USE OF RECYCLED AGGREGATE MATERIALS CHARACTERISTICS IN PAVEMENT 

 

DESIGN ANALYSES 

  

 
 

 
 
 
 
 
 
 
 
 
 
 
 

 
 
 
 
 

 
By 

Ida Gheibi 

 
 
 

A THESIS  

Submitted to  

Michigan State University  

in partial fulfillment of the requirements  

for the degree of  

Civil Engineering—Master of Science  

2020 

 
 
 

 

ABSTRACT 

USE OF RECYCLED AGGREGATE MATERIALS CHARACTERISTICS IN PAVEMENT 

DESIGN ANALYSES 

 
By 

Ida Gheibi 

Use  of  recycled  materials  promotes  sustainability  in  roadway  construction  by  reducing 

consumption  of  energy  and  emission  of  greenhouse  gases  associated  with  mining  and  the 

production  of  natural  aggregates.  Recycled  asphalt  pavements  (RAP)  and  recycled  concrete 

aggregates (RCA) have comparable characteristics to natural aggregates that are currently used in 

roadway  base  course  applications.  This  study  has  developed  a  database  for  RAP  and  RCA 

materials’  characteristics  including  resilient  modulus  (Mr),  California  bearing  ratio  (CBR), 

gradations  along  with  construction  specifications.  RAP  and  RCA  relationships  with  different 

engineering and index properties were investigated and some trends were proposed such as higher 

RAP  content  reveals  higher  summary  of  resilient  modulus  (SMr),  higher  RCA  content  causes 

higher optimum moisture content (OMC) and lower maximum dry unit (MDU). 

In addition, pavement mechanistic-empirical (ME) analyses have been conducted with the material 

inputs collected for the database to determine whether different values of different characteristics 

of  RCA  and  RAP  can  be  used  in  flexible  or  rigid  pavement  designs.  Results  showed  that  Mr 

parameter had the highest impact on pavement distress predictions among gradations and hydraulic 

conductivity.  

 

	

   

 

 

 

 

 

Copyright by 
IDA GHEIBI 
2020 

 

 
 
 
 
 
 
 
 

 
 
 
 
 
 
 
 
 
 
 

 

 
 
 
 
 
 
 
 
 
 
 
 
 
 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 

iv 

I dedicate this thesis to my parents who have always supported me to pursue my dreams. It is 

their unconditional love that motivates me to set higher goals. 

 
 
 

 
 

 

ACKNOWLEDGEMENTS 

 

I would like to first gratefully acknowledge Dr. Bora Cetin, my advisor, for his guidance, 

support, advice and extensive patience during my graduate studies at Michigan State University. 

I would like to thank Dr. Mustafa Hatipoglu as he helped me through early stages of my project. 

Thanks also to Dr. Timothy Gates and Dr. Syed Waqar Haider for being on my committee.  

  

 

 

v 

 

TABLE OF CONTENTS 

  

LIST OF TABLES ....................................................................................................................... viii 
 
LIST OF FIGURES ....................................................................................................................... xi 
 
INTRODUCTION .......................................................................................................................... 1 
BACKGROUND ........................................................................................................................ 4 
DATA ON RCA AND RAP PROPERTIES .............................................................................. 6 

 
CHAPTER 1. PHYSICAL PROPERTIES OF RAP AND RCA ................................................. 12 
1.1.  GRADATION CHARACTERISTICS ......................................................................... 12 
1.2.  COMPACTION CHARACTERISTICS ....................................................................... 14 
PLASTICITY CHARACTERISTICS .......................................................................... 19 
1.3. 

 
CHAPTER 2. MECHANICAL AND HYDRAULIC PROPERTIES OF RAP AND RCA ........ 21 
2.1. HYDRAULIC CONDUCTIVITY ..................................................................................... 21 
2.2. STRENGTH ....................................................................................................................... 26 
2.2.1. IMPACTS OF SELECTED INDEX PROPERTIES ON CBR .................................. 27 
2.2.2. IMPACTS OF RAP/RCA CONTENTS ON CBR ..................................................... 29 
2.3. STIFFNESS ....................................................................................................................... 32 
2.3.1. EFFECTS OF INDEX PROPERTIES ON STIFFNESS OF RCA AND RAP .......... 33 
2.3.2. TEMPERATURE EFFECTS ON RAP AND RCA STIFFNESS .............................. 47 
2.3.3. RESILIENT MODULUS BLENDS OF RAP AND RCA WITH NATURAL 
AGGREGATES .................................................................................................................... 51 
2.4. PERMANENT DEFORMATION ..................................................................................... 59 
2.5. SHEAR STRENGTH ........................................................................................................ 62 

 
CHAPTER 3. DESIGN METHODS ............................................................................................ 65 
3.1. PAVEMENT MECHANISTIC EMPIRICAL DESIGN ................................................... 65 

