-term were crack/break and seat and minimum restoration.

• Saw and seal prior to overlay was the worst treatment among all options evaluated in the 

SPS-6 experiment.

The sawed and sealed joints did not deteriorate significantly on these sections, and they became 

an effective control of reflection cracking. If reflective cracking could be removed from total 

cracking, the saw and sealed sections would have shown similar performance to other treatments.

The findings from this statistical analysis of sections without HMA overlay were as follows:

• The maximum restoration treatment and the control section had statistically equivalent 

performances for short-term transverse slab cracking.

• The minimum restoration treatment provided the worst transverse slab cracking 

performance.

• The small number of sites limited the statistical findings in this study.
156

EFFECT OF DESIGN AND CONSTRUCTION FEATURES AND SITE CONDITIONS 

ON RESPONSE OF REHABILITATED RIGID PAVEMENTS

The study to evaluate the impact of design features and site conditions on response of 

rehabilitated rigid pavements followed the same approach used in the study of performance. 

FWD deflections obtained from the LTPP database were used as the response measure of the 

pavement structure. The main difficulty was to determine which deflection measure to use. 

Sections with concrete slabs at the surface were evaluated as typical rigid pavements. Deflections 

at the center of the slab and at the transfer joints were used in this study. Sections that received 

an HMA overlay were monitored like flexible pavements, and deflections at the center of the 

lane were used.

Two separate analyses were developed to address both deflection measurement patterns. The 

first analysis was performed by selecting only sections with a concrete slab surface. The analysis 

investigated the impact of rehabilitation strategies on deflections at the center of the slab and 

LTE between slabs. The second analysis evaluated the impact of PCC treatments prior to overlay 

on maximum deflection measured at the center of the lane after being overlaid.

JPCP and JRCP structures were evaluated independently. Sections 0601, 0603, and 0605 were 

used to evaluate the maximum deflection at the center of the slab and LTE, while sections 0603, 

0604, 0606, and 0607 were used to evaluate maximum deflection at the center of the lane in the 

composite pavement structures. There were limitations due to the amount of data available, 

especially after the data were grouped by pavement structure type and surface. The statistical 

power of the analysis was limited because of the small sample size (eight sites), and no statistical 

differences were found in the pavement response of JPCP structures.

The only analysis that provided some statistically meaningful results was the evaluation of 

maximum deflection at the center lane of overlaid JRCP structures. Figure 54 (p = 0.0155, 

ANOVA chi-square = 10.4) and figure 55 (p = 0.0351, ANOVA chi-square = 8.6) provide the 

Friedman test results for short-term and long-term maximum deflection, respectively. The 

vertical bars represent the 68 percent interval, indicating the level of variability given by one 

standard deviation from the average WD value for maximum deflections. 
157

Table 89 and table 90 present the ranking of rehabilitation strategies based on measurements of 

maximum deflection at the center of the lane.

1 μm = 0.039 mil

Figure 54. Graph. Maximum deflection (center of lane) short-term WD values for JRCP at 

SPS-6 sites.

1 μm = 0.039 mil

Figure 55. Graph. Maximum deflection (center of lane) long-term WD values for JRCP at 

SPS-6 sites.
158

Table 89. Rankings for short-term maximum deflection at the center of the lane of JRCP 

composite structures in SPS-6 sections.

Maximum Deflection at Center of Lane

Statistical 

Relevance (Y/N) Y p = 0.0155

Ranking 

(if relevant)

Ranking Strategy

Overlay 

(mm)

1 (Lowest 

deflection) Minimum 102

2 Saw/seal 102

2 Maximum 102

4

Crack/break

and seat 102

1 inch = 25.4 mm

Table 90. Rankings for long-term maximum deflection at the center of the lane of JRCP 

composite structures in SPS-6 sections.

Maximum Deflection at Center of Lane

Statistical 

Relevance (Y/N) Y p = 0.0351

Ranking 

(if relevant)

Ranking Strategy

Overlay 

(mm)

1 (Lowest 

deflection) Maximum 102

1 Minimum 102

3 Saw/seal 102

4

Crack/break

and seat 102

1 inch = 25.4 mm

The results suggest that crack/break and seat significantly increased the overall deflections 

measured on the pavement surface. The remaining treatments interchangeably provided 

equivalent maximum deflection magnitudes. These results were expected because crack/break 

and seat was an alternative in which the concrete was reduced to smaller pieces, resulting in 

lower stiffness that increased the maximum deflection at the center of the slab.

RELATIONSHIP BETWEEN STRUCTURAL RESPONSES IMMEDIATELY AFTER 

REHABILITATION AND FUTURE PERFORMANCE

There have been several attempts to find direct relationships or models to predict performance 

based on the structural response of the pavement to loading immediately after rehabilitation. 

These relationships are not as straightforward as expected, and accurately deriving them is 

difficult. The objective of this study was to identify trends in the relationship between 

response measured immediately after the rehabilitation and the observed performance in the 

subsequent years of the pavement’s service life. If identified, these trends can provide important
159

information and guidance to infer the expected pavement performance as a result of the 

rehabilitation strategy.

Different structural responses were evaluated against the average pavement performance 

represented by specific distress levels over time for rehabilitation alternatives of SPS-6 sites. 

LTE between slabs and maximum deflection at the center of the slab were used when the surface 

remained concrete slabs after rehabilitation. Maximum deflection at the center of the lane was 

used when the surface changed to HMA after rehabilitation. The average WD for the specific 

distress was used as the performance measure. Each response was evaluated against all distresses 

used previously in this study. Long term-performance was used, which represented performance 

data for 5 years or more.

The SPS-6 experiment had sites across the United States in different climatic zones and subgrade 

types. Consequently, the results from this study could be impacted by in situ conditions. The 

alternative to circumvent this problem was to normalize the data in each site by a common 

factor. For this purpose, one section was selected to be the normalization factor. Response and 

performance measured at this section were used to normalize the data of the remaining sections 

in each site. After some trial and error, the results provided helpful and qualitative information 

about the expected performance given the pavement response measured after the rehabilitation 

work had been completed.

LTE Versus Performance in JPCP

Section 0602 was selected as the normalization factor for the analysis of sections without 

overlay. Normalized values were computed according to the equation in figure 56. LTE analysis 

used deflections at the edge of the slabs forming the transverse joint. An average ratio between 

deflections at the loaded slab and adjacent slab was used to calculate LTE. Only transverse slab 

cracking exhibited a clear trend with LTE values. Figure 57 shows normalized transverse slab 

cracking versus normalized LTE. As the efficiency of the load transfer increases, the amount of 

transverse slab cracking decreases. This trend suggests that good load transfer joint restoration is 

important to mitigate the development and propagation of slab cracking.

PPPPPPPPPPPPPPPPPPNNNN NNNNNN NN = PPPPPPPPPPPPPPPPPPss ss ss

PPPPPPPPPPPPPPPPPP0602

Figure 56. Equation. Parameter subscript normalized.
160

0

0.5

1

1.5

2

2.5

0.6 0.8 1 1.2 1.4

Normalized Transverse slab 

cracking

Normalized LTE

Figure 57. Graph. Normalized long-term transverse cracking versus normalized LTE 

measured after rehabilitation of JPCP sites.

Maximum Deflection at Center of Slab Versus JPCP Performance

Maximum deflection at the center of the slab was investigated as one possible response that 

could be associated with future performance. The trend between performance based on 

roughness and deflection measured at the center of the slab is shown in figure 58, which suggests

that higher deflections indicate smoother JPCP over time. This trend is not what would normally 

be expected, and other correlations for cracking are further examined in the next section.

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

0.6 0.8 1 1.2 1.4 1.6 1.8 2

Normalized Roughness

Normalized Defl (center slab)

Figure 58. Graph. Normalized long-term roughness versus normalized deflection at the 

center of the slab measured immediately after rehabilitation of JPCP sites.

The level of slab cracking also showed an inverse trend with maximum deflection measured at 

the center of the slab. The results presented in figure 59 show normalized values for total 

cracking as a function of normalized deflection. The trend suggests that slabs with higher 

deflections under FWD loading are less likely to develop cracking. The results shown in 
161

figure 60 for longitudinal cracking also suggest the same observation, although no trend was 

found for transverse cracking (see figure 61). A possible explanation is that stiffer subgrades 

resulted in higher slab curling and warping stresses, which led to increased slab cracking. This 

same result was found in MEPDG.

(1) While stiffer foundations reduced axle load stresses, they 

increased curling and warping stresses, which tended to dominate cracking.

0

0.5

1

1.5

2

2.5

3

3.5

0.6 0.8 1 1.2 1.4 1.6 1.8 2

Normalized Total Cracking

Normalized Defl (center slab)

Figure 59. Graph. Normalized long-term total cracking versus normalized deflection at the 

center of the slab measured immediately after rehabilitation of JPCP sites.

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

Normalized Longitudinal slab 

0.6 1.1 1.6 2.1

cracking

Normalized Defl (center slab)

Figure 60. Graph. Normalized long-term longitudinal slab cracking versus normalized 

deflection at the center of slab measured after rehabilitation of JPCP sites.
162

0

0.5

1

1.5

2

2.5

0.6 1.1 1.6 2.1

Normalized Transverse slab 

cracking

Normalized Defl (center slab)

Figure 61. Graph. Normalized long-term transverse cracking versus normalized deflection 

at the center of slab measured after rehabilitation of JPCP sites.

Faulting was also investigated in this study. The trend obtained from the data analyzed is 

presented in figure 62, suggesting that faulting was inversely proportional to deflection measured 

at the center of the slab. High deflection values yielded low faulting, although the trend was

weak and depended on only one or two points. No logical explanation exists for this result

because the opposite result should occur theoretically. However, the small number of data points 

limited the outcome of the analysis.

0

0.2

0.4

0.6

0.8

1

1.2

1.4

0.6 0.8 1 1.2 1.4 1.6 1.8 2

Normalized Faulting

Normalized Defl (center slab)

Figure 62. Graph. Normalized long-term faulting versus normalized deflection at the 

center of slab measured after rehabilitation of JPCP sites.

Maximum Deflection at Center of Lane Versus Performance of Overlaid JPCP

Maximum deflection at the center of the lane was measured in sections that received an overlay 

as part of the rehabilitation strategy. Sections 0603, 0604, 0606, 0607, and 0608 received 

different PCC restoration treatments, but all were overlaid as the final step in the rehabilitation 

process. Section 0603 was chosen for data normalization. Most of the distresses had clear trends 
163

with the chosen response. The trends agreed with the conventional understanding and 

expectations of the relationship between performance and response.

The positive trend between roughness and maximum deflection is shown in figure 63. There was

a clear indication in the data, suggesting that overlaid JPCP with high deflections were more 

likely to be rougher in the long term when compared to sections with low deflection values. 

Similarly, it was found that overlaid JPCP sections with high center lane deflections were more 

likely to experience increased rutting compared to sections with low deflection values, as 

suggested in figure 64. Since most rutting occurred in the HMA layer, the cause for this result 

was not explainable unless the HMA was so soft that it was contributing to the deflections. 

Normally, deflections are in the foundation of JPCP.

Fatigue cracking exhibited an expected trend with deflection for overlaid JPCP sections. The 

trend in figure 65 suggests that high fatigue cracking was expected when deflections values were

high. The results in figure 66 suggest that high longitudinal cracking values were observed when 

maximum deflection at the center of the lane was low. This indicated that the pavement structure 

was less deformable and more susceptible to surface tensile stresses, which was an important 

contributor to development and propagation of longitudinal cracking.

0

0.5

1

1.5

2

0.6 1.1 1.6 2.1 2.6

Normalized Roughness

Normalized Max Defl (HMA)

Figure 63. Graph. Normalized long-term roughness versus normalized deflection at the 

center of the lane measured after rehabilitation of overlaid JPCP sites.
164

0

0.5

1

1.5

2

2.5

0.6 1.1 1.6 2.1 2.6

Normalized Rutting

Normalized Max Defl (HMA)

Figure 64. Graph. Normalized long-term rutting versus normalized deflection at the center 

of the lane measured after rehabilitation of overlaid JPCP sites.

0

0.5

1

1.5

2

2.5

3

3.5

Normalized Fatigue cracking

0.6 0.8 1 1.2 1.4 1.6 1.8

Normalized Max Defl (HMA)

Figure 65. Graph. Normalized long-term fatigue cracking versus normalized deflection at 

the center of the lane measured after rehabilitation of overlaid JPCP sites.
165

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

0.6 1.1 1.6 2.1 2.6

Normalized Longitudinal 

cracking

Normalized Max Defl (HMA)

Figure 66. Graph. Normalized long-term longitudinal cracking versus normalized 

deflection at the center of the lane measured after rehabilitation of overlaid JPCP sites.

Response Versus Performance in JRCP

The investigation of possible trends between response and performance in JRCP structures did 

not result in any significant conclusions. Different performance measures were analyzed against 

LTE, maximum deflection at the center of the slab, and maximum deflection at the center of the 

lane; however, no relevant conclusions were reached.

167

CHAPTER 7. ANALYSIS OF REHABILITATED PAVEMENT STRUCTURES USING 

MEPDG

INTRODUCTION

One part of this study was to evaluate rehabilitated pavement structures using MEPDG.

(1) The 

objective of the task was to compare MEPDG-predicted performance with field-measured data 

and verify the current calibration against predictions of rehabilitated pavement structures. 

Flexible pavement sections from the SPS-5 experiment and rigid/composite pavement sections 

from the SPS-6 experiment were subject to MEPDG analysis, and the results were compared to 

actual distress measurements from LTPP surveys. All JPCP sections from both experiments were 

used in this analysis.

This research also produced a database of rehabilitated sections extracted from the LTPP 

program that can be used to perform local calibrations. The database is described in appendix E.

MEPDG OVERVIEW

MEPDG is based on principles of both engineering mechanics and field verification to estimate 

performance.

(1) A mechanistic approach is used to predict pavement responses to traffic loads, 

and pavement performance is then estimated based on empirical relationships developed from 

evidence from field data.

Data Requirements

MEPDG considers three main factors in the analysis of pavement performance: traffic, 

environment, and pavement structure.

(1) Each of these factors is described below.

Traffic

Traditionally, traffic inputs for pavement design have been single numbers, such as the annual 

average daily traffic or ESAL concepts. In developing MEPDG, it was recognized that these 

parameters do not sufficiently characterize the variable effects of axle loads distributions, traffic 

characteristics (speed, wander, etc.), and axle and tire configuration on pavements.

MEPDG utilizes the traffic spectra, and the anticipated or historical traffic is classified according 

to axle type (single, tandem, tridem, quad, or special axles) and the distribution of axle weights 

within each axle type.

Environment

There are three basic elements required to consider the environmental factors in MEPDG 

analysis: (1) site-specific environmental data, (2) material-specific data on thermal-related 

properties, and (3) an algorithm to compute the transmission of heat and moisture within 

the pavement structure. MEPDG considers the seasonal effects of temperature and moisture 

on material properties of pavement layers, and consequently, on pavement response 

and performance.
168

Pavement Structure

As with any pavement analysis and design procedure, it is necessary to define the materials used 

in the structure including their properties, thicknesses, and construction characteristics. MEPDG 

can be used to analyze both new and rehabilitated PCC, HMA, and composite (PCC and HMA) 

pavements. Measured mechanical properties can be used to characterize the material’s behavior 

to loading and thermal variations.

Summary of Data Required for MEPDG Analysis

Table 91 provides a list of the data required for MEPDG analysis. The current national 

calibration is defined as level 3 input for material properties. To provide an equivalent level 

of comparison, the input data for this study were collected as level 3.

Table 91. Predominant source of data used for preliminary statistical analysis and MEPDG 

performance models verification.

