Research, Development, and Technology

Turner-Fairbank Highway Research Center

6300 Georgetown Pike

McLean, VA 22101-2296

Relating Ride Quality and 

Structural Adequacy for Pavement 

Rehabilitation/Design Decisions

PUBLICATION NO. FHWA-HRT-12-035 NOVEMBER 2012
FOREWORD

Ride quality and structural adequacy are key pavement performance indicators. The relationship 

between the two has been a topic of frequent and continuing discussion in the pavement 

community, but an accepted and widely used relationship has not been identified to date. This 

report presents the results of a study undertaken to identify and verify the relationship, if any,

between the two performance indicators using the Long-Term Pavement Performance (LTPP)

program and other pavement performance data sources. The study was performed in an effort to 

improve the evaluation and use of pavement condition data in pavement rehabilitation and design 

decisions. More specifically, the project was intended to develop and document a mechanism to 

include both ride quality and structural adequacy values within the context of current networklevel pavement management systems for highway agency implementation to ensure smooth, 

structurally adequate pavements. To accomplish the objective, two major activities were carried 

out: (1) a literature search to gather, review, and synthesize available information on relating ride 

quality and structural adequacy and (2) a review and assessment of data from the LTPP program 

to determine if such a relationship exists. This report details those two activities and their major 

findings, observations, and conclusions.

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

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

1. Report No. FHWA-HRTFHWA-HRT-12-0352. Government Accession No. 3. Recipient's Catalog No.

4. Title and Subtitle

Relating Ride Quality and Structural Adequacy for Pavement 

Rehabilitation/Design Decisions

5. Report Date

November 2012

6. Performing Organization Code

7. Author(s)

Rada, G.R., Ph.D., P.E., Perera, R., Ph.D., P.E., and 

Prabhakar, V., P.E.

8. Performing Organization Report No.

9. Performing Organization Name and Address

Fugro Consultants, Inc.

8613 Cross Park Drive

Austin, TX 78754

10. Work Unit No. (TRAIS)

11. Contract or Grant No.

DTFH61-08-D-00021-T-11001

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, December 2010–December 2011

14. Sponsoring Agency Code

HRDI-30

15. Supplementary Notes

The task order manager was Larry Wiser. The Contracting Officer’s Technical Representative (COTR) was 

Nadarajah Sivaneswaran (HRDI-30), the Contract Officer was Robin K. Hobbs, and the Contract Specialist was 

Sean Wybenga. The task order contractor was Fugro Consultants, Inc., with subcontractors Soil and Materials 

Engineers, Inc. and Woodward Communications, Inc.

16. Abstract

Ride quality and structural adequacy are key pavement performance indicators. The relationship between these

two indicators has been a topic of frequent and continuing discussion in the pavement community, but an 

accepted and widely used relationship has not been identified to date. The objective of this project was to identify 

and verify the relationship between these two performance indicators, if any, using the Long-Term Pavement 

Performance (LTPP) program and other pavement performance data sources. This was done in an effort to 

improve the evaluation and use of pavement condition data in pavement rehabilitation and design decisions. 

More specifically, the project was intended to develop and document a mechanism to include both ride quality 

and structural adequacy values within the context of current network-level pavement management system 

practices for highway agency implementation to ensure smooth pavements that are also structurally adequate. 

Toward the accomplishment of the project objective, two major activities were carried out: (1) a literature search 

to gather, review, and synthesize available information on relating ride quality and structural adequacy and (2) a 

review and assessment of data from the LTPP program to determine if such a relationship exists. This report 

details those two activities as well as their major findings, observations, and conclusions. A viable relationship 

could not be identified. 

17. Key Words

Ride quality, Structural adequacy, Structural capacity, 

Pavement management systems, Pavement rehabilitation, 

Pavement design decisions

18. Distribution Statement

No restrictions. This document is available to the 

public through the National Technical Information 

Service, Springfield, VA 22161.

19. Security Classif. (of this report)

Unclassified

20. Security Classif. (of this page)

Unclassified

21. No. of Pages

179

22. Price

N/A
ii
iii

TABLE OF CONTENTS

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

1.1 PAVEMENT REHABILITATION AND DESIGN DECISIONS................................ 1

1.2 RELATIONSHIP BETWEEN RIDE QUALITY AND STRUCTURAL 

ADEQUACY ........................................................................................................................... 2

1.3 PROJECT GOAL AND OBJECTIVE ......................................................................... 13

1.4 REPORT ORGANIZATION......................................................................................... 14

CHAPTER 2. LITERATURE SEARCH.................................................................................. 15

2.1 OVERVIEW.................................................................................................................... 15

2.2 SPECIFIC FINDINGS ................................................................................................... 17

2.3 SUMMARY ..................................................................................................................... 23

CHAPTER 3. DATA AVAILABILITY AND DATA ASSESSMENT .................................. 25

3.1 INTRODUCTION........................................................................................................... 25

3.2 DATA AVAILABILITY ................................................................................................ 25

3.3 RIDE QUALITY PARAMETER SELECTED FOR STUDY.................................... 27

3.4 STRUCTURAL STRENGTH PARAMETER SELECTED FOR STUDY............... 28

3.4.1 Flexible Pavements.................................................................................................. 28

3.4.2 Rigid Pavements ...................................................................................................... 29

3.5 CONTINUOUS ROUGHNESS PLOT ......................................................................... 30

3.6 EVALUATING CHANGES IN RIDE QUALITY AND STRUCTURAL 

CAPACITY OVER TIME ................................................................................................... 31

3.6.1 Changes in IRI ......................................................................................................... 31

3.6.2 Changes in Structural Strength—Flexible Pavements............................................. 32

3.6.3 Change in Structural Strength—Rigid Pavements................................................... 32

3.7 METHODOLOGY FOR COMPARING RIDE QUALITY-STRUCTURAL 

CAPACITY RELATIONSHIP................................................................................... 33

3.7.1 Flexible Pavements.................................................................................................. 33

3.7.2 Rigid Pavements ...................................................................................................... 35

3.8 TEST SECTIONS SELECTED FOR ANALYSIS...................................................... 35

3.9 ANALYSIS OF GROUP 1 SECTIONS........................................................................ 36

3.9.1 LTPP Section 050119 (Arkansas)............................................................................ 38

3.9.2 LTPP Section 480114 (Texas)................................................................................. 42

3.9.3 LTPP Section 310113 (Nebraska) ........................................................................... 43

3.9.4 LTPP Section 010102 (Alabama)............................................................................ 44

3.9.5 LTPP Section 390112 (Ohio)................................................................................... 46

3.9.6 LTPP Section 040123 (Arizona).............................................................................. 47

3.9.7 LTPP Section 190108 (Iowa)................................................................................... 48

3.10 ANALYSIS OF GROUP 2 SECTIONS ...................................................................... 49

3.10.1 LTPP Section 320101 (Nevada) ............................................................................ 51

3.10.2 LTPP Section 390106 (Ohio)................................................................................. 52

3.10.3 LTPP Section 310117 (Nebraska) ......................................................................... 53

3.10.4 LTPP Section 310118 (Nebraska) ......................................................................... 54
iv

3.11 ANALYSIS OF GROUP 3 SECTIONS ...................................................................... 54

3.11.1 LTPP Section 190101 (Iowa)................................................................................. 55

3.11.2 LTPP Section 190103 (Iowa)................................................................................. 56

3.11.3 LTPP Section 050114 (Arkansas).......................................................................... 58

3.11.4 LTPP Section 050116 (Arkansas).......................................................................... 59

3.12 ANALYSIS OF GROUP 4 SECTIONS ...................................................................... 60

3.12.1 LTPP Section 040502 (Arizona)............................................................................ 62

3.12.2 LTPP Section 240505 (Maryland)......................................................................... 64

3.12.3 LTPP Section 270509 (Minnesota)........................................................................ 66

3.13 ANALYSIS OF GROUP 5 SECTIONS ...................................................................... 68

3.13.1 LTPP Section 040213 (Arizona)............................................................................ 70

3.13.2 LTPP Section 050217 (Arkansas).......................................................................... 71

3.13.3 LTPP Section 390205 (Ohio)................................................................................. 72

3.14 SUMMARY ................................................................................................................... 74

CHAPTER 4. OTHER DATA ANALYSIS CONSIDERATIONS......................................... 79

4.1 INTRODUCTION........................................................................................................... 79

4.2 EVALUATION OF MAINTENANCE AND REPAIR IMPACTS............................ 79

4.3 REVIEW OF IRI TIME HISTORY DATA................................................................. 81

4.4 REVIEW OF DEFLECTION TIME HISTORY DATA ............................................ 92

4.5 ASSESSMENT OF PCC WARPING AND CURLING.............................................. 97

4.5.1 Curling and Warping of Slabs.................................................................................. 97

4.5.2 Diurnal Changes in IRI............................................................................................ 98

4.5.3 Changes in IRI Over Time....................................................................................... 98

4.5.4 Effect of Curling and Warping on FWD Testing .................................................. 100

4.5.5 Effect of Roughness on Structural Capacity.......................................................... 100

4.6 SUMMARY ................................................................................................................... 100

CHAPTER 5. SUMMARY AND CONCLUSIONS............................................................... 103

APPENDIX A. DEFLECTION BELOW CENTER OF 9,000-LB LOAD AND 

SUBGRADE MODULUS PLOTS........................................................................................... 105

A.1 GROUP 1 SECTIONS................................................................................................. 105

A.1.1 Section 050119 (Arkansas)................................................................................... 105

A.1.2 Section 480114 (Texas) ........................................................................................ 106

A.1.3 Section 310113 (Nebraska)................................................................................... 107

A.1.4 Section 010102 (Alabama).................................................................................... 108

A.1.5 Section 390112 (Ohio).......................................................................................... 109

A.1.6 Section 040123 (Arizona)..................................................................................... 110

A.1.7 Section 190108 (Iowa).......................................................................................... 111

A.2 GROUP 2 SECTIONS................................................................................................. 112

A.2.1 Section 320101 (Nevada)...................................................................................... 112

A.2.2 Section 390106 (Nevada)...................................................................................... 113

A.3 GROUP 3 SECTIONS................................................................................................. 114

A.3.1 Section 190101 (Iowa).......................................................................................... 114

A.3.2 Section 190103 (Iowa).......................................................................................... 115

A.3.3 Section 050114 (Arkansas)................................................................................... 116

A.3.4 Section 050116 (Arkansas)................................................................................... 117
v

A.4 GROUP 4 SECTIONS................................................................................................. 118

A.4.1 Section 040502 (Arizona)..................................................................................... 118

A.4.2 Section 240505 (Maryland) .................................................................................. 119

A.4.3 Section 270509 (Minnesota)................................................................................. 120

APPENDIX B. DEFLECTION BELOW LOAD AND AT 60 INCHES FOR A 

9,000-LB LOAD ........................................................................................................................ 121

B.1 GROUP 5 SECTIONS ................................................................................................. 121

B.1.1 Section 040213 (Arizona) ..................................................................................... 121

B.1.2 Section 050217 (Arkansas) ................................................................................... 122

B.1.3 Section 390205 (Ohio) .......................................................................................... 123

APPENDIX C. TIME SEQUENCE IRI PLOTS ................................................................... 125

C.1 GROUP 1 SECTIONS................................................................................................. 125

C.2 GROUP 2 SECTIONS................................................................................................. 128

C.3 GROUP 3 SECTIONS................................................................................................. 130

C.4 GROUP 4 SECTIONS................................................................................................. 132

C.5 GROUP 5 SECTIONS................................................................................................. 134

APPENDIX D. AVERAGE NORMALIZED DEFLECTION AND MID-DEPTH 

SURFACE LAYER TEMPERATURE PLOTS .................................................................... 137

D.1 GROUP 1 SECTIONS................................................................................................. 137

D.2 GROUP 2 SECTIONS................................................................................................. 144

D.3 GROUP 3 SECTIONS................................................................................................. 148

D.4 GROUP 4 SECTIONS................................................................................................. 152

D.5 GROUP 5 SECTIONS................................................................................................. 155

REFERENCES.......................................................................................................................... 159

BIBLIOGRAPHY..................................................................................................................... 163
vi

LIST OF FIGURES

Figure 1. Graph. Progression of roughness on asphalt sections with asphalt overlay.....................3

Figure 2. Graph. Changes in deflection over time at LTPP SMP test section.................................5

Figure 3. Graph. Changes in IRI over time for LTPP SPS-1 test sections in Iowa .........................7

Figure 4. Graph. Changes in IRI over time for LTPP SPS-1 test sections in Arkansas..................7

Figure 5. Graph. Changes in IRI over time for LTPP SPS-1 test sections in Virginia (DGAB).....8

Figure 6. Graph. Changes in IRI over time for LTPP SPS-1 test sections in Virginia (ATB)........8

Figure 7. Graph. Changes in IRI over time for LTPP SPS-1 test sections in Virginia (PATB)......8

Figure 8. Graph. Changes in IRI over time for LTPP SPS-1 test sections in Virginia 

(ATB/PATB)....................................................................................................................................8

Figure 9. Graph. Continuous IRI plot of road profile ....................................................................10

Figure 10. Graph. PSD plot of road profile ...................................................................................10

Figure 11. Graph. Dynamic loads applied to road profile .............................................................11

Figure 12. Graph. Distribution of references.................................................................................17

Figure 13. Equation. UED distress score .......................................................................................18

Figure 14. Equation. UED condition score....................................................................................18

Figure 15. Equation. UED ride score.............................................................................................18

Figure 16. Graph. Sensitivity of SN to UED of ride score ............................................................19

Figure 17. Equation. d0 ..................................................................................................................29

Figure 18. Equation. SNeff..............................................................................................................29

Figure 19. Graph. IRI of 52.8-ft segments in 0.1-mi pavement section ........................................30

Figure 20. Graph. Continuous roughness plot based on 25-ft base length ....................................31

Figure 21. Graph. Continuous IRI plots for two test dates............................................................32

Figure 22. Graph. SN from FWD tests performed at two test dates..............................................32

Figure 23. Graph. SN and IRI data on same plot...........................................................................34

Figure 24. Graph. Normalized SN and IRI data on same plot.......................................................34

Figure 25. Graph. IRI for two test dates, section 050119 (Arkansas) ...........................................39

Figure 26. Graph. SN for two test dates, section 050119 (Arkansas)............................................39

Figure 27. Graph. Deflection below load for 9,000 lb for two test dates, section 050119 

(Arkansas)......................................................................................................................................40

Figure 28. Graph. Subgrade modulus for two test dates, section 050119 (Arkansas)...................40

Figure 29. Graph. SN and IRI for two test dates, section 050119 (Arkansas)...............................41

Figure 30. Graph. Normalized SN and IRI for two test dates, section 050119 (Arkansas)...........41

Figure 31. Graph. SN and IRI for two test dates, section 480114 (Texas)....................................42

Figure 32. Graph. Normalized SN and IRI for two test dates, section 480114 (Texas)................43

Figure 33. Graph. SN and IRI for two test dates, section 310113 (Nebraska) ..............................44

Figure 34. Graph. Normalized SN and IRI for two test dates, section 310113 (Nebraska) ..........44

Figure 35. Graph. SN and IRI for two test dates, section 010102 (Alabama)...............................45

Figure 36. Graph. Normalized SN and IRI for two test dates, section 010102 (Alabama)...........45

Figure 37. Graph. SN and IRI for two test dates, section 390112 (Ohio) .....................................46

Figure 38. Graph. Normalized SN and IRI for two test dates, section 390112 (Ohio) .................47

Figure 39. Graph. SN and IRI for two test dates, section 040123 (Arizona).................................48

Figure 40. Graph. Normalized SN and IRI for two test dates, section 040123 (Arizona).............48

Figure 41. Graph. SN and IRI for two test dates, section 190108 (Iowa) .....................................49

Figure 42. Graph. Normalized SN and IRI for two test dates, section 190108 (Iowa) .................49
vii

Figure 43. Graph. SN and IRI for two test dates, section 320101 (Nevada) .................................52

Figure 44. Graph. Normalized SN and IRI for two test dates, section 320101 (Nevada) .............52

Figure 45. Graph. SN and IRI for two test dates, section 390106 (Ohio) .....................................53

Figure 46. Graph. Normalized SN and IRI for two test dates, section 390106 (Ohio) .................53

Figure 47. Graph. SN and IRI for two test dates, section 190101 (Iowa) .....................................56

Figure 48. Graph. Normalized SN and IRI for two test dates, section 190101 (Iowa) .................56

Figure 49. Graph. SN and IRI for two test dates, section 190103 (Iowa) .....................................57

Figure 50. Graph. Normalized SN and IRI for two test dates, section 190103 (Iowa) .................57

Figure 51. Graph. SN and IRI for two test dates, section 050114 (Arkansas)...............................58

Figure 52. Graph. Normalized SN and IRI for two test dates, section 050114 (Arkansas)...........59

Figure 53. Graph. SN and IRI for two test dates, section 050116 (Arkansas)...............................60

Figure 54. Graph. Normalized SN and IRI for two test dates, section 050116 (Arkansas)...........60

Figure 55. Graph. IRI for before overlay, after overlay, and last test date, section 040502 

(Arizona)........................................................................................................................................62

Figure 56. Graph. SN for before overlay, after overlay, and last test date, section 040502 

(Arizona)........................................................................................................................................63

Figure 57. Graph. SN and IRI for two test dates after overlay, section 040502 (Arizona) ...........63

Figure 58. Graph. Normalized SN and IRI for two test dates after overlay, section 040502 

(Arizona)........................................................................................................................................64

Figure 59. Graph. IRI for before overlay, after overlay, and last test date, section 240505 

(Maryland) .....................................................................................................................................65

Figure 60. Graph. SN for before overlay, after overlay, and last test date, section 240505 

(Maryland) .....................................................................................................................................65

Figure 61. Graph. SN and IRI for two test dates after overlay, section 240505 (Maryland).........66

Figure 62. Graph. Normalized SN and IRI for two test dates after overlay, section 240505 

(Maryland) .....................................................................................................................................66

Figure 63. Graph. IRI for before overlay, after overlay, and last test date, section 270509 

(Minnesota)....................................................................................................................................67

Figure 64. Graph. SN for before overlay, after overlay, and last test date, section 270509 

(Minnesota)....................................................................................................................................67

Figure 65. Graph. SN and IRI for two test dates after overlay, section 270509 (Minnesota) .......68

Figure 66. Graph. Normalized SN and IRI for two test dates after overlay, section 270509 

(Minnesota)....................................................................................................................................68

Figure 67. Graph. Deff and IRI for two test dates, section 040213 (Arizona)................................70

Figure 68. Graph. Normalized Deff and IRI for two test dates, section 040213 (Arizona) ............71

Figure 69. Graph. Deff and IRI for two test dates, section 050217 (Arkansas)..............................72

Figure 70. Graph. Normalized Deff and IRI for two test dates, section 050217 (Arkansas) ..........72

Figure 71. Graph. Deff and IRI for two test dates, section 390205 (Ohio).....................................73

Figure 72. Graph. Normalized Deff and IRI for two test dates, section 390205 (Ohio).................74

Figure 73. Graph. Relationship between changes in IRI and SN ..................................................77

Figure 74. Graph. Relationship between percent changes in IRI and SN......................................77

Figure 75. Graph. Deflection plot for section 050119 (Arkansas) ..............................................105

Figure 76. Graph. Subgrade modulus plot for section 050119 (Arkansas) .................................105

Figure 77. Graph. Deflection plot for section 480114 (Texas)....................................................106

Figure 78. Graph. Subgrade modulus plot for section 480114 (Texas).......................................106

Figure 79. Graph. Deflection plot for section 310113 (Nebraska) ..............................................107
viii

Figure 80. Graph. Subgrade modulus plot for section 310113 (Nebraska) .................................107

Figure 81. Graph. Deflection plot for section 010102 (Alabama)...............................................108

Figure 82. Graph. Subgrade modulus plot for section 010102 (Alabama)..................................108

Figure 83. Graph. Deflection plot for section 390112 (Ohio) .....................................................109

Figure 84. Graph. Subgrade modulus plot for section 390112 (Ohio) ........................................109

Figure 85. Graph. Deflection plot for section 040123 (Arizona) ................................................110

Figure 86. Graph. Subgrade modulus plot for section 040123 (Arizona) ...................................110

Figure 87. Graph. Deflection plot for section 190108 (Iowa) .....................................................111

Figure 88. Graph. Subgrade modulus plot for section 190108 (Iowa) ........................................111

Figure 89. Graph. Deflection plot for section 320101 (Nevada).................................................112

Figure 90. Graph. Subgrade modulus plot for section 320101 (Nevada)....................................112

Figure 91. Graph. Deflection plot for section 390106 (Nevada).................................................113

Figure 92. Graph. Subgrade modulus plot for section 390106 (Nevada)....................................113

Figure 93. Graph. Deflection plot for section 190101 (Iowa) .....................................................114

Figure 94. Graph. Subgrade modulus plot for section 190101 (Iowa) ........................................114

Figure 95. Graph. Deflection plot for section 190103 (Iowa) .....................................................115

Figure 96. Graph. Subgrade modulus plot for section 190103 (Iowa) ........................................115

Figure 97. Graph. Deflection plot for section 050114 (Arkansas) ..............................................116

Figure 98. Graph. Subgrade modulus plot for section 050114 (Arkansas) .................................116

Figure 99. Graph. Deflection plot for section 050116 (Arkansas) ..............................................117

Figure 100. Graph. Subgrade modulus plot for section 050116 (Arkansas) ...............................117

Figure 101. Graph. Deflection plot for section 040502 (Arizona) ..............................................118

Figure 102. Graph. Subgrade modulus plot for section 040502 (Arizona) .................................118

Figure 103. Graph. Deflection plot for section 240505 (Maryland)............................................119

Figure 104. Graph. Subgrade modulus plot for section 240505 (Maryland)...............................119

Figure 105. Graph. Deflection plot for section 270509 (Minnesota) ..........................................120

Figure 106. Graph. Subgrade modulus plot for section 270509 (Minnesota) .............................120

Figure 107. Graph. Deflection at 0 inches for a 9,000-lb load, section 040213 (Arizona) .........121

Figure 108. Graph. Deflection at 60 inches for a 9,000-lb load, section 040213 (Arizona) .......121

Figure 109. Graph. Deflection at 0 inches for a 9,000-lb load, section 050217 (Arkansas) .......122

Figure 110. Graph. Deflection at 60 inches for a 9,000-lb load, section 050217 (Arkansas) .....122

Figure 111. Graph. Deflection at 0 inches for a 9,000-lb load, section 390205 (Ohio) ..............123

Figure 112. Graph. Deflection at 60 inches for a 9,000-lb load, section 390205 (Ohio) ............123

Figure 113. Graph. Time sequence IRI values, section 050119 (Arkansas)................................125

Figure 114. Graph. Time sequence IRI values, section 480114 (Texas).....................................125

Figure 115. Graph. Time sequence IRI values, section 310113 (Nebraska) ...............................126

Figure 116. Graph. Time sequence IRI values, section 010102 (Alabama)................................126

Figure 117. Graph. Time sequence IRI values, section 390112 (Ohio) ......................................127

Figure 118. Graph. Time sequence IRI values, section 040123 (Arizona)..................................127

Figure 119. Graph. Time sequence IRI values, section 190108 (Iowa) ......................................128

Figure 120. Graph. Time sequence IRI values, section 320101 (Nevada) ..................................128

Figure 121. Graph. Time sequence IRI values, section 390106 (Ohio) ......................................129

Figure 122. Graph. Time sequence IRI values, section 310117 (Nebraska) ...............................129

Figure 123. Graph. Time sequence IRI values, section 310118 (Nebraska) ...............................130

Figure 124. Graph. Time sequence IRI values, section 190101 (Iowa) ......................................130

Figure 125. Graph. Time sequence IRI values, section 190103 (Iowa) ......................................131
ix

Figure 126. Graph. Time sequence IRI values, section 050114 (Arkansas)................................131

Figure 127. Graph. Time sequence IRI values, section 050116 (Arkansas)................................132

Figure 128. Graph. Time sequence IRI values, section 040502 (Arizona)..................................132

Figure 129. Graph. Time sequence IRI values, section 240505 (Maryland)...............................133

Figure 130. Graph. Time sequence IRI values, section 270509 (Minnesota)..............................133

Figure 131. Graph. Time sequence IRI values, section 040213 (Arizona)..................................134

Figure 132. Graph. Time sequence IRI values, section 050217 (Arkansas)................................134

Figure 133. Graph. Time sequence IRI values, section 390205 (Ohio) ......................................135

Figure 134. Graph. Average normalized deflection below 9,000-lb load, section 050119 

(Arkansas)....................................................................................................................................137

Figure 135. Graph. Mid-depth temperature of AC layer, section 050119 (Arkansas) ................137

Figure 136. Graph. Average normalized deflection below 9,000-lb load, section 480114 

(Texas) .........................................................................................................................................138

Figure 137. Graph. Mid-depth temperature of AC layer, section 480114 (Texas)......................138

Figure 138. Graph. Average normalized deflection below 9,000-lb load, section 310113 

(Nebraska)....................................................................................................................................139

Figure 139. Graph. Mid-depth temperature of AC layer, section 310113 (Nebraska)................139

Figure 140. Graph. Average normalized deflection below 9,000-lb load, section 010102 

(Alabama) ....................................................................................................................................140

Figure 141. Graph. Mid-depth temperature of AC layer, section 010102 (Alabama).................140

Figure 142. Graph. Average normalized deflection below 9,000-lb load, section 390112 

(Ohio)...........................................................................................................................................141

Figure 143. Graph. Mid-depth temperature of AC layer, section 390112 (Ohio) .......................141

Figure 144. Graph. Average normalized deflection below 9,000-lb load, section 040123 

(Arizona)......................................................................................................................................142

Figure 145. Graph. Mid-depth temperature of AC layer, section 040123 (Arizona) ..................142

Figure 146. Graph. Average normalized deflection below 9,000-lb load, section 190108 

(Iowa)...........................................................................................................................................143

Figure 147. Graph. Mid-depth temperature of AC layer, section 190108 (Iowa) .......................143

Figure 148. Graph. Average normalized deflection below 9,000-lb load, section 320101 

(Nevada).......................................................................................................................................144

Figure 149. Graph. Mid-depth temperature of AC layer, section 320101 (Nevada)...................144

Figure 150. Graph. Average normalized deflection below 9,000-lb load, section 390106 

(Ohio)...........................................................................................................................................145

Figure 151. Graph. Mid-depth temperature of AC layer, section 390106 (Ohio) .......................145

Figure 152. Graph. Average normalized deflection below 9,000-lb load, section 310117 

(Nebraska)....................................................................................................................................146

Figure 153. Graph. Mid-depth temperature of AC layer, section 310117 (Nebraska)................146

Figure 154. Graph. Average normalized deflection below 9,000-lb load, section 310118 

(Nebraska)....................................................................................................................................147

Figure 155. Graph. Mid-depth temperature of AC layer, section 310118 (Nebraska)................147

Figure 156. Graph. Average normalized deflection below 9,000-lb load, section 190101 

(Iowa)...........................................................................................................................................148

Figure 157. Graph. Mid-depth temperature of AC layer, section 190101 (Iowa) .......................148

Figure 158. Graph. Average normalized deflection below 9,000-lb load, section 190103 

(Iowa)...........................................................................................................................................149
x

Figure 159. Graph. Mid-depth temperature of AC layer, section 190103 (Iowa) .......................149

Figure 160. Graph. Average normalized deflection below 9,000-lb load, section 050114 