 
CHAPTER 4. SELECTED PRACTICES OF STATE DOTS ...................................................... 67 
4.1. CALIFORNIA DOT .......................................................................................................... 67 
4.2. ILLINOIS DOT ................................................................................................................. 69 
4.3. MINNESOTA DOT ........................................................................................................... 72 
4.4. MISSOURI DOT ............................................................................................................... 75 
4.5. WISCONSIN DOT ............................................................................................................ 76 
4.6. MICHIGAN DOT .............................................................................................................. 79 

 
CHAPTER 5. INPUTS FOR PAVEMENT MECHANISTIC-EMPIRICAL DESIGN (PMED) 81 
 
CHAPTER 6. DISTRESSES ........................................................................................................ 89 
6.1. INTERNATIONAL ROUGHNESS INDEX (IRI) FOR FLEXIBLE PAVEMENTS ...... 90 
       6.1.1. IMPACT OF SUMMARY RESILIENT MODULUS (SMR) ON IRI ........................ 90 

 

vi 

       6.1.2. IMPACT OF FINES CONTENT ON IRI ................................................................... 91 
       6.1.3. IMPACT OF GRAVEL CONTENT ON IRI .............................................................. 92 
       6.1.4. IMPACT OF SAND CONTENT ON IRI .................................................................... 93 
       6.1.5. IMPACT OF D60 ON IRI ............................................................................................. 94 
6.2. INTERNATIONAL ROUGHNESS INDEX (IRI) FOR RIGID PAVEMENTS .............. 95 
       6.2.1. IMPACT OF SMR ON IRI .......................................................................................... 95 
       6.2.2. IMPACT OF FINES CONTENT ON IRI ................................................................... 96 
       6.2.3. IMPACT OF GRAVEL CONTENT ON IRI .............................................................. 97 
       6.2.4. IMPACT OF SAND CONTENT ON IRI .................................................................... 98 
       6.2.5. IMPACT OF D60 ON IRI ............................................................................................. 99 
6.3. TOTAL RUTTING ON FLEXIBLE PAVEMENTS ...................................................... 100 
       6.3.1. IMPACT OF SMR ON TOTAL RUTTING ............................................................. 100 
       6.3.2. IMPACT OF FINES CONTENT ON TOTAL RUTTING ....................................... 101 
       6.3.3. IMPACT OF GRAVEL CONTENT ON TOTAL RUTTING .................................. 102 
       6.3.4. IMPACT OF SAND CONTENT ON TOTAL RUTTING ....................................... 103 
       6.3.5. IMPACT OF D60 ON TOTAL RUTTING ................................................................ 104 
6.4. MEAN JOINT FAULTING ............................................................................................. 106 
       6.4.1. IMPACT OF SMR ON MEAN JOINT FAULTING ................................................ 106 
       6.4.2. IMPACT OF FINES CONTENT ON MEAN JOINT FAULTING .......................... 107 
       6.4.3. IMPACT OF GRAVEL CONTENT ON MEAN JOINT FAULTING ..................... 108 
       6.4.4. IMPACT OF SAND CONTENT ON MEAN JOINT FAULTING .......................... 109 
       6.4.5. IMPACT OF D60 ON MEAN JOINT FAULTING ................................................... 110 
 
CHAPTER 7. CONCLUSIONS/RECOMMENDATIONS ....................................................... 112 
 
APPENDICES ............................................................................................................................ 117 
    APPENDIX A. GRADATION CHARACTERISTICS OF RCA-RAP DATABASE ........... 118 
    APPENDIX B. RAP DATABASE ......................................................................................... 134 
    APPENDIX C. RCA DATABASE ........................................................................................ 140 
 
REFERENCES ........................................................................................................................... 144 

 
 
 
 
 
 
 
 
 
 
 
 
 
 

 

 

vii 

LIST OF TABLES 

 
 
Table 1. LIST OF THE COLLECTED DATA AND CORRESPONDING RESOURCES .......... 8 

Table 2. INDEX PROPERTY RANGES OF RCA AND RAP .................................................... 14 

Table 3. COMPACTION CHARACTERISTICS RANGES OF RCA AND RAP ...................... 16 

Table 4. AGGREGATE GRADATION FOR SUBBASE APPLICATIONS (CALTRANS 2015)
....................................................................................................................................................... 68 
 
Table 5. AGGREGATE QUALITY CHARACTERISTICS FOR SUBBASE APPLICATIONS 
(CALTRANS 2015) ...................................................................................................................... 68 
 
Table 6. CLASS 2 AGGREGATE GRADATION FOR AGGREGATE BASE APPLICATIONS 
(CALTRANS 2015) ...................................................................................................................... 69 
 
Table 7. CLASS 2 AGGREGATE QUALITY CHARACTERISTICS FOR AGGREGATE 
BASE APPLICATIONS (CALTRANS 2015) ............................................................................. 69 
 
Table 8. CLASS 3 AGGREGATE GRADATION FOR AGGREGATE BASE APPLICATIONS 
(CALTRANS 2015) ...................................................................................................................... 69 
 