Input Group Input Parameter Data Source

Truck traffic

Axle load distributions (single, tandem, 

and tridem) LTPP

Truck volume distribution LTPP

Lane and directional truck distributions LTPP

Tire pressure MEPDG defaults

Axle configuration and tire spacing MEPDG defaults

Truck wander MEPDG defaults

Climate Temperature, wind speed, cloud cover, 

precipitation, and relative humidity

National Climate Data 

Center

Material 

properties

Unbound 

layers and

subgrade

Resilient sodulus—subgrade

all unbound layers MEPDG defaults

Resilient modulus—base/subbase MEPDG defaults

Classification and volumetric properties LTPP

Moisture-density relationships LTPP

Soil-water characteristic relationships MEPDG defaults

Saturated hydraulic conductivity MEPDG defaults

HMA

HMA dynamic modulus LTPP

HMA creep compliance and indirect 

tensile strength MEPDG defaults

Volumetric properties LTPP

HMA coefficient of thermal expansion MEPDG defaults

PCC

PCC elastic modulus LTPP

PCC flexural strength LTPP

PCC coefficient of thermal expansion LTPP

All materials

Unit weight LTPP

Poisson’s ratio MEPDG defaults

Other thermal properties, conductivity, 

heat capacity, and surface absorptivity MEPDG defaults

Note: MEPDG generates climate files using data from the National Climate Data Center.
169

Latest Calibration Efforts

The original calibration for MEPDG was finalized in 2004 and was based on performance data 

from several projects, mainly from the LTPP program for data collected until 2001. Recently, an 

effort under NCHRP Projects 1-40A and 1-40D added 4–5 years of new data to improve the 

national calibration.

(21,22) A summary of the efforts carried out to obtain current calibration by 

pavement type is provided below.

Flexible Pavement Calibration

Data from 49 sections from the GPS-6B and SPS-5 projects were used for the calibration and 

validation of HMA overlays over existing AC structures. Data from three sections of the SPS-6 

experiment were used for the calibration and validation of the HMA overlay over existing 

fractured slab structures. Data from seven sections from the GPS-7B and SPS-6 projects were 

used for the calibration and validation of HMA overlay over existing JPCP structures.

PCC Rehabilitation Calibration

Calibration data were obtained from the LTPP database, the American Concrete Pavement 

Association Longevity and Performance of Diamond-Ground Pavements study, and NCHRP 

Project 10-41, Guidelines for the Design of Unbonded PCC Overlays.

(23) Different datasets were 

used to calibrate restored JPCP.

Data were obtained from the SPS-6 experiment, specifically sections 0601, 0602, and 0605, 

which corresponded to JPCP sections without overlay in the rehabilitation strategy. The 

restoration performed on these test sections ranged from the no treatment control section to 

full depth patching and retrofitting joints with dowels. Specific restoration treatments included

the following:

• Crack sealing.

• Transverse joint sealing.

• Full depth transverse joint repair patch.

• Full depth patching of PCC pavement other than at joint.

• Partial depth patching of PCC pavement other than at joint.

• PCC slab replacement.

• AC shoulder restoration.

• AC shoulder replacement.

• Diamond grinding surface (all sections used in verifying faulting).
170

• Pressure grout subsealing.

• Joint load transfer restoration.

REHABILITATED FLEXIBLE PAVEMENTS

The performance of the 500-ft (152.5-m) sections in the SPS-5 experiment was estimated using 

MEPDG software Version 1.003. Load-associated distress trends were compared to LTPPmeasured distress values from surveys. Three pavement distress types were evaluated including 

roughness, rutting, and cracking.

It should be noted that LTPP-measured distress data and MEPDG-predicted performance data do 

not have the same units of measurement. As a result, MEPDG-predicted performance was 

converted to match the units used in the LTPP database. Table 92 explains the conversion used 

in this analysis.

Table 92. Conversion of MEPDG-predicted performance data to LTPP units.

Performance 

Parameter

LTPP Units for 

the Parameter

MEPDG Units for the 

Parameter

Conversion to LTPP 

Units

Fatigue 

cracking ft2

Percentage of the 

design lane cracked

(Percentage cracked) ×

500_ft×12_ft/100

Longitudinal 

cracking ft ft/mi

(Distress in ft/mile) ×

500_ft/5280_ft

Transverse 

cracking ft ft/mi

(Distress in ft/mile) ×

500_ft/5280_ft

1 ft = 0.305 m

1 ft2 = 0.093 m2

1 mi = 1.61 km

Note: The underscores indicate the format used when entering data into the LTPP database.

Both the LTPP-measured data and the MEPDG-predicted distresses were converted into SI units 

for plotting. The comparative analyses are presented in the following sections.

Roughness

Predicted versus measured pavement roughness was evaluated in terms of IRI values. Figure 67

describes predicted versus measured performance for all sections in the SPS-5 experiment. The 

data were grouped by rehabilitated and control sections (without overlay), and the results were

reasonable overall. However, some bias was noted for both sets of data. The results for 

rehabilitated sections showed a bias for underprediction of IRI, whereas the control sections 

showed a tendency for bias of overprediction. Because the analysis of the control sections 

considered the pavement life since its construction and the window monitored for rehabilitated 

pavements were defined for several years after the initial construction, MEPDG was

overpredicting the IRI levels for new flexible pavements during the last portion of the 

pavement’s life. 

The MEPDG out-of-the-box models were calibrated using only new pavement sections. This 

exercise involving rehabilitated sections from the SPS-5 experiment indicated that the roughness 
171

model could be used to predict IRI values with fairly good accuracy in rehabilitated sections. 

Local calibration of the current model may further improve accuracy of roughness predictions in 

rehabilitated sections.

0

1

2

3

4

5

0 1 2 3 4 5

IRI-predicted, m/km

IRI-measured, m/km

Rehabilitated Sections

Control Sections

Equality Line

1 ft = 0.305 m

1 mi = 1.61 km

Figure 67. Graph. LTPP-measured versus MEPDG-predicted IRI for all SPS-5 sections.

The level of accuracy for the MEPDG roughness model predictions was similar for the control 

sections with poor and fair pavement conditions prior to the beginning of the experiment (see 

figure 68). Similar results were found for rehabilitated sections (see figure 69). The difference in 

this case was that there was a tendency to underpredict rehabilitated sections with poor overall 

condition and IRI values above 10.56 ft/mi (2 m/km).
172

0

1

2

3

4

5

0 1 2 3 4 5

IRI-predicted, m/km

IRI-measured, m/km

Control Sections - Fair Condition

Control Sections - Poor Condition

Equality Line

1 ft = 0.305 m

1 mi = 1.61 km

Figure 68. Graph. LTPP-measured versus MEPDG-predicted IRI for SPS-5 

control sections.

0

1

2

3

4

5

0 1 2 3 4 5

IRI-predicted, m/km

IRI-measured, m/km

Rehab Sections - Fair Condition

Rehab Sections - Poor Condition

Equality Line

1 ft = 0.305 m

1 mi = 1.61 km

Figure 69. Graph. LTPP-measured versus MEPDG-predicted IRI for SPS-5 rehabilitated 

sections.

Another site factor with a visible impact on the accuracy of the models was the climate 

condition. Results in figure 70 and figure 71 suggest that despite the small bias for the control 
173

sections, the current model did a better job predicting IRI in sections located in wet regions in 

comparison to dry locations, especially for rehabilitated sections. The other climate variable in 

the SPS-5 experiment was temperature (freeze versus no-freeze); however, temperature did not 

influence the accuracy of predictions.

0

1

2

3

4

5

0 1 2 3 4 5

IRI-predicted, m/km

IRI-measured, m/km

Control Sections - Dry Region

Control Sections - Wet Region

Equality Line

1 ft = 0.305 m

1 mi = 1.61 km

Figure 70. Graph. LTPP-measured versus MEPDG-predicted IRI for SPS-5 control 

sections in wet and dry regions.
174

0

1

2

3

4

5

0 1 2 3 4 5

IRI-predicted, m/km

IRI-measured, m/km

Rehab Sections - Dry Region

Rehab Sections - Wet Region

Equality Line

1 ft = 0.305 m

1 mi = 1.61 km

Figure 71. Graph. LTPP-measured versus MEPDG-predicted IRI for SPS-5 rehabilitated 

sections in wet and dry regions.

The influence of design features on the MEPDG performance predictions was also investigated. 

The results obtained for the rehabilitated sections were grouped by overlay thickness, mix type, 

and milling. The results of predicted versus measured IRI performance are shown in figure 72

through figure 74. 

The following observations were made:

• MEPDG did a better job predicting the roughness performance of rehabilitated sections 

with thick overlays. Thin overlay predictions were more disperse, especially for high IRI 

values where underprediction was obvious (see figure 72).

• MEPDG did a better job predicting the roughness performance of rehabilitated sections 

with virgin overlays. RAP mix overlay predictions are more disperse, especially for high 

IRI values (see figure 73).

• MEPDG predictions of rehabilitated sections with and without milling prior to overlay 

exhibit the same level of accuracy and bias (see figure 74).
175

0

1

2

3

4

5

0 1 2 3 4 5

IRI-predicted, m/km

IRI-measured, m/km

Rehabilitated Sections - "Thin" Overlay

Rehabilitated Sections - "Thick" Overlay

Equality Line

1 ft = 0.305 m

1 mi = 1.61 km

Figure 72. Graph. LTPP-measured versus MEPDG-predicted IRI for SPS-5 rehabilitated 

sections grouped by thickness.

0

1

2

3

4

5

0 1 2 3 4 5

IRI-predicted, m/km

IRI-measured, m/km

Rehabilitated Sections - "Rap" Mix

Rehabilitated Sections - "Virgin" Mix

Equality Line

1 ft = 0.305 m

1 mi = 1.61 km

Figure 73. Graph. LTPP-measured versus MEPDG-predicted IRI for SPS-5 rehabilitated 

sections grouped by mix type.
176

0

1

2

3

4

5

0 1 2 3 4 5

IRI-predicted, m/km

IRI-measured, m/km

Rehabilitated Sections with "No Milling"

Rehabilitated Sections with "Milling"

Equality Line

1 ft = 0.305 m

1 mi = 1.61 km

Figure 74. Graph. LTPP-measured versus MEPDG-predicted IRI for SPS-5 rehabilitated 

sections grouped by milling.

It is important to note that the group of points with high IRI levels in figure 72 through 

figure 74 (IRI > 9.50 ft/mi (1.8 m/km)) were sections classified as having poor initial conditions. 

Results demonstrate that these sections did not perform well and that, in general, MEPDG 

underpredicted the IRI levels for these sections. Overall, the current MEPDG IRI model predicts 

performance reasonably well, provided it is calibrated using data from new pavement sections. 

Local calibration of the model is likely to improve accuracy and reduce bias, especially for 

rehabilitated sections that were in poor condition prior to rehabilitation.

Rutting

When comparing actual rutting versus MEPDG-estimated rutting, control sections and 

rehabilitated sections were evaluated. The goal was to observe the trends when analyzing new 

pavements and rehabilitated pavements. Control section estimates were obtained by running the 

MEPDG software for a new section; however, the data screened for the analysis were those 

gathered during the survey period of the SPS-5 sites. 

For most control sections, MEPDG overpredicted rutting, while for rehabilitated sections, there 

was not an evident bias (see figure 75). Nonetheless, in many cases, the rutting levels were either 

underpredicted or overpredicted. The control sections were treated as new sections; therefore, the 

rutting predictions included base and subgarde rutting. For overlays, the only rutting considered 

in MEPDG was that of the overlay, and no rutting was allowed in the underlying layers. 

Attempts were made to identify whether there was a consistent reason for underpredictions or 

overpredictions of rutting (i.e., site conditions or design features of the rehabilitated sections), 

but no reason was found. The results in figure 75 suggest that the rutting model needs further 

calibration to reduce bias in predicting the performance of new pavements. Most likely, the lack 
177

of sufficient rutting data for each pavement layer during the initial MEPDG calibration and the 

need to assume individual layer contribution to total rutting led to the results in the figure. A 

revised model is recommended to improve accuracy in predicting the performance of 

rehabilitated pavements. 

0

5

10

15

20

25

30

0 5 10 15 20 25 30

Rutting-predicted, mm

Rutting-measured, mm

Rehabilitated Sections

Equality Line

Control Sections

1 inch = 25.4 mm

Figure 75. Graph. LTPP measured versus MEPDG predicted rutting for SPS-5 sections.

Cracking

MEPDG estimates of top-down longitudinal cracking, low temperature transverse cracking, 

and bottom-up alligator fatigue cracking were computed and compared to actual survey 

measurements available in the LTPP database for the SPS-5 experiment. Predicted versus 

measured longitudinal cracking results are shown in figure 76. With the exception of one site, all 

predictions had zero or near-zero values. MEPDG consistently underpredicts longitudinal 

cracking for both new and rehabilitated pavements. When comparing transverse cracking, 

MEPDG does not predict any transverse cracking in any of the analyses that were performed.

Fatigue cracking was computed as the sum of alligator cracking (developed in the new overlay 

HMA layer) and reflective cracking (cracking in the old surface propagated upward into the new 

layer). In MEPDG, these cracking patterns are represented by cracking types FC1 and FC2, 

respectively. MEPDG predicts fatigue cracking on the surface as a “percentage of the design lane 

cracked.”(1) The MEPDG fatigue cracking outputs were converted into cracked area according to 

table 92. Predicted fatigue cracking data were plotted against measured data and are presented in 

figure 77. It can be concluded from the comparative graph that the fatigue cracking model in 

MEPDG underpredicts the performance of both new and rehabilitated pavements.

The reflective cracking model dominates the total fatigue cracking predictions. If only the fatigue 

cracking associated with the new overlay layer is plotted against the measured fatigue cracking 
178

in the LTPP database, the MEPDG-predicted fatigue cracking is underpredicted (see figure 78). 

The figure suggests that reflective cracking propagating from the existing layer is the major 

contributor to the total fatigue cracking predictions. The reflective cracking model needs further 

improvements to reduce the bias and enhance its accuracy.

0

100

200

300

400

500

600

700

0 100 200 300 400 500 600 700

Longitudinal cracking -predicted, m

Longitudinal cracking-measured, m

Rehabilitated Sections

Control Sections

Equality Line

1 ft = 0.305 m

Figure 76. Graph. LTPP-measured versus MEPDG-predicted longitudinal cracking for 

SPS-5 sections.
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0

100

200

300

400

500

600

0 100 200 300 400 500 600

Cracking-predicted, sq.m

Cracking-measured, sq.m

Rehabilitated Sections

Control Sections

Equality Line

1 ft2 = 0.093 m2

Figure 77. Graph. LTPP-measured versus MEPDG-predicted fatigue and reflective 

cracking for SPS-5 sections.

0

100

200

300

400

500

600

0 100 200 300 400 500 600

Fatigue cracking-predicted, sq.m

Fatigue cracking-measured, sq.m

Rehabilitated Sections

Control Sections

Equality Line

1 ft2 = 0.093 m2

Figure 78. Graph. LTPP-measured versus MEPDG-predicted fatigue cracking for SPS-5 

sections.
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REHABILITATED RIGID PAVEMENTS

The performance of the 500-ft (152.5-m) sections in the SPS-6 experiment was estimated using 

MEPDG software Version 1.003. Estimated and actual load-associated distress trends were 

compared for the following pavement distresses and properties:

• Roughness.

• Rutting.

• Cracking.

• Faulting.

• LTE.

Both the LTPP-measured data and the MEPDG-predicted data were converted into SI units for 

plotting. The comparative analyses are presented in the following sections.