(Arkansas)....................................................................................................................................150

Figure 161. Graph. Mid-depth temperature of AC layer, section 050114 (Arkansas) ................150

Figure 162. Graph. Average normalized deflection below 9,000-lb load, section 050116 

(Arkansas)....................................................................................................................................151

Figure 163. Graph. Mid-depth temperature of AC layer, section 050116 (Arkansas) ................151

Figure 164. Graph. Average normalized deflection below 9,000-lb load, section 040502 

(Arizona)......................................................................................................................................152

Figure 165. Graph. Mid-depth temperature of AC layer, section 040502 (Arizona) ..................152

Figure 166. Graph. Average normalized deflection below 9,000-lb load, section 240505 

(Maryland) ...................................................................................................................................153

Figure 167. Graph. Mid-depth temperature of AC layer, section 240505 (Maryland)................153

Figure 168. Graph. Average normalized deflection below 9,000-lb load, section 270509 

(Minnesota)..................................................................................................................................154

Figure 169. Graph. Mid-depth temperature of AC layer, section 270509 (Minnesota) ..............154

Figure 170. Graph. Average normalized deflection below 9,000-lb load, section 040213 

(Arizona)......................................................................................................................................155

Figure 171. Graph. Mid-depth temperature of PCC layer, section 040213 (Arizona) ................155

Figure 172. Graph. Average normalized deflection below 9,000-lb load, section 050217 

(Arkansas)....................................................................................................................................156

Figure 173. Graph. Mid-depth temperature of PCC layer, section 050217 (Arkansas) ..............156

Figure 174. Graph. Average normalized deflection below 9,000-lb load, section 390205 

(Ohio)...........................................................................................................................................157

Figure 175. Graph. Mid-depth temperature of PCC layer, section 390205 (Ohio) .....................157
xi

LIST OF TABLES

Table 1. Structural properties of SPS-1 test sections.......................................................................6

Table 2. Distribution of references by type and source .................................................................16

Table 3. Distribution of references by type and topic....................................................................16

Table 4. Summary of factors influencing pavement performance.................................................20

Table 5. Relationship between pavement performance measures.................................................21

Table 6. Roughness data availability for SPS-1 projects...............................................................26

Table 7. Roughness data availability for SPS-2 projects...............................................................26

Table 8. Roughness data availability for SPS-5 projects...............................................................27

Table 9. Group 1 sections selected for analysis.............................................................................36

Table 10. IRI and SN for group 1 sections ....................................................................................37

Table 11. Pavement layer thickness for group 1 sections..............................................................38

Table 12. Group 2 sections selected for analysis...........................................................................50

Table 13. IRI and SN for group 2 sections ....................................................................................50

Table 14. Pavement layer thickness, group 2 sections...................................................................51

Table 15. Group 3 sections selected for analysis...........................................................................54

Table 16. IRI and SN for group 3 sections ....................................................................................55

Table 17. Pavement layer thickness, group 3 sections...................................................................55

Table 18. Group 4 sections selected for analysis...........................................................................61

Table 19. IRI and SN for group 4 sections ....................................................................................61

Table 20. Pavement layer thickness before rehabilitation, group 4 sections.................................61

Table 21. Mill and overlay thickness.............................................................................................62

Table 22. Group 5 sections selected for analysis...........................................................................69

Table 23. IRI and effective slab thickness for group 5 sections....................................................69

Table 24. Pavement layer thickness for group 5 sections..............................................................69

Table 25. Flexible pavement sections used in study......................................................................75

Table 26. Change in IRI and SN at evaluated sections..................................................................76

Table 27. Test sections with crack sealing application..................................................................80

Table 28. Test sections with patching application.........................................................................81

Table 29. Construction date of test sections ..................................................................................82

Table 30. Time-sequence IRI values at test sections.....................................................................83

Table 31. Time-sequence deflection values at test sections ..........................................................92

Table 32. Results for sections designed for flexural strength of 550 psi.......................................99

Table 33. Results for sections designed for flexural strength of 900 psi.....................................100

1

CHAPTER 1. INTRODUCTION

1.1 PAVEMENT REHABILITATION AND DESIGN DECISIONS

State highway agencies spend billions of dollars each year on transportation infrastructure assets 

to meet legislative, agency, and public expectations. Pavements are a major component of those 

transportation assets, and pavement rehabilitation—preserving pavements to extend their service 

life and, more importantly, to improve motorists’ safety and satisfaction—is one of the most 

critical, costly, and complex elements. This is especially true at a time when a large percentage 

of pavement networks are reaching the end of their serviceable life and pavement rehabilitation 

has become even more daunting given the funding constraints faced by highway agencies.

In recognition of the importance of pavement rehabilitation, Federal, State, and local policies, 

mandates, procedures, and initiatives are in place to help ensure pavement rehabilitation is done 

in a systematic, well-thought-out manner. All State transportation departments, for example, 

must prepare a Statewide Transportation Improvement Program (STIP), which is a multimodal, 

multiyear financial document listing all projects expected to be funded with Federal participation 

and updated periodically. Only those projects for which construction and operating funds can 

reasonably be expected to be available are included in STIP, and, without STIP inclusion, a 

project is ineligible for Federal funding.

Although the policies, procedures, mandates, and initiatives vary from one State transportation 

department to another, the generic approach to pavement rehabilitation decisions is similar.

Decisions on pavement rehabilitation projects to be carried out in any given construction year are 

done centrally at the top of the department organization, where pavement rehabilitation projects 

compete for funding with the needs of other transportation assets, including new pavement 

construction. In the case of federally funded rehabilitation projects, these decisions are made as 

part of STIP. In addition, decisions are typically made based on work performed over the course 

of many years (e.g., pavement condition surveys on an annual basis or every 2 years), and 

those efforts enable the decisions. Moreover, these decisions generally rely on a pavement 

management system (PMS), which provides network-level condition scores for each pavement 

segment in the system and, on the basis of the score, establishes an initial action to be performed, 

ranging from no action to major rehabilitation or reconstruction.

After the selection of projects for pavement rehabilitation in a given construction year, the actual 

design of the rehabilitation is typically, but not always, turned over to districts or regions. The 

designs generally begin with a review of available historical data, collection of new data, and the 

generation of alternative rehabilitation strategies (often referred to as “pavement type selection”).

The approach and level of sophistication in this design step varies from one State transportation 

department to another, but the principals are generally the same.

Once the various rehabilitation strategies have been defined, the final step typically entails the 

evaluation of those strategies and the selection of the optimal strategy using life-cycle cost 

analyses and other considerations. Again, the approach and level of sophistication in this 

evaluation step vary among State transportation departments, but the principles are generally 

the same.
2

The discussion so far has focused on the generic approach to rehabilitation decisions by State 

highway agencies. PMSs are at the center of those decisions. The term “PMS” was introduced in 

the mid-1960s to define a set of rational procedures that provide optimum pavement strategies 

based on predicted pavement performance, incorporating feedback regarding the various 

attributes, criteria, and constraints involved. Pavement management is, in essence, a coordinated 

systematic process for carrying out all activities related to providing pavements; it is a support

tool that enables pavement engineers and managers to make better, more cost-effective decisions 

concerning pavement assets and their preservation. Key pavement management outcomes 

include the following:

• Formalization of pavement decisionmaking.

• Entire process to provide quality pavements.

• Strong emphasis on economics.

• Involvement of all associated groups—planning, design, construction, maintenance, 

materials, and field groups.

• Use of advanced tools and analysis techniques.

The first generation of PMSs was largely driven by pavement ride quality and distress as a direct 

result of the American Association of State Highway Officials (AASHO) Road Test, which 

introduced the concept of the Present Serviceability Rating (PSR) and the Present Serviceability 

Index (PSI). PSR represents the subjective rating of pavement serviceability on an arbitrary scale 

of 0 to 5. PSI is a more objective measure established through statistical analyses that relates the 

PSR to various pavement physical measurements—roughness, rutting, cracking, and patching.

Without question, PSI is largely driven by pavement roughness.

With advances in technology, PMS began to move away from the present serviceability concept 

to the use of distress (cracking, rutting, etc.) and longitudinal roughness (typically in the form of 

the International Roughness Index (IRI)) as key pavement performance indicators in the 

decisionmaking process. Although both are important indicators that merit emphasis within the 

PMS process, they are not the only indicators. Structural adequacy, for example, is another 

important pavement performance indicator that is critical to making rational pavement 

rehabilitation decisions. Indeed, many State highway agencies are incorporating deflection 

testing as part of their routine PMS activities in recognition of the need to know about the 

structural adequacy of their pavements. This key pavement performance parameter and 

others, such as surface friction and noise, are being introduced in newer PMS generations.

1.2 RELATIONSHIP BETWEEN RIDE QUALITY AND STRUCTURAL ADEQUACY

In 1996, the U.S. Federal Highway Administration (FHWA) conducted a survey of how highway 

users judge roadways. The survey identified that the most important issue for highway users is 

roadway condition. Furthermore, studies of the AASHO Road Test showed that subjective 

evaluation of roadway condition by highway users is primarily judged by pavement roughness.

Clearly, ride quality is a key performance indicator to highway users.
3

Moreover, research studies have shown that pavements that are built smooth generally have a 

longer service life. A study analyzing roughness trends in pavements under study by the LongTerm Pavement Performance (LTPP) program showed that with all other factors being equal, 

pavements follow a generally parallel trend of roughness development over time. Hence, those 

pavements built with better ride quality take longer to reach unacceptable levels of ride quality,

and, subsequently, longer time will be required before rehabilitation.

Figure 1 shows the progression of roughness for a randomly selected set of asphalt pavements 

with an asphalt overlay from the LTPP database.(1) Each line in the figure represents a separate 

test section. As shown, test sections in the lower portion of the graph at an age of 0 years are also 

generally on the lower end of the graph toward the end of the timeline. The sections shown in the 

graph include sections from all over the United States and represent different environmental 

zones, subgrades, and rates of traffic. Accordingly, the progression of roughness would not be 

expected to be the same for all sections.

Figure 1. Graph. Progression of roughness on asphalt sections with asphalt overlay.

Prior to the development of inertial profilers, roughness data were collected using response-type 

roughness measuring systems, commonly referred to as roughometers (e.g., Portland Cement 

Association Road Meter, Mays meter, etc.). The CHLOE profilometer was used to collect 

roughness data in the AASHO Road Test. State highway agencies started using inertial profilers 

to collect network-level roughness in the 1980s. The most common measure of roughness for 

many years was slope variance, in large part because of the various correlations that were 

developed relating roughness to the American Association of State Highway and Transportation 

Officials (AASHTO) PSI. At present, the state of the practice in roughness data collection 

involves the use of inertial profilers with laser sensors, typically mounted on the front bumper at 

transverse locations corresponding to the wheel-paths. The roughness data shown in figure 1 

were collected using this device. In addition, the index value most commonly used to represent 

pavement roughness is IRI.
4

As with roughness, nondestructive deflection testing for the structural evaluation of pavements 

has been used for more than half a century. Prior to the development of devices that applied a 

load onto the pavement surface and measured deflections at several locations, simpler devices,

such as the Benkelman Beam, were used to measure the response of the pavement to a load 

in terms of a maximum deflection. With time and advances in technology, the pavement 

community started to measure multiple deflections at various radial distances from the center of 

the applied load (i.e., deflection basins). Since the 1980s, the most commonly used device has 

been the falling weight deflectometer (FWD). A number of equipment manufacturers produce or 

market FWDs, but all of them rely on impact loads to produce a response in the pavement similar 

to that produced by actual traffic loadings, which is then measured by multiple deflection sensors 

located at varying distances from the center of the load.

Although FWDs represent significant progress from the Benkelman Beam in terms of both 

quantity and quality of data gathered, FWDs are not without shortcomings. For one, they require 

stop-and-go rather than continuous operation. Lane closures are required, causing traffic 

disruptions. The amount of testing is significantly less than with continuous testing, which 

affects operational costs. To overcome these shortcomings, several organizations in the 

United States and Europe have developed devices that can continuously measure pavement 

deflections, such as the FHWA-funded rolling wheel deflectometer. However, FWDs presently 

represent the state of the practice as far as the structural capacity evaluation of pavements is 

concerned. Hence, further discussions in this report regarding deflections and structural 

adequacy are limited to FWDs. 

As equipment technology has evolved, so have methods for analyzing deflection data, which 

allow for multiple complex algorithms to be used in real-time analysis of the deflection data.

Many of the analysis techniques developed in the past, such as Boussinesq’s one-layer and 

Burmeister’s two-layer solutions, are still used today.

(2,3) More complex and rational techniques 

have also been developed, such as finite-element solutions and dynamic analysis techniques, but 

because of their complexity, those procedures are most often used in research. By far, the method 

most often used for the analysis of deflection data is layered elastic theory, which generally 

works well but may have problems under certain conditions (e.g., composite pavements, thin 

layers, etc.). To make matters more complicated, most analysis techniques that use layered 

elastic solutions are heavily dependent on the user or the inputs provided. Results vary 

depending on the specific software used even if the inputs are all the same, and the results 

produced by the software require a significant amount of familiarity with the analysis technique 

used as well as engineering judgment.

Another factor making assessment of structural adequacy challenging is that pavement material 

properties change, sometimes drastically, with changes in surface and subsurface moisture and 

temperature conditions. Figure 2 shows changes in deflection for seven sensors at various radial 

distances over time at an LTPP Seasonal Monitoring Program (SMP) test section. The impact of 

moisture and temperature changes over time is clearly shown in this figure. Do ride quality or 

other performance indicators (e.g., distress and friction) change in a similar fashion?
5

0

100

200

300

400

500

600

700

800

Jun-95 Jan-96 Sep-96 May-97 Jan-98 Sep-98

Deflection (microns)

FWD Survey Date (Month-Year)

Deflection Plot (01_0102)

D1

D2

D3

D4

D5

D6

D7

Figure 2. Graph. Changes in deflection over time at LTPP SMP test section.

In summary, ride quality and structural adequacy are key performance indicators, but the 

relationship between the two is a topic of frequent and continuing discussion in the pavement 

community. It can be argued that ride quality is not an indicator of structural strength because

a pavement with low structural capacity can exist with adequate ride quality. However, if the 

pavement is not properly designed (for anticipated traffic, ambient conditions, etc.), distresses 

will likely develop quickly, which could result in an increase in roughness. It is possible that this 

increase in roughness could be related to structural capacity.

Alternatively, there is the case of a distressed pavement that has a high IRI value 

(e.g., 150 inches/mi). If a thin overly (e.g., 1.5 inches thick) is applied properly on that 

pavement, it will likely reduce the IRI (e.g., to 75 inches/mi). The overlay will certainly 

increase the structural capacity of the pavement, but only by a little. Moreover, the overlay 

could fail rapidly. Hence, it can be argued that there is no relationship between ride quality 

and structural adequacy, but there may be a relationship between deterioration of ride quality 

and structural adequacy of the pavement.

Table 1 shows the pavement structure of the LTPP Specific Pavement Study (SPS)-1 (new hot 

mix asphalt (HMA) pavement) test sections, and figure 3 and figure 4 show the roughness 

progression at some of the LTPP SPS-1 projects. All sections within a project appear to have 

close initial IRI values, but do sections that show a high rate of IRI deterioration have low 

structural capacity?
6

Table 1. Structural properties of SPS-1 test sections.

Test 

Section 

Number

HMA 

Thickness 

(inches)

Layer 2 Layer 3

Material

Thickness

(inches) Material

Thickness

(inches)

1 7 DGAB 8 — —

2 4 DGAB 12 — —

3 4 ATB 8 — —

4 7 ATB 12 — —

5 4 ATB 4 DGAB 4

6 7 ATB 8 DGAB 4

7 4 PATB 4 DGAB 4

8 7 PATB 4 DGAB 8

9 7 PATB 4 DGAB 12

10 7 ATB 4 PATB 4

11 4 ATB 8 PATB 4

12 4 ATB 12 PATB 4

13 4 DGAB 8 — —

14 7 DGAB 12 — —

15 7 ATB 8 — —

16 4 ATB 12 — —

17 7 ATB 4 DGAB 4

18 4 ATB 8 DGAB 4

19 7 PATB 4 DGAB 4

20 4 PATB 4 DGAB 8

21 4 PATB 4 DGAB 12

22 4 ATB 4 PATB 4

23 7 ATB 8 PATB 4

24 7 ATB 12 PATB 4

— Indicates that there is no layer 3.

DGAB = Dense-graded aggregate base.

ATB = Asphalt-treated base.

PATB = Permeable asphalt-treated base.
7

Figure 3. Graph. Changes in IRI over time for LTPP SPS-1 test sections in Iowa.

Figure 4. Graph. Changes in IRI over time for LTPP SPS-1 test sections in Arkansas.

Moreover, by looking at plots of performance over time, such as those shown in figure 5 through 

figure 11 for the LTPP SPS-1 test sections in Virginia and similar plots for both IRI and FWD 

deflections, it is possible to determine if there is a general relationship between changes in IRI 

and structural adequacy. The following figures are shown according to base material type—

dense-graded aggregate base (DGAB), asphalt-treated base (ATB), and permeable asphalttreated base (PATB).
8

Figure 5. Graph. Changes in IRI over time for LTPP SPS-1 test sections in Virginia

(DGAB).

Figure 6. Graph. Changes in IRI over time for LTPP SPS-1 test sections in Virginia (ATB).

Figure 7. Graph. Changes in IRI over time for LTPP SPS-1 test sections in Virginia

(PATB).

Figure 8. Graph. Changes in IRI over time for LTPP SPS-1 test sections in Virginia

(ATB/PATB).
9

In the case of portland cement concrete (PCC) pavements, the IRI value can increase because of 

faulting. If FWD testing is performed at the center of the slab, the results could show that the 

pavement has sufficient structural capacity. Moreover, PCC pavements can be permanently 

curled, which can cause high IRI. In PCC pavements, center-slab FWD testing will also likely 

show that the pavement has suffcient structural capacity. PCC slabs can also have a convex 

shape, where the center of the slab is at a higher elevation compared to the joints. Because of the 

gap in the center of the slab, FWD testing may indicate that the pavement has a low structural

capacity, but the IRI may be acceptable.

References to ride quality have focused almost entirely on IRI, but IRI is not intended to capture 

pavement profile frequencies known to induce dynamic loading from heavy trucks, which is 

more likely to be associated with pavement deterioration. It is thought that dynamic truck 

loadings cause accelerated pavement damage. The dynamic loads applied by heavy vehicles on 

pavements fall into two distinct frequency ranges: 1.5 to 4 Hz (sprung mass bounce, pitch, and 

roll vibration modes) and 8 to 15 Hz (unsprung mass bounce and roll). The sprung mass bounce 

motion is commonly referred to as “body bounce,” and the unsprung mass bounce motion is 

commonly referred to as “wheel hop.”

At 65 mi/h, body bounce at 2 and 2.5 Hz corresponds to spatial frequencies of 48 and 38 ft/cycle, 

respectively. Similarly, at 65 mi/h, axle hop at 10 and 12 Hz corresponds to spatial frequencies 

of 9.6 and 8 ft/cycle, respectively. On new pavements that do not have distress, dynamic loads 

will be mainly influenced by body bounce. As a pavement deteriorates, dynamic loads due to 

axle hop will occur. There is a relationship between frequency, spatial wavelength, and speed.

The magnitude of the dynamic loads applied on the pavement does not necessarily depend on the 

IRI level of the pavement. Instead, the wavelengths present on the roadway have a significant 

influence on the dynamic loads that are applied. If the dominant wavelength in the pavement is 

close to the spatial frequency of the truck, resonance motion will occur in the truck, resulting in 

high dynamic loads being imparted on the pavement.

As previously noted, a truck traveling at 65 mi/h that has a body bounce frequency of 2.5 Hz will 

have a spatial frequency of 38 ft/cycle. If there is significant spectral content in the roadway near 

this wavelength, resonance motion can occur in the truck, which can result in high dynamic loads 

being applied to the pavement.

Figure 9 shows a 25-ft base length continuous IRI plot of a section of roadway. Any point on 

this plot shows the IRI of a 25-ft-long section that is centered at that location. For example, the 

IRI shown at 50 ft is the average IRI from 37.5 to 62.5 ft. The overall IRI of this roadway is 

73 inches/mi. 
10

Figure 9. Graph. Continuous IRI plot of road profile.

Figure 10 shows the power spectral density (PSD) plot of the profile data. A PSD function is a 

statistical representation of the importance of the various wavelengths contained in the profile.

The PSD plot shows that there is significant spectral content close to a wavelength of about 30 ft.

This value is close to the spatial frequency of the body bounce motion of the truck and can result 

in high dynamic loads being applied on the pavement.

Figure 10. Graph. PSD plot of road profile.

Figure 11 shows the dynamic loads that were predicted for the leading trailer axle by a truck 

simulation model. The dynamic loads predicted for a truck with air suspension and for a truck 

with leaf suspension are shown. This pavement section is a fairly smooth pavement with an 

overall IRI of 75 inches/mi. However, it had wavelengths that were close to the natural 

frequency of the body bounce motion of the truck. This caused high dynamic loads to be applied 

on the pavement. There could be other pavement sections that have an IRI of 75 inches/mi that 
11

do not have significant wavelength content close to the natural frequency of the body bounce 

motion of this section. On such a section, the magnitude of the dynamic loads applied on the 

pavement is expected to be lower. Therefore, the IRI level by itself is not a predictor of dynamic 

loads imparted on the pavement. 

Figure 11. Graph. Dynamic loads applied to road profile.

As previously noted, if a new pavement has dominant wavelengths that will cause resonance 

body bounce motion that can cause high dynamic loads, pavement distress may result. Such

distresses will influence the axle hop motion of the truck, resulting in accelerated distress due 

to both body bounce and axle hop.

IRI is influenced by wavelengths ranging from 3 to about 100 ft. So, IRI will include the 

wavelengths that influence dynamic truck loads. The IRI has maximum sensitivity to sinusoids 

with wavelengths of 7.9 and 50.5 ft. The wavelength of 7.9 ft is close to spatial wavelengths that 

have a significant impact on axle hop. The wavelength of 50.5 ft is somewhat close to spatial 

wavelengths that influence body bounce. 

From the information presented thus far, it could be argued that the relationship between ride 

quality and structural adequacy is tenuous at best. However, the discussion has revolved almost 

entirely around IRI as the surrogate to ride quality, which is not intended to specifically capture 

pavement profile features known to induce dynamic loading from heavy trucks, which is more 

likely associated with pavement deterioration. In addition, no clear specific definition of a 

structural adequacy measure has been provided. Accordingly, a more rational look at ride 

quality and structural adequacy is needed.
12

The investigation of the relationship in question must begin with a clear understanding of 

pavement performance and the factors that affect it. More specifically, the separate and 

combined effects of the following four factors define the performance of pavements: 

• Pavement structure:

o Pavement type—HMA, new PCC, HMA overlay over existing HMA, HMA 

overlay over existing PCC, PCC overlay over existing PCC, PCC overlay over 

existing HMA, and others (paver blocks, white topping overlay, etc.).

o Pavement layers—Thicknesses, material types, material properties, drainage, 

shoulders, joints and steel reinforcement in PCC pavements, quality of 

construction and related issues, ambient conditions at time of construction, 

and others.

• Subgrade soil—Material types, material properties, stabilization, embankment, cut/fill, 

depth to bedrock, drainage, and others.

• Traffic—Traffic volumes (design versus actual), traffic loads/load spectra (design 

versus actual), traffic growth (design versus actual), seasonal trends, load restrictions,

and others.

• Environmental conditions—Air and surface temperatures, precipitation, wind, solar 

radiation, subsurface moisture, subsurface temperature, construction ambient conditions, 

unusual or catastrophic events, freeze-thaw cycles, freeze days, and others.

Without question, the best source of data to explore the ride quality-structural adequacy 

relationship is the LTPP program, which was established to provide the data necessary to explain 

how pavements perform and why they perform as they do. The LTPP database contains the most 

complete and comprehensive set of pavement performance data and associated factors, including 

the following: 

• Pavement performance information, including roughness/elevation and deflection data. 

• Pavement structure and subgrade soil information obtained through one or more of the 

following methods: test pits and coring/boring, ground penetrating radar, dynamic cone 

penetrometer, drainage surveys (video), field materials sampling and testing activities, 

laboratory materials testing, specialized testing, and other destructive and nondestructive 

testing (NDT) techniques.

• Traffic information obtained through one or more of the following methods: automatic 

vehicle classifier counts, weigh-in-motion (WIM) measurements, average daily traffic, 

and estimated equivalent single-axle load (ESAL) estimates.

• Environmental information obtained from one or more weather stations (e.g., National 

Climatic Data Center, Canadian Climatic Center, and LTPP-installed stations) or through 

the use of surface or subsurface instrumentation at the SMP test sections.
13

In particular, the use of data associated with the SPS-1 (new asphalt concrete (AC) pavements), 

SPS-2 (new PCC pavements), SPS-5 (rehabilitation of existing AC pavements), SPS-6 

(rehabilitation of existing PCC pavements), and SPS-8 (study of environmental factors in the 

absence of heavy loads) project test sections are considered relevant. Unlike most General 

Pavement Study (GPS) test sections, the SPS data capture pavement performance and the factors 

that affect it over the entire performance life cycle.

1.3 PROJECT GOAL AND OBJECTIVE

The objective of this project was to identify and verify the relationship, if any, between ride 

quality and structural support or between ride deterioration and structural adequacy using LTPP 

and other pavement performance data sources. This was done in an effort to improve the 

evaluation and use of pavement condition data in pavement rehabilitation and design decisions. 

More specifically, this project was intended to develop and document a mechanism to include 

both ride quality and structural adequacy values within the context of current network-level PMS 

practices for highway agency implementation. The results of the project are intended for use by 

pavement management engineers to ensure smooth pavements that are also structurally adequate. 

To accomplish the project objective, the following three tasks were initially performed under 

phase I, “Identification and Demonstration of the Ride-Structure Relationship,” which was

intended to establish the foundation for actual development of the ride quality-structural 

adequacy relationship under phase II, “Guidance for Implementing the Ride-Structure 

Relationship into PMS”:

• Literature search—Available information relating ride quality and structural adequacy 

for pavement rehabilitation and design decisions was gathered, reviewed, and 

synthesized. Pertinent information was gathered through Web-based searches of State 

highway agencies, university pavement research centers, the Transportation Research 

Board (TRB), the American Society of Civil Engineers (ASCE), industry, and other 

national and international (e.g., World Road Association (PIARC) and AustRoads) 

organizations. The information gathered under this task was synthesized and presented by 

relevant topics to serve as the foundation for the work to be carried out under tasks 2 

and 3. As part of this effort, consideration was given to how the ride quality-structural 

adequacy relationship and decisionmaking processes contribute to improved resource 

allocation through the highway agency’s network-level PMS.

• Data review and assessment—This effort focused on the review and assessment of 

relevant data from the LTPP SPS-1, SPS-2, and SPS-5 project test sections because of data 

completeness and because the sections capture pavement performance and the factors that 

affect it over entire performance life cycles. General ride quality-structural adequacy 

trend analyses were performed on those data to see if promising relationships could be 

identified. In the pursuit of relationships, both changes in ride quality or structural 

capacity over time and changes in ride quality or structural capacity within the test 

sections were considered.
14

• Phase I report—Under this task, a draft phase I report was prepared to document the 

findings from the research performed under tasks 1 and 2. The report was to include the 

proposed work plan for the phase II effort. However, because a promising ride qualitystructural adequacy relationship could not be identified, the project team recommended 

not proceeding with the phase II effort.