Table 9. CLASS 3 AGGREGATE QUALITY CHARACTERISTICS FOR AGGREGATE 
BASE APPLICATIONS (CALTRANS 2015) ............................................................................. 69 
 
Table 10. GRADATION RANGES OF DIFFERENT AGGREGATES (IDOT 2016) ............... 71 
 
Table 11. TYPICAL AGGREGATES FOR VARIOUS APPLICATIONS (IDOT 2016) ........... 71 
 
Table 12. COARSE AGGREGATE QUALITY CONTROL SPECIFICATIONS (IDOT 2016) 72 
 
Table 13. QUALITY REQUIREMENTS FOR VIRGIN AGGREGATES (MNDOT 2018) ...... 73 
 
Table 14. QUALITY REQUIREMENTS FOR RECYCLED AGGREGATES (MNDOT 2018) 73 
 
Table 15. GRADATION OF BASE AGGREGATE CONTAINING LESS THAN 25% 
RECYCLED AGGREGATES (MNDOT 2018) .......................................................................... 74 
 
Table 16. GRADATION OF BASE AGGREGATE CONTAINING 25% OR MORE 
RECYCLED AGGREGATES AND 75% OR LESS RECYCLED CONCRETE (MNDOT 2018)
....................................................................................................................................................... 74 
 

 

viii 

Table 17. GRADATION OF BASE AGGREGATE CONTAINING MORE THAN 75% 
RECYCLED CONCRETE (MNDOT 2018) ................................................................................ 75 
 
Table 18. GRADATION CRITERIA OF TYPE 1 AGGREGATE (MODOT 2018) .................. 76 
 
Table 19. GRADATION CRITERIA OF TYPE 5 AGGREGATE (MODOT 2018) .................. 76 
 
Table 20. GRADATION CRITERIA OF TYPE 7 AGGREGATE (MODOT 2018) .................. 76 
 
Table 21. SUITABILITY OF VARIOUS AGGREGATE BASE MATERIALS (WISDOT 2018)
....................................................................................................................................................... 77 
 
Table 22. AGGREGATE BASE PHYSICAL PROPERTIES (WISDOT 2018) ......................... 78 
 
Table 23. GRADATION REQUIREMENTS OF DENSE-GRADED AGGREGATE BASE 
MATERIALS EXCEPT FOR RECLAIMED ASPHALT (WISDOT 2018) ............................... 78 
 
Table 24. GRADING REQUIREMENTS FOR DENSE-GRADED AGGREGATES (MDOT 
2012) ............................................................................................................................................. 79 
 
Table 25. PHYSICAL REQUIREMENTS FOR DENSE-GRADED AGGREGATES (MDOT 
2012) ............................................................................................................................................. 80 
 
Table 26. GRADING REQUIREMENTS FOR GRANULAR MATERIALS (MDOT 2012) .... 80 

Table 27. GENERAL INPUTS ..................................................................................................... 82 

Table 28. TRAFFIC INPUTS ....................................................................................................... 83 

Table 29. BASE INPUTS INVESTIGATING SMR EFFECT OF RAP ...................................... 84 

Table 30. BASE INPUTS INVESTIGATING SMR EFFECT OF RCA ...................................... 84 

Table 31. BASE INPUTS INVESTIGATING FINES CONTENT EFFECT OF RAP ............... 84 

Table 32. BASE INPUTS INVESTIGATING FINES CONTENT EFFECT OF RCA ............... 85 

Table 33. BASE INPUTS INVESTIGATING GRAVEL CONTENT EFFECT OF RAP .......... 85 

Table 34. BASE INPUTS INVESTIGATING GRAVEL CONTENT EFFECT OF RCA .......... 86 

Table 35. BASE INPUTS INVESTIGATING SAND CONTENT EFFECT OF RAP ............... 86 

Table 36. BASE INPUTS INVESTIGATING SAND CONTENT EFFECT OF RCA ............... 87 

Table 37. BASE INPUTS INVESTIGATING D60 EFFECT OF RAP ........................................ 87 

 

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Table 38. BASE INPUTS INVESTIGATING D60 EFFECT OF RCA ........................................ 88 

Table 39. PAVEMENT DISTRESS TYPES AND TARGET VALUES FOR FLEXIBLE 
PAVEMENT ................................................................................................................................. 89 
 
Table 40. PAVEMENT DISTRESS TYPES AND TARGET VALUES FOR JCPC .................. 89 

Table 41. SUMMARY OF DATABASE ................................................................................... 116 

Table 42. GRADATION CHARACTERISTICS OF RCA-RAP DATABASE ........................ 118 
 
Table 43. RAP DATABASE ...................................................................................................... 134 
 
Table 44. RCA DATABASE ...................................................................................................... 140 
 
 

 

 

 

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LIST OF FIGURES 

Figure 1. MAXIMUM DRY UNIT WEIGHT (MDU) VERSUS RAP CONTENT .....................16 

Figure 2. MAXIMUM DRY UNIT WEIGHT (MDU) VERSUS RAP CONTENT (WHISKER 
PLOT) ............................................................................................................................................16 
 