Roughness

Pavement roughness was evaluated in terms of IRI values. Figure 79 and figure 80 describe 

predicted versus measured roughness for all sections in the SPS-6 experiment. Figure 79 presents 

results for all the sections in which the rehabilitation treatment had no overlay. These sections, 

0601, 0602, and 0605, received only restoration treatments in the PCC layer or no treatment at 

all. Figure 80 shows the trends for all sections in which the rehabilitation treatment had overlay

(sections 0603, 0604, 0606, 0607, and 0608). Both figures suggest that the IRI model provides 

fairly good predictions of roughness performance. Sections without overlays were slightly 

underpredicted, especially for sections with restoration (minimum or maximum). Sections with 

overlays were predicted more consistently with measured values, especially for IRI values lower 

than 9.50 ft/mi (1.8 m/km). For IRI values higher than 1.8 m/km, the models consistently 

underpredicted performance.
181

1 ft = 0.305 m

1 mi = 1.61 km

Figure 79. Graph. LTPP-measured versus MEPDG-predicted IRI for SPS-6 sections 

without overlay.

1 ft = 0.305 m

1 mi = 1.61 km

Figure 80. Graph. LTPP-measured versus MEPDG-predicted IRI for SPS-6 sections 

with overlay.
182

Climate condition influenced MEPDG roughness predictions. Figure 81 and figure 82 present 

predicted versus measured IRI for sites located in wet and dry regions. The results suggest that 

sites located in wet regions had predictions that were more accurate and less biased than sites 

located in dry regions; however, there was still underprediction for high IRI levels. MEPDG 

consistently underpredicts high IRI values (higher than 9.50 ft/mi (1.8 m/km)) in dry regions. 

Figure 83 and figure 84 show predicted versus measured IRI for sites located in freeze and 

no-freeze regions. The results suggest that sites located in no-freeze regions have predictions that 

are more accurate and less biased than sites located in freeze regions. MEPDG consistently 

underpredicts high IRI values (higher than 9.50 ft/mi (1.8 m/km)) in freeze regions.

1 ft = 0.305 m

1 mi = 1.61 km

Figure 81. Graph. LTPP-measured versus MEPDG-predicted IRI for SPS-6 sections in 

wet regions.
183

1 ft = 0.305 m

1 mi = 1.61 km

Figure 82. Graph. LTPP-measured versus MEPDG-predicted IRI for SPS-6 sections in 

dry regions.

1 ft = 0.305 m

1 mi = 1.61 km

Figure 83. Graph. LTPP-measured versus MEPDG-predicted IRI for SPS-6 sections in 

freeze regions.
184

1 ft = 0.305 m

1 mi = 1.61 km

Figure 84. Graph. LTPP-measured versus MEPDG-predicted IRI for SPS-6 sections in 

no-freeze regions.

Despite the variations in the quality of predictions among different site factors, predictions of 

sections with overlays were consistently better than sections without overlays, including the 

control section. This was surprising because most of the the MEPDG calibration effort was 

devoted to new pavement conditions.

Rutting

Predicted versus measured rutting data are shown in figure 85 for SPS-6 sections with HMA 

overlays on JPCP. The results suggest that the rutting model was consistently overpredicting for 

HMA over cracked and seated JPCP . The results also suggest that MEPDG underpredicts for 

regular HMA over JPCP slab. This is likely caused by the MEPDG assumption for HMA over 

cracking and seated pavement. The total rutting in all layers is predicted; thus, some 

overprediction occurred. For HMA over existing JPCP, the rutting output was only in HMA.
185

1 inch = 25.4 mm

Figure 85. Graph. LTPP-measured versus MEPDG-predicted rutting for SPS-6 sections 

with overlays.

Cracking

Estimates of longitudinal top-down fatigue cracking and fatigue bottom-up alligator cracking 

were computed using MEPDG. Predicted versus measured longitudinal fatigue cracking results 

in wheel paths only are shown in figure 86. The MEPDG software does not predict longitudinal 

cracking on HMA overlays over JPCP. Total fatigue cracking data (i.e., new cracking originated 

at the new HMA overlay plus reflective cracking from propagated cracks in the PCC layer) 

are shown in figure 87. The results suggest that the MEPDG fatigue cracking model may 

underpredict and overpredict the levels of cracking. Reflective cracking was the only component 

with predictions higher than zero, as expected. 

Several attempts were made to isolate the sections being underpredicted and overpredicted based 

on climate conditions, pavement condition prior to overlay, or type of treatment, but the results 

were inconclusive. It was difficult to identify sources of cracking during surveys, and reflective 

cracking usually was not measured for the LTPP experiments. The confusion on the source of 

cracking measured in addition to the existing emprical model for reflective cracking incorporated 

in MEPDG highlights the need for future studies under the LTPP program, particularly to 

address improvements to the existing model for reflective cracking to be based on reliable data 

for this type of distress.
186

1 ft = 0.305 m

Figure 86. Graph. LTPP-measured versus MEPDG-predicted longitudinal cracking for 

HMA overlaid SPS-6 sections.

1 ft = 0.305 m

Figure 87. Graph. LTPP-measured versus MEPDG-predicted fatigue and reflective

cracking for HMA overlaid SPS-6 sections.
187

Faulting

Trends for MEPDG predicted versus measured faulting are shown in figure 88 for SPS-6 

sections without overlay. The results suggest that MEPDG underpredicts faulting for the 

majority of rehabilitated sections. The sites were grouped by climate conditions; however, the 

results did not provide any information on possible influence of climate conditions. An attempt 

was made to isolate pavement surface condition prior to rehabilitation. Predicted versus 

measured faulting for SPS-6 sections grouped by pavement surface condition is shown in 

figure 89 and figure 90. Faulting in pavements in fair condition prior to rehabilitation was 

consistently underpredicted, as suggested in figure 89. Predictions were more accurate for 

sections with pavements in poor condition prior to rehabilitation (see figure 90).

1 inch = 25.4 mm

Figure 88. Graph. LTPP-measured versus MEPDG-predicted faulting for SPS-6 sections 

without HMA overlay.
188

1 inch = 25.4 mm

Figure 89. Graph. LTPP-measured versus MEPDG-predicted faulting for SPS-6 sections 

without HMA overlay with fair pavement condition prior to rehabilitation.

1 inch = 25.4 mm

Figure 90. Graph. LTPP-measured versus MEPDG-predicted faulting for SPS-6 sections 

without HMA overlay with poor pavement condition prior to rehabilitation.
189

Load Transfer Efficiency

LTE was estimated for SPS-6 sections without HMA overlay using MEPDG. Predicted versus 

measured data from LTPP SPS-6 sections are plotted in figure 91. The results suggest that the 

LTE model slightly overpredicted LTE for sections without any rehabilitation (control), but 

estimates were considered reasonable. The results were better for sections that received some 

maintenance/rehabilitation work (minimum and maximum). Site conditions were investigated, 

and no further trends were observed.

Figure 91. Graph. LTPP-measured versus MEPDG-predicted LTE for SPS-6 sections 

without HMA overlay.

SUMMARY AND CONCLUSIONS

The MEPDG roughness models for both flexible and rigid pavements provided good predictions 

of rehabilitated sections with and without HMA overlay. There were some biases in the 

predictions, which could be addressed with local or a revised general calibration. MEPDG tends 

to underpredict roughness for rigid pavement sections with IRI values above 9.50 ft/mi 

(1.8 m/km). This bias was more characteristic of sections located in dry and freeze regions.

The HMA rutting model needs further enhancements to further predict permanent deformation 

accurately in HMA overlay over flexible and rigid pavements. Interestingly, the rutting model 

overpredicted performance of HMA overlays over crack/break and seat restored rigid pavements 

and underpredicted for the rest of restoration treatments (saw and seal and minimum and 

maximum restorations prior to overlays). MEPDG considers the cracked/broken PCC layer as a 

new granular base layer. Permanent deformation was predicted for the new layer and the 

subgrade, which is normally the reason for the overprediction of total rutting identified in this 

study. The rutting model clearly needs calibration before use with overlaid pavements.
190

The cracking models for HMA overlays, particularly the empirical reflection cracking, need 

further enhancements to provide more accurate predictions. The models for fatigue cracking 

(new and reflective) and longitudinal cracking were not capable of predicting consistent and 

comparable performance with measured values. MEPDG did not predict transverse cracking in 

any of the SPS-5 or SPS-6 sections, although some transverse cracking was measured 

during surveys.
191

CHAPTER 8. STUDY FINDINGS, CONCLUSIONS, AND RECOMMENDATIONS

This chapter provides the findings and conclusions from the analysis of preventive maintenance 

treatments and performance of different pavement rehabilitation alternatives. Recommendations 

for future research are provided at the end of the chapter.

PREVENTIVE MAINTENANCE TREATMENTS

The findings presented in this section are based on the analysis of 81 SPS-3 flexible pavement 

sites and 34 SPS-4 rigid pavement sections subjected to different preventive maintenance 

treatments. Most of the flexible pavement sites were monitored for at least 4 years, and about 

22 percent of the sites were monitored for 10 years or more. Most of the rigid pavement sites 

were monitored for at least 4 years.

Preventive Maintenance Effectiveness for Flexible Pavements

From the analysis of SPS-3 sites, the following effects of preventive maintenance treatments on 

pavement performance were observed:

IRI:

• Of all of the SPS-3 treatments, only thin overlay was effective in mitigating and delaying 

the progression of roughness; however, this treatment was effective only for pavements 

in freeze zones, high traffic, or poor condition.

Rutting:

• Thin overlay mitigated and slowed the progression of rutting under all circumstances. 

• Chip seal was more effective than slurry seal in wet freeze zones but was only marginally 

more effective in dry freeze zones.

• There were no significant differences between slurry seal, crack seal, and the no 

treatment control scenario with respect to rutting.

Fatigue cracking:

• Thin overlays and chips seals were more effective than slurry seal and crack seal 

treatments in mitigating fatigue cracking. 

• With respect to fatigue cracking, thin overlays performed better than most other 

treatments if the pavement was in a freeze zone, in a wet climatic region, subject to high 

traffic, or initially in poor condition. 
192

Preventive Maintenance Effectiveness for Rigid Pavements

The study of the SPS-4 sites showed that the performance of the joint/crack sealed sections and 

undersealed sections was not significantly different from the performance of control sections. 

Additionally, no meaningful difference between the two treatments was found. The analysis was 

weakened by the small number of sites and only 4 years of performance history that included 

recorded surveys with undersealing treatment. While 34 sites included the survey measurements 

for joint/crack sealed sections, only 10 sites had data for undersealed sections. 

REHABILITATED FLEXIBLE PAVEMENTS

The findings presented in this section are based on the analysis of 18 SPS-5 rehabilitated flexible 

pavement experimental sites with 162 core test sections. Most of the sections were monitored for 

at least 9 years.

Evaluation of Rehabilitation Strategies with Respect to Performance

To analyze data from the SPS-5 experiment, a gradual statistical analysis was used in which 

the data from each site were analyzed first, followed by a consolidated analysis of all sites 

simultaneously in search for general trends and broader conclusions about pavement 

performance and its dependency on design features and site conditions. The results obtained in 

the consolidated analysis mostly agree with the results found in the individual site analyses. A 

summary of the analysis findings with respect to major pavement performance indicators is 

provided below.

IRI:

• Rehabilitation strategies with milling prior to overlay provided better roughness 

performance (i.e., smoother) for all site conditions.

• Strategies with thick overlays provided smoother pavements for all site conditions.

• Strategies with virgin or RAP mixes had equivalent performance when used under 

wet conditions.

• Strategies with RAP mixes provided smoother pavements when used in dry conditions.

• Traffic level and freeze conditions did not impact roughness performance ranking.

Rutting:

• Rehabilitation strategies with thin overlays performed better than thick overlays in the 

short term. In the long term, the ranking of best strategies was more evenly distributed for 

both thick and thin overlays.

• The ranking of best strategies was evenly distributed among the two mix types (virgin

and RAP) in the short term. In the long term, rehabilitation strategies with virgin mixes 

were in the top ranking of performance more frequently (lowest rutting), with the 
193

exception of fair pavement surface under freeze conditions, which corresponded to 

33 percent of all sites.

• Strategies with milling did not improve rutting performance more than alternatives 

without milling.

• Surprisingly, the level of traffic did not affect rutting performance of the selected 

rehabilitation strategies.

Fatigue cracking:

• Short-term fatigue cracking performance was not affected significantly by any design 

features under any site conditions, which makes sense because overlays were designed to 

minimize fatigue cracking in the short term.

• Rehabilitation strategies with thick overlays provided better performance for fatigue 

cracking under all site conditions evaluated.

• Strategies with milling prior to overlay performed better to mitigate development and 

propagation of fatigue cracking in all site conditions.

• In regions with a dry climate, alternatives without milling performed as well as solutions 

with milling.

• Strategies with RAP mixes were better ranked for sites with low traffic.

Transverse cracking:

• There were no differences identified in short-term performance among the rehabilitation 

strategies in freezing zones.

• Among the sites located in no-freeze zones, the remaining site conditions did not have 

any impact on short-term performance.

• Strategies with virgin mixes and thick overlays ranked best for long-term transverse 

cracking performance.

• Strategies with RAP mixes performed better than virgin mixes when the site had low 

traffic and when the site had high traffic and a dry climate.

• Milling prior to overlay did not improve performance more than alternatives

without milling.

Longitudinal cracking (in wheel paths):

• Rehabilitation strategies with milling prior to overlay were consistently better for 

improving performance than alternatives without milling.
194

• Strategies with virgin mixes were consistently better than alternatives with RAP in sites 

located in wet climates.

• There was no difference in ranking between strategies with virgin and RAP mixes in 

dry conditions.

• Overlay thickness was not a significant factor affecting performance associated with 

longitudinal cracking.

In terms of the effect of design features or construction practices, the following conclusions 

were made:

Overlay thickness:

• Overlay thickness was the most influential design feature. Thick overlays consistently 

performed better than thin overlays, as expected. 

• The impact of thickness on performance was more evident in the long term (more than 

5 years) for most of the distresses. The exception was rutting, which had no evidence 

suggesting that either thin or thick overlays provided less rutting.

Milling:

• The analysis of milling prior to overlay suggested that replacing the distressed portion of 

the surface layer improved the performance for the majority of distresses commonly 

observed in flexible pavements.

RAP mixes:

• The majority of sites did not show significant differences in performance between 

sections overlaid with virgin and RAP mixes. However, when differences existed, they 

were mostly in favor of virgin mixes.

Evaluation of Rehabilitation Strategies with Respect to Structural Responses

For evaluation of structural responses, a maximum FWD deflection measured under the center of 

the load was used as a structural response indicator. The study concentrated on evaluating FWD 

maximum deflections against the average pavement performance during the service life of SPS-5 

sites. As with the analysis of pavement performance presented above, a gradual statistical 

analysis was used beginning with the analysis of individual sites, followed by a consolidated 

analysis of all sites simultaneously. The results from the consolidated analysis supported the 

findings from the analysis of individual sites. A summary of the analysis findings with respect to 

structural response is as follows:

• Rehabilitation strategies with thick overlays provided the lowest structural response 

independent of site conditions.
195

• Strategies with RAP mix overlays had the lowest structural response in freeze 

regions, while strategies with virgin mixes presented lower deflections under 

no-freeze conditions.

• Milling prior to overlay did not affect the structural response. In fact, in no-freeze zones, 

strategies without milling presented lower deflections.

• When comparing wet and dry climates, pavement surface condition, and traffic level, 

none had a significant impact on structural responses associated with each rehabilitation 

alternative.

In terms of the effect of design features or construction practices, the following conclusions 

were made:

Overlay thickness:

• Rehabilitation strategies with thick overlays had lower maximum deflection values 

compared to alternatives with thin overlays, as expected.

RAP mixes:

• There were no differences in pavement response between strategies using virgin and RAP

mix overlays.

Milling:

• Strategies with milling prior to overlay did not impact the structural response more than 

alternatives without milling.