This report documents the phase I results and findings, as detailed under the task 3 summary.

1.4 REPORT ORGANIZATION

The information presented in this report is organized into the following sections:

• Chapter 1. Introduction—Includes project background information, the project goal 

and objective, and the report organization.

• Chapter 2. Literature Search—Provides the results of the literature search, including 

the sources of information and a summary of information contained in the more relevant 

references.

• Chapter 3. Data Review and Assessment—Details the results and findings from the 

review and assessment of relevant data from the LTPP SPS and GPS test sections, 

including the selection of test sections and the pursuit of promising ride quality-structural 

adequacy relationships. The primary criteria used in the selection of test sections and 

subsequent analyses were changes in ride quality or structural capacity over time and 

changes in ride quality or structural capacity within the test sections.

• Chapter 4. Other Data Analysis Considerations—Presents additional data analyses 

performed as part of the study to validate the findings and conclusions presented in 

chapter 3.

• Chapter 5. Summary and Conclusions—Highlights the major observations, findings,

and conclusions from the phase I effort.

• Four appendices contain plots generated during the data review and assessment effort as 

well as the data analysis validations, which are not included in the main text of the report.

• The references list contains relevant references identified from the literature search or 

used in the preparation of this report.

• The bibliography contains references identified from the literature search that were not 

considered of sufficient relevance to include in the project.
15

CHAPTER 2. LITERATURE SEARCH

The objective of the literature search was to collect, review, and synthesize available information 

relating ride quality and structural adequacy for pavement rehabilitation and design decisions.

Pertinent information was gathered through Web-based searches of State highway agencies, 

university pavement research centers, TRB, ASCE, industry, and other national and international 

(e.g., PIARC and AustRoads) organizations. A particularly relevant source of information was 

the references database prepared under the LTPP program and posted on the program’s Web site 

(http://www.ltpp.org). In addition to looking at previous attempts to establish such a relationship, 

the following topics were also considered during the literature search:

• Relationships between ride quality and structural adequacy.

• Factors influencing pavement performance.

• Structural- and functional-based approaches for pavement evaluations.

• Relationship between ride and distress.

The key observations, findings, and conclusions from the literature search are detailed in 

this chapter.

2.1 OVERVIEW

The purpose of the literature review was to identify, review, and synthesize information for 

eventual use in the planning and execution of an effort to look for the potential relationship 

between ride quality and structural adequacy of pavement structures. A total of 62 references 

were identified from various sources and reviewed. Of those, 16 references were considered of 

particular value to the project. They have been synthesized and included in the references list of 

this report. The remaining 47 references were not considered sufficiently relevant and have been 

included in the bibliography section.

Each of the 16 relevant references was reviewed by identifying the reference type, source, 

objectives and goals, findings and observations, relevance to the project, and other pertinent 

information. Table 2 shows the distribution of these references by type and source. As shown, 

the majority (62 percent) of references were from studies related to the LTPP program. Although 

the LTPP program has been categorized separately, it could be considered together with the

transportation departments since all LTPP test sections are on State highways. Table 2 also 

shows that the bulk of references were articles (69 percent). Five reports (31 percent) relevant 

to the current study were reviewed in addition to the articles.
16

Table 2. Distribution of references by type and source.

Type

State 

Transportation 

Department/ 

University

LTPP 

Program Total

Report/

guideline 3 2

5 

(31 percent)

Article/

presentation 3 8

11 

(69 percent)

Total

6 

(38 percent)

10 

(62 percent)

16 

(100 percent)

Table 3 shows the distribution of elements in the references that are relevant to this study on 

relating ride quality to structural adequacy for rehabilitation and design decisions. The values 

shown in this table indicate the number of references of the total (16) that contained a topic 

related to the current study. As expected, many of the references covered more than one 

topic. The majority of these references relate to factors influencing pavement performance 

(43 percent). Understanding the factors influencing pavement performance was considered an 

important first step in the effort to establish a relationship between ride quality and structural 

adequacy. Only two promising studies were identified in the literature search that directly relate 

to the research topic at hand. One article on the topic of structural and functional evaluation 

approaches was reviewed, and six references that looked at relationships between ride and 

distress were reviewed. Figure 12 shows the distribution of the topics considered essential for 

evaluating a relationship between ride and structural adequacy.

Table 3. Distribution of references by type and topic.

Type

Relationship 

Between 

Ride and 

Structural 

Adequacy

Factors 

Influencing 

Pavement 

Performance

Structural- and 

FunctionalBased 

Approaches for 

Pavement 

Evaluations

Relationship 

Between 

Ride and 

Distress Total

Report/

guideline 2 1 0 2

5 

(31 percent)

Article/

presentation 0 6 1 4

11 

(69 percent)

Total

2 

(13 percent)

7 

(43 percent)

1 

(6 percent)

6 

(38 percent)

16 

(100 percent)
17

Relationships Betw een 

Ride and Structural 

Adequacy

13%

Factors Influencing 

Pavement Performance

43%

Structural and 

Functional Based 

Approaches for 

Pavement Evaluations

6%

Relationship Betw een 

Ride and Distress

38%

Figure 12. Graph. Distribution of references.

2.2 SPECIFIC FINDINGS

Two studies relate directly to this study—relating ride quality to structural adequacy for 

rehabilitation and design considerations. The first was an FHWA study conducted by 

Von Quintus et al. on LTPP data that looked at the dissipated work obtained from deflection 

time history data and pavement condition data (distresses, IRI, etc.) to see if a relationship 

exists between the dissipated work and pavement performance.(4) In this study, dissipated 

work was defined as the area under the loaded and unloaded portion of the stress-strain curve 

(hysteresis loop) and was used to define the viscoelastic and inelastic properties of pavement 

material. Several LTPP sites with varying IRI values, distress magnitudes, and traffic levels 

were analyzed to determine if a relationship existed between the dissipated work and pavement 

performance. The dissipated work and hysteresis loop were found to vary extensively by 

structure and pavement type. Based on the sections evaluated in the study, lower amounts of 

dissipated work were observed on PCC-surfaced pavements than on AC-surfaced pavements.

The findings from the study indicate that the greater the dissipated work, the greater the amount 

of pavement distress observed in terms of magnitude, severity, and type. The conclusions from 

this study indicate that dissipated work can be used to determine the performance behavior of 

pavement structures. 

The second study was performed by Zhang et al. and looked at the structural adequacy of 

pavements in implementing pavement management decisions.(5) The study evaluated various 

methods to look at the structural condition of the roadway prior to applying thin overlays to 

correct ride. The study indicated that the Texas Department of Transportation (TxDOT)

pavement management information system (PMIS) database shows a yearly decrease of 
18

0.3 points in ride score for the highway network in Texas as a result of the increase in 

pavement roughness attributed to permanent deformation. The permanent deformation was 

a result of inadequate pavement strength for existing traffic loads. The study was aimed at 

determining a structural index using the FWD data to evaluate the structural adequacy prior 

to planning maintenance. 

In the process of determining a suitable methodology for characterizing structural estimators, the 

TxDOT study looked at the deterioration process of the pavement. As the deterioration process 

represents the behavior of a non-linear system, it can be characterized by different rates of 

deterioration in different stages of the pavement service life. The true condition of a pavement at 

any moment can be described more accurately if the deterioration rate is known. Unfortunately, 

a mathematical solution to this problem is impossible because there are no models that can 

precisely represent the true deterioration process of a pavement. Even complicated mathematical 

models such as sigmoid forms cannot be calibrated accurately enough to represent a true 

deterioration process. 

The TxDOT study points out that if the general mathematical formula describing the transition of 

a system from one state to another is not available, one can use the finite difference between the 

states. The study presents a unique way of characterizing the condition deterioration (ride and 

distress). It also proposes a method to characterize deterioration in terms of differences between 

condition measures over a unit time period, normalized to the initial condition, to give a more 

accurate picture of pavement deterioration. Furthermore, the study points out the importance of 

considering the traffic applied when determining the pavement deterioration. An equal yearly 

drop in the condition score of a pavement subjected to different ESALs represents different 

structural conditions of the pavement. The normalized drop in condition divided by the ESALs 

for the year, called the “unit ESAL deterioration” (UED), provides a more accurate condition of 

the pavement. Structural failure occurs when the roughness starts progressing at a high rate,

and the UED concept helps describe the deterioration rate. In the study’s analysis the UED is 

calculated as the normalized yearly drop in the PMIS scores (ride, condition, and distress scores) 

caused by a single ESAL for a consecutive two-year period, as shown in figure 13 to figure 15.

UED (Distress Score) = (dDS/(DS×ESALy))*106

Figure 13. Equation. UED distress score.

UED (Condition Score) = (dCS/(CS × ESALy))*106

Figure 14. Equation. UED condition score.

UED (Ride Score) = (dRS/(RS × ESALy))*106

Figure 15. Equation. UED ride score.

Where:

DS = Distress score in initial year.

RS = Ride score in initial year.

CS = Condition score in initial year.

dDS = Yearly drop in distress score.

dCS = Yearly drop in condition score.
19

dRS = Yearly drop in ride score.

ESALy = Estimated amount of ESALs in a year.

The results from the TxDOT study indicate that different factors, such as dRS, dCS/CS, and 

UED(RS), show different levels of sensitivity to the structural estimators, but the outputs from 

all considered methods indicate some level of sensitivity to the UED values. As deterioration 

increases, the structural estimators tend to produce smaller values. The factor defined as 

UED(RS) showed the best trend for all methods (structural estimators considered). The intent 

of the trend analyses was to visualize whether there was a trend between the deterioration 

variables (e.g., UED of the PMIS score values) and the pavement structural estimators 

(e.g., structural number (SN)). However, it was not the intention of the study to quantify the 

correlation between them through regression analysis or other means. An example of the trend 

found between SN and UED(RS) is shown in figure 16. The study also puts forth the concept of 

a structural condition index, a ratio of the effective SN (SNeff) to the required SN (SNreqd), as a 

measure of structural adequacy.

Figure 16. Graph. Sensitivity of SN to UED of ride score.

In order to investigate a potential relationship between ride quality and structural adequacy, it is 

important to understand the factors that influence pavement performance. Seven of the reviewed 

references identify factors influencing pavement performance. The findings from these studies 

are summarized in table 4. 
20

Table 4. Summary of factors influencing pavement performance.

Pavement 

Surface Type

Performance 

Indicator

Most Influencing 

Factors

Least Influencing 

Factors

Factors Not 

Influencing

Reference 

No.

Hot mix AC 

(HMAC) Overlay roughness

Overlay thickness, 

climatic zones Subgrade type — 6

HMAC Overlay roughness — —

IRI prior to overlay, 

overlay thickness, and 

milling prior to overlay 7

Jointed plain 

concrete (JPC)

Cracking and 

roughness

Base type, pavement 

drainage, and slab 

thickness — — 8

HMAC Roughness

Base type, drainage, and 

climatic conditions

Base thickness and

subgrade type — 9

HMAC

Roughness, rutting, 

fatigue cracking, and 

transverse cracking — — — 10

HMAC

Roughness and 

rutting Construction — — 11

JPC

Roughness and 

faulting Dowels — — 12

Jointed 

reinforced 

concrete Roughness

Moisture in subgrade, 

joint spacing, thicker 

slabs, and concrete 

modulus — — 12

Continuously 

reinforced 

concrete Roughness — — — 12

— Indicates that the reference did not apply.
21

A study by Vepa et al. looked at structural- and functional-based approaches for pavement 

evaluations.(13) In this study, approaches including the 1993 AASHTO procedure based on NDT 

data, a pavement condition rating procedure, and a survivor curve method were used to evaluate 

the remaining life of flexible and rigid pavements. The conclusions from the study indicate that 

structural failure-based remaining life calculations result in conservative estimates compared to 

functional failure-based methodologies.

Finally, in an effort to identify an indirect relationship between ride and structural adequacy, 

studies relating ride and distress were reviewed. Six references were identified. The results from 

four of these studies are summarized in table 5. The other two references included models to 

relate IRI and distress and are discussed in detail in the following paragraphs.

Table 5. Relationship between pavement performance measures.

Pavement Type

Performance 

Measures

Statistically 

Significant 

Relationship

Strength of 

Relationship

Reference 

No.

HMAC and HMAC over PCC IRI and distress Yes Weak 14

HMAC and HMAC over PCC IRI and rutting Yes Weak 14

HMAC 

IRI and 

Pavement 

Condition Index Yes Weak 15

HMAC

IRI and initial 

IRI, fatigue, and 

rutting Yes

Strong, but mainly 

influenced by 

initial IRI 16

HMAC IRI and distress Yes Strong 17

In the Mechanistic-Empirical Pavement Design Guide (MEPDG), the functional adequacy for 

both flexible and rigid pavements is quantified by pavement smoothness.

(18) The parameter used 

to define pavement smoothness in the MEPDG is IRI. 

In the MEPDG, models are available to empirically predict the IRI at any point in the life 

of the pavement by adding the increase in IRI of the pavement due to pavement distress 

and a site factor to a known initial IRI of the pavement. The site factor accounts for the 

increase in roughness due to the shrink/swell and frost heave characteristics of the subgrade. 

Distress prediction models are used to predict the distresses that are used as an input to the 

roughness models.

The MEPDG presents models for predicting the IRI for the following pavement types:

• New HMA pavements and HMA overlays of flexible pavements (the model form is the 

same for both, but coefficients in the model are different for the two pavement types).

• HMA overlays of rigid pavements.

• Jointed plain concrete pavements (JPCP).

• Continuously reinforced concrete pavements (CRCP).
22

The following is a brief description of the distress types and site factors included in the 

roughness prediction models for each of the pavement types:

• New HMA pavements and HMA overlays of flexible pavements—The distress types 

included in the roughness prediction model are (1) area of fatigue cracking expressed as a 

percent of total lane area (combined alligator, longitudinal, and reflection cracking in the 

wheel path, with length of cracks multiplied by 1 ft to convert length to an area basis), 

(2) length of transverse cracking (includes the reflection of transverse cracks in the 

existing HMA pavement), and (3) average rut depth. The site factor is a function of the 

pavement age, plasticity index of the subgrade, average annual freezing index, and 

average annual precipitation. The model form for roughness prediction is the same for 

new HMA pavements and HMA overlays of flexible pavements, but the coefficients in 

the model are different for the two pavement types.

• HMA overlays of rigid pavements—The distress types affecting IRI as well as the 

parameters considered in the site factor are the same as those for new HMA pavements 

and HMA overlays of flexible pavements. The coefficients in the model for each distress 

type as well as the site factor are different from those used in the HMA pavement models.

• JPCP—The distress types included in the roughness prediction model are (1) percentage 

of slabs with transverse cracks (all severities), (2) percentage of joints with spalling 

(medium and high severities), and (3) total cumulative faulting per mile (in inches). The 

site factor included in the model is a function of the pavement age, freezing index, and 

percent of subgrade material passing the No. 200 sieve.

• CRCP—The only distress type included in the model is the number of medium and high 

severity punchouts. As in the case of the JPCP model, the site factor included in the 

model is a function of the pavement age, freezing index, and percentage of subgrade 

material passing the No. 200 sieve.

As previously described, in all of the models presented in the MEPDG for predicting roughness, 

age is included in the site factor, which accounts for the increase in roughness that occurs over 

time due to the frost heave and shrink/swell characteristics of the subgrade.

The three distress types considered in the roughness prediction model for new HMA pavements 

and flexible overlay of HMA pavements are fatigue cracking, transverse cracking, and rut depth. 

The amount of fatigue cracking in the pavement should have a strong influence on the structural 

strength of the pavement as determined from FWD testing conducted along the wheel path. 

However, transverse cracks are unlikely to impact the structural strength of the pavement as 

determined from the FWD testing if the FWD test is carried out away from a crack location. Rut 

depths may or may not affect the structural strength of the pavement as determined from FWD 

testing. If the rutting is caused by a weak base or subbase layer, the structural strength of the 

pavement will be affected. However, rutting caused by the distortion of the HMA layer may not 

result in a loss of structural capacity of the pavement. Rutting caused by weak subgrade, base, or 

subbase layers can result in early fatigue cracking of the pavement.
23

The three distress types considered in the roughness prediction model for JPCP pavements are 

transverse cracks, joint spalling, and faulting. FWD tests to evaluate the structural capacity of 

JPCP pavements are conducted at the center of the slab. Transverse cracks present on the slab 

will affect the structural capacity of a JPCP slab as determined from FWD testing. However, 

joint spalling and faulting are not related to the structural strength of the concrete pavement. 

Spalling may be caused by concrete durability issues as well as by low load transfer at joints. 

Faulting is also related to low load transfer at joints and can be exacerbated by the presence of 

erodible bases. 

The only distress type influencing the roughness of CRCP pavements is punchouts, which are

load-related distresses.

In the MEPDG roughness models, some of the distresses that result in an increase in IRI will 

result in a decrease in the structural strength of the pavement. However, some distresses that 

contribute to the increase in roughness may not necessarily cause a decrease in the structural 

strength of the pavement. The MEPDG models account for the increase in roughness due to 

shrink/swell and frost heave characteristics of the subgrade. Changes in the pavement profile 

caused by shrink/swell and frost heave of the subgrade may not directly impact the structural 

strength of a pavement. However, these actions could initiate pavement distress, which would 

have an impact on roughness.

Lastly, the World Bank has developed software called Highway Development and Management 

(HDM) System to make comparative cost estimates and economic evaluation of different policy 

options.(19) The HDM-III model was developed using data collected from a multiyear empirical 

study carried out in Brazil. The statistical relationships in this model were validated and 

extended using data from several other deterioration studies carried out in various locations such 

as Kenya, the Caribbean, India, and Texas. The revised and improved models are included in the 

latest version, HDM-4. HDM-4 includes a model for predicting roughness of roadways. The 

roughness prediction model predicts the incremental change in roughness during an analysis year 

based on contributions to roughness from five sources: (1) change in roughness due to structural 

deterioration, (2) cracking, (3) rutting, (4) potholes, and (5) environmental effects. Models are 

provided to predict the incremental change in roughness due to each of the factors. The HDM-4 

model has been widely used in many countries with calibration to suit local conditions.

2.3 SUMMARY

Although a few studies were identified during the literature search that indicated a potential 

relationship between structural response and pavement performance, none of these studies 

established a direct relationship between ride quality and structural adequacy. As discussed in 

this chapter, several studies have been successful at relating ride quality to pavement condition 

or distress. In fact, the roughness models in the MEPDG use distress as an input to predict 

roughness. Similarly, structural response has been used to predict certain distresses. While it is 

evident that a multitude of factors influence pavement performance in different ways (i.e., ride 

condition and structural response), a strong correlation between the three different performance 

measures has yet to be established such that measurement of any one performance indicator is 

adequate to identify both the structural and functional condition of the pavement.

25

CHAPTER 3. DATA AVAILABILITY AND DATA ASSESSMENT

3.1 INTRODUCTION

Roughness indices computed from the profile data collected at LTPP sections are stored in the 

LTPP database. The roughness indices available in the LTPP database are IRI, root-mean-square 

vertical acceleration (RMSVA) for base lengths of 1, 2, 4, 8, 16, 32, 64, and 128 ft, slope 

variance, and Mays output. The IRI of the left and right wheel paths and the mean IRI (average 

of the left and right wheel paths) are available in the LTPP database. Although RMSVA, slope 

variance, and Mays output have been used in the past as measures of roughness, these indices are 

not currently used.

An assessment of the availability of IRI values and FWD data for SPS-1, SPS-2, and SPS-5 was 

performed to obtain a general idea about the length of time over which data have been collected 

at these projects.

Thereafter, a few sections were selected from each experiment to investigate the change in ride 

quality and structural strength that had occurred over time and to investigate if there was a 

relationship between the change in ride quality and change in structural strength. The primary 

emphasis was placed on analyzing data from SPS-1 projects. Hence, most of the test sections 

analyzed were SPS-1 sections.

3.2 DATA AVAILABILITY

Table 6 shows the following information for the SPS-1 projects: State where the project is 

located, construction date of the project, last available profile date in the database, and number of 

times profile data were collected at the project. Similar information for SPS-2 and SPS-5 is 

shown in table 7 and table 8, respectively. The information shown in table 6 through table 8 was 

obtained from work performed for a previous research project, and more recent roughness data 

are expected to be available in the most recent LTPP data release. There is a possibility that 

monitoring of one or more sections in a SPS project may have stopped at an earlier date than that 

listed as the last available profile date in these tables because of rehabilitation being performed 

on the test sections. It appears that most SPS-1 test sections that had a weak pavement structure 

(e.g., sections 2 and 13) failed within a very short time period after being opened to traffic.

Based on the information shown in table 6 through table 8, adequate ride quality data are 

available to evaluate changes in roughness at SPS-1, SPS-2, and SPS-5 sections. A review of the 

FWD data for these projects also indicated that adequate test data are available in the LTPP 

database to evaluate changes in structural strength over time.
26

Table 6. Roughness data availability for SPS-1 projects.

State

Construction

Date

Last Available

Profile Date

Number of 

Times Profiled

Alabama 3/1/1993 5/4/2005 9

Arizona 8/1/1993 3/27/2006 13

Arkansas 3/15/1994 5/22/2007 8

Delaware 5/1/1996 6/13/2006 14

Florida 2/1/1995 7/26/2006 8

Iowa 5/19/1992 9/22/2004 11

Kansas 11/1/1993 3/15/2004 9

Louisiana 7/1/1997 8/7/2006 3

Michigan 11/1/1995 6/2/2006 10

Nebraska 1/1/1995 4/24/2002 9

Nevada 9/1/1995 8/27/2006 12

New Mexico 11/1/1995 4/24/2006 7

Ohio 9/1/1995 8/9/2006 12

Oklahoma 6/1/1997 4/11/2007 8

Texas 6/1/1997 3/19/2007 11

Virginia 11/28/1995 12/2/2006 18

Table 7. Roughness data availability for SPS-2 projects.

State

Construction

Date

Last Available

Profile Date

Number of 

Times Profiled

Arizona 10/1/1993 08/11/2006 12

Arkansas 12/1/1995 4/2/2005 6

California 2000 11/7/2004 7

Colorado 11/1/1993 06/02/2006 10

Delaware 5/1/1996 06/11/2006 14

Iowa 12/1/1994 10/29/2004 9

Kansas 8/1/1992 06/05/2006 14

Michigan 11/1/1993 08/16/2006 17

Nevada 9/1/1995 12/3/2003 10

North Carolina 1/1/1994 06/14/2006 18

North Dakota 11/1/1994 5/18/2004 6

Ohio 8/14/1996 08/08/2006 12

Washington 11/1/1995 06/07/2006 11

Wisconsin 1/1/1997 9/12/2005 9
27

Table 8. Roughness data availability for SPS-5 projects.

State/Province

Construction

Date

Last Available

Profile Date

Number of 

Times Profiled

Alabama 12/19/1991 8/3/2006 10

Alberta 10/3/1990 6/12/2006 16

Arizona 4/20/1990 3/24/2006 13

California 4/25/1992 3/20/2007 12

Colorado 10/3/1991 4/24/2000 9

Florida 4/5/1995 7/27/2006 8

Georgia 6/7/1993 5/2/2005 8

Maine 6/20/1995 7/29/2004 8

Manitoba 9/1/1989 6/8/2006 15

Maryland 3/31/1992 6/15/2006 15

Minnesota 9/15/1990 6/6/2005 13

Mississippi 9/24/1990 4/13/1999 5

Montana 9/11/1991 6/7/2005 14

New Jersey 8/18/1992 6/10/2006 18

New Mexico 9/11/1996 4/24/2006 7

Oklahoma 7/8/1997 4/11/2007 8

Texas 9/1/1991 4/10/2007 11

3.3 RIDE QUALITY PARAMETER SELECTED FOR STUDY

In selecting an appropriate ride quality parameter to be used in this study, parameters including 

PSD plots, smoothness indices developed for selecting locations for WIM scales, and IRI 

were investigated. 

A road profile encompasses a spectrum of sinusoidal wavelengths. A PSD function is a statistical 

representation of the importance of the various wavelengths contained in the profile.

(20) A 

Fourier transform is used to generate a PSD plot from profile data. A PSD plot can assist in data 

interpretation by detecting cases where a significant portion of roughness is concentrated in a 

specific waveband and by detecting the type of content (i.e., short or long wavelengths) that 

dominates the profile.

(21) Profile data collected on the same road section at two different times 

can be used to investigate the changes that have occurred for a specific wavelength. However, a 

PSD plot will not give any information about the location within a pavement section where 

changes have occurred. Hence, an investigation to determine whether there is a correlation 

between locations within a test section where changes in structural strength have taken place 

and changes in the ride quality of that area cannot be performed using a PSD plot. If changes 

in a pavement profile have occurred only at a few localized locations, there is a possibility for a 

PSD plot to give misleading results, as the PSD plot is generated by fitting sine waves to the 

pavement profile.

Smoothness indices for finding a suitable location to place a WIM scale were developed under a 

research project sponsored by FHWA.

(22) These indices were developed to see if the smoothness 

of the pavement before the WIM site is suitable such that the axle hop and body bounce motions 
28

of a truck will not have an influence on the weights recorded. Two indices were developed, one 

based on short wavelengths that cause axle hop and the other based on long wavelengths that 

cause body bounce motion. A location was deemed suitable for establishing a WIM scale if the 

pavement before the WIM location met smoothness criteria based on the short and long 

wavelength smoothness indices. These WIM indices and IRI had a high correlation.

(22) Hence, 

using the WIM indices as the smoothness index in this study would not provide additional 

information that is not already provided by IRI.

IRI is widely used throughout the world as a ride quality indicator. It is a measurement of the 

roughness in the road that impacts the vehicle response and, thereby, the riding comfort of 

passengers in the vehicle.

(20) IRI correlates well with the vertical passenger acceleration, which is 

related to the ride quality experienced by a passenger in a vehicle.

(20) State highway agencies in 

the United States use IRI to track the ride quality of their pavement network. The profile data on 

LTPP sections are collected along the left and right wheel path using an inertial profiler, and 

these data are used to compute the IRI of the wheel paths. The computed IRI values and the 

profile data are stored in the LTPP database. Locations of high IRI values within a test section 

can be determined by using a continuous IRI plot (described later in this report). Because of the 

wide acceptance of IRI by State highway agencies and the ability of a continuous IRI plot to 

pinpoint locations within a section where high changes in IRI have occurred, IRI was selected as 

the ride quality parameter to be used in this study. 

3.4 STRUCTURAL STRENGTH PARAMETER SELECTED FOR STUDY

3.4.1 Flexible Pavements

The parameters considered to evaluate the structural strength of the pavements in this study 

include the SNeff of the pavement and the Structural Adequacy Index (SAI). The SN concept was 

developed during the AASHO Road Test and is widely used in the United States to design and 

evaluate the structural strength of flexible pavements. SNeff can be calculated using deflection 

data collected by an FWD. 

Several agencies use SAI as a means to assess the structural ability of the pavement to support 

the anticipated traffic loads. Typically, the maximum allowable deflection is determined as a 

function of the anticipated traffic and compared against the measured deflection to determine 

SAI. To use this method, the anticipated traffic must be known. Although the LTPP database 

contains observed traffic information, future traffic estimates are not available. Hence, SNeff was 

selected as the parameter to represent the structural strength of the pavement in this study.

The procedure to determine the SN of a flexible pavement from FWD measurements is described 

in the AASHTO Guide for the Design of Pavement Structures.