Figure 3. MAXIMUM DRY UNIT WEIGHT (MDU) VERSUS RCA CONTENT ....................17 

Figure 4. MAXIMUM DRY UNIT WEIGHT (MDU) VERSUS RCA CONTENT (WHISKER 
PLOT) ............................................................................................................................................17 
 
Figure 5. OPTIMUM MOISTURE CONTENT (OMC) VERSUS RAP CONTENT ..................17 

Figure 6. OPTIMUM MOISTURE CONTENT (OMC) VERSUS RAP CONTENT (WHISKER 
PLOT) ............................................................................................................................................18 
 
Figure 7. OPTIMUM MOISTURE CONTENT (OMC) VERSUS RCA CONTENT ..................18 

Figure 8. OPTIMUM MOISTURE CONTENT (OMC) VERSUS RCA CONTENT (WHISKER 
PLOT) ............................................................................................................................................18 
 
Figure 9. THE EFFECT OF COMPACTION METHOD ON THE DEGREE OF THE 
COMPACTION .............................................................................................................................19 
 
Figure 10. HYDRAULIC CONDUCTIVITY VERSUS RAP CONTENT...................................23 

Figure 11. HYDRAULIC CONDUCTIVITY VERSUS RCA CONTENT ..................................24 

Figure 12. HYDRAULIC CONDUCTIVITY VERSUS D10 OF 100% RAP ...............................24 

Figure 13. HYDRAULIC CONDUCTIVITY VERSUS FINES CONTENT OF 100% RAP ......25 

Figure 14. HYDRAULIC CONDUCTIVITY VERSUS FINES CONTENT OF DIFFERENT 
RAP BLENDS ...............................................................................................................................25 
 
Figure 15. HYDRAULIC CONDUCTIVITY VERSUS FINE CONTENT OF 100% RCA ........26 

Figure 16. CBR VERSUS GRAVEL TO SAND RATIO OF 100% RAPS ..................................27 

Figure 17. CBR VERSUS FINES CONTENT OF 100% RAP SAMPLES ..................................28 

Figure 18. CBR VERSUS GRAVEL TO SAND RATIO OF RCA SAMPLES ...........................28 

 

xi 

Figure 19. CBR VERSUS FINES CONTENT OF RCA SAMPLES ............................................29 

Figure 20. CBR VERSUS RAP CONTENT .................................................................................30 

Figure 21. CBR VERSUS RCA CONTENT .................................................................................31 

Figure 22. NORMALIZED CBR VERSUS RCA CONTENT .....................................................32 

Figure 23. SMR AND GRAVEL TO SAND RATIO OF 100% RAPS .........................................34 

Figure 24. SMR VERSUS GRAVEL TO SAND RATIO OF 100% RAPS (WHISKER PLOT) .34 

Figure 25. SMR VERSUS FINES CONTENT OF 100% RAPS ...................................................35 

Figure 26. SMR VERUS FINES CONTENT OF 100% RAPS (WHISKER PLOT) ....................35 

Figure 27. SMR VERSUS GRAVEL TO SAND RATIO OF 100% RCAS ..................................36 

Figure 28. SMR VERSUS GRAVEL TO SAND RATIO OF 100% RCAS (WHISKER PLOT) .36 

Figure 29. SMR VERSUS FINES CONTENT OF 100% RCAS ..................................................37 

Figure 30. SMR VERSUS FINES CONTENT OF 100% RCAS (WHISKER PLOT) ..................37 

Figure 31. SMR VERSUS MAXIMUM DRY UNIT WEIGHT OF 100% RAP ..........................38 

Figure 32. SMR VERSUS MAXIMUM DRY UNIT WEIGHT OF 100% RAP (WHISKER 
PLOT) ............................................................................................................................................38 
 
Figure 33. SMR VERSUS OPTIMUM MOISTURE CONTENT OF 100% RAP ........................38 

Figure 34. SMR VERSUS OPTIMUM MOISTURE CONTENT OF 100% RAP (WHISKER 
PLOT) ............................................................................................................................................39 
 
Figure 35. SMR VERSUS D30 OF 100% RAP ..............................................................................39 

Figure 36. SMR VERSUS D30 OF 100% RAP (WHISKER PLOT) .............................................40 

Figure 37. SMR VERSUS D60 OF 100% RAP ..............................................................................40 

Figure 38. SMR VERSUS D60 OF 100% RAP (WHISKER PLOT) .............................................40 

Figure 39. SMR VERSUS CC OF 100% RAP ...............................................................................41 

Figure 40. SMR VERSUS CU OF 100% RAP ...............................................................................41 

 

xii 

Figure 41. SMR VERSUS CC OF 100% RAP (WHISKER PLOT) ...............................................42 

Figure 42. SMR VERSUS CU OF 100% RAP (WHISKER PLOT) ..............................................42 

Figure 43. SMR VERSUS MDU OF 100% RCA ..........................................................................43 