Evaluation of Structural Responses Immediately After Rehabilitation and Future 

Performance

The objective of this evaluation was to identify trends in the relationship between response 

measured after the rehabilitation and the observed performance in subsequent years of the 

pavement’s service life. Only long-term performance was used for this analysis, which included

performance data of 5 years or more. The following summarizes the analysis findings:

IRI:

• The trend between roughness and maximum deflection suggests that roughness, as 

measured by IRI values, was positively related to the deflection values measured after the 

rehabilitation of the pavement structure. The higher the deflection after rehabilitation, the 

higher the IRI over the long term.

Rutting:

• The center load FWD deflection after the pavement’s rehabilitation did not provide 

adequate qualitative information about the rutting performance predictions. The 
196

instantaneous FWD deflections could not be associated with the material’s behavior 

impacting performance for rutting.

Fatigue cracking:

• No statistically significant trend was found between fatigue cracking performance and 

center load FWD deflection.

Transverse cracking:

• Higher values of transverse cracking were found when the pavement had higher center

load FWD deflections.

Longitudinal cracking:

• No significant correlation was found between longitudinal cracking and center

load deflection.

REHABILITATED RIGID PAVEMENTS

Findings presented in this section are based on the analysis of 14 SPS-6 rehabilitated rigid 

pavement sites, specifically 8 JPCP and 6 JRCP. Most of the sections were monitored for at least 

6 years. The findings from the analysis are described separately for JPCP and JRCP sites.

Evaluation of JPCP Rehabilitation Strategies with Respect to Performance

The results from the statistical analysis led to the following conclusions with respect to major 

pavement performance indicators, total cracking and IRI:

Total cracking:

• Rehabilitation strategies without overlays were the most effective to mitigate cracking 

development and propagation. Specifically, HMA overlays over jointed concrete 

pavements exhibited more total cracking than when the pavement was not overlaid.

• Saw and seal (when counted as an existing crack) showed more total cracking than other 

alternatives, but the control of reflection cracks (through sawing and sealing) was the 

design goal for this alternative. The smoothness of sawed and sealed overlays was similar 

to other overlays of similar thickness.

• Crack/break and seat of JPCP had no significant effect in reducing the amount of 

cracking, since it performed similarly to the 4-inch (102-mm) overlay over noncracked 

JPCP (with both minimum and maximum restorations).

• The three alternatives without overlays, no treatment control scenario, minimum 

restoration, and maximum restoration, were found to be the best choices (i.e., reduced 

total cracking) for both short-term and long-term performance.
197

• Crack/break and seat with 4-inch (102-mm) overlays was the best alternative among 

those which involved overlays to reduce cracking.

• The sawed and sealed joints did not deteriorate significantly on these sections, and they 

became an effective control of reflection cracking. If they were counted for total 

cracking, the sawed and sealed sections would have shown similar performance to other 

HMA overlays.

IRI:

• Rehabilitation strategies with HMA overlay were significantly smoother than treatments 

without overlay for both the short term and long term.

• The best alternative to improve roughness performance was the thicker overlay 

alternative crack/break and seat with 8-inch (203-mm) overlays. This alternative also has

the highest cost.

• Crack/break and seat with 8-inch (203-mm) overlays and minimum restoration with 

4-inch (102-mm) overlays (without crack/break and seat) were statistically equivalent and 

were found to be the best alternatives for most of the scenarios evaluated when both 

short-term and long-term roughness performance were considered. 

• Crack/break and seat with 4-inch (102-mm) overlay was among the worst alternatives to 

improve roughness performance.

• Saw and seal alternative provided similar smoothness to other 4-inch (102-mm) overlays. 

It should be noted that the best performance alternative may not be the lowest cost alternative. 

Selection of a rehabilitation alternative must also consider the cost and long-term maintenance.

The analysis of impact of site conditions led to the conclusion that different climate regions and 

surface conditions did not have a significant impact on roughness and total cracking performance 

for the rehabilitation strategies included in the SPS-6 JPCP experiment.

Effect of PCC Restoration Prior to Overlay

The impact of PCC restoration preoverlay treatments on performance of overlaid sections was 

investigated in the JPCP sites of the SPS-6 experiment. Transverse cracking was the only distress 

for which statistical differences were found between the four treatments. The conclusions from 

this study were as follows:

• The best alternative to limit the development and propagation of transverse cracking 

among all options with 4-inch (102-mm) overlays was crack/break and seat.

• Minimum and maximum restorations had an equivalent impact on short-term transverse 

cracking performance.
198

The analysis of impact of site conditions led to the following additional conclusions:

• Statistical differences in performance of overlaid sections were observed only for 

transverse cracking and short-term roughness when individual site characteristics were

considered.

• The rankings of best treatments prior to overlay remained the same regardless of site 

characteristics (i.e., surface condition or climate region).

• There was no impact on performance due to variations in surface condition prior to 

rehabilitation or the climatic region where the LTPP site was located. 

• Minimum, maximum, and saw and seal restorations provided the best short-term 

roughness performance, but there was no difference between the rehabilitation 

alternatives for long-term performance. Specifically, for the long term, these three 

restorations showed the same roughness.

• Crack/break and seat and minimum restoration were the best alternatives to mitigate the 

development and propagation of transverse cracking in the long term.

Effect of PCC Restoration Without Overlay

Three sections in each SPS-6 site did not receive overlays as part of their rehabilitation 

strategies. These sections were used to evaluate the impact of PCC restoration on performance. 

The small number of sections available for this study significantly reduced the power of the 

analysis and the chances of finding statistical differences among the treatment alternatives. 

No statistical differences in performance were found for short-term performance. The only 

performance indicator that showed statistical differences between the treatments was long-term 

roughness. From the analysis of long-term roughness, the findings supported by the statistical 

analysis were as follows:

• The maximum restoration treatment produced the smoothest pavement over the 

long term. 

• The minimum restoration treatment produced the second smoothest pavement over the 

long term.

• The no treatment control section, which received no rehabilitation, was the roughest 

pavement over the long term, as expected. 

An attempt was made to evaluate the impact of site conditions on performance; however, the 

results were not statistically significant. 

Evaluation of JRCP Rehabilitation Strategies with Respect to Performance

Similar to JPCP findings, the results of the JRCP analyses suggested that rehabilitation strategies 

with HMA overlays improved roughness performance, while strategies without overlays were 
199

better at improving total cracking development and propagation. The main conclusions were

as follows.

Total cracking:

• Rehabilitation strategies without overlays were the best when considering total cracking.

• Saw and seal, when counted as cracking, had the highest total cracking among all options 

evaluated. However, the sawed and sealed joints remained in reasonably good condition 

over time.

• Crack/break and seat of JRCP had no significant effect on reducing the amount of 

cracking since it performed similarly to the 4-inch (102-mm) overlay over noncracked 

JRCP (with minimum and maximum restoration).

IRI:

• Rehabilitation strategies with overlay had significantly better roughness performance 

(i.e., were smoother) than treatments without overlay.

• Minimum and maximum restorations with overlays were the best strategies to improve 

short-term performance for roughness.

• For long-term performance, the best alternative was the thick overlay alternative 

crack/break and seat with 8-inch (203-mm) overlays.

The sawed and sealed joints did not deteriorate significantly on these sections, and they became 

an effective control of reflection cracking. If they were removed from total cracking, the sawed

and sealed sections would have shown similar performance to other HMA overlays.

Effect of PCC Restoration Prior to Overlay

The impact of PCC restoration treatments on the performance of overlaid sections was 

investigated in JRCP sites of the SPS-6 experiment. Transverse cracking was the only distress 

for which statistical differences were found between the four treatments. The conclusions from 

this study were as follows:

• Crack/break and seat was the best alternative for short-term performance.

• Minimum and maximum restorations had an equivalent impact on short-term 

performance.

• The best alternatives to limit the development and propagation of transverse cracking in 

the long term were crack/break and seat and minimum restoration.

• Saw and seal prior to overlay when counted as cracks had the highest total cracking 

among all options evaluated in the SPS-6 experiment. 
200

The sawed and sealed joints did not deteriorate significantly on these sections, and they became 

an effective control of reflection cracking. If they were removed from total cracking, the saw and 

sealed sections would have shown similar performance to other HMA overlays.

Effect of PCC Restoration Without Overlay

Three sections in each SPS-6 site did not receive an overlay as part of their rehabilitation 

strategies. These sections were used to evaluate the impact of PCC restoration on performance. 

Distresses common to rigid pavements were used as performance measures. The only 

performance indicator that showed statistical differences between the treatments was short-term 

transverse reflection slab cracking. The findings from this statistical analysis were as follows:

• The maximum restoration treatment and the control section had statistically equivalent 

performances for short-term transverse slab cracking.

• The minimum restoration treatment provided the worst transverse slab cracking 

performance.

• The small number of sites limited the statistical findings in this study.

Evaluation of Rehabilitation Strategies with Respect to Structural Responses 

FWD deflections were used as the response measure of the pavement structure. Deflections at 

the center of the slab and at the transfer joints were used in this study. JPCP and JRCP structures 

were evaluated independently. Sections that received an HMA overlay were monitored like 

flexible pavements, and deflections at the center of the lane were used. 

There were limitations due to the amount of data available, especially after the data were 

grouped by pavement structure type and surface. Because of the small sample size (eight sites), 

the statistical power of the analysis was low, and no statistical differences were found in the 

pavement response of JPCP structures.

The only analysis that provided some statistically meaningful results was the evaluation of 

maximum deflection at the center lane of overlaid JRCP structures. The results suggested that 

crack/break and seat significantly increased the overall deflections measured on the pavement 

surface. The remaining treatments interchangeably provided equivalent maximum deflection 

magnitudes. These results were expected since crack/break and seat was an alternative in which 

the concrete slab was reduced to smaller pieces resulting in lower stiffness, and this increased the 

maximum deflection at the center of the slab.

Evaluation of Structural Responses Immediately After Rehabilitation and Future 

Performance

The objective of this study was to identify trends in the relationship between response measured 

immediately after the rehabilitation and the observed performance in the subsequent years of the 

pavement’s service life. LTE between slabs and maximum deflection at the center of the slab 

were used when the surface remained concrete slabs after rehabilitation. Maximum deflection at 

the center of the lane was used when the surface changed to HMA after rehabilitation. 
201

LTE Versus Performance in JPCP

Only transverse slab cracking exhibited a clear trend with LTE values in no overlaid JPCP 

sections, indicating that as the efficiency of the load transfer increased, the amount of transverse 

slab cracking decreased. This trend suggested that good load transfer joint restoration was

important to mitigate the development and propagation of slab cracking.

Maximum Deflection at Center of Slab Versus JPCP Performance

The trend between performance based on roughness and deflection measured at the center of the 

slab suggested that the higher the deflection, the smoother the JPCP over time. This trend was

not what would normally be expected. The level of slab cracking also showed an inverse trend 

with maximum deflection measured at the center of the slab. The trend suggested that slabs 

with higher deflections under FWD loading were less likely to develop cracking. A possible 

explanation was that stiffer subgrades resulted in higher slab curling and warping stresses, which 

led to increased slab cracking. This same result was found in MEPDG.

(1) While stiffer 

foundations reduced axle load stresses, they increased curling and warping stresses, which often 

tended to dominate cracking.

Faulting was also investigated, and the observed trend suggested that faulting was inversely 

proportional to deflection measured at the center of the slab. High deflection values yielded low 

faulting, although the trend was weak and depended on only one or two points. There was no 

logical explanation for this result. 

Maximum Deflection at Center of Lane Versus Performance of Overlaid JPCP

For sections that received an overlay as part of the rehabilitation strategy, there was a clear 

indication that overlaid JPCP with high deflections were more likely to become rougher 

pavements in the long term compared to sections with low deflection values. 

Overlaid JPCP sections with high center lane deflections were more likely to experience 

higher rutting than sections with low deflection values. Since all rutting occurred in the HMA 

layer, the cause for this result was not explainable unless the HMA was so soft that it contributed

significantly to the total deflection. Normally, nearly all deflection was in the foundation 

for JPCP.

The fatigue cracking trend suggested that high fatigue cracking was expected when deflection 

values were high. High longitudinal cracking values were observed when maximum deflections 

at the center of the lane were low, which indicated that the pavement structure was less 

deformable and more susceptible to surface tensile stresses, which was an important contributor 

to the development and propagation of longitudinal cracking.

Response Versus Performance in JRCP

The investigation of possible trends between response and performance in JRCP structures did 

not result in any meaningful conclusions. Different performance measures were analyzed against 

LTE, maximum deflection at the center of the slab, and maximum deflection at the center of the 

lane; however, no relevant conclusion was determined.
202

FINDINGS FROM MEPDG ANALYSES

MEPDG analysis was used to compare MEPDG-predicted performance of rehabilitated 

pavement sections with field-measured data and to verify current calibration against predictions 

of rehabilitated pavement structures. The following summarizes the findings from the 

MEPDG analysis.

The findings for the roughness model are as follows:

• The roughness models for flexible pavements and rigid pavements provided good overall 

predictions of rehabilitated sections with and without HMA overlay. 

• There was some bias in the predictions, which could be addressed with local or revised 

general calibration. The model had a tendency to underpredict roughness for rigid 

pavement sections with IRI values above 9.50 ft/mi (1.8 m/km). This bias was more 

characteristic of sections located in dry and freeze regions.

The findings for the rutting model are as follows:

• This model needs further enhancement to more accurately predict permanent 

deformation in HMA overlay over flexible and rigid pavements before it can be used 

with overlaid pavements.

• The model overpredicts performance of HMA overlays over crack/break and seat 

restored rigid pavements 

• The model underpredicts performance of HMA overlays for saw and seal and minimum 

and maximum restorations prior to overlays. 

• MEPDG considers the cracked/broken PCC layer as new granular base layer. Permanent 

deformation is predicted for the new layer and even the subgrade, which is normally the 

cause of the overprediction of total rutting identified in this study. 

The finds for cracking models for HMA overlays are as follows:

• The cracking models for HMA overlays (particularly the empirical reflection cracking)

need further enhancement to provide more accurate predictions. 

• The models for fatigue cracking (new and reflective) and longitudinal cracking were not 

capable of predicting consistent and comparable performance with measured values. 

• MEPDG did not predict transverse cracking in any of the SPS-5 or SPS-6 sections;

however, some transverse cracking was measured during surveys.
203

RECOMMENDATIONS FOR FUTURE RESEARCH

The following list provides suggestions for future research to further build on the knowledge 

gained from this study.

Researchers could monitor or create a new LTPP experiment to examine new and rehabilitated 

sections, including the following focus areas:

• Monitor rutting for flexible pavements, focusing on trenching and forensic studies to 

measure the contribution of individual layers to total rutting.

• Develop a means to assess and gather data on reflective cracking to obtain data to 

calibrate improved models to incorporate in MEPDG.

• Monitor response and performance data to develop or improve MEPDG models.

• Add new rigid pavement sections to the experiment to monitor undersealing of 

rigid pavements. The sample size used in this analysis was too small to obtain any 

meaningful conclusions.

• Review LTPP procedures to measure fatigue cracking of rehabilitated sections. There is 

evidence that cracking for such conditions was mostly associated with the propagation of 

cracks from the existing pavement prior to the overlay.

Another possible research plan includes future improvements of MEPDG models, including

the following:

• Reassess the impact of existing conditions prior to overlay on MEPDG models for IRI. In 

general, MEPDG underpredicts IRI levels for poor surface conditions and thin overlays, 

particularly with RAP mixes.

• Use LTPP data to reduce bias on IRI estimates for aged pavements. In general, MEPDG 

overpredicts IRI for the control sections.