(23) In this procedure, the 

deflection data are first used to determine the subgrade modulus. Then, the effective pavement 

modulus (Ep), which is the effective modulus of all pavement layers above the subgrade, is 

determined. Ep is calculated as a function of the deflection measured directly beneath the load, 

the applied pressure, the load plate radius of the FWD, the total thickness of the pavement layers 

above the subgrade, and the subgrade modulus, as shown in figure 17.
29





























































































 



 +

−

+





















































+

=

p

R

p

R

E

a

D

M

E

a

D M

d pa

2

2

3

0

1

1 1

1

1 1.5

Figure 17. Equation. d0.

Where:

d0 = Deflection at center of load corrected to 68 °F in inches.

p = Pressure applied by the FWD load plate in psi.

a = FWD load plate radius in inches.

D = Total thickness of pavement layers above subgrade in inches.

MR = Subgrade resilient modulus in psi.

Ep = Effective pavement modulus of all layers above subgrade in psi.

SN is estimated from Ep using the equation in figure 18.

3

eff 0045D Ep SN = 0.

Figure 18. Equation. SNeff.

Where:

SNeff = Effective structural number.

Ep = Effective pavement modulus of all pavement layers in psi.

D = Total thickness of all pavement layers above subgrade in inches. 

SN can be determined for each FWD test location. Because the deflection measured at the center 

of the load plate depends on the temperature of the asphalt layer, this deflection is adjusted to a 

standard temperature of 68 °F before computing SN.

3.4.2 Rigid Pavements

Effective slab thickness was the parameter selected in this study to define the structural strength 

of rigid pavements. The FWD data were used to compute an effective concrete slab thickness 

using the computer program ILLI-BACK. This program computes an effective slab thickness 

using FWD data based on a user input elastic modulus for concrete. A concrete modulus value of 

4.5 million psi was used for this analysis. The program can use either an elastic solid or a denseliquid foundation below the PCC slab. A dense-liquid foundation was used in this study. The

program estimates a modulus of subgrade reaction (k-value) and the effective concrete slab 
30

thickness for each FWD sensor at a test location and outputs an average k-value and effective 

slab thickness. 

3.5 CONTINUOUS ROUGHNESS PLOT

IRI is reported in units of inches per mile. The IRI of a pavement segment can be computed over 

any desired length (e.g., 500 ft, 0.1 mi, 0.5 mi, 1 mi, etc.). The test sections used in the LTPP 

program for both GPS and SPS studies are 500 ft long except for two sections in the SPS-6 

experiment that are 1,000 ft long. For each LTPP section, the IRI of the left and right wheel path 

computed from the profile data collected at the section are stored in the LTPP database. This 

stored IRI value represents the average IRI of the 500-ft section. The average IRI does not 

provide any information about the variability of IRI within a test section.

Consider a pavement section that is 0.1 mi long with a right wheel path IRI of 96 inches/mi. 

As previously described, this IRI value represents the average IRI over the 0.1-mi length. This 

section can be divided into 10 52.8-ft segments. The IRI values of these 10 segments are shown 

in figure 19. The IRI of the 0.1-mile long segment is the average IRI of these 10 52.8-ft 

segments. Figure 19 shows that the IRI of segment 6 is significantly higher than the rest of the 

segments and that segment 9 has the lowest IRI of all segments. As shown in the figure, the IRI 

is not uniform within this 0.1-mi segment, with a significant localized roughness event occurring 

in segment 6.

Figure 19. Graph. IRI of 52.8-ft segments in 0.1-mi pavement section.

Instead of using a single value to show the IRI of a road over a fixed distance, a continuous 

roughness plot can be used to show how IRI varies with distance along a roadway. Figure 20

shows a continuous IRI plot based on a 25-ft base length for the same data that were used to 

compute the IRI of 52.8-ft segments shown in figure 19. The IRI shown at any location in 

figure 20 is the average IRI over a 25-ft length (i.e., base length of the continuous roughness 

plot) that is centered at that location. For example, the IRI shown in this plot at a distance of 

100 ft is the average IRI from 87.5 to 112.5 ft. Any base length can be used for generating a 
31

continuous IRI plot. Typically, a base length of 25 ft is used for locating areas of localized 

roughness. A detailed description of continuous roughness plots is presented by Sayers.

(24)

Figure 20. Graph. Continuous roughness plot based on 25-ft base length.

3.6 EVALUATING CHANGES IN RIDE QUALITY AND STRUCTURAL CAPACITY 

OVER TIME

3.6.1 Changes in IRI

Figure 21 shows the right wheel path continuous IRI plots (based on a 25-ft base length) for 

SPS-1 section 050119 in Arkansas for profile runs performed on July 6, 1995, and March 18, 

2004. In 1995, data on this test section were collected immediately after construction. The IRI 

values of the right wheel path for the 500-ft LTPP section for July 6, 1995, and March 19, 2004,

were 47 and 98 inches/mi, respectively. The continuous IRI plot shows most of the increase in 

IRI occurred between about 150 and 260 ft. This information would not be known if only the 

average IRI of the section was evaluated. Hence, as shown in this example, continuous IRI plots 

provide a method to determine the locations within the section where significant changes in IRI 

occur over time. 
32

Figure 21. Graph. Continuous IRI plots for two test dates.

3.6.2 Changes in Structural Strength—Flexible Pavements

As described earlier, SN was used to characterize the structural strength of flexible pavements. 

FWD testing is performed on flexible pavements in the LTPP program at 50-ft intervals. An SN

value can be computed at each FWD test location. Figure 22 shows the SN values computed 

from FWD data collected along the right wheel path of SPS-1 section 050119 in Arkansas for

March 15, 1994, and May 24, 2004. Such a plot can be used to evaluate the change in SN that 

occurred at each FWD test location over time.

Figure 22. Graph. SN from FWD tests performed at two test dates.

3.6.3 Change in Structural Strength—Rigid Pavements

As previously described, the effective concrete slab thickness was used to characterize the 

structural strength of rigid pavements. The data from FWD tests performed at the center of the 

slab were used for this analysis, and the effective slab thickness was computed at each center
33

slab FWD test location. Similar to the SN analysis, the effective slab thickness determined from 

tests performed at different time periods was used to evaluate the change in this parameter. 

Distress within a PCC slab is expected to result in an increase in IRI values, while the effective 

slab thickness is expected to decrease if distress is located within a slab. An important point to 

remember is that distress frequently occurs at joints in PCC pavements (e.g., faulting and

spalling), which causes an increase in IRI. However, such distress will not impact the deflection 

obtained at the center of the slab, which is used to compute the effective slab thickness. 

3.7 METHODOLOGY FOR COMPARING RIDE QUALITY-STRUCTURAL 

CAPACITY RELATIONSHIP 

For each LTPP test section, profile data are available for five repeat runs for each monitoring 

date. One representative profile run was selected for generating the IRI values for analysis in 

this study. The structural capacity data used for analysis are described throughout this section 

according to pavement type.

3.7.1 Flexible Pavements

For flexible pavements, four load levels (6,000, 9,000, 12,000, and 16,000 lb) were used 

at each FWD test location, with four drops for each load level. This test sequence resulted in 

16 deflection basins for each test location. SN values were computed for all 16 drops and then 

averaged. The average SN at each test location was used for analysis.

FWD testing on LTPP flexible pavements was performed along the center of the lane and the 

right wheel path at 50-ft intervals. Profile data at LTPP test sections were collected along the left 

and right wheel path. Hence, for flexible pavements, the SN values computed from FWD data 

collected along the right wheel path were compared with a continuous IRI plot for the right 

wheel path to examine if there was a relationship between the change in IRI and change in 

SN. Profile testing and FWD testing were not performed on the same day at LTPP test sections. 

Therefore, IRI and FWD data collected on dates close to each other were selected from the LTPP 

database for analysis.

Figure 21 shows that a large increase in IRI occurred along the right wheel path of the test 

section between 150 and 260 ft. If this increase in IRI occurred because of pavement distress 

along the right wheel path, a reduction in the SN within these limits is expected when SN data 

for the two test dates are compared. Locations with a low subgrade modulus can result in 

subgrade settlement or movement, causing a dip in the pavement and resulting in an increase in 

IRI. The subgrade modulus at each FWD test location was computed using the procedure 

described in the AASHTO Guide for Design of Pavement Structures and plotted versus distance 

to evaluate if locations where high changes in IRI occur can be related to locations with a low 

subgrade modulus.(23) The deflection below the load of the FWD represents the response due to 

the pavement structure and the subgrade. The deflections below the load of the FWD were also 

plotted versus the distance and compared with the continuous IRI plot to see if there was any 

relationship between high changes in roughness and the deflection below the load. 
34

For all flexible pavements considered in this study, the continuous IRI and SN data were 

plotted on the same graph to evaluate changes and compare the relationship between the two data 

parameters. Figure 23 shows an example of such a plot, with SN and IRI data for two test dates.

Figure 23. Graph. SN and IRI data on same plot.

Thereafter, normalized plots were created to visualize the percent changes in IRI and SN. 

Figure 24 shows an example of a normalized plot. The normalized IRI values were computed 

by dividing the continuous IRI value at each location for the initial and final test dates by the 

average initial IRI of the test section (i.e., average IRI for the entire section) and then expressing 

the computed value as a percentage. The normalized SN values were computed by dividing SN

at each test location for the initial and final test dates by the average initial SN (i.e., average SN

of the section for the initial test date) and then expressing the computed value as a percentage. 

Figure 24. Graph. Normalized SN and IRI data on same plot.
35

3.7.2 Rigid Pavements

For rigid pavements, three load levels (9,000, 12,000, and 16,000 lb) were used at each FWD test 

location, with four drops for each load level. This test sequence resulted in 12 deflection basins 

for each test location. The effective concrete slab thickness (Deff) values were computed for all 

12 drops and then averaged. The average Deff at each test location was used for analysis.

FWD tests on rigid pavements were performed at the center of the slab. The center slab 

deflections were used to compute Deff. The continuous IRI plots for the right wheel path were 

then compared to Deff to evaluate if a decrease in effective slab thickness was noted at locations 

that had a high increase in IRI. In addition, the plot showing deflection below the load was 

compared with the continuous IRI plot to see if any relationship could be detected between 

changes in IRI and changes in deflection.

Thereafter, normalized plots were created to visualize the percent changes in IRI and Deff. The 

normalized IRI values were computed by dividing the continuous IRI value at each location for 

the initial and final test dates by the average initial IRI of the test section (i.e., average IRI for the 

entire section) and then expressing the computed value as a percentage. The normalized Deff

values were computed by dividing the Deff at each test location for the initial and final test dates 

by the average initial Deff (i.e., average Deff of the section for the initial test date) and then 

expressing the computed value as a percentage. 

3.8 TEST SECTIONS SELECTED FOR ANALYSIS

The pavement sections selected for the study were divided into the following five groups:

• Group 1: The sections in this group were selected by evaluating the change in IRI that 

occurred at SPS-1 sections. The change in IRI since construction was computed for all 

SPS-1 sections. Thereafter, seven sections were selected for analysis such that the change 

in IRI for the sections covered a wide range. 

• Group 2: A previous study evaluated the change in effective pavement thickness at 

SPS-1 sections over time.

(25) The effective pavement thickness in that study was 

computed from FWD data. Four sections that showed a significant decrease in the 

effective pavement thickness were selected for analysis. 

• Group 3: In a previous study, SPS-1 sections with different base types appeared to 

behave differently from a structural point of view.(25) Based on this observation, a pair of 

sections with aggregate base and ATB was selected from two SPS-1 projects for analysis.

• Group 4: This group consists of flexible pavements that have been subjected to an AC 

overlay. Three test sections from the SPS-5 experiment were selected for analysis. The 

selected sections have had a significant increase in IRI since the overlay.

• Group 5: The sections in this group were selected by evaluating the change in IRI that 

occurred at SPS-2 sections. The change in IRI since construction was computed for all 
36

SPS-2 sections. Thereafter, three sections that showed a significant change in IRI since 

construction were selected for analysis.

3.9 ANALYSIS OF GROUP 1 SECTIONS

Table 9 shows the following parameters for the test sections selected for analysis: LTPP section 

number, date corresponding to first IRI (first IRI date), date corresponding to last IRI (last IRI 

date), FWD test date close to the first IRI date (first FWD date), FWD test date close to the last 

IRI date (last FWD date), and the time difference between the first and last dates for IRI and 

FWD data collection.

Table 9. Group 1 sections selected for analysis.

LTPP 

Section

IRI Date FWD Date

Time Difference Between 

First and Last Date (years)

First Date Last Date First Date Last Date IRI Data FWD Data

050119,

Arkansas 7/6/1995 3/19/2004 3/15/1994 5/24/2004 8.7 10.2

480114,

Texas 9/8/1997 3/19/2007 11/17/1997 6/24/2004 9.5 6.6

310113,

Nebraska 11/1/1995 3/20/2000 8/3/1995 10/14/1999 4.4 4.2

010102,

Alabama 8/25/1994 5/4/2005 6/21/1995 4/29/2005 10.7 9.9

390112,

Ohio 8/14/1996 5/5/2005 11/6/1996 9/1/2004 8.7 7.8

040123,

Arizona 1/27/1994 3/27/2006 2/16/1994 4/7/2005 12.2 11.2

190108,

Iowa 10/15/1993 9/22/2004 5/19/1993 6/27/2005 10.9 13.9

Table 10 shows the IRI values for the 500-ft-long sections for the first and last profile dates for 

the selected profile runs as well as the average SN values for the section for the first and last 

FWD date.
37

Table 10. IRI and SN for group 1 sections.

LTPP Section

IRI (inches/mi) SN

Change Between 

First and Last*

First 

Date

Last 

Date

First 

Date

Last 

Date

IRI 

(in/mi) SN

050119, Arkansas 48 98 4.51 5.40 50 -0.89

480114, Texas 46 65 10.90 10.39 19 0.51

310113, Nebraska 93 126 5.73 5.82 33 -0.09

010102, Alabama 62 204 2.86 2.19 143 0.67

390112, Ohio 57 101 7.83 7.39 44 0.44

040123, Arizona 52 138 7.94 7.26 86 0.68

190108, Iowa 49 141 8.30 9.94 93 -1.64

*A negative change in SN indicates that the SN increased from the first to the last date.

Table 11 shows the average pavement layer thickness of the selected test section computed from 

the layer thickness data in the LTPP database.
38

Table 11. Pavement layer thickness for group 1 sections.

LTPP 

Section Layer Type

Layer 

Thickness 

(inches) Material Type

050119,

Arkansas

AC 6.8 Hot-mixed, dense-graded

PATB 3.4 Open-graded, hot laid, central plant mix

Granular 

base (GB) 4.1 Crushed stone

480114,

Texas

AC 6.8 Hot-mixed, dense-graded

GB 12.1 Crushed stone

Treated 

subgrade 

(TS) 23 Lime-treated soil

310113,

Nebraska

AC 5.1 Hot-mixed, dense-graded

GB 8 Crushed stone

Granular 

subbase 

(GS) 24 Fine-grained soils, lean inorganic clay

010102,

Alabama

AC 4.2 Hot-mixed, dense-graded

GB 12 Crushed stone

390112,

Ohio

AC 4 Hot-mixed, dense-graded

ATB 11.8 HMAC

PATB 4 Open-graded, hot laid, central plant mix

040123,

Arizona

AC 6.8 Hot-mixed, dense-graded

ATB 7.9 HMAC

PATB 3.8 Open-graded, hot laid, central plant mix

190108,

Iowa

AC 6 Hot-mixed, dense-graded

PATB 4.5 Open-graded, hot laid, central plant mix

GB 8 Crushed stone

GS 24 Fine-grained soils, lean clay with sand

3.9.1 LTPP Section 050119 (Arkansas)

The first and last profile dates for section 050119 (Arkansas) were July 6, 1995, and March 19, 

2004, and the IRI of the right wheel path increased by 50 inches/mi (from 48 to 98 inches/mi)

during this 9-year period. The first and last FWD dates for this section were March 15, 1994, and 

May 24, 2004, and the average SN for this section increased by 0.89 (from 4.51 to 5.40) during 

this 10-year period. Figure 25 shows the continuous IRI plots for this section for the first and 

last profile dates, and figure 26 shows the SN values for the first and last FWD dates. Figure 27

shows the deflection measured below the load for a 9,000-lb load for the first and last FWD 

dates. Figure 28 shows the subgrade modulus estimated from the FWD data for the first and last 

FWD dates. Figure 29 shows the first and last IRI and SN values on a single plot. The straight, 

solid line in this plot corresponds to the average IRI at the last profile date. This line can be used 

as a reference to identify areas that have a high IRI value at the last profile date. Figure 30 shows 
39

the normalized IRI and SN data for the first and last dates. For all other sections, only the SN 

and IRI single plot and the normalized plot are shown. Plots for deflection below the load for 

a normalized load of 9,000 lb and the subgrade modulus for all sections are included in 

appendix A.

Figure 25. Graph. IRI for two test dates, section 050119 (Arkansas).

Figure 26. Graph. SN for two test dates, section 050119 (Arkansas).
40

Figure 27. Graph. Deflection below load for 9,000 lb for two test dates, 

section 050119 (Arkansas).

Figure 28. Graph. Subgrade modulus for two test dates, section 050119 (Arkansas).
41

Figure 29. Graph. SN and IRI for two test dates, section 050119 (Arkansas).

Figure 30. Graph. Normalized SN and IRI for two test dates, section 050119 (Arkansas).

For this test section, SN corresponding to the last test date was higher than SN corresponding to 

the first test date at all test locations. Figure 29 and figure 30 show that a large increase in IRI 

occurred in this section between about 160 and 240 ft. Only one FWD test point is located within 

these limits (at 200 ft), and SN corresponding to that test point does not show any significant 

difference when compared to SN obtained at the other test locations. The average increase in SN

for this section between the two FWD test dates was 0.89, with the SN at 200 ft increasing by 

0.85. The deflection below the load as well as the subgrade modulus at 200 ft does not show 

any trends that suggest a weaker subgrade was present at this location. Figure 27 shows the 

deflection below the load was lower at the last FWD date compared to the first FWD date at all 
42

test locations. Figure 28 shows the subgrade modulus for the last FWD date was lower than that 

for the first FWD date at all locations.

3.9.2 LTPP Section 480114 (Texas)

The first and last profile dates for section 480114 (Texas) were September 8, 1997, and 

March 19, 2007, and the IRI of the right wheel path increased by 19 inches/mi (from 46 to 

65 inches/mi) during this 10-year period. The first and last FWD dates for this section were 

November 17, 1997, and June 24, 2004, and the average SN of this section decreased by 

0.51 (from 10.90 to 10.39), during this 7-year period.

Figure 31 shows the first and last IRI and SN values, and figure 32 shows the normalized IRI and 

SN plots. The first 120 ft of the test section had a higher increase in IRI compared to the rest of 

the section. However, the decrease in SN that occurred at the test locations within these limits 

does not appear to be significantly different from the decrease in SN that occurred at the other 

test points. The average decrease in SN for this section was 0.51, and the average decrease in SN

at the first three FWD locations was 0.46. No relationship was noted between the increase in IRI 

and the deflection below the load or the subgrade modulus.

Figure 31. Graph. SN and IRI for two test dates, section 480114 (Texas).
43

Figure 32. Graph. Normalized SN and IRI for two test dates, section 480114 (Texas).

3.9.3 LTPP Section 310113 (Nebraska)

The first and last profile dates for section 310113 (Nebraska) were November 1, 1995, and 

March 20, 2000, and the average IRI of the right wheel path increased by 33 inches/mi (from 

93 to 126 inches/mi) during this 4-year period. The first and last FWD dates for this section 

were August 3, 1995, and October 14, 1999, and the average SN of this section increased by 

0.09 (from 5.73 to 5.82) during this 4-year period. 

Figure 33 shows the first and last IRI and SN values for this section, and figure 34 shows the 

normalized IRI and SN plots. No major changes in IRI occurred at any localized location within 

the test section. A slight increase in SN occurred over time at about half of the test locations, and 

the other half showed a slight decrease in SN. No test location showed a change in SN that was 

vastly different than the rest of the test locations. No relationship was noted between the increase 

in IRI and the deflection below the load or the subgrade modulus.
44

Figure 33. Graph. SN and IRI for two test dates, section 310113 (Nebraska).

Figure 34. Graph. Normalized SN and IRI for two test dates, section 310113 (Nebraska).

3.9.4 LTPP Section 010102 (Alabama)

The first and last profile dates for section 010102 (Alabama) were August 25, 1994, and 

May 4, 2005, and the average IRI of the right wheel path increased by 143 inches/mi (from 

62 to 204 inches/mi) during this 11-year period. The first and last FWD dates for this section 

were June 21, 1995, and April 29, 2005, and the average SN of this section decreased by 

0.67 (from 2.86 to 2.19) during this 10-year period.

Figure 35 shows the first and last IRI and SN values, and figure 36 shows the normalized 

IRI and SN plots. The IRI of the last 300 ft of the test section showed a high increase 

in IRI when compared to the first 200 ft. IRI of the first 200 ft of the section increased 
45

from 75 to 114 inches/mi, and IRI of the section from 200 to 500 ft increased from 53 to 

271 inches/mi. The highest increase in IRI occurred between about 260 and 380 ft. The average 

decrease in SN for the first 200 ft was 0.59, and average decrease in SN between 250 and 500 ft 

was 0.74. Although the last 300 ft of the section had a higher increase in IRI and showed a larger 

decrease in SN when compared to the first 200 ft, the decrease in SN of the last 300 ft was only 

slightly higher than that for the first 200 ft. In addition, a small SN decrease of 0.24 was noted at 

300 ft, which was within the limits that showed the highest increase in IRI for this section. No 

relationship was noted between the increase in IRI and the deflection below the load or the 

subgrade modulus.

Figure 35. Graph. SN and IRI for two test dates, section 010102 (Alabama).

Figure 36. Graph. Normalized SN and IRI for two test dates, section 010102 (Alabama).
46

3.9.5 LTPP Section 390112 (Ohio)

The first and last profile dates for section 390112 (Ohio) were August 14, 1996, and May 5, 

2005, and the IRI of the right wheel path increased by 44 inches/mi (from 57 to 101 inches/mi) 

during this 9-year period. The first and last FWD dates for this section were November 6, 1996,

and September 1, 2004, and the average SN of this section decreased by 0.44 (from 7.83 to 7.39)

during this 8-year period.

Figure 37 shows the first and last IRI and SN values, and figure 38 shows the normalized IRI and 

SN plots. SN corresponding to the last FWD date was slightly higher than SN corresponding to 

the first FWD date at the first test location. At all other test locations, SN decreased, with the 

decrease ranging from 0.37 to 0.76 and an average value of 0.51. High IRI values at the last 

profile date were noted between approximately 180 to 210 ft, 230 to 310 ft, and 390 to 430 ft. 

The lowest initial and final SN at this section occurred at 200 ft (within 180 to 210 ft), which was 

the area that had a high increase in IRI. Hence, for this particular area, a high increase in IRI was 

associated with a low initial SN. However, the decrease in SN at 200 ft was 0.51, which was 

equal to the average decrease in SN for this section. Two FWD test points are located between 

230 and 310 ft, and the average decrease in SN at these two points was 0.49, while the decrease 

in SN at 400 ft (within 390 to 430 ft) was 0.45. The decrease in SN at these locations was less 

than the average decrease in SN for this section. No relationship was noted between the increase 

in IRI and the deflection below the load or the subgrade modulus.

Figure 37. Graph. SN and IRI for two test dates, section 390112 (Ohio).
47

Figure 38. Graph. Normalized SN and IRI for two test dates, section 390112 (Ohio).

3.9.6 LTPP Section 040123 (Arizona)

The first and last profile dates for section 040123 (Arizona) were January 27, 1994, and 

March 27, 2006, and the average IRI of the right wheel path increased by 86 inches/mi from 

(52 to 138 inches/mi) during this 12-year period. The first and last FWD dates for this section 

were February 16, 1994, and April 7, 2005, and the average SN of this section decreased by 

0.68 (from 7.94 to 7.26) during this 11-year period. 

Figure 39 shows the first and last IRI and SN values, and figure 40 shows the normalized IRI and 

SN plots. A higher decrease in SN was observed between 0 and 200 ft compared to 250 to 500 ft. 

All test locations between 0 and 200 ft showed a decrease in SN, with an average decrease of 

1.48. Four of the six test locations between 250 and 500 ft showed an increase in SN. For the two 

points that showed a decrease in SN, the average decrease was 0.40. A significant increase in IRI 

occurred within the section between the following approximate limits: about 80 to 140 ft, 210 to 

260 ft, and 300 to 350 ft. An FWD test point that was close to a peak IRI location occurred only 

at 100 ft. At this location, a decrease in SN of 1.14 was noted. The average decrease in SN at test 

locations between 0 and 200 ft was 1.57 and was more than the decrease in IRI noted at 100 ft. 

However, the change in IRI seen at these test locations was much less when compared to the 

change in IRI seen at 100 ft. No relationship was noted between the increase in IRI and the 

deflection below the load or the subgrade modulus.
48

Figure 39. Graph. SN and IRI for two test dates, section 040123 (Arizona).

Figure 40. Graph. Normalized SN and IRI for two test dates, section 040123 (Arizona).

3.9.7 LTPP Section 190108 (Iowa)

The first and last profile dates for section 190108 (Iowa) were October 15, 1993, and 

September 22, 2004, and the IRI of the right wheel path increased by 93 inches/mi (from 

49 to 141 inches/mi) during this 11-year period. The first and last FWD dates for this section 

were May 19, 1993, and April 24, 2007, and the average SN of this section increased by 

1.64 (from 8.30 to 9.94) during this 14-year period.

Figure 41 shows the first and last IRI and SN values, and figure 42 shows the normalized IRI and 

SN plots. SN at the last FWD date was greater than SN at the first FWD date at all test locations. 

The peaks in the IRI plot for the last IRI date are locations where major increases in IRI had 
49

occurred. Except at one location (450 ft), the FWD data points are located outside the peak IRI 

areas. The average increase in SN between the FWD test dates at this section was 1.65, with SN

at 450 ft showing an increase of 2.13 between the two test dates. No relationship was noted 

between the increase in IRI and the deflection below the load or the subgrade modulus.

Figure 41. Graph. SN and IRI for two test dates, section 190108 (Iowa).

Figure 42. Graph. Normalized SN and IRI for two test dates, section 190108 (Iowa).

3.10 ANALYSIS OF GROUP 2 SECTIONS

Table 12 shows the following parameters for the test sections selected for analysis: LTPP section 

number, date corresponding to first IRI (first IRI date), date corresponding to last IRI (last IRI 

date), FWD test date close to the first IRI date (first FWD date), FWD test date close to the last 
50

IRI date (last FWD date), and the time difference between first and last dates for IRI and FWD 

data collection. 

Table 12. Group 2 sections selected for analysis.

LTPP 

Section

IRI Date FWD Date

Time Difference Between 

First and Last Date (years)

First Date Last Date First Date Last Date IRI Data FWD Data

320101,

Nevada 12/3/1996 8/7/2006 3/27/1996 8/28/2006 9.7 10.4

390106,

Ohio 8/14/1996 8/9/2006 11/5/1996 7/15/2008 10.0 11.7

310117,

Nebraska 11/1/1995 4/24/2002 8/2/1995 7/9/2002 6.5 6.9

310118,

Nebraska 11/1/1995 4/24/2002 8/3/1995 7/10/2002 6.5 6.9

Table 13 shows the IRI values for the 500-ft-long sections for the first and last profile dates for 

the selected profile runs as well as the average SN for the first and last FWD date. Table 14

shows the average pavement layer thickness of the group 2 sections computed from the layer 

thickness data available in the LTPP database.