Figure 44. SMR VERSUS MDU OF 100% RCA (WHISKE PLOT) ............................................43 

Figure 45. SMR VERSUS OPTIMUM MOISTURE CONTENT OF 100% RCA .......................44 

Figure 46. SMR VERSUS OPTIMUM MOISTURE CONTENT OF 100% RCA (WHISKER 
PLOT) ............................................................................................................................................44 
 
Figure 47. SMR VERSUS D30 OF 100% RCA ..............................................................................44 

Figure 48. SMR VERSUS D30 OF 100% RCA (WHISKER) ........................................................45 

Figure 49. SMR VERSUS D60 OF 100% RCA ..............................................................................45 

Figure 50. SMR VERSUS D60 OF 100% RCA (WHISKER PLOT) .............................................45 

Figure 51. SMR VERSUS CC OF 100% RCA ...............................................................................46 

Figure 52. SMR VERSUS CC OF 100% RCA (WHISKER PLOT) ..............................................46 

Figure 53. SMR VERSUS CU OF 100% RCA ...............................................................................46 

Figure 54. SMR VERSUS CU OF 100% RCA (WHISKER PLOT) ..............................................47 

Figure 55. SMR VERSUS TESTING TEMPERATURE OF 100% RAPS ...................................48 

Figure 56. NORMALIZED SMR VERSUS TEMPERATURE OF 100% RAPS .........................49 

Figure 57. SMR VERSUS TEMPERATURE OF 100% RCA ......................................................49 

Figure 58. NORMALIZED SMR VERSUS TEMPERATURE OF 100% RCA ...........................50 

Figure 59. SMR VERSUS TEMPERATURE OF 100% RCA (WHISKER PLOT) ......................50 

Figure 60. SMR VERSUS OMC OF 100% RAPS .........................................................................51 

Figure 61. SMR VERSUS RAP CONTENT ..................................................................................55 

Figure 62. NORMALIZED SMR VERSUS RAP CONTENT ......................................................56 

Figure 63. SMR VERSUS RAP CONTENT (WHISKER PLOT) .................................................56 

 

xiii 

Figure 64. SMR VERSUS RCA CONTENT .................................................................................58 

Figure 65. SMR VERSUS RCA CONTENT .................................................................................58 

Figure 66. NORMALIZED SMR AND RCA CONTENT .............................................................58 

Figure 67. SMR VERSUS RCA CONTENT (WHISKER PLOT) ................................................59 

Figure 68. PERMANENT STRAIN VERSUS RAP CONTENT .................................................61 

Figure 69. PERMANENT STRAIN VERSUS RCA CONTENT .................................................61 

Figure 70. COHESION VERSUS RAP CONTENT .....................................................................63 

Figure 71. FRICTION ANGLE VERSUS RAP CONTENT ........................................................63 

Figure 72. COHESION VERSUS RCA CONTENT .....................................................................63 

Figure 73. FRICTION ANGLE VERSUS RCA CONTENT ........................................................64 

Figure 74. IRI VERSUS DIFFERENT SMR OF RAP ...............................................................90 

Figure 75. IRI VERSUS DIFFERENT SMR OF RCA ...............................................................91 

Figure 76. IRI VERSUS DIFFERENT FINES CONTENT OF RAP IN FLEXIBLE 
PAVEMENT ..................................................................................................................................91 
 
Figure 77. IRI VERSUS DIFFERENT FINES CONTENT OF RCA IN FLEXIBLE 
PAVEMENT ..................................................................................................................................92 
 
Figure 78. IRI VERSUS DIFFERENT GRAVEL CONTENT OF RAP IN FLEXIBLE 
PAVEMENT ..................................................................................................................................92 
 
Figure 79. IRI VERSUS DIFFERENT GRAVEL CONTENT OF RCA IN FLEXIBLE 
PAVEMENT ..................................................................................................................................93 
 
Figure 80. IRI VERSUS DIFFERENT SAND CONTENT OF RAP IN FLEXIBLE 
PAVEMENT ..................................................................................................................................93 
 
Figure 81. IRI VERSUS DIFFERENT SAND CONTENT OF RCA IN FLEXIBLE 
PAVEMENT ..................................................................................................................................94 
 
Figure 82. IRI VERSUS DIFFERENT D60 OF RAP IN FLEXIBLE PAVEMENT ....................94 

Figure 83. IRI VERSUS DIFFERENT D60 OF RCA IN FLEXIBLE PAVEMENT ....................95 

 

xiv 

Figure 84. IRI VERSUS DIFFERENT SMR OF RAP IN RIGID PAVEMENT ..........................95 

Figure 85. IRI VERSUS DIFFERENT SMR OF RCA IN RIGID PAVEMENT ..........................96 

Figure 86. IRI VERSUS DIFFERENT FINES CONTENT OF RAP IN RIGID PAVEMENT ...97 

Figure 87. IRI VERSUS DIFFERENT FINES CONTENT OF RCA IN RIGID PAVEMENT ...97 

Figure 88. IRI VERSUS DIFFERENT GRAVEL CONTENT OF RAP IN RIGID 
PAVEMENT ..................................................................................................................................98 
 