• Revise MEPDG models. MEPDG analysis results for IRI of SPS-6 sections with no 

overlays presented some bias. In general, the MEPDG models underpredict the IRI level, 

particularly for sections with maximum restoration. It is recommended to revise the

MEPDG models for such conditions to remove bias, particularly for pavements with 

restoration procedures and pavements located in freeze zones. In general, MEPDG 

overpredicts rutting for sections rehabilitated with crack/break and seat alternatives. 

MEPDG models can be improved if the bias is removed with revised models or with 

improved calibration based on LTPP data for such sections. Except for crack/break and 

seat, MEPDG estimates for rutting on sections with overlays are underpredicted. The 

MEPDG models for such conditions should be revised or recalibrated to remove 

existing bias.
204

• Improve the MEPDG empirical model for reflective cracking through calibration efforts 

based on results obtained in this study. Two issues need to be addressed in the future. The 

first is how fatigue, longitudinal, and transverse cracking may be masked by reflective 

cracking. It was difficult to separate reflective cracking from other types of cracking 

during the survey measurements. The attempt to incorporate every type of cracking in the 

analysis conducted in this study was not very successful, particularly due to the possible 

confusion when measuring individual types of cracking and due to the poor performance 

of reflective cracking models in MEPDG. Revised models and procedures to identify 

reflective cracking during the surveys can help improve MEPDG estimates for cracking 

of rehabilitated sections of both flexible and rigid pavements.

The recommendations for technology transfer are as follows:

• Develop publications based on findings of this study that can be distributed to the 

industry to help engineers find the best maintenance treatment or rehabilitation 

alternatives for their specific conditions.

• Promote use of SPS-5 and SPS-6 data and findings to improve local and general 

calibration for MEPDG analysis of rehabilitated pavement sections.

• Make MEPDG input data from this project available to users for local calibration of 

MEPDG models.
205

APPENDIX A. SUMMARY STATISTICAL ANALYSIS

FLEXIBLE PAVEMENTS —SPS-5

The tables in this section describe the statistical results from the ANOVA performed in each site 

of the SPS-5 experiment. The number found after the State names represents the State code in 

the LTPP database. If statistical differences were found, they are described as “Y” in the 

statistical difference column, and the corresponding p-value is shown. If no statistical differences 

were found, they are described as “N.”

Table 93. Summary of individual statistical analysis results for SPS-5 site in Alabama (1).

Distress

Overlay Thickness Mix Type Milling

Statistical 

Difference

Best 

Performance Statistical 

Difference

Best 

Performance Statistical 

Difference

Best 

Performance

Short Long Short Long Short Long

Roughness N Thin N N

Rutting N Thin Thin N Virgin N

No 

mill

Fatigue N Thick Thick N Virgin Virgin N Mill Mill

Transverse

Y

(p = 0.015) Thick Thick N Virgin

Y

(p = 0.00002) Mill Mill

Longitudinal

Y

(p = 0.003) Thin N Virgin Virgin

Y

(p = 0.013) Mill Mill

Note: Blank cells indicate no difference between design factors.

Table 94. Summary of individual statistical analysis results for SPS-5 site in Arizona (4).

Distress

Overlay Thickness Mix Type Milling

Statistical 

Difference

Best 

Performance Statistical 

Difference

Best 

Performance Statistical 

Difference

Best 

Performance

Short Long Short Long Short Long

Roughness

Y

(p = 0) Thick Thick

Y

(p = 0) Virgin N Mill Mill

Rutting

Y

(p = 0.004) Thin Thick

Y

(p = 0.0004) Virgin Virgin N

No 

mill

Fatigue N Thick Thick N

Y

(p = 0.005) Mill Mill

Transverse N N Virgin Virgin N

Longitudinal N Thin

Y

(p = 0.01) Virgin Virgin N

Note: Blank cells indicate no difference between design factors.
206

Table 95. Summary of individual statistical analysis results for SPS-5 site in California (6).

Distress

Overlay Thickness

Statistical 

Difference

Best 

Performance Statistical 

Difference

Best 

Performance Statistical 

Difference

Best 

Performance

Short Long Short Long Short Long

Roughness

Y

(p = 0.00001) Thick Thick

Y

(p = 0.0499) Virgin Virgin N Mill Mill

Rutting

Y

(p = 0.0025) Thick N N

Fatigue

Y

(p = 0.036) Thick N Virgin Virgin

Y

(p = 0.031) Mill Mill

Transverse N Thick

Y

(p = 0.0036) Virgin Virgin N

Longitudinal N N

Y

(p = 0.011)

No 

mill

No 

mill

Note: Blank cells indicate no difference between design factors.

Table 96. Summary of individual statistical analysis results for SPS-5 site in Colorado (8).

Distress

Overlay Thickness Mix Type Milling

Statistical 

Difference

Best 

Performance Statistical 

Difference

Best 

Performance Statistical 

Difference

Best 

Performance

Short Long Short Long Short Long

Roughness N Thick

Y

(p = 0.027) RAP N N

Rutting

Y

(p = 0.034) Thick

Y

(p = 0) RAP N

Y

(p =

0.034)

Fatigue N Thick N RAP N N

Transverse

Y

(p = 0.01) Thick N RAP N

Y

(p =

0.01)

Longitudinal N Thick N RAP N N

Note: Blank cells indicate no difference between design factors.
207

Table 97. Summary of individual statistical analysis results for SPS-5 site in Florida (12).

Distress

Overlay Thickness Mix Type Milling

Statistical 

Difference

Best 

Performance Statistical 

Difference

Best 

Performance Statistical 

Difference

Best 

Performance

Short Long Short Long Short Long

Roughness N Thin Thin N Virgin Virgin

Y

( p = 0.031) Mill Mill

Rutting N Thin Thin N Virgin Virgin

Y

(p = 0.02) Mill Mill

Fatigue N Thin N Virgin N Mill

Transverse N N N

Longitudinal N Thick N

Y

(p = 0.021)

No 

mill

Note: Blank cells indicate no difference between design factors.

Table 98. Summary of individual statistical analysis results for SPS-5 site in Georgia (13).

Distress

Overlay Thickness Mix Type Milling

Statistical 

Difference

Best 

Performance

Statistical 

Difference

Best 

Performance Statistical 

Difference

Best 

Performance

Short Long Short Long Short Long

Roughness N N Virgin Virgin N

Rutting N N N

Fatigue N N N

Transverse

Longitudinal N Thin N N

Note: Blank cells indicate no difference between design factors.

Table 99. Summary of individual statistical analysis results for SPS-5 site in Maine (23).

Distress

Overlay Thickness Mix Type Milling

Statistical 

Difference

Best 

Performance Statistical 

Difference

Best 

Performance Statistical 

Difference

Best 

Performance

Short Long Short Long Short Long

Roughness N Thin N N

No 

mill

No 

mill

Rutting N N

Y

(p = 0.005)

No 

mill

No 

mill

Fatigue

Transverse

Longitudinal N N

Y

(p = 0.02) mill

Note: Blank cells indicate no difference between design factors.
208

Table 100. Summary of individual statistical analysis results for SPS-5 site in 

Maryland (24).

Distress

Overlay Thickness Mix Type Milling

Statistical 

Difference

Best 

Performance Statistical

Difference

Best 

Performance Statistical 

Difference

Best 

Performance

Short Long Short Long Short Long

Roughness N Thick x N Virgin x

Y

(p = 0.0196) Mill x

Rutting

Y

(p = 0.0045) Thin x

Y

(p = 0) Virgin x N x

Fatigue

Transverse

Longitudinal

Note: Blank cells indicate no difference between design factors.

Table 101. Summary of individual statistical analysis results for SPS-5 site in 

Minnesota (27).

Distress

Overlay Thickness Mix Type Milling

Statistical 

Difference

Best 

Performance Statistical 

Difference

Best 

Performance Statistical 

Difference

Best 

Performance

Short Long Short Long Short Long

Roughness

Y

(p = 0.00045) Thick N N Mill Mill

Rutting N

Y

(p = 0.0095) Virgin N

Fatigue

Transverse N N RAP N

No 

mill

Longitudinal N N N

Note: Blank cells indicate no difference between design factors.
209

Table 102. Summary of individual statistical analysis results for SPS-5 site in 

Mississipi (28).

Distress

Overlay Thickness Mix Type Milling

Statistical 

Difference

Best 

Performance Statistical 

Difference

Best 

Performance Statistical 

Difference

Best 

Performance

Short Long Short Long Short Long

Roughness N Thick Thick N Virgin Virgin N Mill Mill

Rutting

Y

(p = 0.0006) Thin Thin N N

Fatigue

Y

(p = 0.0217) Thick Thick

Y

(p = 0.0066) Virgin Virgin N

Transverse N

Y

(p = 0.0028) Virgin N

Longitudinal

Y

(p = 0.0396) Thin Thick N Virgin Virgin N

Note: Blank cells indicate no difference between design factors.

Table 103. Summary of individual statistical analysis results for SPS-5 site in Missouri (29).

Distress

Overlay Thickness Mix Type Milling

Statistical 

Difference

Best 

Performance Statistical 

Difference

Best 

Performance Statistical 

Difference

Best 

Performance

Short Long Short Long Short Long

Roughness N Thick N RAP N

No 

mill

Rutting N Thin

Y

(p = 0) Virgin N Mill

Fatigue N Thin N RAP N

No 

mill

Transverse N N N

Longitudinal N N N Mill

Note: Blank cells indicate no difference between design factors.
210

Table 104. Summary of individual statistical analysis results for SPS-5 site in 

Montana (30).

Distress

Overlay Thickness Mix Type Milling

Statistical 

Difference

Best 

Performance Statistical 

Difference

Best 

Performance Statistical 

Difference

Best 

Performance

Short Long Short Long Short Long

Roughness

Y

(p = 0) Thick

Y

(p = 0.0359) Virgin N Mill

Rutting N Thick Thick N RAP N

Fatigue N Thick N Virgin Virgin N

Transverse N Thick Thick N RAP RAP N Mill Mill

Longitudinal N Thick Thick N RAP RAP N Mill Mill

Note: Blank cells indicate no difference between design factors.

Table 105. Summary of individual statistical analysis results for SPS-5 site in 

New Jersey (34).

Distress

Overlay Thickness Mix Type Milling

Statistical 

Difference

Best 

Performance Statistical 

Difference

Best 

Performance Statistical 

Difference

Best 

Performance

Short Long Short Long Short Long

Roughness N Thick Thick N

Y

(p = 0.00097) Mill Mill

Rutting N Thick Thick N Virgin Virgin N

Fatigue

Y

(p = 0.0093) Thick

Y

(p = 0.00034) Virgin N

Transverse N Thick Thick

Y

(p = 0.0081) Virgin

Y

(p = 0.019) Mill Mill

Longitudinal N N Virgin Virgin

Y

(p = 0.0198) Mill

Note: Blank cells indicate no difference between design factors.
211

Table 106. Summary of individual statistical analysis results for SPS-5 site in 

New Mexico (35).

Distress

Overlay Thickness Mix Type Milling

Statistical 

Difference

Best 

Performance Statistical 

Difference

Best 

Performance Statistical 

Difference

Best 

Performance

Short Long Short Long Short Long

Roughness N N N

Rutting

Y

(p = 0.025) Thin N N

No 

mill

No 

mill

Fatigue N

Y

(p = 0.003) RAP N

No 

mill

Transverse N Thick N

Y

(p = 0.00011) Mill Mill

Longitudinal N

Y

(p = 0.00014) Virgin Virgin N

Note: Blank cells indicate no difference between design factors.

Table 107. Summary of individual statistical analysis results for SPS-5 site in 

Oklahoma (40).

Distress

Overlay Thickness Mix Type Milling

Statistical 

Difference

Best 

Performance Statistical 

Difference

Best 

Performance Statistical 

Difference

Best 

Performance

Short Long Short Long Short Long

Roughness

Y

(p = 0.014) Thick Thick N Virgin N Mill Mill

Rutting N

Y

(p = 0) RAP N

Fatigue N N N

Transverse

Y

(p = 0.028) Thick Thick N N Mill Mill

Longitudinal N N N Mill

Note: Blank cells indicate no difference between design factors.
212

Table 108. Summary of individual statistical analysis results for SPS-5 site in Texas (48).

Distress

Overlay Thickness Mix Type Milling

Statistical 

Difference

Best 

Performance Statistical 

Difference

Best 

Performance Statistical 

Difference

Best 

Performance

Short Long Short Long Short Long 

Roughness N Thick Thick N RAP RAP N Mill

Rutting N N RAP N

Fatigue N

Y

(p = 0.024) Virgin N

No 

mill

Transverse

Y

(p = 0.0016) Thick Thick

Y

(p = 0) Virgin N Mill Mill

Longitudinal

Y

(p = 0.001) Thick Thick

Y

(p = 0) Virgin Virgin N Mill Mill

Note: Blank cells indicate no difference between design factors.

Table 109. Summary of individual statistical analysis results for SPS-5 site in Alberta (81).

Distress

Overlay Thickness Mix Type Milling

Statistical 

Difference

Best 

Performance Statistical 

Difference

Best 

Performance Statistical 

Difference

Best 

Performance

Short Long Short Long Short Long

Roughness N N N

Rutting N N Virgin N

Fatigue

Y

(p = 0.003) Thick Thick

Y

(p = 0.033) Virgin Virgin N Mill Mill

Transverse N Thick

Y

(p = 0.0098) RAP RAP N Mill Mill

Longitudinal N Thin Thin N Virgin Virgin N

Note: Blank cells indicate no difference between design factors.

Table 110. Summary of individual statistical analysis results for SPS-5 site in 

Manitoba (83).

Distress

Overlay Thickness Mix Type Milling

Statistical 

Difference

Best 

Performance Statistical 

Difference

Best 

Performance

Statistical 

Difference

Best 

Performance

Short Long Short Long Short Long

Roughness

Y

(p = 0) Thick Thick N RAP

Y

(p = 0.01) Mill

Rutting N N N

No 

mill

Fatigue

Y

(p = 0.0197) Thick N Virgin N

Transverse

Y

(p = 0.0107) Thin N N

Longitudinal N N N Mill

Note: Blank cells indicate no difference between design factors.
The following tables provide the WD calculations used in the consolidated analysis with the Friedman test.

Table 111. Long-term average WD-IRI values for SPS-5 sites.

Section

Experimental Design Sites (State Codes)/Average WD-IRI values (m/km)

Mill Mix

Thickness 

(mm) 1 4 6 8 12 13 23 24 27 28 29 30 34 35 40 48 81 83

0501 No None 80 108 70 92 97 193 88 130 134 39 113 127 98

0502 No RAP 51 55 134 130 65 49 40 42 80 90 96 72 74 70 44 86 82 93 104

0503 No RAP 127 53 77 75 50 49 40 54 71 87 114 62 62 45 33 66 76 89 69

0504 No Virgin 127 57 82 74 56 42 40 56 86 95 87 71 48 51 37 70 93 101 71

0505 No Virgin 51 58 92 102 55 36 40 45 90 101 110 69 57 57 39 64 95 83 107

0506 Yes Virgin 51 48 71 81 87 32 36 52 59 92 101 69 56 51 37 66 90 72 117

0507 Yes Virgin 127 56 88 73 65 37 39 55 63 72 83 83 61 52 42 62 83 93 59

0508 Yes RAP 127 65 64 64 52 46 49 48 53 80 92 62 48 48 35 61 74 78 63

0509 Yes RAP 51 55 115 142 62 37 40 60 76 87 108 84 62 49 37 64 78 94 84

1 ft = 0.305 m

1 mi = 1.61 km

1 inch = 25.4 mm

Note: Higher WD values indicate rougher pavement over time. Blank cells indicate data are not available.

Table 112. Long-term average WD-rutting values for SPS-5 sites.