Table 13. IRI and SN for group 2 sections.

LTPP Section

IRI (inches/mi) SN

Change Between 

First and Last*

First 

Date

Last 

Date

First 

Date

Last

Date

IRI 

(inches/mi) SN

320101, Nevada 57 57 11.91 11.23 0 0.68

390106, Ohio 71 114 6.94 5.04 43 1.90

310117, Nebraska 68 53 8.32 7.30 -15 1.02

310118, Nebraska 74 54 9.21 7.62 -20 1.59

*A negative IRI indicates IRI at the last date was less than the IRI at the first date.
51

Table 14. Pavement layer thickness, group 2 sections.

LTPP 

Section

Layer

Type

Layer

Thickness 

(inches) Material Type

320101,

Nevada

AC 7.2 Hot-mixed, dense-graded

GB 8.5 Crushed gravel

GS 22.8 Soil-aggregate mixture (predominantly coarse-grained)

TS 12 Lime-treated soil

390106,

Ohio

AC 6.7 Hot-mixed, dense-graded

ATB 7.9 HMAC

GB 3.8 Crushed stone

310107,

Nebraska

AC 7.1 Hot-mixed, dense-graded

PATB 3.8 Open-graded

GB 4 Crushed stone

GS 24 Fine-grained soils, lean inorganic clay

310118,

Nebraska

AC 4.3 Hot-mixed, dense-graded

ATB 8.2 HMAC

GB 4 Crushed stone

GS 24 Fine-grained soils, lean inorganic clay

3.10.1 LTPP Section 320101 (Nevada)

The first and last profile dates for section 320101 (Nevada) were December 3, 1996, and 

August 7, 2006, and the IRI of the right wheel path remained the same at 57 inches/mi over this 

10-year period. The first and last FWD dates for this section were March 27, 1996, and August 

28, 2006, and the average SN of this section decreased by 0.68 (from 11.91 to 11.23) over this 

10-year period. 

Figure 43 shows the first and last IRI and SN values, and figure 44 shows the normalized IRI and 

SN plots. SN decreased from the first to the last FWD date at all test locations, with the decrease 

in SN ranging from 0.13 to 1.41. However, as seen in figure 43 and figure 44, there is virtually 

no noticeable change in IRI throughout the section. 
52

Figure 43. Graph. SN and IRI for two test dates, section 320101 (Nevada).

Figure 44. Graph. Normalized SN and IRI for two test dates, section 320101 (Nevada).

3.10.2 LTPP Section 390106 (Ohio)

The first and last profile dates for section 390106 (Ohio) were August 14, 1996, and August 9, 

2006, and the IRI of the right wheel path increased by 43 inches/mi (from 71 to 114 inches/mi)

during this 10-year period. The first and last FWD dates for this section were November 5, 1996,

and July 15, 2008, and the average SN of the section decreased by 1.90 from (6.94 to 5.04)

during this 12-year period.

Figure 45 shows the first and last IRI and SN values, and figure 46 shows the normalized IRI and 

SN plots. An increase in IRI was observed at most locations within the section, with the highest 

change in IRI occurring between about 140 and 190 ft. The highest increase in IRI occurred 

close to 150 ft, where an FWD test was performed. SN decreased from the first to the last FWD 
53

dates at all test locations. The decrease in SN at 150 ft was 2.06, slightly higher than the average 

decrease in SN of 1.90 for this section. A decrease in SN greater than the 2.06 decrease that was 

observed at 150 ft was noted at 50, 100, 200, and 450 ft. The magnitude of the IRI change at 

these locations was much less than that observed at 150 ft. No relationship was noted between 

the increase in IRI and the deflection below the load or the subgrade modulus (see appendix A).

Figure 45. Graph. SN and IRI for two test dates, section 390106 (Ohio).

Figure 46. Graph. Normalized SN and IRI for two test dates, section 390106 (Ohio).

3.10.3 LTPP Section 310117 (Nebraska)

The first and last profile dates for section 310117 (Nebraska) were November 1, 1995, and 

April 24, 2002, and the IRI of the right wheel path decreased by 15 inches/mi (from 68 to 

53 inches/mi) during this 7-year period. The LTPP database indicated this section was diamond 

ground on July 12, 2000. The reduction in IRI is attributed to the diamond grinding. The first and 

last FWD dates for this section were August 2, 1995, and July 9, 2002, and the average SN of 
54

this section decreased by 1.02 (from 8.32 to 7.30) during this 7-year period. IRI and SN plots 

were not developed for this section because it was subjected to diamond grinding.

3.10.4 LTPP Section 310118 (Nebraska)

The first and last profile dates for section 310118 (Nebraska) were November 1, 1995,

and April 24, 2002, and the IRI of the right wheel path decreased by 20 inches/mi (from 

74 to 54 inches/mi) during this 7-year period. This section is in the same SPS-1 project as 

section 310117 (Nebraska). The LTPP database indicated the section was diamond ground on 

July 12, 2000. The reduction in IRI is attributed to the diamond grinding. The first and last FWD 

dates for this section were August 3, 1995, and July 10, 2002, and the average SN of this section 

decreased by 1.59 (from 9.21 to 7.62) during this 7-year period. IRI and SN plots were not 

developed for this section because it was subjected to diamond grinding.

3.11 ANALYSIS OF GROUP 3 SECTIONS

Table 15 shows the following parameters for the test sections selected for analysis: LTPP section 

number, date corresponding to first IRI (first IRI date), date corresponding to last IRI (last IRI 

date), FWD test date close to the first IRI date (first FWD date), FWD test date close to the last 

IRI date (last FWD date), and the time difference between first and last dates for IRI and FWD 

data collection. 

Table 15. Group 3 sections selected for analysis.

LTPP 

Section

IRI Date FWD Date

Time Difference Between 

First and Last Date (years)

First Date Last Date First Date Last Date IRI Data FWD Data

190101,

Iowa 10/15/1993 9/22/2004 5/19/1993 6/28/2005 10.9 12.1

190103,

Iowa 10/15/1993 9/22/2004 5/19/1993 6/29/2005 10.9 12.1

050114,

Arkansas 7/7/1995 4/6/2005 3/16/1994 5/12/2005 9.8 11.2

050116,

Arkansas 7/7/1995 4/6/2005 3/16/1994 5/11/2005 9.8 11.2

Table 16 shows the IRI values for the 500-ft-long section for the first and last profile dates for 

the selected profile runs as well as the average SN for the section for the first and last FWD date. 

Table 17 shows the pavement layer thickness for group 3 sections.
55

Table 16. IRI and SN for group 3 sections.

LTPP Section

IRI (inches/mi) SN

Change Between 

First and Last*

First Last First Last

IRI 

(inches/mi) SN

190101, Iowa 83 159 7.48 7.62 76 -0.14

190103, Iowa 46 92 9.39 8.68 46 0.71

050114, Arkansas 49 72 4.26 5.13 23 -0.87

050116, Arkansas 68 63 7.81 10.30 -5 -2.49

*A negative change in SN indicates SN at the last date was higher than SN at the first date. A negative 

change in IRI indicates IRI at the last date was lower than IRI at the first date.

Table 17. Pavement layer thickness, group 3 sections.

LTPP 

Section

Layer

Type

Layer

Thickness 

(inches) Material Type

190101,

Iowa

AC 7.7 Hot-mixed, dense-graded

GB 8 Crushed stone

GS 25 Fine-grained soils, clay with gravel

190103,

Iowa

AC 3.8 Hot-mixed, dense-graded

ATB 8.4 HMAC

GS 24 Fine-grained soils, clay with gravel

050114,

Arkansas

AC 6.9 Hot-mixed, dense-graded

GB 11 Gravel (uncrushed)

050116,

Arkansas

AC 4.1 Hot-mixed, dense-graded

ATB 11.8 HMAC

Sections 190101 and 190103 are both test sections in the Iowa SPS-1 project. Section 190101 

has DGAB, and section 190103 has ATB. Section 050114 and 050116 are test sections in the 

Arkansas SPS-1 project. Section 050114 has DGAB, and section 050116 has ATB. In each 

project, the test section with the DGAB base showed a higher increase in IRI between the first 

and the last dates when compared to the test section with ATB.

3.11.1 LTPP Section 190101 (Iowa)

The first and last profile dates for section 190101 (Iowa) were October 15, 1993, and 

September 22, 2004, and the IRI of the right wheel path increased by 76 inches/mi (from 83 to 

159 inches/mi) during this 11-year period. The first and last FWD dates for this section were 

May 19, 1993, and June 28, 2005, and the average SN of this section increased by 0.14 (from 

7.48 to 7.62) during this 12-year period.

Figure 47 shows the first and last IRI and SN values, and figure 48 shows the normalized IRI and 

SN plots. SN at the last FWD date was greater than SN at the first FWD date at all test locations, 

except for the last three (400, 450, and 500 ft). There are five peaks in the IRI plot for the last IRI 

date, and, except for two, the peak IRI locations fall outside locations where FWD testing was 
56

conducted. SN values are available between 380 to 410 ft and 440 to 460 ft, where two of the 

peaks occur. The reductions in SN at 400 and 450 ft were 0.31 and 1.39, respectively. Therefore, 

a reduction in SN was seen at the locations that had a high increase in IRI. No relationship was 

noted between the increase in IRI and the deflection below the load or the subgrade modulus 

(see appendix A).

Figure 47. Graph. SN and IRI for two test dates, section 190101 (Iowa).

Figure 48. Graph. Normalized SN and IRI for two test dates, section 190101 (Iowa).

3.11.2 LTPP Section 190103 (Iowa)

The first and last profile dates for section 190103 (Iowa) were October 15, 1993, and 

September 22, 2004, and the IRI of the right wheel path increased by 46 inches/mi

(from 46 to 92 inches/mi) during this 11-year period. The first and last FWD dates for this 
57

section were May 19, 1993, and June 29, 2005, and the average SN of this section decreased by 

0.71 (from 9.39 to 8.68) during this 12-year period.

Figure 49 shows the first and last IRI and SN values, and figure 50 shows the normalized IRI and 

SN plots. SN at the last FWD date was lower than SN at the first FWD date at all test locations. 

An increase in IRI is noted throughout the section, with a major increase in IRI close to 250 ft. 

An FWD test was performed at 250 ft, and the decrease in SN observed at this location was 0.32, 

which was less than the average decrease in SN at this section. No relationship was noted 

between the increase in IRI and the deflection below the load or the subgrade modulus 

(see appendix A).

Figure 49. Graph. SN and IRI for two test dates, section 190103 (Iowa).

Figure 50. Graph. Normalized SN and IRI for two test dates, section 190103 (Iowa).
58

3.11.3 LTPP Section 050114 (Arkansas)

The first and last profile dates for section 050114 (Arkansas) were July 7, 1995, and April 6, 

2005, and the IRI of the right wheel path increased by 23 inches/mi (from 49 to 72 inches/mi)

during this 10-year period. The first and last FWD dates for this section were March 16, 1994,

and May 12, 2005, and the average SN of this section increased by 0.87 (from 4.26 to 5.13)

during this 11-year period.

Figure 51 shows the first and last IRI and SN values, and figure 52 shows the normalized IRI and 

SN plots. SN at the last FWD date was greater than SN at the first FWD date at all test locations. 

The increase in SN at the FWD test locations ranged from 0.55 to 1.25 and averaged 0.87. An 

increase in IRI between the test dates is noted for the entire section, but there were no major 

localized roughness increases in this section. The greatest increase in IRI within the section 

occurred between 350 to 400 ft, which borders the FWD tests that were performed at 350 and 

400 ft. However, a FWD test point is not located within these limits. No relationship was noted 

between the increase in IRI and the deflection below the load or the subgrade modulus (see 

appendix A).

Figure 51. Graph. SN and IRI for two test dates, section 050114 (Arkansas).
59

Figure 52. Graph. Normalized SN and IRI for two test dates, section 050114 (Arkansas).

3.11.4 LTPP Section 050116 (Arkansas)

The first and last profile dates for section 050116 (Arkansas) were July 7, 1995, and April 6, 

2005, and the IRI of the right wheel path decreased by 5 inches/mi (from 68 to 63 inches/mi)

during this 10-year period. The first and last FWD dates for this section were March 16, 1994,

and May 11, 2005, and the average SN of this section increased by 2.49 (from 7.81 to 10.30)

during this 11-year period.

Figure 53 shows the first and last IRI and SN values, and figure 54 shows the normalized IRI and 

SN plots. SN at the last FWD date was greater than SN at the first FWD date at all test locations. 

The increase in SN ranged from 0.92 to 3.13 and averaged 2.49. The overall IRI of this section 

decreased from 68 to 63 inches/mi. The continuous IRI plots show little change in IRI, with the 

IRI for the last date showing a slight increase at some locations and a slight decrease at other 

locations. The highest IRI for the first and last IRI dates occurred around 270 ft. No relationship 

was noted between the increase in IRI and the deflection below the load or the subgrade modulus 

(see appendix A).
60

Figure 53. Graph. SN and IRI for two test dates, section 050116 (Arkansas).

Figure 54. Graph. Normalized SN and IRI for two test dates, section 050116 (Arkansas).

3.12 ANALYSIS OF GROUP 4 SECTIONS

The test sections in group 4 are SPS-5 sections. FWD testing and roughness data collection

were performed at these test sections before and immediately after rehabilitation. The date 

corresponding to the data collection performed immediately after rehabilitation is referred to 

as the first IRI date or first FWD date. Table 18 shows the following information for the test 

sections selected for analysis: LTPP section number, date when IRI data were collected before 

rehabilitation, date corresponding to first IRI (first IRI date), date corresponding to last IRI (last 

IRI date), date when FWD data were collected before rehabilitation, FWD test date close to the 

first IRI date (first FWD date), FWD test date close to the last IRI date (last FWD date), and the 

time difference between first and last dates for IRI and FWD data collection. 
61

Table 18. Group 4 sections selected for analysis.

LTPP 

Section

IRI Date FWD Date

Time Difference 

Between First and 

Last Date (years)

Before 

Overlay

First 

Date

Last 

Date

Before 

Overlay

First 

Date

Last

Date

IRI 

Data

FWD 

Data

040502,

Arizona 2/5/1990 9/21/1990 3/24/2006 1/18/1990 10/3/1991 9/15/2008 16.1 18.7

240505,

Maryland 1/24/1992 6/11/1992 6/15/2006 2/20/1992 8/25/1992 4/7/2009 14.4 17.1

270509,

Minnesota 5/24/1990 7/13/1993 6/6/2005 7/22/1990 11/6/1990 6/7/2005 15.0 14.9

Table 19 shows the IRI values for the 500-ft-long sections for the selected profile runs and 

the average SN for the section for the three test dates shown in table 18. Table 20 shows the 

average pavement layer thickness of the three test sections before rehabilitation obtained from 

the data in the LTPP database. Table 21 shows the milling depths and overlay thickness for the 

three sections.

Table 19. IRI and SN for group 4 sections.

LTPP Section

IRI (inches/mi) SN

Change Between 

First and Last Date

Before 

Overlay

First 

Date

Last 

Date

Before 

Overlay

First 

Date

Last 

Date

IRI 

(inches/mi) SN

040502, Arizona 139 60 244 3.39 5.91 4.78 184 1.13

240505, Maryland 148 69 228 6.15 8.13 7.40 159 0.73

270509, Minnesota 197 54 117 4.52 5.94 5.78 63 0.16

Table 20. Pavement layer thickness before rehabilitation, group 4 sections.

LTPP 

Section

Layer 

Type

Layer 

Thickness 

(inches) Material Type

040502,

Arizona

AC 0.9 Hot-mixed, open-graded

AC 4.2 Hot-mixed, dense-graded

GB 14.7 Soil-aggregate mixture (predominantly coarse-grained)

240505,

Maryland

AC 1.1 Hot-mixed, open-graded

AC 3.5 Hot-mixed, dense-graded

TB 3.7 Cement aggregate mixture

GS 5.9 Crushed stone

TS 8.9 Cement-treated soil

270509,

Minnesota

AC 6.9 Hot-mixed, dense-graded

GB 4.7 Crushed gravel

GS 12.6 Gravel (uncrushed)
62

Table 21. Mill and overlay thickness.

Section

Milled 

Thickness 

(inches)

Overlay 

Thickness 

(inches)

040502, Arizona 1.4 2.7

240505, Maryland — 2.1

270509, Minnesota 1.9 3.6

— Indicates milling was not performed.

3.12.1 LTPP Section 040502 (Arizona)

IRI before rehabilitation of section 040503 (Arizona) was 139 inches/mi, and IRI immediately 

after the overlay was 60 inches/mi. Rehabilitation resulted in IRI decreasing by 79 inches/mi. 

The first and last profile dates for this section were September 21, 1990, and March 24, 2006, 

and IRI of the right wheel path increased by 184 inches/mi (from 60 to 244 inches/mi) during 

this 16-year period. 

SN before rehabilitation of this section was 3.39, and it increased to 5.91 after rehabilitation. The 

first and last FWD dates for this section were October 3, 1991, and September 15, 2008, and the 

average SN decreased by 1.13 (from 5.91 to 4.78) during this 17-year period.

Figure 55 shows the continuous IRI plots for before the overlay (February 5, 1990), immediately 

after the overlay (September 21, 1990), and at the last IRI date (March 24, 2006). The continuous 

IRI plot had higher values at the last date compared to the before overlay plot except at a few 

locations. Figure 56 shows the SN plots for before the overlay (January 8, 1990), immediately 

after the overlay (October 3, 1991), and at the last SN date (September 15, 2008). The 

rehabilitation resulted in an increase in SN at all test locations. SN at all test locations for the 

last date was lower than SN immediately after rehabilitation (first date) at all test locations. 

Figure 55. Graph. IRI for before overlay, after overlay, and last test date, 

section 040502 (Arizona).
63

Figure 56. Graph. SN for before overlay, after overlay, and last test date, 

section 040502 (Arizona).

Figure 57 shows the IRI and SN values after the overlay and at the last test date, and figure 58

shows the normalized IRI and SN plots. IRI increased throughout the section, with the highest 

increases between 80 and 110 ft and 420 and 460 ft. SN at 100 ft had a decrease of 1.06, which 

was lower than the average decrease in SN at the section. SN at 450 ft had the lowest decrease 

for this section, which was 0.31.

Figure 57. Graph. SN and IRI for two test dates after overlay, section 040502 (Arizona).
64

Figure 58. Graph. Normalized SN and IRI for two test dates after overlay, 

section 040502 (Arizona).

3.12.2 LTPP Section 240505 (Maryland)

IRI before rehabilitation of this section was 148 inches/mi, and IRI immediately after the overlay 

was 69 inches/mi. The rehabilitation resulted in IRI decreasing by 79 inches/mi. The first (after 

rehabilitation) and last profile dates were June 11, 1992, and June 15, 2006, and IRI of the right 

wheel path increased by 159 inches/mi (from 69 to 228 inches/mi) during this 14-year period. 

SN before rehabilitation of this section was 6.15, and it increased to 8.13 after rehabilitation. The 

first (after rehabilitation) and last FWD dates for this section were August 25, 1992, and April 7, 

2009, and the average SN decreased by 0.73 (from 8.13 to 7.40) during this 17-year period.

Figure 59 shows the IRI plots for before the overlay (January 24, 1992), immediately after the 

overlay (June 1, 1992), and at the last IRI date (June 15, 2006). Six distinct peaks are shown in 

the IRI plot for last IRI date, and, except for one, these peaks generally correspond to the peaks 

in the before-overlay IRI plot. Figure 60 shows the SN plots for before the overlay (February 20, 

1992), immediately after the overlay (August 25, 1992), and at the last FWD date (April 27, 

2009). SN at all test locations increased after rehabilitation. SN at the last FWD date was 

lower than SN immediately after rehabilitation (first FWD date) for all test locations.
65

Figure 59. Graph. IRI for before overlay, after overlay, and last test date, 

section 240505 (Maryland).

Figure 60. Graph. SN for before overlay, after overlay, and last test date, 

section 240505 (Maryland).

Figure 61 shows the IRI and SN values for the first (immediately after rehabilitation) and last test 

dates, and figure 62 shows the normalized IRI and SN plots. High increases in IRI were noted 

between 120 and 150 ft, 180 and 210 ft, 230 and 250 ft, 270 and 310 ft, and 330 and 360 ft. 

FWD test locations were present at 200, 300, and 350 ft. The decreases in SN at 200, 300, and 

350 ft were 0.19, 0.52, and 0.91 respectively, with the decrease at 200 ft greater than the average 

decrease in SN for the section (0.73). 
66

Figure 61. Graph. SN and IRI for two test dates after overlay, section 240505 (Maryland).

Figure 62. Graph. Normalized SN and IRI for two test dates after overlay, 

section 240505 (Maryland).

3.12.3 LTPP Section 270509 (Minnesota)

IRI before rehabilitation of section 270509 (Minnesota) was 197 inches/mi, and IRI immediately 

after the overlay was 54 inches/mi. Rehabilitation resulted in IRI decreasing by 143 inches/mi. 

The first and last profile dates for this section were July 13, 1993, and June 6, 2005, and 

IRI of the right wheel path increased by 63 inches/mi (from 54 to 117 inches/mi) during this 

12-year period. 

SN before rehabilitation of this section was 4.52, and it increased to 5.94 after rehabilitation. The 

first (after rehabilitation) and last FWD dates for this section were November 6, 1990, and June 

27, 2005, and the average SN decreased by 0.16 (from 5.94 to 5.78) during this 15-year period.
67

Figure 63 shows the IRI plots for before the overlay (May 24, 1990), immediately after the 

overlay (July 13, 1993), and at the last IRI date (June 6, 2005). A significant reduction in IRI 

occurred due to the overlay. Figure 64 shows the SN plots for before the overlay (July 22, 1990), 

immediately after the overlay (November 6, 1990), and at the last SN date (June 7, 2005). The 

overlay resulted in an increase in SN at all test locations. 

Figure 63. Graph. IRI for before overlay, after overlay, and last test date, 

section 270509 (Minnesota).

Figure 64. Graph. SN for before overlay, after overlay, and last test date, 

section 270509 (Minnesota).

Figure 65 shows the IRI and SN at the first test date (after overlay) and the last test date, and 

figure 66 shows the normalized IRI and SN plots. An increase in IRI is noted throughout the 

section, but no localized areas showed a very high increase in IRI. Some test locations showed 

an increase in SN, while others showed a decrease, ranging from 0.06 to 0.57.
68

Figure 65. Graph. SN and IRI for two test dates after overlay, section 270509 (Minnesota).

Figure 66. Graph. Normalized SN and IRI for two test dates after overlay, 

section 270509 (Minnesota).

3.13 ANALYSIS OF GROUP 5 SECTIONS

The test sections in group 5 are SPS-2 test sections. Table 22 shows the following information 

for the test sections selected for analysis: LTPP section number, date corresponding to first IRI 

(first IRI date), date corresponding to last IRI (last IRI date), FWD test date close to the first IRI 

date (first FWD date), FWD test date close to the last IRI date (last FWD date), and the time 

difference between first and last dates for IRI and FWD data collection.
69

Table 22. Group 5 sections selected for analysis.

LTPP 

Section

IRI Date FWD Date

Time Difference Between 

First and Last Date (years)

First Date Last Date First Date Last Date IRI Data FWD Data

040213,

Arizona 1/25/1994 8/11/2006 2/8/1994 12/15/2004 12.6 10.9

050217,

Arkansas 2/6/1997 4/2/2005 11/14/1996 9/20/2004 8.2 7.9

390205,

Ohio 8/14/1996 8/8/2006 12/30/1996 9/9/2004 10.0 7.7

Table 23 shows the IRI values for the 500-ft-long sections and the average effective slab 

thicknesses for the test dates shown in table 22. Table 24 shows the average pavement layer 

thickness for the test sections determined from the data in the LTPP database.

Table 23. IRI and effective slab thickness for group 5 sections.

LTPP Section

IRI (inches/mi)

Effective Slab 

Thickness (inches)

Change Between First 

and Last Date*

First 

Date

Last 

Date

First 

Date

Last 

Date

IRI 

(inches/mi)

Effective Slab 

Thickness

(inches)

040213, Arizona 95 165 9.45 9.00 70 0.45

050217, Arkansas 86 160 13.80 16.80 74 -3.00

390205, Ohio 89 161 9.81 10.20 72 -0.39

*A negative effective slab thickness indicates the effective slab thickness at the last date was higher than that for 

the first date.

Table 24. Pavement layer thickness for group 5 sections.

LTPP 

Section Layer Type

Layer Thickness 

(inches)

040213, 

Arizona

PCC 7.9

Aggregate base 5.8

050217, 

Arkansas

PCC 8.3

Lean concrete base

(LCB) 6.3

390205, 

Ohio

PCC 8.0

LCB 6.2

Plots of deflection measured below the load and at a distance of 60 inches from the center of the 

load plate for the first and last FWD date for all sections are included in appendix B. For the 

September 20, 2004, FWD test for test section 050217, non-decreasing deflections were 

encountered at several test locations. The ILLI-BACK program computed high and unreasonable 

effective slab thickness at these locations. Some of the extremely high effective slab thicknesses 

were not considered in computing the average, yet the average was higher than the initial 

effective slab thickness. Sections 050217 and 390205 both had a LCB. 
70

The ILLI-BACK program appears to have combined the PCC and LCB thicknesses when 

determining the effective slab thickness for these two sections. The computed effective slab 

thickness for section 040213 was also higher than the actual slab thickness.

3.13.1 LTPP Section 040213 (Arizona)

The first and last profile dates for section 040213 (Arizona) were January 25, 1994, and 

August 11, 2006, and the IRI of the right wheel path increased by 70 inches/mi (from 95 to 

165 inches/mi) during this 13-year period. The first and last FWD test dates for this section 

were February 8, 1994, and December 15, 2004, and the average effective slab thickness of 

this section showed a decrease of 0.45 inches (from 9.45 to 9.00 inches) during this period.

Figure 67 shows the first and last IRI and effective slab thickness, and figure 68 shows 

the normalized IRI and Deff plots. An increase in IRI is seen across the entire section. The 

effective slab thickness at the last FWD date shows an increase for the first three data points 

and a decrease for the rest of the points. There are three locations within the section where 

large changes in IRI occurred, but these locations fall between FWD test locations. No 

relationship between change in IRI and deflections (below the load and 60 inches from the 

load) was observed. 

Figure 67. Graph. Deff and IRI for two test dates, section 040213 (Arizona).
71

Figure 68. Graph. Normalized Deff and IRI for two test dates, section 040213 (Arizona).

3.13.2 LTPP Section 050217 (Arkansas)

The first and last profile dates for section 050217 (Arkansas) were February 16, 1997, and 

April 2, 2005, and the IRI of the right wheel path increased by 74 inches/mi (from 86 to 

160 inches/mi) during this 8-year period. The first and last FWD dates for this section were 

November 14, 1996, and September 20, 2004, and the average effective slab thickness of this 

section increased by 3 inches (from 13.80 to 16.80 inches). As previously described, nondecreasing deflections were noted at many test locations for the September 20, 2004, test, and 

these deflections caused high effective slab thickness values to be computed at such locations. 

This resulted in a much higher effective slab thickness for the last test date than for the first 

test date.

Figure 69 shows the first and last IRI and effective slab thickness, and figure 70 shows the 

normalized IRI and Deff plots. Some of the high Deff values computed for the second test date 

are not shown in these plots, and no FWD data were available after 382 ft for the first FWD date. 