Figure 89. IRI VERSUS DIFFERENT GRAVEL CONTENT OF RCA IN RIGID 
PAVEMENT ..................................................................................................................................98 
 
Figure 90. IRI VERSUS DIFFERENT SAND CONTENT OF RAP IN RIGID PAVEMENT ...99 

Figure 91. IRI VERSUS DIFFERENT SAND CONTENT OF RCA IN RIGID PAVEMENT ...99 

Figure 92. IRI VERSUS DIFFERENT D60 OF RAP IN RIGID PAVEMENT ..........................100 

Figure 93. IRI VERSUS DIFFERENT D60 OF RCA IN RIGID PAVEMENT ..........................100 

Figure 94. TOTAL RUTTING VERSUS DIFFERENT SMR OF RAP ......................................101 

Figure 95. TOTAL RUTTING VERSUS DIFFERENT SMR OF RCA ......................................101 

Figure 96. TOTAL RUTTING VERSUS DIFFERENT FINES CONTENT OF RAP ...............102 

Figure 97. TOTAL RUTTING VERSUS DIFFERENT FINES CONTENT OF RCA ..............102 

Figure 98. TOTAL RUTTING VERSUS DIFFERENT GRAVEL CONTENT OF RAP ..........103 

Figure 99. TOTAL RUTTING VERSUS DIFFERENT GRAVEL CONTENT OF RCA .........103 

Figure 100.  TOTAL RUTTING VERSUS DIFFERENT SAND CONTENT OF RAP ............104 

Figure 101. TOTAL RUTTING VERSUS DIFFERENT SAND CONTENT OF RCA .............104 

Figure 102. TOTAL RUTTING VERSUS DIFFERENT D60 OF RAP ......................................105 

Figure 103. TOTAL RUTTING VERSUS DIFFERENT D60 OF RCA ......................................105 

Figure 104. MEAN JOINT FAULTING VERSUS DIFFERENT SMR OF RAP .......................107 

Figure 105. MEAN JOINT FAULTING VERSUS DIFFERENT SMR OF RCA ......................107 

 

xv 

Figure 106. MEAN JOINT FAULTING VERSUS DIFFERENT FINES CONTENT OF RAP 108 

Figure 107. MEAN JOINT FAULTING VERSUS DIFFERENT FINES CONTENT OF 

RCA .............................................................................................................................................108 

Figure 108. MEAN JOINT FAULTING VERSUS DIFFERENT GRAVEL CONTENT OF 
RAP ..............................................................................................................................................109 
 
Figure 109. MEAN JOINT FAULTING VERSUS DIFFERENT GRAVEL CONTENT OF 
RCA .............................................................................................................................................109 
 
Figure 110. MEAN JOINT FAULTING VERSUS DIFFERENT SAND CONTENT OF RAP 110 

Figure 111. MEAN JOINT FAULTING VERSUS DIFFERENT SAND CONTENT OF 

RCA .............................................................................................................................................110 

Figure 112. MEAN JOINT FAULTING VERSUS DIFFERENT D60 OF RAP .........................111 

Figure 113. MEAN JOINT FAULTING VERSUS DIFFERENT D60 OF RCA ........................111 

 

xvi 

INTRODUCTION 

 
4.3 million km (2.6 million miles) out of 6.6 million km (4.1 million miles) of total public roads 

are paved roads in the United States of America (Bureau of Transportation Statistics (BTS 2017) 

and more than 90% of the paved roads are flexible pavements (Copeland 2011). The main function 

of flexible pavements is distributing the vehicle loads to the layers beneath the asphalt surface 

layer (e.g. base, subbase, and subgrade layers). Thus, the characteristics and properties of these 

layers  are  very  important  for  the  long-term  pavement  performance  (Little  and  Nair  2009, 

Tutumluer  et  al.  2015).  Aggregate  base  layer  is  the  first  layer  beneath  the  asphalt  surface 

(Cosentino and Kalajian 2001; Yohannes et al. 2009). It is made of coarse-grained aggregates to 

provide a stiff and highly permeable layer (Schuettpelz et al. 2010, Haider et al. 2014, Cetin et al. 

2014, Edil and Cetin 2015). The high stiffness of aggregate base layer improves the stability of the 

sublayers  by  improving  the  vertical  load  distribution  (Zornberg  2017).  Therefore,  stiffer  base 

course has less permanent deformation and increases the lifespan of the pavement (Edil et al. 