Section

Experimental Design Sites (State Codes)/Average WD-Rutting Values (mm)

Mill Mix

Thickness 

(mm) 1 4 6 8 12 13 23 24 27 28 29 30 34 35 40 48 81 83

0501 No None 0.36 0.15 0.33 0.56 0.36 0.27 0.55 0.33 0.31 0.14 0.41 0.36 0.36

0502 No RAP 51 0.10 0.19 0.16 0.13 0.16 0.13 0.27 0.17 0.10 0.36 0.14 0.17 0.11 0.12 0.11 0.23 0.25 0.14

0503 No RAP 127 0.13 0.15 0.10 0.11 0.17 0.13 0.27 0.25 0.08 0.43 0.19 0.12 0.09 0.15 0.17 0.16 0.33 0.17

0504 No Virgin 127 0.14 0.11 0.16 0.09 0.15 0.14 0.31 0.21 0.07 0.60 0.12 0.17 0.11 0.15 0.12 0.21 0.28 0.13

0505 No Virgin 51 0.12 0.12 0.15 0.12 0.13 0.12 0.25 0.15 0.09 0.33 0.12 0.13 0.10 0.12 0.16 0.18 0.18 0.16

0506 Yes Virgin 51 0.09 0.11 0.12 0.14 0.11 0.12 0.35 0.12 0.09 0.36 0.12 0.20 0.13 0.15 0.15 0.25 0.25 0.18

0507 Yes Virgin 127 0.13 0.21 0.20 0.17 0.14 0.13 0.33 0.22 0.09 0.59 0.08 0.17 0.12 0.18 0.15 0.25 0.22 0.21

0508 Yes RAP 127 0.21 0.14 0.11 0.13 0.16 0.12 0.32 0.19 0.08 0.56 0.17 0.11 0.10 0.16 0.11 0.18 0.23 0.22

0509 Yes RAP 51 0.13 0.16 0.13 0.09 0.13 0.13 0.30 0.43 0.11 0.33 0.11 0.17 0.13 0.15 0.09 0.16 0.26 0.15

1 inch = 25.4 mm

Note: Higher WD values indicate increased rutting in pavement over time. Blank cells indicate data are not available.

213
Table 113. Long-term average WD-fatigue cracking values for SPS-5 sites.

Section

Experimental Design Sites (State Codes)/Average WD-Fatigue Cracking Values (m2)

Mill Mix

Thickness 

(mm) 1 4 6 8 12 13 23 24 27 28 29 30 34 35 40 48 81 83

0501 No None 2,305 692 13 810 1 51 1,927 2,475 11 0 46 377 2,305 692

0502 No RAP 51 2,566 966 38 0 0 25 0 458 0 1,263 463 1 1 3 1,480 916 2,566 966

0503 No RAP 127 513 137 1 0 0 5 0 46 0 993 151 0 10 8 1,052 734 513 137

0504 No Virgin 127 475 111 0 0 0 96 0 4 2 0 178 2 1 0 384 544 475 111

0505 No Virgin 51 1,467 674 1 0 0 183 0 94 0 16 165 1 4 0 700 681 1,467 674

0506 Yes Virgin 51 474 1,261 0 0 0 9 0 198 3 1 7 6 1 0 765 822 474 1,261

0507 Yes Virgin 127 528 840 0 1 0 0 0 0 108 0 45 4 1 5 273 489 528 840

0508 Yes RAP 127 85 180 0 0 0 84 0 258 0 725 47 0 1 8 399 498 85 180

0509 Yes RAP 51 2,204 16 0 1 0 0 0 705 2 1,511 650 2 0 29 1,272 1,068 2,204 16

1 ft2 = 0.093 m2

1 inch = 25.4 mm

Note: Higher WD values indicate increased pavement cracking over time. Blank cells indicate data are not available.

Table 114. Long-term average WD-transverse cracking values for SPS-5 sites.

Section

Experimental Design Sites (State Codes)/Average WD-Transverse Cracking Values (m)

Mill Mix

Thickness 

(mm) 1 4 6 8 12 13 23 24 27 28 29 30 34 35 40 48 81 83

0501 No None 0 154 63 38 140 245 201 32 270 33 91 30 32

0502 No RAP 51 110 87 153 69 5 0 0 134 262 96 0 26 199 47 62 220 96 188

0503 No RAP 127 4 339 194 11 0 0 0 54 196 136 0 14 69 44 24 98 88 151

0504 No Virgin 127 0 40 83 43 0 0 0 32 200 3 0 35 50 3 5 4 61 250

0505 No Virgin 51 54 216 197 64 8 0 0 152 327 50 0 57 155 56 52 186 288 81

0506 Yes Virgin 51 1 50 152 90 2 0 0 129 294 65 1 51 9 2 33 4 130 39

0507 Yes Virgin 127 1 2 100 10 0 0 0 4 149 1 4 10 11 0 0 2 143 208

0508 Yes RAP 127 1 207 257 9 0 0 0 59 217 80 0 10 51 2 0 73 54 225

0509 Yes RAP 51 13 339 209 40 0 0 0 5 230 32 1 0 47 9 30 155 19 110

1 ft = 0.305 m

1 inch = 25.4 mm

Note: Higher WD values indicate increased pavement cracking over time. Blank cells indicate data are not available.

214
Table 115. Long-term average WD-longitudinal cracking values for SPS-5 sites.

Section

Experimental Design Sites (State Codes)/Average WD-Longitudinal Cracking Values (m)

Mill Mix

Thickness 

(mm) 1 4 6 8 12 13 23 24 27 28 29 30 34 35 40 48 81 83

0501 No None 0 364 842 1,039 939 894 239 563 670 380 53 170 250

0502 No RAP 51 95 47 268 722 2 304 277 795 843 209 52 377 862 405 252 797 575 741

0503 No RAP 127 143 337 430 552 2 209 292 624 549 101 96 186 949 508 113 646 579 848

0504 No Virgin 127 86 26 362 715 9 132 302 429 677 52 33 176 827 103 83 80 704 669

0505 No Virgin 51 92 130 342 996 27 293 277 486 894 47 465 270 585 268 28 797 319 932

0506 Yes Virgin 51 0 78 485 673 0 144 214 627 737 52 88 205 599 158 36 337 84 574

0507 Yes Virgin 127 19 3 459 410 0 129 277 651 649 17 74 89 753 60 65 19 456 578

0508 Yes RAP 127 69 285 497 152 73 135 218 745 369 170 116 266 926 559 0 631 578 921

0509 Yes RAP 51 100 329 492 152 8 206 138 99 572 146 54 322 826 411 48 639 544 392

1 ft = 0.305 m

1 inch = 25.4 mm

Note: Higher WD values indicate increased pavement cracking over time. Blank cells indicate data were not available.

215

217

APPENDIX B. PRACTICAL GUIDE: SELECTION OF PAVEMENT MAINTENANCE 

ALTERNATIVES

This appendix is intended to help users select the best pavement maintenance alternatives based 

on the results of this study and on specific conditions of pavement sections planned for 

maintenance. The most relevant differences in performance determined in this research are those 

for flexible pavements under the SPS-3 experiment, which is partially related to the larger 

sample size and the number of alternatives evaluated in the study. Under the SPS-4 experiment, 

only the performance of one maintenance alternative, joint/crack seal, could be evaluated. 

The second treatment, undersealing, had a sample size that was too small to obtain any 

meaningful results. 

FLEXIBLE PAVEMENTS

Five alternatives were evaluated for flexible pavements: control, thin overlay, slurry seal, crack 

seal, and chip seal.

The conditions that were evaluated included climate (temperature and moisture), subgrade type 

(fine grained versus coarse grained), traffic loading (low versus high), and pavement condition 

(good, fair, or poor).

The best performances among the alternative treatments evaluated were thin overlay and chip 

seal. Thin overlay was most effective when rutting or roughness were the major existing 

distresses. Chip seal was the most effective when fatigue cracking was the major existing 

distress. Table 116 summarizes the best alternatives given specific conditions of the 

pavement section.

Table 116. Preferred flexible pavement treatments.

Distress

Preferred 

Treatment

Temperature Precipitation Subgrade Traffic Pavement Condition

Freeze

Nofreeze Dry Wet Fine Coarse Low High Good Fair Poor

Fatigue 

Cracking

1st choice CH CH CH CH CH CH CH CH CH CH TH

2d choice TH — — TH — TH — TH — — CH

Rutting 1st choice TH TH TH TH TH TH TH TH TH TH TH

2d choice CH — CH — — — — — — — —

Roughness 1st choice TH None None None TH TH None TH None None TH

CH = chip seal and TH = thin overlay.

— Indicates that no data are available.

Note: None means that neither treatment alternative performed significantly better than the control section. CH is not included as an option for 

roughness because it was never the preferred treatment method.
218

Example

An engineer is planning the maintenance of a road section placed on a coarse subgrade with

a high level of traffic. The section is located in a wet, no-freeze location, and the existing 

pavement condition is poor with fatigue cracking and roughness being the major existing 

distresses. In this case, the engineer should concentrate only on the choices to mitigate 

fatigue cracking and roughness, since these are the major distresses. Table 117 provides the 

possible options.

Table 117. Flexible pavement example.

Distress

Preferred 

Treatment

Temperature Precipitation Subgrade Traffic

Pavement 

Condition

No-freeze Wet Coarse High Poor

Fatigue 

cracking

1st choice CH CH CH CH TH

2d choice — TH TH TH CH

Roughness 1st choice — — TH TH TH

CH = chip seal and TH = thin overlay. 

— Indicates that no data are available.

From the table, the choice appears straightforward. Although chip seal is the best choice for 

fatigue cracking under most conditions, thin overlay is also a good choice for fatigue cracking, 

particularly if the pavement is in poor condition. Moreover, only thin overlays can help mitigate 

roughness. If the difference in cost between chip seal and thin overlay is not an issue, the 

pavement treatment choice is thin overlay. 

RIGID PAVEMENTS

Three alternatives were evaluated for rigid pavements: control, joint/crack seal, and 

undersealing.

The conditions that were evaluated included climate (temperature and moisture), subgrade type 

(fine grained versus coarse grained), traffic loading (low versus high), and pavement condition 

(good, fair, or poor).

There were no differences in performance between the control and the two maintenance 

alternatives evaluated in this study. However it is important to note that the sample size was 

small, particularly for the evaluation of undersealing, which only had eight sites. 
219

APPENDIX C. PRACTICAL GUIDE: FACTORS AFFECTING PERFORMANCE OF 

REHABILITATED FEXIBLE PAVEMENTS

INTRODUCTION

This appendix summarizes the research results of the SPS-5 experiment to help engineers select 

the best rehabilitation alternatives for rigid pavements among those evaluated in the experiment

and, from a performance perspective, as a function of specific site conditions and distresses in 

the existing pavement. 

The selection is made based on the best alternative in each group. Despite the practicality of the 

information, tables in this section should be used with caution, particularly when the sources of 

distresses are associated with construction, new techniques, or other unusual circumstances not 

reflected in the SPS-6 experiment.

The design factors and site characteristics investigated in the SPS-5 experiment were as follows:

• Site conditions: Climate (wet versus dry and freeze versus no-freeze), pavement 

condition (fair versus poor), and traffic (low versus high).

• Design features: Surface preparation (milling versus no milling), overlay material (virgin

versus recycled HMA), and overlay thickness (thin versus thick).

SELECTION PROCESS

This section summarizes the rehabilitation alternatives that are most likely to provide best 

performances under a given set of conditions. Within each group, the impact of design features is 

characterized by ranking the rehabilitation strategies from the best to the worst. Each distress is 

evaluated independently. Only rankings with statistical significance are shown in the table. If 

there is no ranking associated with one particular distress, no statistical difference in 

performance was found, which indicates that none of the design features evaluated had 

differential impact on performance.

The tables presented in this appendix can be used as a guide to determine which design features 

may perform better among the options evaluated in this study. An example is described here and 

summarized in table 118. Table 119 through table 127 can be used to evaluate which design 

feature will provide better performance measured by the distresses listed in the tables. The 

selection is made based on the best alternative in each group.

Selection Process Example

An engineer will select a rehabilitation alternative for the following conditions:

• The existing pavement is in fair condition, and fatigue cracking is the major distress type 

followed by a medium level of roughness that should be mitigated. The level of rutting is 

minor, and no transverse or longitudinal cracking is observed.
220

• The section is located in a no-freeze zone and in wet conditions. The level of traffic is 

considered high.

The selection process involves gathering the information from each table containing the ranking 

of alternatives for each specific condition. Using the information in the example, the best 

alternatives for wet conditions are taken from table 120 and included in table 118. The same 

process is performed for each of the site conditions, and the information is included in table 118. 

As a result, the combination of design features presented in the table is likely to provide the best 

performance to the selected distresses.

Table 118. Selection of design features to improve performance of rehabilitated flexible 

pavements.

Site 

Condition

Roughness Rutting Fatigue Cracking

Mill Thickness Mix Type Mill Thickness Mix Type Mill Thickness Mix Type

Wet Yes Thin Virgin

No Thin

Virgin

Virgin

No Thick RAP

Yes Thin

Yes Thin Virgin

Yes Thick Virgin

No-freeze — — —

Yes Thin Virgin

No Thick Virgin

No Thin Virgin

Yes Thin RAP

Existing 

fair 

pavement Yes Thick RAP

Yes Thick RAP

— — —

No Thin Virgin

No Thick RAP

High traffic Yes Thick RAP No Thin Virgin

No Thick Virgin

Yes Thick Virgin

Yes Thick RAP

Final 

selection Yes Thick RAP No Thin Virgin Yes Thick Virgin

— Indicates that no preferred treatment was statistically found.
Table 119. Summary of performance for all SPS-5 sections.