Most of the increase in IRI at this section occurred between 130 and 330 ft. The effective slab 

thickness at the last FWD date was higher than that for the first date for all test locations. No 

relationship between the increase in IRI and the effective slab thickness can be seen in the plot. 

No relationship between change in IRI and deflections (below the load and at 60 inches from 

the load) could be observed.
72

Figure 69. Graph. Deff and IRI for two test dates, section 050217 (Arkansas).

Figure 70. Graph. Normalized Deff and IRI for two test dates, section 050217 (Arkansas).

3.13.3 LTPP Section 390205 (Ohio)

The first and last profile dates for section 390205 (Ohio) were August 14, 1996, and August 8, 

2006, and the IRI of the right wheel path increased by 72 inches/mi (from 89 to 161 inches/mi)
73

during this 10-year period. The first and last FWD dates for this section were December 30, 

1996, and September 9, 2004, and the average effective slab thickness of this section showed 

an increase of 0.39 inches (from 9.81 to 10.20 inches) during this 8-year period.

Figure 71 shows the first and last IRI and effective slab thickness, and figure 72 shows the 

normalized IRI and Deff plots. Most of the increase in IRI at this section occurred between the 

start of the section and about 200 ft. Within the first 200 ft, the effective slab thickness at the last 

FWD date was lower than that for the first date at three locations and the same at one location. 

Among the rest of the FWD test locations within this section, half showed a decrease in effective 

slab thickness, and the other half showed an increase between the first and last FWD dates. No 

relationship between change in IRI and deflections (below the load and at 60 inches from the 

load) could be observed.

Figure 71. Graph. Deff and IRI for two test dates, section 390205 (Ohio).
74

Figure 72. Graph. Normalized Deff and IRI for two test dates, section 390205 (Ohio).

3.14 SUMMARY

Table 25 shows all flexible pavement sections used in the analysis. As previously described, the 

IRI and FWD data collections were not performed at the same time at LTPP sections. The first 

IRI and FWD dates correspond to the first time IRI and FWD data were collected at a test 

section, and the last dates were selected such that the last IRI and FWD dates were close to 

each other. Overall, the time period used to evaluate IRI and SN changes at a section were 

reasonably close to each other.
75

Table 25. Flexible pavement sections used in study.

Group

LTPP 

Section

IRI Date FWD Date

Time Difference

Between First and Last 

Date (years)

First Date Last Date First Date Last Date IRI Data FWD Data

1

050119 7/6/1995 3/19/2004 3/15/1994 5/24/2004 8.7 10.2

480114 9/8/1997 3/19/2007 11/17/1997 6/24/2004 9.5 6.6

310113 11/1/1995 3/20/2000 8/3/1995 10/14/1999 4.4 4.2

010102 8/25/1994 5/4/2005 6/21/1995 4/29/2005 10.7 9.9

390112 8/14/1996 5/5/2005 11/6/1996 9/1/2004 8.7 7.8

040123 1/27/1994 3/27/2006 2/16/1994 4/7/2005 12.2 11.1

190108 10/15/1993 9/22/2004 5/18/1993 6/27/2005 10.9 12.1

2

320101 12/3/1996 8/7/2006 3/27/1996 8/28/2006 9.7 10.4

390106 8/14/1996 8/9/2006 11/5/1996 7/15/2008 10.0 11.7

310117 11/1/1995 4/24/2002 8/2/1995 7/9/2002 6.5 6.9

310118 11/1/1995 4/24/2002 8/3/1995 7/10/2002 6.5 6.9

3

190101 10/15/1993 9/22/2004 5/19/1993 6/28/2005 10.9 12.1

190103 10/15/1993 9/22/2004 5/19/1993 6/29/2005 10.9 12.1

050114 7/7/1995 4/6/2005 3/16/1994 5/12/2005 9.8 11.2

050114 7/7/1995 4/6/2005 3/16/1994 5/11/2005 9.8 11.2

4

040502 9/21/1990 3/24/2006 10/3/1991 9/15/2008 15.5 17.0

240505 6/11/1992 6/15/2006 8/25/1992 4/7/2009 14.0 16.6

270509 7/13/1993 6/6/2005 11/6/1990 6/7/2005 11.9 14.6

Table 26 shows the changes in IRI and SN that had occurred at the sections between the first 

and last dates expressed as magnitude of the change as well as the percent change. Only three 

sections showed a decrease in IRI between the first and last dates (310117 (Nebraska), 310118

(Nebraska), and 050116 (Arkansas)). The decrease in IRI at sections 310117 and 310118 in 

Nebraska occurred because of a treatment that was applied on the pavement. Of the 18 sections 

evaluated in this study, 12 sections showed a decrease in SN between the first and last dates, and 

6 sections showed an increase in SN. 
76

Table 26. Change in IRI and SN at evaluated sections.

Group

LTPP 

Section

IRI 

(inches/mi) SN

Change Between 

First and Last Date* Increase 

in IRI 

(percent)**

Decrease 

in SN

(percent)**

First 

Date

Last 

Date

First 

Date

Last 

Date

IRI 

(inches/mi) SN

1

050119 48 98 4.51 5.40 50 -0.89 105 -20

480114 46 65 10.90 10.39 19 0.51 42 5

310113 93 126 5.73 5.82 33 -0.09 35 -2

010102 62 204 2.86 2.19 143 0.67 232 23

390112 57 101 7.83 7.39 44 0.44 77 6

040123 52 138 7.94 7.26 86 0.68 163 9

190108 49 141 8.30 9.94 93 -1.64 191 -20

2

320101 57 57 11.91 11.23 0 0.68 0 6

390106 71 114 6.94 5.04 43 1.90 61 27

310117 68 53 8.32 7.30 -15 1.02 -22 12

310118 74 54 9.21 7.62 -20 1.59 -27 17

3

190101 83 159 7.48 7.62 76 -0.14 92 -2

190103 46 92 9.39 8.68 46 0.71 100 8

050114 49 72 4.26 5.13 23 -0.87 47 -20

050116 68 63 7.81 10.30 -5 -2.49 -7 -32

4

040502 60 244 5.91 4.78 184 1.13 307 19

240505 69 228 8.13 7.40 159 0.73 230 9

270509 54 117 5.94 5.78 63 0.16 117 3

*A positive change in IRI indicates that IRI of the section increased. A positive change in SN indicates that SN of the 

section decreased.

**Percent changes between first and last dates.

Some sections showed an increase in SN between the first and last dates. Some of the factors 

that may have contributed to the increase include hardening of the AC layer with age resulting in 

an increase in the structural layer coefficient for the asphalt layer, changes in moisture conditions 

in the GB/SB layers that resulted in an increase in the structural layer coefficient for these layers, 

or the effect of the temperature adjustment factor. The deflection below the load was adjusted 

to a standard temperature of 68 °F before computing the SN values using the temperature 

adjustment factors shown in the 1993 AASHTO Guide for Design of Pavement Structures.

(23)

However, each AC mix is expected to have unique adjustment factors, and the difference in the 

adjustment factors presented in the AASHTO Guide for Design of Pavement Structures with the 

actual behavior of the mix may result in errors when the deflections are adjusted to 68 °F.(23)

Figure 73 shows the relationship between changes in IRI and SN observed at the sections, and 

figure 74 shows this relationship for percent changes. Data for sections 310117 and 310118 in 

Nebraska, which had a treatment that caused a decrease in SN, are not shown in these plots.
77

Figure 73. Graph. Relationship between changes in IRI and SN.

Figure 74. Graph. Relationship between percent changes in IRI and SN.

As shown in these figures, there is no relationship between change or percent change in IRI 

and the change or percent change in SN. Because only three rigid pavements were evaluated, 

sufficient data were not available to conduct a similar comparison as presented for 

flexible pavements.

At all of the analyzed flexible pavement sections, continuous IRI plots for first and last dates 

were compared with SN values estimated from FWD measurements at the first and last dates. If 

there was a relationship between IRI and SN, it was hypothesized that areas where large changes 

in IRI had occurred should show large decreases in SN. However, such a relationship was not 
78

seen in the analyzed sections. Generally, no major changes in SN associated with localized areas 

were seen at the evaluated sections. However, in most sections, major IRI changes were noticed 

at localized areas within the section. At these areas, the changes in SN were not significantly 

different from changes in SN that had occurred at areas where major changes in IRI had not 

occurred. Comparison of continuous IRI plots with deflection below the FWD load and 

estimated subgrade modulus plots also did not show any relationship between changes in IRI 

and deflection or subgrade modulus or between changes in IRI and changes in deflection or 

subgrade modulus.

For the rigid pavements, the effective slab thickness instead of SN was used as the structural 

strength parameter in this study. Similar to flexible pavements, no relationship was seen between 

changes in IRI and changes in effective slab thickness.
79

CHAPTER 4. OTHER DATA ANALYSIS CONSIDERATIONS

4.1 INTRODUCTION

To validate the findings and conclusions presented in chapter 3, the following additional analyses 

were performed:

• Evaluation of maintenance and repair impacts, intended to demonstrate that maintenance 

and repair activities on the selected test sections had little, if any, impact on the study 

findings and conclusions.

• Review of IRI time-history data, intended to confirm that the change between the first 

and last IRI survey dates used in the analyses was reasonable and not due to outliers in 

the first or last dates. 

• Review of deflection time-history data, intended to confirm that the change between the 

first and last FWD (SN or Deff) test dates used in the analyses was reasonable and not due 

to outliers on the first or last dates.

• Assessment of PCC warping and curling, intended to address the effects of warping and 

curling on the study findings and conclusions for the PCC pavement test sections.

Each of these analyses is explained in this chapter. The first three are based on data specific to 

the study, while the fourth is based on the findings and conclusions from other literature and 

another FHWA study carried out at approximately the same time as this one.

4.2 EVALUATION OF MAINTENANCE AND REPAIR IMPACTS

Information on maintenance and repair activities for each of the test sections during the time 

periods in the study was obtained from the LTPP database to assess the potential impact of these 

activities on ride quality and structural adequacy. The following discussion addresses each of the 

maintenance activities reported along with the extent of the section affected (length or percent 

area of the test section). The main types of maintenance activities identified included crack 

sealing, seal coats, joint sealing, patching (partial-depth, full-depth, skin, and strip patching), 

and grinding. 

Crack sealing is intended to help reduce moisture infiltration through surface cracks into 

the layers below, which could accelerate pavement deterioration. This maintenance activity 

is not expected to improve the ride quality or structural adequacy of the pavement. Table 27

summarizes test sections where crack sealing was reported. As shown in the table, for sections 

where the quantity of crack sealing was reported, the quantity of treatment applied was small 

compared to the total length of the section.
80

Table 27. Test sections with crack sealing application.

LTPP Section Date Quantity

040502, Arizona 5/1/2002 Information not available in the LTPP database

050217, Arkansas 12/3/2002 Information not available in the LTPP database

270509, Minnesota 6/15/1991 10 ft

320101, Nevada 5/1/2002 98 ft

040123, Arizona 5/1/2001 248 ft

040123, Arizona 4/2/2002 Information not available in the LTPP database

The application of a fog seal coat was reported for LTPP section 040502 in Arizona, where it 

was applied three times: May 1998, August 2001, and April 2003. However, no information 

was provided about the area over which the treatment was applied. Similar to crack sealing, 

this maintenance activity is not expected to impact the ride quality or structural adequacy of 

the pavement. As noted in the next section, IRI over time data for the section do not indicate a 

reduction in IRI as a result of the fog seal coats.

Section 050217 in Arkansas is reported to have received joint sealing in February 1997. This 

maintenance activity helps reduce pumping, faulting, joint spalling, and blowups. Joint sealing 

will not improve the structural adequacy of a section. However, deflection values are consistent 

for this section through October 2003, which could be attributed, at least partially, to the 

application of the joint sealing in 1997.

Another maintenance activity reported for the sections in question is patching, which includes 

partial-depth patching (for PCC pavements), full-depth patching, skin patching, and strip 

patching. Patching helps temporarily or permanently address localized pavement distresses, 

which could improve structural adequacy and affect ride quality, depending on the type of 

patching. Table 28 summarizes the sections that received patching. As shown in the table, for 

those sections where the quantity of patching has been reported, the area of patching was 

relatively small compared to the total section. It is anticipated that only those sections that 

received full-depth patches may have affected ride quality and structural adequacy; however, 

no information on the patching extent is available to confirm this.
81

Table 28. Test sections with patching application.

LTPP 

Section

Maintenance 

Activity Date Maintenance Activity Description Quantity

050217 12/3/2002

Partial-depth patching of PCC 

pavements at joints 2 ft2

240505 4/1/2009

Machine premix patch (placing premix 

with paver roller)

Information not available 

in LTPP database

270509 8/1/2001 Skin patching* 76 ft2

190101 6/1/2001 Strip patching** 2,800 ft2

190103 7/1/2001 Strip patching 2,480 ft2

010102 4/17/2003 Strip patching

Information not available 

in LTPP database

010102 4/17/2003 Full-depth patching*** of AC pavement

Information not available 

in LTPP IMS database

050119 5/15/1999 Full-depth patching of AC pavement 560 ft2

190108 7/1/2001 Strip patching 3,120 ft2

*Skin patching is using hand tools or hot pot to apply liquid asphalt and aggregate.

**Strip patching is using a spreader and distributor to apply hot liquid asphalt and aggregate.

***Full-depth patching includes removing damaged material and repairing the supporting layer.

Another maintenance activity reported for the sections in question was grinding performed at 

two AC sections. Grinding, which can improve skid resistance and ride quality, is reported to 

have been applied over the entire area for sections 310117 and 310118 in Nebraska on July 12, 

2000. The grinding had a reported average depth of 0.5 inches, which could have slightly 

reduced structural adequacy. Both of these sections are in group 2 and were not considered in the 

analysis because of grinding that was carried out at the sections (see sections 3.10.3 and 3.10.4).

In summary, limited maintenance and repair activities were applied to some of the test sections 

during the time periods considered in the analysis. Those activities included crack sealing, PCC 

joint sealing, patching (skin, strip, and full-depth patching at AC sections and partial-depth 

patching at a section), and grinding. Of these, only full-depth patching and grinding may have 

affected ride quality, structural adequacy, or both. However, the impact depends on the extent of 

the patching. Further information on whether patching affected ride quality is provided in 

section 4.3. The effect of patching on the observed deflections is discussed in section 4.4.

4.3 REVIEW OF IRI TIME HISTORY DATA

In chapter 3, the change in IRI over time that occurred at a test section was evaluated by 

considering IRI at the first profile date and at the last profile date (i.e., the last date available in 

the database). The time-sequence IRI values at the test sections that were used in this study were 

evaluated to investigate if any sudden drops in IRI could be noticed, which would indicate that 

maintenance or a rehabilitation activity had occurred at that site.

The changes in IRI that occurred at the test sections were evaluated by preparing a table and then 

using the data from this table to prepare plots, with time = 0 being assigned to the construction 

date of the test section. The construction date was assumed to be the date the section was opened 
82

to traffic except for a few sections. For LTPP sections 050119 (Arkansas), 190108 (Iowa), 

190101 (Iowa), 190103 (Iowa), 050114 (Arkansas), and 050116 (Arkansas), the first FWD 

date was before the traffic open date. The first FWD date for these sections was assigned 

as the construction date. For LTPP section 390205 (Ohio), the first profile date was before the 

traffic open date, and the first profile date was assigned as the construction date for this section. 

Table 29 shows the construction dates assigned to the sections as well as the first profile and first 

FWD dates.

Table 29. Construction date of test sections.

Group

LTPP 

Section State

Construction 

Date

First IRI 

Date

First FWD 

Date

1

050119 Arkansas 3/15/1994 7/6/1995 3/15/1994

480114 Texas 6/1/1997 9/8/1997 11/17/1997

310113 Nebraska 8/1/1995 11/1/1995 8/3/1995

010102 Alabama 3/1/1993 8/25/1994 6/21/1995

390112 Ohio 9/1/1995 8/14/1996 11/6/1996

040123 Arizona 8/1/1993 1/27/1994 2/16/1994

190108 Iowa 5/18/1993 10/15/1993 5/18/1993

2

320101 Nevada 9/1/1995 12/3/1996 3/27/1996

390106 Ohio 9/1/1995 8/14/1996 11/5/1996

310117 Nebraska 1/1/1995 11/1/1995 8/2/1995

310118 Nebraska 1/1/1995 11/1/1995 8/3/1995

3

190101 Iowa 5/19/1993 10/15/1993 5/19/1993

190103 Iowa 5/19/1993 10/15/1993 5/19/1993

050114 Arkansas 3/16/1994 7/7/1995 3/16/1994

050116 Arkansas 3/16/1994 7/7/1995 3/16/1994

4

040502 Arizona 4/20/1990 9/21/1990 10/3/1991

240505 Maryland 3/31/1992 6/11/1992 8/25/1992

270509 Minnesota 9/15/1990 7/13/1993 11/6/1990

5

040213 Arizona 10/1/1993 1/25/1994 2/8/1994

050217 Arkansas 12/1/1995 2/6/1997 11/14/1996

390205 Ohio 8/14/1996 8/14/1996 12/30/1996

Table 30 shows the time-sequence right wheel path IRI values of the test sections. The IRI 

values shown are the average IRI obtained from the five profiler runs performed at the test 

section on each test date. The time shown in the table is the time from the construction date, 

with time being zero at the construction date. Appendix C includes plots of the time-sequence 

IRI values.
83

Table 30. Time-sequence IRI values at test sections.

Group Section Profile Date

Time 

(years)

Right Wheel 

Path IRI 

(inches/mi)

1

050119,

Arkansas

7/6/1995 1.3 48

7/1/1997 3.3 49

1/22/2001 6.9 82

4/1/2002 8.1 79

4/23/2003 9.1 81

3/19/2004 10.0 98

480114,

Texas

9/8/1997 0.3 46

4/2/1998 0.8 54

12/10/1999 2.5 47

5/9/2000 2.9 44

4/24/2001 3.9 47

10/17/2001 4.4 53

5/21/2003 6.0 61

5/22/2003 6.0 62

1/21/2005 7.6 62

12/2/2005 8.5 63

3/19/2007 9.8 66

310113,

Nebraska

11/1/1995 0.2 94

4/17/1996 0.7 114

2/18/1997 1.5 114

5/16/1998 2.8 125

5/7/1999 3.8 121

10/13/1999 4.2 115

3/20/2000 4.6 125

010102,

Alabama

8/25/1994 1.5 61

1/10/1996 2.9 56

7/3/1997 4.3 57

1/27/1998 4.9 66

9/28/1999 6.6 79

3/14/2001 8.0 91

3/10/2002 9.0 56

1/29/2003 9.9 140

4/27/2004 11.2 209

5/4/2005 12.2 205
84

Table 30. Time-sequence IRI values at test sections—continued.

Group Section Profile Date

Time 

(years)

Right Wheel 

Path IRI 

(inches/mi)

1

390112,

Ohio

8/14/1996 1.0 58

12/27/1996 1.3 58

12/8/1997 2.3 70

11/12/1998 3.2 86

10/20/1999 4.1 91

8/16/2000 5.0 92

11/4/2001 6.2 97

12/6/2002 7.3 92

2/4/2004 8.4 101

5/5/2005 9.7 98

040123,

Arizona

1/27/1994 0.5 53

2/27/1995 1.6 47

1/23/1997 3.5 56

4/8/1998 4.7 54

12/4/1998 5.3 54

11/17/1999 6.3 58

12/19/2000 7.4 59

11/6/2001 8.3 70

2/20/2002 8.6 59

3/2/2003 9.6 56

3/10/2004 10.6 93

3/15/2005 11.6 69

3/27/2006 12.7 113

190108,

Iowa

10/15/1993 0.4 53

2/15/1995 1.7 51

4/16/1996 2.9 60

9/25/1997 4.4 83

10/13/1998 5.4 104

7/19/1999 6.2 114

5/22/2000 7.0 120

5/29/2001 8.0 134

8/6/2001 8.2 119

11/22/2002 9.5 123

9/22/2004 11.4 139
85

Table 30. Time-sequence IRI values at test sections—continued.

Group Section Profile Date

Time 

(years)

Right Wheel 

Path IRI 

(inches/mi)

2

320101,

Nevada

12/3/1996 1.3 58

4/22/1997 1.6 57

11/18/1997 2.2 59

8/28/1998 3.0 58

10/16/1999 4.1 57

6/14/2000 4.8 56

6/19/2001 5.8 56

6/10/2002 6.8 56

7/31/2002 6.9 56

10/13/2003 8.1 57

8/4/2004 8.9 57

8/27/2006 11.0 56

390106,

Ohio

8/14/1996 1.0 71

12/27/1996 1.3 74

12/8/1997 2.3 96

11/12/1998 3.2 105

10/20/1999 4.1 107

8/16/2000 5.0 108

11/4/2001 6.2 109

12/6/2002 7.3 109

4/29/2003 7.7 111

2/4/2004 8.4 126

5/5/2005 9.7 119

8/9/2006 10.9 118

310117,

Nebraska

11/1/1995 0.8 68

4/17/1996 1.3 81

2/18/1997 2.1 63

5/16/1998 3.4 67

5/7/1999 4.3 66

10/13/1999 4.8 63

3/20/2000 5.2 67

5/16/2001 6.4 75

4/24/2002 7.3 54
86

Table 30. Time-sequence IRI values at test sections—continued.

Group Section Profile Date

Time 

(years)

Right Wheel 

Path IRI 

(inches/mi)

2

310118,

Nebraska

11/1/1995 0.8 74

4/17/1996 1.3 82

2/18/1997 2.1 81

5/16/1998 3.4 82

5/7/1999 4.3 82

10/13/1999 4.8 76

3/20/2000 5.2 82

5/16/2001 6.4 63

4/24/2002 7.3 54

3

190101,

Iowa

10/15/1993 0.4 85

2/15/1995 1.7 91

4/16/1996 2.9 94

9/25/1997 4.4 100

10/13/1998 5.4 111

7/19/1999 6.2 119

5/22/2000 7.0 122

5/29/2001 8.0 121

8/6/2001 8.2 115

11/22/2002 9.5 121

9/22/2004 11.4 158

190103,

Iowa

10/15/1993 0.4 46

2/15/1995 1.7 52

4/16/1996 2.9 61

9/25/1997 4.4 66

10/13/1998 5.4 72

7/19/1999 6.2 73

5/22/2000 7.0 77

5/29/2001 8.0 87

8/6/2001 8.2 89

11/22/2002 9.5 85

9/22/2004 11.4 92

050114,

Arkansas

7/7/1995 1.3 50

7/1/1997 3.3 53

1/22/2001 6.9 57

4/1/2002 8.0 62

4/23/2003 9.1 62

3/19/2004 10.0 61

4/6/2005 11.1 72
87

Table 30. Time-sequence IRI values at test sections—continued.

Group Section Profile Date

Time 

(years)

Right Wheel 

Path IRI 

(inches/mi)

3 050116,

Arkansas

7/7/1995 1.3 67

7/1/1997 3.3 59

1/22/2001 6.9 61

4/1/2002 8.0 66

4/23/2003 9.1 62

3/19/2004 10.0 62

4/6/2005 11.1 63

4

040502,

Arizona

9/21/1990 0.4 60

1/15/1992 1.7 70

2/22/1993 2.8 66

2/3/1997 6.8 81

12/9/1997 7.6 88

12/11/1998 8.6 112

11/11/1999 9.6 129

12/6/2000 10.6 139

11/15/2001 11.6 169

11/4/2002 12.6 162

2/6/2004 13.8 192

12/14/2004 14.7 191

3/24/2006 15.9 241

240505,

Maryland

6/11/1992 0.2 66

6/25/1993 1.2 71

12/6/1995 3.7 75

12/10/1996 4.7 84

12/18/1997 5.7 88

8/19/1998 6.4 96

10/20/1999 7.6 118

12/5/2000 8.7 95

10/8/2002 10.5 98

11/14/2003 11.6 100

6/30/2004 12.3 116

4/26/2005 13.1 134

9/22/2005 13.5 115

6/15/2006 14.2 207
88

Table 30. Time-sequence IRI values at test sections—continued.

Group Section Profile Date

Time 

(years)

Right Wheel 

Path IRI 

(inches/mi)

4 270509,

Minnesota

7/13/1991 0.8 55

10/31/1992 2.1 66

11/16/1993 3.2 70

7/17/1994 3.8 76

7/16/1997 6.8 102

9/30/1998 8.0 114

6/10/1999 8.7 117

9/20/2000 10.0 124

8/19/2001 10.9 100

12/10/2002 12.2 100

2/25/2004 13.5 106

10/9/2004 14.1 113

6/6/2005 14.7 115

5

040213,

Arizona

1/25/1994 0.3 94

3/5/1995 1.4 82

1/27/1997 3.3 108

12/4/1997 4.2 114

12/8/1998 5.2 115

11/15/1999 6.1 127

12/5/2000 7.2 116

11/8/2001 8.1 129

10/30/2002 9.1 116

2/4/2004 10.4 101

12/12/2004 11.2 114

8/11/2006 12.9 165

050217,

Arkansas

2/6/1997 1.2 85

11/16/2000 5.0 91

4/3/2002 6.3 127

4/9/2003 7.4 89

3/12/2004 8.3 135

4/2/2005 9.3 135
89

Table 30. Time-sequence IRI values at test sections—continued.

Group Section Profile Date

Time 

(years)

Right Wheel 

Path IRI 

(inches/mi)

5 390205,

Ohio

8/14/1996 0.0 87

12/27/1996 0.4 82

12/8/1997 1.3 90

11/12/1998 2.2 91

10/20/1999 3.2 91

8/16/2000 4.0 92

11/4/2001 5.2 100

12/6/2002 6.3 90

4/29/2003 6.7 98

2/4/2004 7.5 101

5/5/2005 8.7 130

8/8/2006 10.0 163

Lateral variations in the profiled paths can affect the IRI value.

(26) Hence, some variability in the 

time-sequence IRI values is expected. Maintenance activities, such as patching and spall repairs 

(PCC pavements) that repair pavement distress, can cause a reduction in IRI. Placement of an 

AC overlay will cause a significant reduction in IRI. After maintenance or rehabilitation, the 

IRI values will show a gradual increase with time. An IRI value that is greater than the previous 

and subsequent values is likely the result of lateral variability in the profiled path. Such a 

phenomenon can occur in PCC pavements due to curling and warping effects.

The time-sequence IRI values were evaluated to determine if evidence of maintenance 

or rehabilitation could be detected. A reduction in IRI greater than 10 inches/mi between 

two adjacent profile dates was noted in the time-sequence IRI values at the following sections:

• Group 1, section 010102 (Alabama): IRI for March 14, 2001, March 10, 2002, and 

January 29, 2003, were 91, 56, and 140 inches/mi, respectively. The cause of the sudden 

drop in IRI for March 10, 2002, is not clear. The tables do not indicate maintenance was 

carried out on this section between March 14, 2001, and March 10, 2002. 