2012a). Highway base layer is a very critical component of pavement structures. There are two 

primary  functions  of  highway  base  layers:  (1)  acting  as  a  foundation  to  provide  adequate 

mechanical support to the asphalt or concrete layer to prevent fatigue and occurrence of rutting 

failures, and (2) providing adequate drainage to move the excessive infiltrated water out and away 

from the pavement structure. Materials used in highway base layer construction are responsible 

for distributing the wheel loads uniformly to the subgrade layer so they can protect the subgrade 

layer from excessive loading at a single location and ultimately increase the service life of the 

pavements (Yoder and Witzack 1975, Xiao et al. 2011). It is very well known that majority of the 

 

1 

rutting failures occur due to lack of required mechanical properties of the materials used in the 

highway base layer construction (Tutumluer and Pan 2008, Xiao et al. 2011). 

While large amounts of virgin unbound granular materials are used for the aggregate base layers 

in pavement constructions (Perkins et al. 2005, Haider et al. 2014, Hatipoglu et al. 2020), the lack 

of good quality material availability and high cost of virgin aggregates (VA) have made engineers 

to look for alternative sources such as recycled concrete aggregates (RCAs) and recycled asphalt 

pavements  (RAPs).  These  materials  additionally  provide  environmental  benefits  for  being 

recycled materials.  As a result, in this project alternative materials are being investigated to see if 

they meet the essential pavement performance criteria. The main focus of this project is to collect 

index and performance data of these two types of recycled base materials. Therefore, this thesis 

reports the properties of these materials used in such applications. 

Department of transportations (DOTs) nationwide have been trying to implement the mechanistic 

pavement  design  approach  (Rahn  and  Biehler  2008)  for  pavement  design  and  analyses.  The 

Mechanistic-Empirical Pavement Design Guide (MEPDG) represents a major improvement over 

its predecessors. However, accurate and reliable data first must be collected to take the advantage 

of  such  improvements  in  the  pavement  design.  In  this  pavement  design  approach,  pavement 

performance  is  evaluated  based  on  mechanistically  determined  critical  stresses,  strains, 

temperatures, and moisture levels that are in turn the inputs to empirical prediction models for 

specific pavement distresses such as rutting, fatigue cracking, thermal cracking, and roughness for 

flexible  pavements  and  cracking,  faulting,  and  roughness  for  rigid  pavements.  Accurate 

characterization of the traffic, climate, and material input parameters is therefore important to 

ensure that the theoretical computation of pavement stresses, strains, temperatures, and moisture 

levels are accurate at the critical locations within the system. Depending on the desired level of 

 

2 

accuracy of input parameter, three levels of input are provided from Level 1 (highest level of 

accuracy) to level 3 (lowest level of accuracy). Depending on the criticality of the project and the 

available resources, the designer has the flexibility to choose any one of the input levels for the 

design as well as use a mix of levels.  

The material parameters required for pavement foundation materials including unbound granular 

materials, subgrade, and bedrock may be classified in one of three major groups: (1) pavement 

response model material inputs, (2) Enhanced Integrated Climatic Model (EICM) material inputs, 

and  (3)  other  material  inputs.  Pavement  response  model  materials  input  required  are  resilient 

modulus  (Mr)  used  for  quantifying  the  stress  dependent  stiffness  of  unbound  materials  under 

moving  wheel  loads.  Material  parameters  associated  with  EICM  are  those  parameters  that  are 

required and used by the EICM models to predict the temperature and moisture conditions within 

a  pavement  system.  These  inputs  include  Atterberg  limits,  gradation,  and  saturated  hydraulic 

conductivity.  

Proper implementation of the PMED requires realistic values for the input parameters. The main 

inputs  include  general  site  and  project  information,  allowable  distress  limits  and  associated 

reliability  levels,  traffic  volumes  and  axle  load  distributions,  pavement  structure,  material 

properties,  groundwater  depth,  and  climate.  Pavement  structures  generally  contain  3  layers: 

asphalt/Portland  cement  concrete  (PCC)  (often  consisting  of  several  sublayers  or  lifts), 

base/subbase,  and  subgrade.  The  layers  beneath  the  asphalt/PCC  usually  consist  of  unbound 

materials,  and  their  physical  and  engineering  properties  are  very  crucial  for  overall  pavement 

performances and service life (Haider et al. 2014, Gopisetti et al. 2019, Hatipoglu et al. 2020, 

Gopisetti et al. 2020). This past literature clearly concluded that material properties are crucial 

parameters  that  must  be  taken  into  account  during  the  design  of  pavements.  Therefore,  the 

 

3 

properties of recycled asphalt pavement (RAP) and recycled concrete aggregate (RCA) materials 

should be well understood as they play an important role in pavement design as a base layer. To 

address this need, the research team created a large database summarizing the characteristics of 

RCA and RAP that had been used for such applications in pavements. At the end of this thesis, the 

impact of properties of these materials were evaluated on pavement distress predictions via use of 

the AASHTOware Pavement ME software version 2.6.0. These analyses were conducted using, 

the lowest, the highest and the median value of different properties of RAP and RCA. The “Inputs” 

chapter  and  “Distresses”  chapter  provide  detailed  information  about  input  parameters  and 

performance distress evaluations.  