Distress

Roughness Rutting Fatigue Cracking Longitudinal 

Cracking

Transverse 

Cracking

Deflection

Ranking Strategy Ranking Strategy Ranking Strategy Ranking Strategy Ranking Strategy Ranking Strategy

1

Mill, 

thick, 

RAP 1

No mill, 

thin, 

virgin 1

No mill, 

thick, 

virgin 1

Mill, 

thick, 

virgin 1

Mill, 

thick, 

virgin 1

Mill, 

thick, 

virgin

2

No mill, 

thick, 

RAP 1

Mill, 

thick, 

RAP 1

Mill, 

thick, 

RAP 2

Mill, 

thin, 

virgin 2

No mill, 

thick, 

virgin 2

Mill, 

thick, 

RAP

2

Mill, 

thin, 

virgin 1

No mill, 

thin, 

RAP 1

Mill, 

thick, 

virgin 2

No mill, 

thick, 

virgin 3

Mill, 

thick, 

RAP 2

No mill, 

thick, 

RAP

2

Mill, 

thick, 

virgin 1

Mill, 

thin, 

virgin 4

Mill, 

thin, 

virgin 2

Mill, 

thin, 

RAP 3

Mill, 

thin, 

RAP 2

No mill, 

thick, 

virgin

221
Table 120. Summary of performance for SPS-5 sections in wet zones.

Distress

Roughness Rutting Fatigue Cracking

Longitudinal 

Cracking

Transverse 

Cracking Deflection

Ranking Strategy Ranking Strategy Ranking Strategy Ranking Strategy Ranking Strategy Ranking Strategy

1

Mill, 

thin, 

virgin 1

No mill, 

thin, 

virgin 1

No mill, 

thick, 

RAP 1

Mill, 

thin, 

virgin 1

No mill, 

thick, 

virgin 1

Mill, 

thick, 

RAP

2

Mill, 

thick, 

RAP 1

Mill, 

thin, 

virgin 1

Mill, 

thin, 

virgin 1

Mill, 

thick, 

virgin 1

Mill, 

thick, 

virgin 1

Mill, 

thick, 

virgin

2

Mill, 

thick, 

virgin 3

No mill, 

thin, 

RAP 1

Mill, 

thick, 

virgin 3

No mill, 

thick, 

virgin 3

Mill, 

thin, 

RAP 1

No mill, 

thick, 

RAP

2

No mill, 

thick, 

RAP 3

No mill, 

thick, 

RAP 4

No mill, 

thick, 

virgin 3

Mill, 

thin, 

RAP 3

Mill, 

thick, 

RAP 1

No mill, 

thick, 

virgin

2

No mill, 

thick, 

virgin 3

Mill, 

thin, 

RAP 4

Mill, 

thick, 

RAP 3

No mill, 

thin, 

virgin 3

Mill, 

thin, 

virgin 5

Mill, 

thin, 

virgin

2

No mill, 

thin, 

RAP 3

Mill, 

thick, 

RAP 4

No mill, 

thin, 

virgin 3

Mill, 

thick, 

RAP 3

No mill, 

thick, 

RAP 5

Mill, 

thin, 

RAP

2

No mill, 

thin, 

virgin 3

Mill, 

thick, 

virgin 4

Mill, 

thin, 

RAP 3

No mill, 

thin, 

RAP 3

No mill, 

thin, 

virgin 5

No mill, 

thin, 

virgin

2

Mill, 

thin, 

RAP 3

No mill, 

thick, 

virgin 4

No mill, 

thin, 

RAP 3

No mill, 

thick, 

RAP 3

No mill, 

thin, 

RAP 8 None

222
Table 121. Summary of performance for SPS-5 sections in dry zones.

Distress

Roughness Rutting Fatigue Cracking

Longitudinal 

Cracking

Transverse 

Cracking Deflection

Ranking Strategy Ranking Strategy Ranking Strategy Ranking Strategy Ranking Strategy Ranking Strategy

1

Mill, 

thick, 

RAP 1

No mill, 

thick, 

virgin 1

Mill, 

thick, 

virgin 1

Mill, 

thick, 

virgin

2

No mill, 

thick, 

RAP 1

No mill, 

thin, 

virgin 2

No mill, 

thick, 

virgin 1

No mill, 

thick, 

virgin

3

Mill, 

thick, 

virgin 1

Mill, 

thick, 

RAP 2

Mill, 

thick, 

RAP 1

Mill, 

thick, 

RAP

3

No mill, 

thick, 

virgin 4

Mill, 

thin, 

RAP 2

Mill, 

thin, 

RAP 1

No mill, 

thick, 

RAP

3

Mill, 

thin, 

virgin 4

No mill, 

thick, 

RAP 2

No mill, 

thick, 

RAP 5

No mill, 

thin, 

virgin

Note: Blank cells indicate that no preferred treatment was found.

223
Table 122. Summary of performance for SPS-5 sections in freeze zones.

Distress

Roughness Rutting Fatigue Cracking

Longitudinal 

Cracking

Transverse 

Cracking Deflection

Ranking Strategy Ranking Strategy Ranking Strategy Ranking Strategy Ranking Strategy Ranking Strategy

1

Mill, 

thick, 

RAP 1

No mill, 

thin, 

virgin 1

No mill, 

thick, 

RAP

1

No mill, 

thick, 

RAP 1

Mill, 

thick, 

RAP 1

Mill, 

thick, 

RAP

1

Mill, 

thick, 

virgin 1

No mill, 

thick, 

virgin 3

No mill, 

thick, 

virgin

1

Mill, 

thin, 

virgin 1

No mill, 

thin, 

RAP 3

Mill, 

thick, 

virgin

Note: Blank cells indicate that no preferred treatment was found.

224
Table 123. Summary of performance for SPS-5 sections in no-freeze zones.

Distress

Roughness Rutting Fatigue Cracking

Longitudinal 

Cracking

Transverse 

Cracking Deflection

Ranking Strategy Ranking Strategy Ranking Strategy Ranking Strategy Ranking Strategy Ranking Strategy

1

Mill, 

thin, 

virgin 1

No mill, 

thick, 

virgin 1

Mill, 

thick, 

virgin 1

Mill, 

thick, 

virgin 1

Mill, 

thick, 

virgin

1

No mill, 

thin, 

virgin 2

Mill, 

thin, 

virgin 2

Mill, 

thin, 

virgin 2

No mill, 

thick, 

virgin 2

No mill, 

thick, 

virgin

1

Mill, 

thin, 

RAP 2

Mill, 

thick, 

virgin 2

No mill, 

thick, 

virgin 3

Mill, 

thin, 

virgin 3

Mill, 

thick, 

RAP

Note: Blank cells indicate that no preferred treatment was found.

225
Table 124. Summary of performance for SPS-5 sections in fair surface condition prior to rehabilitation.

Distress

Roughness Rutting Fatigue Cracking

Longitudinal 

Cracking

Transverse 

Cracking Deflection

Ranking Strategy Ranking Strategy Ranking Strategy Ranking Strategy Ranking Strategy Ranking Strategy

1

Mill, 

thick, 

RAP 1

Mill, 

thick, 

RAP 1

Mill, 

thick, 

virgin 1

Mill, 

thick, 

virgin 1

Mill, 

thick, 

RAP

2

No mill, 

thick, 

RAP 1

No mill, 

thin, 

virgin 1

Mill, 

thin, 

virgin 2

Mill, 

thick, 

RAP 2

No mill, 

thick, 

RAP

2

Mill, 

thin, 

virgin 1

No mill, 

thick, 

RAP 3

Mill, 

thick, 

RAP 3

Mill, 

thin, 

RAP 2

Mill, 

thick, 

virgin

2

Mill, 

thin, 

RAP 4

No mill, 

thick, 

virgin 3

No mill, 

thick, 

virgin 3

No mill, 

thick, 

virgin 2

No mill, 

thick, 

virgin

Note: Blank cells indicate that no preferred treatment was found.

226
Table 125. Summary of performance for SPS-5 sections in poor surface condition prior to rehabilitation.

Distress

Roughness Rutting Fatigue Cracking

Longitudinal 

Cracking

Transverse 

Cracking Deflection

Ranking Strategy Ranking Strategy Ranking Strategy Ranking Strategy Ranking Strategy Ranking Strategy

1

mill, 

thick, 

RAP 1

No mill, 

thin, 

virgin 1

No mill, 

thick, 

virgin

2

Mill, 

thin, 

virgin 1

Mill, 

thin, 

virgin 1

Mill, 

thick, 

virgin

2

Mill, 

thick, 

virgin 3

Mill, 

thin, 

RAP 3

No mill, 

thick, 

RAP

2

No mill, 

thick, 

RAP 3

No mill, 

thin, 

RAP 4

Mill, 

thick, 

RAP

2

No mill, 

thick, 

virgin 3

No mill, 

thick, 

virgin 5

Mill, 

thin, 

virgin

2

No mill, 

thin, 

Virgin 3

No mill, 

thick, 

RAP 6

No mill, 

thin, 

Virgin

2

No mill, 

thin, 

RAP 3

Mill, 

thick, 

RAP 6

Mill, 

thin, 

RAP

2

Mill, 

thin, 

RAP 3

Mill, 

thick, 

virgin 8

No mill, 

thin, 

RAP

Note: Blank cells indicate that no preferred treatment was found.

227
Table 126. Summary of performance for SPS-5 sections with low traffic levels.

Distress

Roughness Rutting Fatigue Cracking

Longitudinal 

Cracking

Transverse 

Cracking Deflection

Ranking Strategy Ranking Strategy Ranking Strategy Ranking Strategy Ranking Strategy Ranking Strategy

1

Mill, 

thick, 

RAP 1

No mill, 

thin, 

virgin 1

No mill, 

thick, 

virgin 1

No mill, 

thick, 

RAP

1

Mill, 

thin, 

virgin 1

Mill, 

thin, 

virgin 1

Mill, 

thick, 

virgin 1

Mill,

thick, 

virgin

1

Mill, 

thick, 

virgin 3

No mill, 

thin, 

RAP 1

Mill, 

thick, 

RAP 1

No mill, 

thick, 

virgin

1

No mill, 

thick, 

RAP 3

No mill, 

thick, 

virgin 1

No mill, 

thick, 

RAP 4

Mill, 

thick, 

RAP

Note: Blank cells indicate that no preferred treatment was found.

228
Table 127. Summary of performance for SPS-5 sections with high traffic levels.

Distress

Roughness Rutting Fatigue Cracking

Longitudinal 

Cracking

Transverse 

Cracking Deflection

Ranking Strategy Ranking Strategy Ranking Strategy Ranking Strategy Ranking Strategy Ranking Strategy

1

Mill, 

thick, 

RAP 1

No mill, 

thin, 

virgin 1

No mill, 

thick, 

virgin 1

No mill, 

thick, 

virgin

2

No mill, 

thick, 

RAP 2

No mill, 

thick

RAP 1

Mill, 

thick, 

virgin 1

Mill, 

thick, 

RAP

2

No mill, 

thick, 

virgin 2

No mill, 

thin, 

RAP 1

Mill, 

thick, 

RAP 1

No mill, 

thick, 

RAP

2

Mill, 

thick, 

virgin 2

No mill, 

thick, 

virgin 4

No mill, 

thick

RAP 4

Mill, 

thick, 

virgin

2

Mill, 

thin, 

virgin 2

Mill, 

thick

RAP 4

No mill, 

thin, 

virgin 5

Mill, 

thin, 

RAP

2

No mill, 

thin, 

virgin 2

Mill, 

thin, 

RAP 4

Mill, 

thin

virgin 5

Mill , 

thin, 

virgin

Note: Blank cells indicate that no preferred treatment was found.

229

231

APPENDIX D. PRACTICAL GUIDE: FACTORS AFFECTING PERFORMANCE OF 

REHABILITATED RIGID PAVEMENTS

INTRODUCTION

This appendix summarizes the research results of the SPS-6 experiment to help engineers select 

the best rehabilitation alternatives for rigid pavements. The selection is based on alternatives 

evaluated in the SPS-6 experiment and from a performance perspective as a function of specific 

site conditions and distresses in the existing pavement. 

The selection is made based on the best alternative in each group. Despite the practicality of the 

information, the tables in this section should be used with caution, particularly when the sources 

of distresses are associated with construction, new techniques, or other unusual circumstances 

not reflected in the SPS-6 experiment.

The design factors and site characteristics investigated in the SPS-6 experiment were as follows:

• Site conditions: Climate (wet versus dry and freeze versus no-freeze) and pavement 

condition (fair versus poor).

• Design features: Surface PCC restoration (minimum, maximum, saw and seal, 

crack/break, and seat) and overlaid (4 and 8 inches (102 and 203 mm)) versus not 

overlaid.

SELECTION PROCESS

This section summarizes the rehabilitation alternatives that are most likely to provide best 

performances under a given set of conditions. Within each group, the impact of design features is 

characterized by ranking the rehabilitation strategies from the best to the worst. Each distress is 

evaluated independently. Only rankings with statistical significance are provided in the tables. 

If there is no ranking associated with one particular distress, no statistical difference in 

performance was found, which indicates that none of the design features evaluated had 

differential impact on performance.

The tables can be used as a guide to determine which rehabilitation design alternatives will

perform better among the options evaluated in this study. This selection process is only 

applicable to JPCP sections. The study described in the main volume of this report suggests that 

all rehabilitation strategies applied to JRCP sections were equivalent in performance when the 

sections were grouped by site conditions. The number of JRCP sections available was small and 

significantly limited the results from a statistical analysis standpoint.

An example is described for JPCP and summarized in table 128. To create this table, information

was taken from table 129 through table 134 to evaluate which of the design features evaluated in 

this study would provide better performance as measured by the level of distresses listed in the 

tables. The selection is made based on the best alternative for each group.
232

Selection Process Example

An engineer will select a rehabilitation alternative for the following conditions:

• The existing pavement is in fair condition, and cracking is the major distress type 

followed by a medium level of roughness that should be mitigated. 

• The section is located in a no-freeze zone and in wet conditions.

The selection process involves gathering the information from each table containing the ranking 

of alternatives for each specific condition. Using the information in the example, the best 

alternatives for wet conditions were taken from table 130. The same process was performed for 

each of the site conditions. As result, the combination of design features presented in table 128

should provide the best alternatives to address existing distresses and have satisfactory 

performance over the design life of the rehabilitated pavement. Based on the information in the 

table, the choice should be crack/break and seat with an 8-inch (203-mm) HMA surface layer 

because the best alternatives for cracking will not mitigate roughness. In addition, crack/break 

and seat is the second best alternative for total cracking.

Table 128. Selection of design features to improve performance of rehabilitated rigid 

pavements (JPCP).

Site Condition

Roughness Total Cracking

Restoration

Thickness 

(mm) Restoration

Thickness 

(mm)

Wet

Crack/break and 

seat 203 None None

Minimum 

restoration 102 None None

No-freeze

Crack/break and 

seat 203 None None

Existing fair 

pavement

Crack/break and 

seat 203

Minimum 

restoration None

Crack/break and 

seat 203

Maximum 

restoration None

1 inch = 25.4 mm
233

Table 129. Summary of performance for all JPCP SPS-6 sections.

Distress

Roughness Total Cracking

Ranking Strategy

Overlay 

(mm) Ranking Strategy

Overlay 

(mm)

1

Crack/break and 

seat 203 1 None1 None

2 Minimum 102 1 Minimum None1

2 Maximum 102 1 Maximum None1

2 Saw/seal 102 4

Crack/break

and seat 203

5 Maximum None 4

Crack/break

and seat 102

5

Crack/break and 

seat 102 4 Maximum 102

5 Minimum None 4 Minimum 102

8 None None 8 Saw/seal 102

1 inch = 25.4 mm

1

Indicates that based on the distress survey data for cracking, the alternatives without overlays were 

found to perform better; however, the user should apply these results with caution. It is difficult 

to differentiate fatigue cracking from reflective cracking, and it seems that reflective cracking is 

measured as fatigue, longitudinal, or transverse cracking. In this situation, for overlaid pavement, 

reflective cracking from JPCP joints may have been measured as one of the categories of cracking 

(fatigue, transverse, or longitudinal). For nonoverlaid pavements, the joints are not measured as 

cracking, causing the differences in performance identified in the statistical analysis.
234

Table 130. Summary of performance for JPCP SPS-6 sections in wet zones.

Distress

Roughness Total Cracking

Ranking Strategy

Overlay 

(mm) Ranking Strategy

Overlay 

(mm)

1

Crack/break and 

seat 203 1 None1 None

1 Minimum 102 2 Minimum None1

3 Maximum 102 2 Maximum None1

3 Saw/seal 102 2

Crack/break

and seat 102

3 Maximum None 2

Crack/break

and seat 203

3

Crack/break and 

seat 102 2 Minimum 102

3 Minimum None 2 Maximum 102

8 None None 8 Saw/seal 102

1 inch = 25.4 mm

1

Indicates that based on the distress survey data for cracking, the alternatives without overlays were 

found to perform better; however, the user should apply these results with caution. It is difficult 

to differentiate fatigue cracking from reflective cracking, and it seems that reflective cracking is 

measured as fatigue, longitudinal, or transverse cracking. In this situation, for overlaid pavement, 

reflective cracking from JPCP joints may have been measured as one of the categories of cracking 

(fatigue, transverse, or longitudinal). For nonoverlaid pavements, the joints are not measured as 

cracking, causing the differences in performance identified in the statistical analysis.

Table 131. Summary of performance for JPCP SPS-6 sections in dry zones.

Distress

Roughness Total Cracking

Ranking Strategy

Overlay 

(mm) Ranking Strategy

Overlay 

(mm)

1

Crack/break and 

seat 203

2 Maximum 102

2 Minimum 102

2 Saw/seal 102

2

Crack/break and 

seat 102

2 Maximum None

7 None None

7 Minimum None

1 inch = 25.4 mm

Note: Blank cells indicate that no statitstical difference in performance was found.
235

The performance of all rehabilitation strategies for JPCP SPS-6 sections in freeze zones were 

equivalent.