• Group 1, section 040123 (Arizona): IRI ranged between 56 and 59 inches/mi from 

January 23, 1997, (3d profile date) to March 2, 2003, (10th profile date), except for 

November 6, 2001, (8th profile date), when the IRI value was 70 inches/mi. The reason 

for a high IRI value on November 6, 2001, is not clear. The IRI on March 2, 2003,

(10th profile date) was 56 inches/mi. The IRI values for the profile dates subsequent to 

March 2, 2003 (March 10, 2004, March 15, 2005, and March 27, 2006) were 93, 69, and 

113 inches/mi, respectively. These values show a drop in IRI of 24 inches/mi between 

March 10, 2004, and March 15, 2006, and an increase in IRI of 44 inches/mi between 

March 15, 2005, and March 27, 2006. IRI values for the five runs on each of these dates 

showed significant variations, and the operator comments indicated there was cracking 

and raveling along the wheel-paths. The maintenance tables do not indicate repairs were 
90

carried out on this section during this time frame. Accordingly, the variations in IRI noted 

at this section seem to be caused by lateral variations in the profiled path.

• Group 1, section 190108 (Iowa): The last four IRI values at this section (May 29, 2001,

August 6, 2001, November 22, 2002, and September 22, 2004) were 134, 119, 123, and 

139 inches/mi, respectively. These values show a drop in IRI of 15 inches/mi between 

May 29, 2001, and August 6, 2001. The maintenance tables indicate that strip patching 

was performed on this section on July 1, 2001. The reduction in IRI seen between 

May 29, 2001, and August 6, 2001, may be due to this patching.

• Group 2, section 310117 (Nebraska): IRI ranged between 63 and 68 inches/mi for the 

seven profile dates between November 1, 1995, and March 20, 2000. However, IRI at the 

second profile date on April 17, 1996, was 81 inches/mi. The reason for the high IRI 

value is not clear. IRI on May 16, 2001 (eighth profile date) and April 24, 2002 (ninth 

and last profile date) were 75 and 54 inches/mi, with a reduction in IRI of 21 inches/mi 

occurring between the two test dates. The maintenance tables indicate grinding was 

performed on this section around this time period, and the reduction in IRI is attributed to 

this grinding. IRI at the first profile date for this section was 68 inches/mi, and IRI at the 

last profile date was 54 inches/mi, which was less than the IRI at the first profile date.

• Group 2, section 310118 (Nebraska): IRI for March 20, 2000 (seventh profile date), 

May 16, 2001 (eighth profile date), and April 24, 2002 (ninth and last profile date) were 

82, 63, and 54 inches/mi, respectively, with a reduction in IRI of 19 inches/mi occurring 

between March 20, 2000, and May 16, 2001. IRI reduced further by 9 inches/mi between 

May 16, 2001, and April 24, 2002. The maintenance tables indicate grinding was 

performed on this section around this time period, and the reduction in IRI probably 

occurred because of the grinding. The IRI at the first profile date for this section was 

74 inches/mi, and IRI at the last profile date was 54 inches/mi, which was less than the 

IRI at the first profile date.

• Group 4, section 240505 (Maryland): IRI from June 11, 1992 (1st profile date) to 

June 30, 2004 (11th profile date) gradually increased from 66 to 116 inches/mi. However 

on October 20, 1999 (seventh profile date), IRI was 118 inches/mi, with the IRI previous 

to this date being 96 inches/mi and the IRI subsequent to this date being 95 inches/mi. 

The maintenance tables do not indicate any activity performed between October 20, 

1999, and December 5, 2000, on this section. Hence, the cause for the high IRI on 

October 29, 1999, is not clear. The IRI for the last three profile dates (April 26, 2005, 

September 22, 2005, and June 15, 2006) were 134, 115, and 207 inches/mi, respectively. 

The maintenance tables do not indicate any maintenance activities occurred within this 

section between April 26, 2005, and September 22, 2005. The profile operator 

comments indicated that cracking was present in the section, and a reduction in IRI 

was noted between April 26, 2005, and September 22, 2005. The increase in IRI from

September 22, 2005, to June 15, 2006, may have occurred because of lateral variability 

in the profiled path.

• Group 4, section 270509 (Minnesota): IRI on September 20, 2000 (eighth profile date) 

and August 19, 2001 (ninth profile date) were 124 and 100 inches/mi, respectively. 
91

Thereafter, from December 2, 2002 (10th profile date) to June 6, 2005 (13th and last

profile date), IRI showed a gradual increase from 100 to 115 inches/mi. These IRI trends 

indicate some type of maintenance activity was performed on this section between 

September 20, 2000, and August 19, 2001. The maintenance tables indicate skin patching 

was performed on August 1, 2001, which probably caused the reduction in roughness.

• Group 5, section 040213 (Arizona): IRI increased from 94 to 114 inches/mi from 

January 25, 1994, to December 12, 2004, with this section being profiled 11 times during 

this period. The time-sequence IRI values were variable, with four reductions in IRI 

greater than 10 inches/mi between subsequent profile dates during this period. The cause 

for this reduction in IRI as well as the variability in the IRI values is not clear and may be 

due to curling and warping effects of the PCC pavement. 

• Group 5, section 050217 (Arkansas): IRI was 89 inches/mi on April 9, 2003, 

127 inches/mi on April 3, 2002, and 135 inches/mi on March 12, 2004. The cause 

for the low IRI value on April 9, 2003, is not clear and may be due to curling or 

warping effects of the PCC slab. 

• Group 5, section 390205 (Ohio): IRI was 100 inches/mi on November 4, 2001, 

92 inches/mi on August 16, 2000, and 90 inches/mi on December 6, 2002. The cause 

for the high IRI value on August 16, 2000, is not clear and may be due to curling or 

warping effects of the concrete slab. 

As described, there were several cases where an IRI value for a particular date was higher than 

the preceding and subsequent IRI values. Also, variable IRI values over time were noted at one 

PCC section. An evaluation of the profile data to investigate the cause for the high IRI or 

variable IRI was not performed because it was outside the scope of this study.

For sections 310117 and 310118 in Nebraska, the IRI on the last profile date was less than the 

IRI at the first profile date because of grinding. These two sections were not used in the analysis 

to determine the relationship between ride quality and structural strength.

For the remaining sections, a reduction in ride quality between subsequent profile dates could 

be attributed to maintenance activities for only two test sections: sections 190108 (Iowa) and 

270509 (Minnesota). In the case of the former, strip patching is believed to have caused IRI to 

decrease by 15 inches/mi (from 134 to 119 inches/mi), but IRI increased to 139 inches/mi in 

3 years. For the latter, skin patching is believed to have caused an IRI reduction of 24 inches/mi 

(from 124 to 100 inches/mi). Subsequently, IRI increased to 115 inches/mi in 4 years. Neither 

maintenance activity is expected to have a significant effect on the structural adequacy of 

the pavement. 

Based on the review of the time-sequence IRI data, using the IRI at the first and last profile dates 

to determine the change in IRI that occurred at the test section appears reasonable. The selected 

data values do not appear to be influenced by errors in data collection that would have influenced 

the IRI value.
92

4.4 REVIEW OF DEFLECTION TIME HISTORY DATA

In chapter 3, the change in SN that occurred over time at a test section was evaluated by 

considering SN determined from the first and last FWD dates (i.e., last FWD date available in 

the database). The time-sequence average deflection values obtained below the center of the load 

plate for a 9,000-lb load at the test sections were studied to evaluate the changes in deflection 

over time. Such a plot shows if the deflections were affected by patching that was performed at 

the test sections and also verifies that that the first and last SN values used in the analysis were 

not outliers.

The modulus of the AC layer changes with temperature, and deflections obtained on ACsurfaced pavements depend on the temperature. The deflection below the load was adjusted to a 

standard temperature of 68 °F before evaluating the deflections. The deflection adjustment was 

performed using the procedure outlined in the 1993 AASHTO Guide for Design of Pavement 

Structures.

(23) The AC modulus versus temperature relationship depends on the properties of the 

AC mix. However, only one set of adjustment factors are provided in the guide and applied to all 

AC surfaces irrespective of mix properties. The guide presents adjustment factors for AC 

temperatures between 30 and 120 °F. The validity of these adjustment factors when correcting 

the deflection from a temperature close to the limits (i.e., 30 and 120 °F) could be questionable. 

Seasonal effects that cause changes in moisture conditions in the base/subbase and subgrade also 

can have a significant effect on the deflection measured below the load.

Table 31 shows the time-sequence average deflection below the load for a 9,000-lb load 

corrected to a temperature of 68 °F for each section. The temperature at the mid-depth of the 

surface layer (i.e., AC for AC-surfaced pavements and PCC for PCC-surfaced pavements) at 

the time of testing is also shown in this table. For AC-surfaced pavements, the deflections shown

are those obtained along the right wheel path, and the value shown is the average of all 

deflections obtained within the section. For PCC sections, the average deflections obtained at the 

center of the slab are shown. The time-sequence deflection plots are included in appendix D. 

For each section, a plot showing the time-sequence temperature values at the mid-depth of the 

surface layer is shown below the deflection plot.

Table 31. Time-sequence deflection values at test sections.

Group Section

FWD Test 

Date

Time 

(years)

Avg. Deflection Below 

Load for 9,000 lb 

Corrected for 

Temperature (mil)

Temperature

of AC (°F)

Deflections

Avg.

(mil)

Std 

Dev 

(mil)

COV

(Percent)

1 050119

3/15/1994 0.0 7.40 65

5.97 0.73 12

2/5/1996 1.9 4.92 27

3/12/1999 5.0 6.07 56

4/5/2001 7.1 6.17 72

4/29/2003 9.1 5.45 78

3/4/2004 10.0 6.21 61

5/24/2004 10.2 5.54 82
93

Table 31. Time-sequence deflection values at test sections—continued.

Group Section

FWD Test 

Date

Time 

(years)

Avg. Deflection Below 

Load for 9,000 lb 

Corrected for 

Temperature (mil)

Temperature 

of AC (°F)

Deflections

Avg.

(mil)

Std 

Dev 

(mil)

COV

(Percent)

1

480114

11/17/1997 0.5 5.99 54

5.20 0.40 8

8/19/1999 2.2 4.82 130

5/10/2000 2.9 4.95 86

2/13/2002 4.7 4.88 70

11/12/2003 6.5 5.22 85

6/24/2004 7.1 5.34 87

310113

8/3/1995 0.0 27.43 103

6/11/1997 1.9 29.01 84 26.76 2.17 8

10/14/1999 4.2 23.84 59

010102

3/10/1993 0.0 5.27 84

4.50 1.01 23

6/20/1995 2.3 5.93 104

4/18/1996 3.1 4.60 88

7/22/1998 5.4 5.62 98

5/18/2000 7.2 4.54 100

5/23/2002 9.2 3.85 87

2/20/2004 11.0 2.94 64

4/28/2005 12.2 3.28 73

390112

11/6/1996 1.2 3.98 61

5.21 0.78 15 9/16/1999 4.0 5.23 63

4/12/2001 5.6 5.50 83

9/1/2004 9.0 6.13 93

0401223

2/16/1994 0.5 3.06 71

2.98 0.28 9

2/17/1995 1.5 2.87 74

1/7/1998 4.4 2.63 65

2/11/1999 5.5 2.60 59

5/2/2001 7.8 3.45 79

4/14/2003 9.7 3.20 94

4/7/2005 11.7 3.03 78

190108

5/18/1993 0.0 11.91 70

9.31 1.23 13

9/11/1995 2.3 8.94 66

5/12/1997 4.0 8.92 63

10/5/1999 6.4 8.64 54

2/13/2001 7.7 9.42 44

6/27/2005 12.1 8.05 114
94

Table 31. Time-sequence deflection values at test sections—continued.

Group Section

FWD Test 

Date

Time 

(years)

Avg. Deflection Below 

Load for 9,000 lb 

Corrected for 

Temperature (mil)

Temperature 

of AC (°F)

Deflections

Avg.

(mil)

Std 

Dev 

(mil)

COV

(Percent)

2

320101

3/27/1996 0.6 7.02 71

7.32 0.70 10

3/13/1997 1.5 6.02 67

8/19/1999 4.0 8.10 112

3/24/2000 4.6 6.89 70

3/6/2001 5.5 6.90 61

3/19/2003 7.6 8.05 63

3/29/2004 8.6 7.00 68

3/22/2005 9.6 7.58 52

8/28/2006 11.0 8.04 79

390106

11/5/1996 1.2 4.69 57

6.71 1.78 27

12/19/1997 2.3 4.86 48

9/15/1999 4.0 6.45 97

4/12/2001 5.6 6.89 72

10/8/2004 9.1 7.34 62

7/15/2008 12.9 10.04 89

310117

8/2/1995 0.6 10.82 103

12.10 2.17 18 6/9/1997 2.4 10.64 92

10/12/1999 4.8 11.09 84

7/9/2002 7.5 15.84 112

310118

8/3/1995 0.6 9.82 82

11.00 3.60 33 6/10/1997 2.4 9.72 99

10/13/1999 4.8 7.45 81

7/10/2002 7.5 17.03 90

3

190101

5/19/1993 0.0 14.69 74

13.71 0.90 7

4/25/1995 1.9 12.02 83

9/12/1995 2.3 13.53 68

10/8/1999 6.4 13.43 64

2/16/2001 7.8 13.90 34

6/28/2005 12.1 14.68 113

190103

5/19/1993 0.0 7.27 94

6.41 1.12 18

9/23/1993 0.3 5.64 69

9/13/1995 2.3 5.78 79

5/14/1997 4.0 6.06 73

10/8/1999 6.4 5.64 73

2/20/2001 7.8 5.64 42

6/29/2005 12.1 8.81 88
95

Table 31. Time-sequence deflection values at test sections—continued.

Group Section

FWD Test 

Date

Time 

(years)

Avg. Deflection Below 

Load for 9,000 lb 

Corrected for 

Temperature (mil)

Temperature 

of AC (°F)

Deflections

Avg.

(mil)

Std 

Dev 

(mil)

COV

(Percent)

3

050114

3/16/1994 0.0 11.05 86

6.35 1.41 22

2/7/1996 1.9 7.90 47

3/16/1999 5.0 6.99 85

4/9/2001 7.1 7.06 107

5/1/2003 9.1 7.17 81

5/26/2004 10.2 6.49 99

5/12/2005 11.2 7.65 91

050116

3/16/1994 0.0 3.56 86

3.25 0.43 13

2/6/1996 1.9 2.95 47

3/15/1999 5.0 2.75 85

4/9/2001 7.1 2.80 107

4/30/2003 9.1 3.87 81

5/25/2004 10.2 3.76 99

5/11/2005 11.2 3.04 91

4

040502

1/16/1991 0.7 6.88 57

9.47 3.46 36

10/3/1991 1.5 4.05 90

10/19/1994 4.5 8.25 99

9/12/1996 6.4 7.25 111

11/13/1997 7.6 10.15 73

12/10/1998 8.6 13.88 55

12/14/1999 9.7 15.96 54

10/17/2000 10.5 8.33 98

12/11/2002 12.7 10.73 77

12/11/2003 13.7 12.78 73

9/15/2008 18.4 5.87 126

240505

8/25/1992 0.4 6.58 94

6.45 0.81 13

8/8/1994 2.4 6.30 107

10/16/1995 3.5 6.46 68

5/7/1997 5.1 6.30 93

7/7/1999 7.3 5.02 118

8/28/2001 9.4 6.27 92

6/25/2003 11.2 5.87 111

6/8/2004 12.2 6.33 109

5/25/2005 13.2 8.42 63

4/7/2009 17.0 6.98 60
96

Table 31. Time-sequence deflection values at test sections—continued.

Group Section

FWD Test 

Date

Time 

(years)

Avg. Deflection Below 

Load for 9,000 lb 

Corrected for 

Temperature (mil)

Temperature 

of AC (°F)

Deflections

Avg.

(mil)

Std 

Dev 

(mil)

COV

(Percent)

4 270509

6/18/1991 0.8 13.89 101

11.88 2.35 20

6/17/1992 1.8 10.78 80

9/29/1993 3.0 7.95 52

8/23/1995 4.9 16.20 108

6/7/1999 8.7 12.45 83

8/21/2001 10.9 10.03 82

8/20/2003 12.9 12.61 99

6/7/2005 14.7 11.15 99

5

040213

2/8/1994 0.4 4.41 60

6.62 2.52 38

3/6/1995 1.4 12.58 80

11/6/1997 4.1 6.08 85

1/11/1999 5.3 4.95 63

12/7/2001 8.2 5.81 65

12/18/2003 10.2 6.45 68

12/15/2004 11.2 6.09 72

050217

11/14/1996 1.0 3.48 49

3.27 0.25 8

4/21/1999 3.4 3.46 81

7/30/2001 5.7 3.46 100

10/9/2003 7.9 3.10 69

9/20/2004 8.8 2.85 77

390205

12/30/1996 0.4 4.68 48

6.05 1.06 17

7/22/1997 0.9 5.10 78

9/10/1999 3.1 5.51 84

4/4/2001 4.6 6.83 79

4/15/2003 6.7 7.73 90

9/9/2004 8.1 6.47 67

COV = Coefficient of variation.

Evaluation of the time-sequence data showed that major changes in deflections had not 

occurred at most sites. At 15 of the 21 sections evaluated in this study, the coefficient of 

variation (COV) of the time-sequence deflection values was 20 percent or less. COV values 

greater than 20 percent were obtained at the following sites: 010102 in Alabama (23 percent), 

390106 in Ohio (27 percent), 310118 in Nebraska (33 percent), 050114 in Arkansas (22 percent), 

040502 in Arizona (36 percent), and 040213 in Arizona (38 percent). Section 310118 in 

Nebraska was not used in the analysis. 
97

The following observations were made at the other sections that had COV values greater than

20 percent:

• 010102 (Alabama): Overall, the time-sequence deflection data showed a decrease with 

time with some scatter, which caused the high COV value.

• 390106 (Ohio): The time-sequence deflection data showed an increase over time, which 

caused the high COV value.

• 050114 (Arkansas): The average deflection for the first FWD date was much higher than 

the average deflection at the other test dates and is attributed as the cause for the high 

COV. The cause for the high deflections at the first FWD date is not clear.

• 040502 (Arizona): The time-sequence deflections showed large variability. The 

temperature at time of testing at this section for the different test dates ranged from 54 to 

126 °F. The variability in the deflections may be related to the effects of the temperature 

adjustment factor.

• 040213 (Arizona): This is a PCC section, and the deflection in March 1996 was more 

than double the deflections obtained at the other test section, which resulted in a high 

COV value. The high deflection may be due to excessive downward curing at the time 

of testing.

Table 28 shows the patching activities performed on the test sections. There are two cases where 

full-depth patching was performed. If this patching was along the right wheel path where FWD 

deflections were performed, the SN value of the pavement may show an increase over the SN

obtained for the previous FWD date. However, the increase in SN depends on the quantity of 

patching that was performed. Section 050119 had 560 ft2 of full-depth patching, and the average 

deflection after the patching was only 2 percent less than that before patching. Hence, no 

increase in SN was expected at this section due to patching. The amount of full-depth patching 

performed on section 190108 is unknown. Skin patching and strip patching are expected to have 

little, if any, any impact on the structural strength of the pavement. The reason strip patching was 

performed is not known; filling of ruts is a possible reason.

Based on the review of the time-sequence deflection values, the use of the first and last FWD 

deflections at a site to characterize the change in SN appears to be reasonable.

4.5 ASSESSMENT OF PCC WARPING AND CURLING

4.5.1 Curling and Warping of Slabs

The shape of PCC slabs in a pavement can vary depending on the temperature and moisture 

gradient within the slab. A concrete slab can take the following shapes: (1) curled up, when the 

joints are at a higher elevation than the center of the slab, (2) curled down, when the center of the 

slab is at a higher elevation than the joints, or (3) flat. Changes in the slab shape caused by 

temperature effects are referred to as curling, while changes in the slab shape due to moisture 

effects are referred to as warping. 
98

When the temperature of the pavement surface is lower than the temperature at the bottom of the 

slab in the night and early morning hours, the edges of the slab tend to curl upward. When the 

surface of the slab heats up during the day and is at a higher temperature than the bottom of

the slab, the edges of the slab tends to curl downward. These changes in slab shape due to 

temperature are superimposed on the original shape of the slab. Usually, a pavement can either 

be curled upward or downward, and the temperature gradient influences the severity of the 

curvature.(26) A PCC slab can change shape from a curled up position during the early morning 

hours to a curled down position in the afternoon as the surface of the pavements heats up. The 

curvature that is built into the slab depends on factors such as mix properties, base support, slab 

length, slab thickness, and temperature and moisture conditions during curing.

(26)

Changes in the 

moisture within a slab can also cause a slab to change shape, and these changes occur over time. 

For example, if the moisture content in the top portion of the slab reduces over time and is less 

than at the bottom of the slab, the edges of the slab will curl upward. 

Curvature in a slab (either upward or downward) contributes to roughness. Byrum et al. 

developed an equation to predict the IRI due to slab curvature.(27) From an analysis of GPS-3 

data in the LTPP database, Byrum et al. noted undoweled slabs have a higher level of curvature 

compared to doweled slabs.

4.5.2 Diurnal Changes in IRI

As discussed in the previous section, the shape of a PCC slab can change during the day due to 

temperature variations, which causes changes in roughness. Karamihas et al. presented IRI 

changes that occurred because of temperature-related slab curling at 11 test sections in the 

Michigan SPS-2 project.(28) Profile measurements were obtained on March 28, 1997, at this 

SPS-2 project starting at 5:07 a.m. and ending at 3:42 p.m., with measurements obtained over 

approximately 10 h. The air temperature during this period increased from 51 to 74 °F. Three of 

the pavement sections in this project showed no change in IRI over the period. The mean IRI 

(average of left and right wheel paths) of six sections decreased continuously during testing, with 

the reduction in IRI ranging from 10 to 25 inches/mi. All of these sections were curled up, and 

the degree of the upward curling reduced as the air temperature increased, resulting in a decrease 

in IRI. Two sections showed increases in IRI ranging from 6 to 12 inches/mi. Both of these 

sections were curled downwards, and the degree of downward curling increased with the 

increase in air temperature, causing IRI to increase.

4.5.3 Changes in IRI Over Time

Karamihas and Senn studied the progression of IRI at 21 test sections (12 LTPP sections 

and 9 State supplemental sections) at the LTPP SPS-2 project in Arizona over 16 years after 

construction.(29) Two of the supplemental sections were surfaced with AC, and the other 

seven sections were surfaced with PCC. Four of the PCC sections were non-doweled, and the 

other three were doweled and had designs that were of interest to the Arizona Department of 

Transportation. The results obtained by Karamihas and Senn at the 12 LTPP SPS-2 sections 

are presented in this section.(29)

Investigation of the profiles obtained at the SPS-2 sections indicated roughness in some test 

sections was caused by longitudinal and transverse cracking and some built-in localized defects. 
99

However, slab curvature had a significant contribution to roughness in some sections and, in 

some cases, was the dominant contributor to roughness. Evaluation of the time-sequence 

roughness values at the test sections showed significant variability in roughness from year to 

year at many sections because of changes in slab curvature due to diurnal and seasonal effects. In 

this study, objective profile analysis methods were used to quantify the level of slab curvature in 

each section. A procedure for estimating the gross strain gradient needed to deform the slab to 

the shape noted in the profile was developed to produce a pseudo strain gradient (PSG) value. 

The level of slab curvature in the section was then summarized by the average PSG value. 

Variations in the average PSG over time were able to explain the changes in roughness over time 

at the sections that had a PCC design flexural strength of 550 psi. A good correlation existed at 

these sections between the change in IRI and the change in PSG. Table 32 shows the change in 

IRI that occurred at the test sections that were designed for a flexural strength of 550 psi over a 

16-year period, with a positive change indicating an increase in IRI. This table also shows the 

IRI when the IRI contribution caused by slab curvature was removed. All of these sections were 

curled up, and the degree of upward curling increased with time. The increase in upward curling 

of the slabs was the major contributor to the increase in IRI at these test sections. Although not 

stated by Karamihas and Senn, the increase in upward curling with time was likely related to 

slab warping.

Table 32. Results for sections designed for flexural strength of 550 psi.

Factor

Section

040213 040217 040221 040215 040219 040223

PCC flexural strength (psi) 550 550 550 550 550 550

PCC thickness (inches) 8 8 8 11 11 11

Base type DGAB LCB PATB DGAB LCB PATB

Direction of curl Up Up Up Up Up Up

IRI change (inches/mi), left 20 -12 9 34 20 28

IRI change (inches/mi), right 101 -7 11 38 24 22

IRI change curl removed 

(inches/mi), left -3 12 2 -6 6 -6

IRI change curl removed 

(inches/mi), right 72 9 2 -5 12 -5

Table 33 shows the changes in IRI that occurred at the test sections that were designed for a PCC 

flexural strength of 900 psi. Little change in IRI was noticed at most of the sections, and a good 

relationship between the change in PSG and change in IRI could not be established for these 

sections. Hence, the IRI values with the curling effects removed are not shown in this table.
100

Table 33. Results for sections designed for flexural strength of 900 psi.

Factor

Section

040214 040218 040222 040216 040220 040224

PCC flexural strength (psi) 900 900 900 900 900 900

PCC thickness (inches) 8 8 8 11 11 11

Base type DGAB LCB PATB DGAB LCB PATB

Direction of curl, initial (0.32 years) Up Up Up Up Up Up

Direction of curl, initial (16.32 years) Down Up Up Down Up Up

IRI change (inches/mi), left 15 -14 4 3 3 20

IRI change (inches/mi), right 19 -15 -1 18 3 16

4.5.4 Effect of Curling and Warping on FWD Testing

Upward curling of the pavement at the edges of the slab does not have an effect on FWD tests 

conducted at the center of the slab, as the center of the slab will be in contact with the base. 

However, downward curling of the slab where the mid-slab is at a higher elevation when 

compared to edges will have a significant impact on mid-slab FWD testing. This occurs because 

the center of the slab will not be in contact with the base when the slab is curled downward, and 

the degree of downward curling is expected to have a significant impact on the deflections 

obtained at the center of the slab. 

4.5.5 Effect of Roughness on Structural Capacity

The information presented in the previous section shows that diurnal variations in the shape of a 

PCC slab can have a significant effect on the IRI value. Additionally, changes in slab curvature 

can occur over time that can cause an increase in roughness. These changes in roughness have no 

relationship to the structural capacity of the pavement. However, it should be noted that an 

increase in downward curling over time can result in premature mid-panel cracking initiating 

at the bottom of the slab, while an increase in upward curling over time can result in top-down 

cracking adjacent to the joints.

4.6 SUMMARY

Information on the maintenance and repair activities applied to each of the test sections during 

the time periods considered in the study was obtained from the LTPP database to assess the 

potential impact of these activities on ride quality and structural adequacy. Only a limited 

amount of maintenance was performed. The maintenance activities carried out at the test sections 

were crack sealing, fog sealing, joint sealing, partial-depth patching (at a PCC section), grinding, 

and patching at AC sections (full-depth, skin, and strip). Only grinding and full-depth patching 

may have an impact on ride quality, structural adequacy, or both. 

Based on the review of the time-sequence IRI data, using IRI at the first and last profile dates to 

determine the change in IRI that occurred at a test section appears reasonable. The selected data 

values do not appear to be influenced by errors in data collection.
101

Little change in deflections occurred over time at many sections. The COV of the deflections 

values was less than 20 percent at 15 of the 21 sections evaluated in this study. At the sections 

that had a COV greater than 20 percent, the high COV values were attributed to: (1) deflections 

showing an increase with time, (2) deflections showing a decrease with time, (3) possible 

influence of the temperature adjustment factor on the adjusted deflections, and (4) one 

deflection in the time-sequence deflections being much higher than the other values. 

The two AC sections where grinding was performed were not considered in this study. The 

limited maintenance activities that were performed on other sections appeared to have little or no 

influence on either the time-sequence IRI or deflection values. Based on the review of the timesequence IRI and time-sequence deflection values, the use of the first and last profile and FWD 

dates to characterize changes in IRI and SN appears to be reasonable.