Table 132. Summary of performance for JPCP SPS-6 sections in no-freeze zones.

Distress

Roughness Total Cracking

Ranking Strategy

Overlay 

(mm) Ranking Strategy

Overlay 

(mm)

1

Crack/break and 

seat 203 1 None1 None

2 Minimum 102 2 Minimum None1

2 Saw/seal 102 2 Maximum None1

4 Maximum 102 2

Crack/break 

and seat 203

4 Maximum None 2

Crack/break

and seat 102

4

Crack/break and 

seat 102 2 Maximum 102

7 Minimum None 2 Minimum 102

8 None None 8 Saw/seal 102

1 inch = 25.4mm

1

Indicates that based on the distress survey data for cracking, the alternatives without overlays were 

found to perform better; however, the user should apply these results with caution. It is difficult 

to differentiate fatigue cracking from reflective cracking, and it seems that reflective cracking is 

measured as fatigue, longitudinal, or transverse cracking. In this situation, for overlaid pavement, 

reflective cracking from JPCP joints may have been measured as one of the categories of cracking 

(fatigue, transverse, or longitudinal). For nonoverlaid pavements, the joints are not measured as 

cracking, causing the differences in performance identified in the statistical analysis.
236

Table 133. Summary of performance for JPCP SPS-6 sections in fair surface condition 

prior to rehabilitation.

Distress

Roughness Total Cracking

Ranking Strategy

Overlay 

(mm) Ranking Strategy

Overlay 

(mm)

1

Crack/break and 

seat 203 1 Maximum None1

2 Maximum 102 1 Minimum None1

2 Minimum 102 3 None1 None

2 Maximum None 3

Crack/break

and seat 203

2 Saw/seal 102 3

Crack/break

and seat 102

2 Minimum None 3 Minimum 102

2

Crack/break and 

seat 102 3 Maximum 102

8 None None 8 Saw/seal 102

1 inch = 25.4 mm

1

Indicates that based on the distress survey data for cracking, the alternatives without overlays were 

found to perform better; however, the user should apply these results with caution. It is difficult 

to differentiate fatigue cracking from reflective cracking, and it seems that reflective cracking is 

measured as fatigue, longitudinal, or transverse cracking. In this situation, for overlaid pavement, 

reflective cracking from JPCP joints may have been measured as one of the categories of cracking 

(fatigue, transverse, or longitudinal). For nonoverlaid pavements, the joints are not measured as 

cracking, causing the differences in performance identified in the statistical analysis.

Table 134. Summary of performance for JPCP SPS-6 sections in poor surface condition 

prior to rehabilitation.

Distress

Roughness Total Cracking

Ranking Strategy

Overlay 

(mm) Ranking Strategy

Overlay 

(mm)

1

Crack/break and 

seat 203

2 Minimum 102

2 Saw/seal 102

2 Maximum 102

2

Crack/break and 

seat 102

2 Maximum None

7 Minimum None

7 None None

1 inch = 25.4 mm

Note: Blank cells indicate that no significant difference in performance was found.
237

APPENDIX E. PERFORMANCE AND INPUT DATABASE FOR MEPDG ANALYSIS

This section is an electronic appendix and explains the electronic file structure and fields in the 

various tables in the database. Performance data of SPS-5 and SPS-6 experiments were compiled 

into this database for comparison with MEPDG analysis results. The database also contains the 

input data used in the MEPDG analyses. The data provided in this database were used during 

phase 2 of this project. Moreover, it allows for the creation of the input files for all sections in 

SPS-5 and SPS-6 experiments.

PERFORMANCE DATA

Performance data for all SPS-5 and SPS-6 sections are stored in the database. These data were 

used in phase 2 of this project. The performance data tables are labeled “Performance” followed 

by the distress type. The following lists the tables and respective fields:

Table name: Performance_Roughness

• Fields:

• STATE_CODE: Numerical code for State or province. U.S. codes are consistent 

with Federal information processing standards.

• SHRP_ID: Test section identification number assigned by LTPP program. Must be 

combined with STATE_CODE to be unique. 

• Date: Survey date.

• IRI Mean: Average of IRI measurements, inch/mi.

• IRI Std Dev: Standard deviation of IRI measurements, inch/mi.

• IRI Num: Number of IRI measurements.

Table name: Performance_Rutting

• Fields:

• STATE_CODE: Numerical code for State or province. U.S. codes are consistent 

with Federal information processing standards.

• SHRP_ID: Test section identification number assigned by LTPP program. Must be 

combined with STATE_CODE to be unique.

• Date: Survey date.

• Rut Depth Mean: Average of rutting measurements, inch/mi.
238

• Rut Depth Std Dev: Standard deviation of rutting measurements, inch/mi.

• Rut Depth Num: Number of rutting measurements.

Table name: Performance_Fatigue_cracking

• Fields:

• STATE_CODE: Numerical code for State or province. U.S. codes are consistent 

with Federal information processing standards.

• SHRP_ID: Test section identification number assigned by LTPP program. Must be 

combined with STATE_CODE to be unique.

• Date: Survey date.

• Low Severity: Low severity, ft

2

.

• Moderate Severity: Moderate severity, ft2

.

• High Severity: High severity, ft2

.

• Total Severity: Total severity, ft2

.

Table name: Performance_Longitudinal_cracking

• Fields:

• STATE_CODE: Numerical code for State or province. U.S. codes are consistent 

with Federal information processing standards.

• SHRP_ID: Test section identification number assigned by LTPP program. Must be 

combined with STATE_CODE to be unique.

• Date: Survey date.

• Not Sealed Low Severity: Low severity, ft.

• Not Sealed Moderate Severity: Moderate severity, ft.

• Not Sealed High Severity: High severity, ft.

• Not Sealed Total: Total, ft.

• Sealed Low Severity: Low severity, ft.

• Sealed Moderate Severity: Moderate severity, ft.
239

• Sealed High Severity: High severity, ft.

• Sealed Total: Total, ft.

• Total Low Severity: Low severity, ft.

• Total Moderate Severity: Moderate severity, ft.

• Total High Severity: High severity, ft.

• Total: Total, feet.

Table name: Performance_Transverse_cracking

• Fields:

• STATE_CODE: Numerical code for State or province. U.S. codes are consistent 

with Federal information processing standards.

• SHRP_ID: Test section identification number assigned by LTPP program. Must be 

combined with STATE_CODE to be unique.

• Date: Survey date.

• Not Sealed Low Severity: Low severity, ft.

• Not Sealed Moderate Severity: Moderate severity, ft.

• Not Sealed High Severity: High severity, ft.

• Not Sealed Total: Total, ft.

• Sealed Low Severity: Low severity, ft.

• Sealed Moderate Severity: Moderate severity, ft.

• Sealed High Severity: High severity, ft.

• Sealed Total: Total, ft.

• Total Low Severity: Low severity, ft.

• Total Moderate Severity: Moderate severity, ft.

• Total High Severity: High severity, ft.

• Total: Total, ft.
240

Table name: Performance_Faulting

• Fields:

• STATE_CODE: Numerical code for State or province. U.S. codes are consistent 

with Federal information processing standards.

• SHRP_ID: Test section identification number assigned by LTPP program. Must be 

combined with STATE_CODE to be unique.

• Date: Survey date.

• Average: Average of faulting measurements, inch.

• Minimum: Minimum of faulting measurements, inch.

• Maximum: Maximum of faulting measurements, inch.

• Std Dev: Standard deviation of faulting measurements, inch.

Table name: Performance_PCC_slab_cracking

• Fields:

• STATE_CODE: Numerical code for state or province. U.S. codes are consistent with 

Federal information processing standards.

• SHRP_ID: Test section identification number assigned by LTPP program. Must be 

combined with STATE_CODE to be unique.

• Date: Survey date.

• Longitudinal Not Sealed Low Severity: Longitudinal cracking low severity, ft.

• Longitudinal Not Sealed Moderate Severity: Longitudinal cracking moderate 

severity, ft.

• Longitudinal Not Sealed High Severity: Longitudinal cracking high severity, ft.

• Longitudinal Not Sealed Total: Total longitudinal cracking not sealed, ft.

• Longitudinal Sealed Low Severity: Longitudinal cracking low severity, ft.

• Longitudinal Sealed Moderate Severity: Longitudinal cracking moderate 

severity, ft.

• Longitudinal Sealed High Severity: Longitudinal cracking high severity, ft.
241

• Longitudinal Sealed Total: Total longitudinal cracking not sealed, ft.

• Transverse Not Sealed Low Severity: Transverse cracking low severity, ft.

• Transverse Not Sealed Moderate Severity: Transverse cracking moderate 

severity, ft.

• Transverse Not Sealed High Severity: Transverse cracking high severity, ft.

• Transverse Not Sealed Total: Total transverse cracking not sealed, ft.

• Transverse Sealed Low Severity: Transverse cracking low severity, ft.

• Transverse Sealed Moderate Severity: Transverse cracking moderate severity, ft.

• Transverse Sealed High Severity: Transverse cracking high severity, ft.

• Transverse Sealed Total: Total transverse cracking not sealed, ft.

• Total Low Severity: Total longitudinal and transverse cracking low severity, ft.

• Total Moderate Severity: Total longitudinal and transverse cracking moderate 

severity, ft.

• Total High Severity: Total longitudinal and transverse cracking high severity, ft.

• Total: Total longitudinal and transverse cracking, ft.

MEPDG INPUT DATA

Data used to create the MEPDG run files are stored in two tables in the database. One table 

contains the data for SPS-5 sections, and the other contains data for SPS-6 sections. Additional 

input data could not be placed in the database file and were stored in folders to support the 

main database. 

Traffic data for monthly adjust factors (MAFs) and axle load factors (ALFs) were stored in files 

already in the format required by MEPDG. These files are located in the folder called “Traffic—

Supporting Files.” Climate files are also stored in the “Climate—Supporting Files” folder. 

References to the files stored outside the database are located in the appropriate fields in the 

MEPDG inputs table in the database.
242

The following tables and respective fields were populated and stored in the database:

• Table name: SPS-5 MEPDG Inputs.

• Fields:

• STATE_CODE: Numerical code for State or province. U.S. codes are consistent 

with Federal information processing standards.

• SHRP_ID: Test section identification number assigned by LTPP program. Must be 

combined with STATE_CODE to be unique.

• Design Life: Number of years of service life in the LTPP program after rehabilitation.

• Subgrade Construction Month: Subgrade construction month.

• Pavement Construction Month: Pavement construction month.

• Traffic Open Date: Date pavement was opened to traffic after rehabilitation.

• Traffic_AADTT: Average annual daily truck traffic.

• Traffic_MAF: Name of file containing the monthly adjusted factors, in MEPDG 

format.

• Traffic_VCD: Vehicle class distribution, separated by commas (classes 4–13).

• Traffic_HD: Hourly distribution.

• Traffic Growth Factor: Traffic growth factor.

• ALF: Name of file containing the axle load factors in MEPDG format. This file is 

located in the supporting folders to the database.

• Number of Axles Per Truck: Name of file containing the number of axles per truck, 

in MEPDG format. This file is located in the supporting folders to the database.

• Climate: Name of file containing the climate data, in MEPDG format. This file is 

located in the supporting folders to the database.

• Structure: Description of pavement layers and thicknesses.

• Pavement Rating: Pavement rating before rehabilitation.

• Rutting: Pavement rutting before rehabilitation.

• Milling Thickness: Milling thickness before rehabilitation.
243

• HMA_Retained 3

/4-inch Sieve: HMA-retained 3/4–inch (19.05-mm) sieve.

• HMA_Retained 3/8-inch Sieve: HMA-retained 3/8–inch (9.53-mm) sieve.

• HMA_Retained #4 Sieve: HMA-retained #4 sieve.

• HMA_% Passing #200 Sieve: HMA percentage passing #200 sieve.

• HMA_Asphalt Binder Type: HMA asphalt binder type.

• HMA_Effective Binder Content: HMA effective binder content.

• HMA_Air Voids: HMA air voids.

• Unbound Material Properties: Unbound resilient modulus, when available.

• Table name: SPS-6 MEPDG Inputs.

• Fields:

• ID: Numerical code for State or province. U.S. codes are consistent with Federal 

information processing standards.

• SHRP_ID: Test section identification number assigned by LTPP program. Must be 

combined with STATE_CODE to be unique.

• Design Life: Number of years of service life in the LTPP program after rehabilitation

• Subgrade Construction Month: Subgrade construction month.

• Pavement Construction Month: Pavement construction month.

• Traffic Open Date: Date pavement was opened to traffic after rehabilitation.

• Traffic_AADTT: Average annual daily truck traffic.

• Traffic_MAF: Name of file containing the monthly adjusted factors, in MEPDG 

format.

• Traffic_VCD: Vehicle class distribution, separated by commas (classes 4–13).

• Traffic_HD: Hourly distribution.

• Traffic Growth Factor: Traffic growth factor.

• ALF: Name of file containing the axle load factors in MEPDG format. This file is 

located in the supporting folders to the database.
244

• Number of Axles Per Truck: Name of file containing the number of axles per truck 

in MEPDG format. This file is located in the supporting folders to the database.

• Climate: Name of file containing the climate data in MEPDG format. This file is 

located in the supporting folders to the database.

• Structure: Description of pavement layers and thicknesses.

• Joint Spacing (ft): Joint spacing, ft.

• Pavement Rating: Pavement rating before rehabilitation.

• Modulus of Rupture (psi): PCC modulus of rupture.

• Elastic Modulus (psi): PCC modulus of rupture.

• % Slabs w/ Transverse Cracks Before: Percentage slabs with transverse cracking 

before rehabilitation.

• % Slabs w/ Transverse Cracks Fixed: Percentage slabs with transverse cracking 

fixed during rehabilitation.

• HMA_Retained 3

/4-inch Sieve: HMA-retained 3/4-inch (19.05-mm) sieve.

• HMA_Retained 3/8-inch Sieve: HMA-retained 3/8-inch (9.53-mm) sieve.

• HMA_Retained #4 Sieve: HMA-retained #4 sieve.

• HMA_% Passing #200 Sieve: HMA percentage passing #200 sieve.

• HMA_Asphalt Binder Type: HMA asphalt binder type.

• HMA_Effective Binder Content: HMA effective binder content.

• HMA_Air Voids: HMA air voids.

• Unbound Material Properties: Unbound resilient modulus, when available.
245

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246

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(Project SP20-50(2)), National Cooperative Highway Research Program, Washington, DC.

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Treatment Performance Review: SPS-4 5-Year Data Analysis, Report No. FHWA-RD-97-

155, Federal Highway Administration, Washington, DC.

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Maintenance Materials: SPS-4 Supplemental Joint Seal Experiment, Report No. FHWA-RD99-151, Federal Highway Administration, Washington, DC.

18. Peshkin, D.G, Hoerner, T.E, and Zimmerman K.A. (2004). Optimal Timing of Pavement 

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Highway Research Program, Washington, DC.

19. Peshkin, D.G. (2003). Guide for Optimal Timing of Pavement Preventive Maintenance 

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LTPP Faulting Data, Report No. FHWA-RD-00-076, Federal Highway Administration, 

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(10/16) (Web Document 74), National Cooperative Highway Research Program, 

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22. Thompson M., Barenberg, E., Brown, S., Irwin, L. (2006). NCHRP 1-40A: “Independent 

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23. Witczak, M. (2006). NCHRP 1-40D: “Technical Assistance to NCHRP and NCHRP Project 

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247

24. Owusu-Antwi, E. (1998). NCHRP 10-41: “Evaluation of Unbonded Portland Cement 

Concrete Overlays,” NCHRP Report 415, Transportation Research Board, Washington, DC.


HRDI-30/10-11(500)E Recycled

Recyclable