A past study has shown that significant diurnal variations in IRI can occur. A recently concluded 

FHWA study showed that the degree of curvature in a slab can increase over time, and curvature 

of the slab can have a significant effect on the IRI. Changes in IRI that occur due to changes in 

slab shapes have no relationship with the structural adequacy of the pavement.

103

CHAPTER 5. SUMMARY AND CONCLUSIONS

Ride quality and structural adequacy are key pavement performance indicators. The relationship 

between these two indicators has been a topic of frequent and continuing discussion in the 

pavement community, but an accepted and widely used relationship has not been identified to 

date. To address this issue, FHWA sponsored a study to identify and verify the relationship, if 

any, between ride quality and structural support or ride deterioration and structural adequacy 

using the LTPP pavement performance data. 

The FHWA study was undertaken in an effort to improve the evaluation and use of pavement 

condition data in pavement rehabilitation and design decisions. More specifically, this project 

was intended to develop and document a mechanism to include both ride and structural 

adequacy values within the context of current network-level PMS practices for highway agency 

implementation. The results of the project were intended for use by PMS engineers to ensure 

smooth pavements that are also structurally adequate. 

A literature search was undertaken to collect, review, and synthesize available information on 

relating ride quality and structural adequacy for pavement rehabilitation and design decisions. 

Pertinent information was sought through Web-based searches of State highway agencies, 

university pavement research centers, TRB, ASCE, industry, and other national and international 

organizations. A total of 62 references were identified, but only 16 were considered relevant 

to the study. Moreover, while these 16 references contained valuable information, they did 

not contribute to the direct or indirect identification of a potential ride quality-structural 

capacity relationship.

Following completion of the literature search, a review and assessment of selected LTPP 

pavement performance data were undertaken to see if a ride quality-structural capacity 

relationship could be identified through the analysis of these data. 

A total of 21 LTPP sections were identified and broken down into 5 groups according to 

pavement type (new AC, AC overlay over AC, and PCC), base type (granular or asphalt treated), 

changes in IRI over time, and changes in structural capacity over time. Historical pavement 

smoothness (profile) and structural capacity (FWD deflection) data were extracted from the 

LTPP database for the 21 sections, and the resulting data were analyzed. IRI was used to 

characterize ride quality, while SN and Deff were used to characterize the structural capacity of 

flexible and rigid pavements, respectively.

Continuous IRI and SN or Deff plots were generated to see if a viable ride quality-structural 

capacity relationship could be identified. It was hypothesized that areas where large changes in 

IRI had occurred should show large decreases in SN or Deff. However, such relationship could 

not be observed for the sections and data investigated. In general, no major changes in SN or Deff

associated with localized areas of roughness were observed. In most sections, significant IRI 

changes were noticed at localized areas. Comparisons of continuous IRI and maximum 

deflection (i.e., below the FWD load center) or estimated subgrade modulus plots were also 

performed, but again, a relationship could not be identified.
104

A number of additional analyses were conducted to validate the study findings and conclusions.

The evaluation of maintenance and repair activities showed that only a limited amount of 

maintenance had been performed on the study sections; with few exceptions, they did not affect 

the study findings. The review of IRI and FWD time history data confirmed that the use of the 

first and last test dates at a site to characterize the change in IRI and SN appears reasonable.

Finally, the assessment of PCC warping and curling concluded that changes in IRI that occur due 

to changes in slab shapes have no relationship with the structural adequacy of the pavement.

In view of the findings, actual development of a ride quality-structural adequacy relationship and 

guidance for implementing the relationship into PMS was not pursued, as it could not be justified 

on the basis of the approach taken in this study. The lack of correlation found in the study, 

however, is considered of value to PMS practitioners, as it indicates that good ride quality does 

not mean good structural support or lower funding requirements to maintain the pavements. This 

becomes an important consideration for those wishing to base performance measures on ride 

quality indicators. 

It is also important to recognize that these findings are based on the approach taken in the study. 

It is possible that other researchers will pursue alternate approaches that will yield a reliable 

relationship. However, while a relationship would be expedient for PMS applications, a 

fundamental understanding of the differences in factors causing structural deterioration and 

roughness (as well as the variable cause-effect relationship) makes it unlikely to find a simple 

relationship, particularly one excluding most other factors. 

It is hypothesized that a strong relationship between the two performance indicators in question 

would require the inclusion of many other variables, potentially undoing its usefulness for the 

intended purpose in PMS. Clearly, pavement structural and functional performances are not 

independent of each other, even though they are not related in a one-to-one manner that can 

provide a PMS shortcut. However, this does not mean that structural parameters are not 

important for consideration in roughness prediction models, that roughness could not be one 

factor in the rate of structural deterioration, or that many common factors do not affect both 

roughness and structural capacity.
105

APPENDIX A. DEFLECTION BELOW CENTER OF 9,000-LB LOAD 

AND SUBGRADE MODULUS PLOTS

A.1 GROUP 1 SECTIONS

A.1.1 Section 050119 (Arkansas)

Figure 75. Graph. Deflection plot for section 050119 (Arkansas).

Figure 76. Graph. Subgrade modulus plot for section 050119 (Arkansas).
106

A.1.2 Section 480114 (Texas)

Figure 77. Graph. Deflection plot for section 480114 (Texas).

Figure 78. Graph. Subgrade modulus plot for section 480114 (Texas).
107

A.1.3 Section 310113 (Nebraska)

Figure 79. Graph. Deflection plot for section 310113 (Nebraska).

Figure 80. Graph. Subgrade modulus plot for section 310113 (Nebraska).
108

A.1.4 Section 010102 (Alabama)

Figure 81. Graph. Deflection plot for section 010102 (Alabama).

Figure 82. Graph. Subgrade modulus plot for section 010102 (Alabama).
109

A.1.5 Section 390112 (Ohio)

Figure 83. Graph. Deflection plot for section 390112 (Ohio).

Figure 84. Graph. Subgrade modulus plot for section 390112 (Ohio).
110

A.1.6 Section 040123 (Arizona)

Figure 85. Graph. Deflection plot for section 040123 (Arizona).

Figure 86. Graph. Subgrade modulus plot for section 040123 (Arizona).
111

A.1.7 Section 190108 (Iowa)

Figure 87. Graph. Deflection plot for section 190108 (Iowa).

Figure 88. Graph. Subgrade modulus plot for section 190108 (Iowa).
112

A.2 GROUP 2 SECTIONS

A.2.1 Section 320101 (Nevada)

Figure 89. Graph. Deflection plot for section 320101 (Nevada).

Figure 90. Graph. Subgrade modulus plot for section 320101 (Nevada).
113

A.2.2 Section 390106 (Nevada)

Figure 91. Graph. Deflection plot for section 390106 (Nevada).

Figure 92. Graph. Subgrade modulus plot for section 390106 (Nevada).
114

A.3 GROUP 3 SECTIONS 

A.3.1 Section 190101 (Iowa)

Figure 93. Graph. Deflection plot for section 190101 (Iowa).

Figure 94. Graph. Subgrade modulus plot for section 190101 (Iowa).
115

A.3.2 Section 190103 (Iowa)

Figure 95. Graph. Deflection plot for section 190103 (Iowa).

Figure 96. Graph. Subgrade modulus plot for section 190103 (Iowa).
116

A.3.3 Section 050114 (Arkansas)

Figure 97. Graph. Deflection plot for section 050114 (Arkansas).

Figure 98. Graph. Subgrade modulus plot for section 050114 (Arkansas).
117

A.3.4 Section 050116 (Arkansas)

Figure 99. Graph. Deflection plot for section 050116 (Arkansas).

Figure 100. Graph. Subgrade modulus plot for section 050116 (Arkansas).
118

A.4 GROUP 4 SECTIONS

A.4.1 Section 040502 (Arizona)

Figure 101. Graph. Deflection plot for section 040502 (Arizona).

Figure 102. Graph. Subgrade modulus plot for section 040502 (Arizona).
119

A.4.2 Section 240505 (Maryland)

Figure 103. Graph. Deflection plot for section 240505 (Maryland).

Figure 104. Graph. Subgrade modulus plot for section 240505 (Maryland).
120

A.4.3 Section 270509 (Minnesota)

Figure 105. Graph. Deflection plot for section 270509 (Minnesota).

Figure 106. Graph. Subgrade modulus plot for section 270509 (Minnesota).
121

APPENDIX B. DEFLECTION BELOW LOAD AND AT 60 INCHES 

FOR A 9,000-LB LOAD

B.1 GROUP 5 SECTIONS

B.1.1 Section 040213 (Arizona)

Figure 107. Graph. Deflection at 0 inches for a 9,000-lb load, section 040213 (Arizona).

Figure 108. Graph. Deflection at 60 inches for a 9,000-lb load, section 040213 (Arizona).
122

B.1.2 Section 050217 (Arkansas)

Figure 109. Graph. Deflection at 0 inches for a 9,000-lb load, section 050217 (Arkansas).

Figure 110. Graph. Deflection at 60 inches for a 9,000-lb load, section 050217 (Arkansas).
123

B.1.3 Section 390205 (Ohio)

Figure 111. Graph. Deflection at 0 inches for a 9,000-lb load, section 390205 (Ohio).

Figure 112. Graph. Deflection at 60 inches for a 9,000-lb load, section 390205 (Ohio).

125

APPENDIX C. TIME SEQUENCE IRI PLOTS

C.1 GROUP 1 SECTIONS

Figure 113. Graph. Time sequence IRI values, section 050119 (Arkansas).

Figure 114. Graph. Time sequence IRI values, section 480114 (Texas).
126

Figure 115. Graph. Time sequence IRI values, section 310113 (Nebraska).

Figure 116. Graph. Time sequence IRI values, section 010102 (Alabama).
127

Figure 117. Graph. Time sequence IRI values, section 390112 (Ohio).

Figure 118. Graph. Time sequence IRI values, section 040123 (Arizona).
128

Figure 119. Graph. Time sequence IRI values, section 190108 (Iowa).

C.2 GROUP 2 SECTIONS

Figure 120. Graph. Time sequence IRI values, section 320101 (Nevada).
129

Figure 121. Graph. Time sequence IRI values, section 390106 (Ohio).

Figure 122. Graph. Time sequence IRI values, section 310117 (Nebraska).
130

Figure 123. Graph. Time sequence IRI values, section 310118 (Nebraska).

C.3 GROUP 3 SECTIONS

Figure 124. Graph. Time sequence IRI values, section 190101 (Iowa).
131

Figure 125. Graph. Time sequence IRI values, section 190103 (Iowa).

Figure 126. Graph. Time sequence IRI values, section 050114 (Arkansas).
132

Figure 127. Graph. Time sequence IRI values, section 050116 (Arkansas).

C.4 GROUP 4 SECTIONS

Figure 128. Graph. Time sequence IRI values, section 040502 (Arizona).
133

Figure 129. Graph. Time sequence IRI values, section 240505 (Maryland).

Figure 130. Graph. Time sequence IRI values, section 270509 (Minnesota).
134

C.5 GROUP 5 SECTIONS

Figure 131. Graph. Time sequence IRI values, section 040213 (Arizona).

Figure 132. Graph. Time sequence IRI values, section 050217 (Arkansas).
135

Figure 133. Graph. Time sequence IRI values, section 390205 (Ohio).

137

APPENDIX D. AVERAGE NORMALIZED DEFLECTION AND MID-DEPTH 

SURFACE LAYER TEMPERATURE PLOTS

D.1 GROUP 1 SECTIONS

Deflection Below Load for 9000 lb Load, Corrected for Temperature - Section 050119

0

2

4

6

8

10

0 1 2 3 4 5 6 7 8 9 10 11

Time (Years)

Avegare Deflection (mils)

Feb-96

Mar-94

Mar-99

Apr-01

Apr-03

Mar-04

May-04

Figure 134. Graph. Average normalized deflection below 9,000-lb load, 

section 050119 (Arkansas).

Temperature of Asphalt Concrete - Section 050119

0

30

60

90

120

150

0 1 2 3 4 5 6 7 8 9 10 11

Time (Years)

Temperature (° F)

Mar-94

Feb-96

Mar-99

Apr-01

Apr-03

Mar-04

May-04

Figure 135. Graph. Mid-depth temperature of AC layer, section 050119 (Arkansas).
138

Deflection Below Load for 9000 lb Load, Corrected for Temperature - Section 480114

0

2

4

6

8

10

0 1 2 3 4 5 6 7 8

Time (Years)

Avegare Deflection (mils)

Nov-97

Aug-99

May-00

Feb-02

Nov-03

Jun-04

Figure 136. Graph. Average normalized deflection below 9,000-lb load,

section 480114 (Texas).

Temperature of Asphalt Concrete - Section 480114

0

30

60

90

120

150

0 1 2 3 4 5 6 7 8

Time (Years)

Temperature (° F)

Nov-97

Aug-99

May-00

Feb-02

Nov-03

Jun-04

Figure 137. Graph. Mid-depth temperature of AC layer, section 480114 (Texas).
139

Deflection Below Load for 9000 lb Load, Corrected for Temperature - Section 310113

0

10

20

30

40

50

0 1 2 3 4 5

Time (Years)

Avegare Deflection (mils)

Aug-98

Jun-97

Oct-99

Figure 138. Graph. Average normalized deflection below 9,000-lb load,

section 310113 (Nebraska).

Temperature of Asphalt Concrete - Section 310113

0

30

60

90

120

150

0 1 2 3 4 5

Time (Years)

Temperature (° F)

Aug-98

Jun-97

Oct-99

Figure 139. Graph. Mid-depth temperature of AC layer, section 310113 (Nebraska).
140

Deflection Below Load for 9000 lb Load, Corrected for Temperature - Section 010102

0

2

4

6

8

10

0 1 2 3 4 5 6 7 8 9 10 11 12 13

Time (Years)

Avegare Deflection (mils)

Mar-93

Jun-95

Apr-96

Jul-98

May-00

May-02

Feb-04

Apr-05

Figure 140. Graph. Average normalized deflection below 9,000-lb load, 

section 010102 (Alabama).

Temperature of Asphalt Concrete - Section 010102

0

30

60

90

120

150

0 1 2 3 4 5 6 7 8 9 10 11 12 13

Time (Years)

Temperature (° F)

Mar-93

Jun-95

Apr-96

Jul-98

May-00

May-02

Feb-04

Apr-05

Figure 141. Graph. Mid-depth temperature of AC layer, section 010102 (Alabama). 
141

Deflection Below Load for 9000 lb Load, Corrected for Temperature - Section 390112

0

2

4

6

8

10

0 1 2 3 4 5 6 7 8 9 10

Time (Years)

Avegare Deflection (mils)

Nov-96

Sep-99

Apr-01

Sep-04

Figure 142. Graph. Average normalized deflection below 9,000-lb load, 

section 390112 (Ohio).

Temperature of Asphalt Concrete - Section 390112

0

30

60

90

120

150

0 1 2 3 4 5 6 7 8 9 10

Time (Years)

Temperature (° F)

Nov-96

Sep-99

Apr-01

Sep-04

Figure 143. Graph. Mid-depth temperature of AC layer, section 390112 (Ohio).
142

Deflection Below Load for 9000 lb Load, Corrected for Temperature - Section 040123

0

2

4

6

8

10

0 1 2 3 4 5 6 7 8 9 10 11 12

Time (Years)

Avegare Deflection (mils)

Feb-94

Feb-96 Jan-98

Feb-99

May-01

Apr-03

Apr-05

Figure 144. Graph. Average normalized deflection below 9,000-lb load, 

section 040123 (Arizona).

Temperature of Asphalt Concrete - Section 040123

0

30

60

90

120

150

0 1 2 3 4 5 6 7 8 9 10 11 12

Time (Years)

Temperature (° F)

Feb-94

Feb-96

Jan-98

Feb-99

May-01

Apr-03

Apr-05

Figure 145. Graph. Mid-depth temperature of AC layer, section 040123 (Arizona).
143

Deflection Below Load for 9000 lb Load, Corrected for Temperature - Section 190108

0

4

8

12

16

20

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Time (Years)

Avegare Deflection (mils)

May-93

Sep-95 May-97 Oct-99

Feb-01

Jun-05

Apr-07

Figure 146. Graph. Average normalized deflection below 9,000-lb load, 

section 190108 (Iowa).

Temperature of Asphalt Concrete - Section 190108

0

30

60

90

120

150

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Time (Years)

Temperature (° F)

May-93 Sep-95

May-97 Oct-99

Feb-01

Jun-05

Apr-07

Figure 147. Graph. Mid-depth temperature of AC layer, section 190108 (Iowa).
144

D.2 GROUP 2 SECTIONS

Deflection Below Load for 9000 lb Load, Corrected for Temperature - Section 320101

0

4

8

12

16

20

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14

Time (Years)

Avegare Deflection (mils)

Mar-96

Mar-97

Aug-99

Mar-00

Mar-01 Mar-03

Mar-04

Mar-05

Aug-06

Jun-09

Figure 148. Graph. Average normalized deflection below 9,000-lb load, 

section 320101 (Nevada).

Temperature of Asphalt Concrete - Section 320101

0

30

60

90

120

150

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14

Time (Years

Temperature (°F)

Mar-96 Mar-97

Aug-99

Mar-00

Mar-01

Mar-03

Mar-04

Mar-05

Aug-06

Jun-09

Figure 149. Graph. Mid-depth temperature of AC layer, section 320101 (Nevada).
145

Deflection Below Load for 9000 lb Load, Corrected for Temperature - Section 390106

0

4

8

12

16

20

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14

Time (Years)

Avegare Deflection (mils)

Nov-96

Dec-97

Sep-99

Apr-01

Oct-04

Jul-08

Figure 150. Graph. Average normalized deflection below 9,000-lb load, 

section 390106 (Ohio).

Temperature of Asphalt Concrete - Section 390106

0

30

60

90

120

150

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14

Time (Years)

Temperature (°F)

Nov-96

Dec-97

Sep-99

Apr-01 Oct-04

Jul-08

Figure 151. Graph. Mid-depth temperature of AC layer, section 390106 (Ohio).
146

Deflection Below Load for 9000 lb Load, Corrected for Temperature - Section 310117

0

4

8

12

16

20

0 1 2 3 4 5 6 7 8

Time (Years)

Avegare Deflection (mils)

Aug-95 Jun-97

Oct-99

Jul-02

Figure 152. Graph. Average normalized deflection below 9,000-lb load, 

section 310117 (Nebraska).

Temperature of Asphalt Concrete - Section 310117

0

30

60

90

120

150

0 1 2 3 4 5 6 7 8

Time (Years)

Temperature (° F)

Aug-95

Jun-97

Oct-99

Jul-02

Figure 153. Graph. Mid-depth temperature of AC layer, section 310117 (Nebraska).
147

Deflection Below Load for 9000 lb Load, Corrected for Temperature - Section 310118

0

4

8

12

16

20

0 1 2 3 4 5 6 7 8

Time (Years)

Avegare Deflection (mils)

Aug-95

Jun-97

Oct-99

Jul-02

Figure 154. Graph. Average normalized deflection below 9,000-lb load, 

section 310118 (Nebraska).

Temperature of Asphalt Concrete - Section 310118

0

30

60

90

120

150

0 1 2 3 4 5 6 7 8

Time (Years)

Temperature (° F)

Aug-95

Jun-97

Oct-99

Jul-02

Figure 155. Graph. Mid-depth temperature of AC layer, section 310118 (Nebraska).
148

D.3 GROUP 3 SECTIONS

Deflection Below Load for 9000 lb Load, Corrected for Temperature - Section 190101

0

4

8

12

16

20

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Time (Years)

Avegare Deflection (mils)

May-93

Apr-95

Sep-95

Oct-99

Feb-01

Jun-05

Apr-07

Figure 156. Graph. Average normalized deflection below 9,000-lb load, 

section 190101 (Iowa).

Temperature of Asphalt Concrete - Section 190101

0

30

60

90

120

150

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Time (Years)

Temperature (° F)

May-93

Apr-95

Sep-95

Oct-99

Feb-01

Jun-05

Apr-07

Figure 157. Graph. Mid-depth temperature of AC layer, section 190101 (Iowa).
149

Deflection Below Load for 9000 lb Load, Corrected for Temperature - Section 190103

0

4

8

12

16

20

0 1 2 3 4 5 6 7 8 9 10 11 12 13

Time (Years)

Avegare Deflection (mils)

Feb-01

May-93

Sep-93

Sep-95

May-97

Oct-99 Jun-05

Figure 158. Graph. Average normalized deflection below 9,000-lb load, 

section 190103 (Iowa).

Temperature of Asphalt Concrete - Section 190103

0

30

60

90

120

150

0 1 2 3 4 5 6 7 8 9 10 11 12 13

Time (Years)

Temperature (° F)

May-93

Sep-93

Sep-95

May-97

Oct-99

Feb-01

Jun-05

Figure 159. Graph. Mid-depth temperature of AC layer, section 190103 (Iowa).
150

Deflection Below Load for 9000 lb Load, Corrected for Temperature - Section 050114

0

4

8

12

16

20

0 1 2 3 4 5 6 7 8 9 10 11 12

Time (Years)

Avegare Deflection (mils)

Mar-94

Feb-96

Mar-99

Apr-01

May-03

May-04

May-05

Figure 160. Graph. Average normalized deflection below 9,000-lb load, 

section 050114 (Arkansas).

Temperature of Asphalt Concrete - Section 050114

0

30

60

90

120

150

0 1 2 3 4 5 6 7 8 9 10 11 12

Time (Years)

Temperature (° F)

Mar-94

Feb-96

Mar-99

Apr-01

May-03

May-04

May-05

Figure 161. Graph. Mid-depth temperature of AC layer, section 050114 (Arkansas).
151

Deflection Below Load for 9000 lb Load, Corrected for Temperature - Section 050116

0

4

8

12

16

20

0 1 2 3 4 5 6 7 8 9 10 11 12

Time (Years)

Avegare Deflection (mils)

Mar-94 Feb-96 Mar-99 Apr-01 Apr-03 May-04

May-05

Figure 162. Graph. Average normalized deflection below 9,000-lb load, 

section 050116 (Arkansas).

Temperature of Asphalt Concrete - Section 050116

0

30

60

90

120

150

0 1 2 3 4 5 6 7 8 9 10 11 12

Time (Years)

Temperature (° F)

Mar-94

Feb-96

Mar-99

Apr-01

Apr-03

May-04

May-05

Figure 163. Graph. Mid-depth temperature of AC layer, section 050116 (Arkansas).
152

D.4 GROUP 4 SECTIONS

Deflection Below Load for 9000 lb Load, Corrected for Temperature - Section 040502

0

4

8

12

16

20

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

Time (Years)

Avegare Deflection (mils)

Mar-94

Mar-94

Mar-94

Mar-94

Mar-94

Dec-03

Mar-94

Mar-94

Mar-94

Mar-94

Mar-94

Mar-94

Mar-94

Mar-94

Mar-94

Mar-94

Mar-94

Mar-94

Mar-94

Mar-94

Mar-94

Mar-94

Mar-94

Mar-94

Mar-94

Mar-94

Mar-94

Mar-94

Mar-94

Dec-99

Jan-91

Oct-91

Oct-94

Sep-96

Nov-97

Dec-98

Sep-08

Dec-02

Oct-00

Figure 164. Graph. Average normalized deflection below 9,000-lb load, 

section 040502 (Arizona).

Temperature of Asphalt Concrete - Section 040502

0

30

60

90

120

150

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

Time (Years)

Temperature (° F)

Jan-91

Oct-91

Oct-94

Sep-96

Nov-97

Dec-98 Dec-99

Oct-00

Sep-08

Dec-03

Dec-02

Figure 165. Graph. Mid-depth temperature of AC layer, section 040502 (Arizona).
153

Deflection Below Load for 9000 lb Load, Corrected for Temperature - Section 240505

0

4

8

12

16

20

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

Time (Years)

Avegare Deflection (mils)

Aug-92

Aug-94 May-97 Jul-99

Aug-01

Jun-03

May-05

Jun-04

Apr-09

Oct-95

Figure 166. Graph. Average normalized deflection below 9,000-lb load, 

section 240505 (Maryland).

Temperature of Asphalt Concrete - Section 240505

0

30

60

90

120

150

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

Time (Years)

Temperature (° F)

Aug-92

Aug-94

Oct-95

May-97

Jul-99

Aug-01

Jun-03

Jun-04

May-05 Apr-09

Figure 167. Graph. Mid-depth temperature of AC layer, section 240505 (Maryland).
154

Deflection Below Load for 9000 lb Load, Corrected for Temperature - Section 270509

0

4

8

12

16

20

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16

Time (Years)

Avegare Deflection (mils)

Mar-94 Jun-91

Jun-92

Sep-93

Aug-95

Jun-99

Aug-01

Aug-03

Jun-05

Figure 168. Graph. Average normalized deflection below 9,000-lb load, 

section 270509 (Minnesota).

Temperature of Asphalt Concrete - Section 270509

0

30

60

90

120

150

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16

Time (Years)

Temperature (° F)

Jun-91

Jun-92

Sep-93

Aug-95

Jun-99 Aug-01

Aug-03

Jun-05

Figure 169. Graph. Mid-depth temperature of AC layer, section 270509 (Minnesota).
155

D.5 GROUP 5 SECTIONS

Deflection Below Load for 9000 lb Load - Section 040213

0

4

8

12

16

20

0 1 2 3 4 5 6 7 8 9 10 11 12

Time (Years)

Avegare Deflection (mils)

Feb-94

Mar-95

Nov-97

Jan-99

Dec-01

Dec-03

Dec-04

Figure 170. Graph. Average normalized deflection below 9,000-lb load, 

section 040213 (Arizona).

Temperature of PCC - Section 040213

0

30

60

90

120

150

0 1 2 3 4 5 6 7 8 9 10 11 12

Time (Years)

Temperature (° F)

Feb-94

Mar-95 Nov-97

Jan-99 Dec-01 Dec-03

Dec-04

Figure 171. Graph. Mid-depth temperature of PCC layer, section 040213 (Arizona).
156

Deflection Below Load for 9000 lb Load - Section 050217

0

4

8

12

16

20

0 1 2 3 4 5 6 7 8 9 10

Time (Years)

Avegare Deflection (mils)

Nov-96 Apr-99 Jul-01 Oct-03 Sep-04

Figure 172. Graph. Average normalized deflection below 9,000-lb load, 

section 050217 (Arkansas).

Temperature of PCC - Section 050217

0

30

60

90

120

150

0 1 2 3 4 5 6 7 8 9 10

Time (Years)

Temperature (° F)Nov-96

Apr-99

Jul-01

Oct-03 Sep-04

Figure 173. Graph. Mid-depth temperature of PCC layer, section 050217 (Arkansas).
157

Deflection Below Load for 9000 lb Load - Section 390205

0

4

8

12

16

20

0 1 2 3 4 5 6 7 8 9

Time (Years)

Avegare Deflection (mils)

Dec-96

Jul-97 Sep-99

Apr-01

Apr-03 Sep-04

Figure 174. Graph. Average normalized deflection below 9,000-lb load, 

section 390205 (Ohio).

Temperature of PCC - Section 390205

0

30

60

90

120

150

0 1 2 3 4 5 6 7 8 9

Time (Years)

Temperature (° F)

Dec-96

Jul-97

Sep-99 Apr-01

Apr-03

Sep-04

Figure 175. Graph. Mid-depth temperature of PCC layer, section 390205 (Ohio).

159

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