This thesis reports the collected data for RCA and RAPs used in highway base layers and provide 

recommendations about how to use this data for pavement design and analysis.  

BACKGROUND 

Use of recycled materials promotes sustainability in roadway construction by reducing 

consumption of energy and emission of greenhouse gases associated with mining and production 

of natural aggregates (Lee et al. 2010 and Lee et al. 2011). Recycled materials often manifest 

mechanical behavior that is distinct from that of natural aggregate due to the composition and the 

nature of particulate characteristics. The most widely used recycled aggregates in roadway 

construction are recycled asphalt pavement (RAP) and recycled concrete aggregate (RCA) (Edil 

et al. 2012a). The performance of a pavement system mostly depends on stiffness of the 

pavement structure under specified traffic loads and environmental conditions. RAP and RCA 

have comparable stiffness to natural aggregates that are currently used in roadway base course 

applications (FHWA 2008, Guthrie et al., 2007, Edil et al. 2012a). Hence, their performance 

should be evaluated based upon their relative engineering or index properties.  

 

4 

In order to obtain recycled asphalt pavement (RAP), old asphalt pavement surfaces are milled to a 

specific depth (depending on the asphalt course thickness) and then processed (Edil 2011). In 

simple terms, RAP is a mixture of aged bitumen and aggregate, which is obtained as a by-product 

of pavement milling (Taha et al. 1999). On the other hand, RCA was obtained via crushing of the 

existing hardened concrete of old pavement surfaces or other structures (e.g. buildings and bridges) 

(Edil et al. 2012a).  

RAP and RCA can be either used at the same construction site or stockpiled for future applications. 

Producing and using them at the same construction site can help to reduce the cost and the duration 

of the construction. In fact, up to 30% of cost savings could be achieved by in-place recycling for 

a recycled aggregate generation (Edil 2011).  

The properties of RAP or RCA as an unbound aggregate are certainly depending on several factors 

that relate back to the production of asphalt or concrete as well as the processes followed during 

the production of RAP or RCA. Some of these factors are listed below:  

•  The type of the road (interstate highway, arterial highway, or parking lot) that is milled 

may affect the binder content of the produced RAP since different bituminous content are 

used in different asphalt mixtures.  

•  The regional differences in location of the milled road may result in different RAPs and 

RCAs due to different geological composition and formation of aggregates.  

•  Processing  operation  that  is  used  to  create  RAP  and  RCA  may  affect  the  grain  size 

distribution of these materials due to the different opening sizes of the screens used by the 

different milling operation stations. 

•  The time of exposure of RAP and RCA to atmospheric conditions during stockpiling may 

affect the stiffness of the binder content of RAP as asphalt changes its properties when 

 

5 

exposed to drastic temperatures (cold or hot) for a long period of time (Ullah and Tanyu 

2019) and carbonation of remaining cement content in RCAs (Bestgen et al. 2016). 

•  The type of concrete, quality of raw materials, water/cement ratio, coarse/fine aggregate 

ratio, age of concrete, compaction of concrete, temperature, relative humidity and curing 

of concrete can affect the strength of the recycled concrete all of which come from the 

origin of RCA.  

DATA ON RCA AND RAP PROPERTIES 

Material  characteristics  such  as  mineralogy,  gradation,  angularity,  texture,  and  durability  are 

different for each RCA and RAP materials, and these differences affect the engineering properties 

of them (Tutumluer 2013, Tan et al. 2014). The index properties of RAP and RCA are also highly 

affected  by  several  factors  such  as  the  aggregate  source,  the  aggregate  type,  and  the  type  of 

crushing  operations.  While  determining  the  properties  of  these  recycled  materials  before  the 

pavement  design  and  construction  is  preferred,  it  may  be  costly  and  take  a  long  time  to  be 

completed  for  DOTS.  Therefore,  it  is  important  to  establish  a  database  with  the  information 

collected  from  previous  studies  which  would  provide  some  insight  information  about  the 

boundaries and average properties of these materials and can be used by DOTs during pavement 

analyses  and  designs.  Table  1  summarizes  the  list  of  the  RCA/RAP  data  collected  from  the 

literature.  It  also  shows  the  number  of  available  data  for  each  characteristic  along  with  the 

corresponding data source.  Approximately 50 different studies were examined to create Table 1. 

The  RCA  and  RAP  materials  for  the  available  data  was  captured  for  the  states  of  Minnesota, 

Colorado, Michigan, California, Texas, Ohio, New Jersey, Wisconsin, Illinois, Montana, Virginia, 

Florida, Tennessee, Maryland, New Mexico, Washington, Utah and Rhode Island. The laboratory 

 

6 

data  of  more  than  40  different  recycled  samples  were  collected  in  terms  of  geomechanical 

properties. Most of the samples used in the studies were 100% recycled materials, while there were 

also some blended RCA-RAP materials with natural aggregates at different mixture ratios.  

 

 

 

 

 

 

 

7 

Table 1. LIST OF THE COLLECTED DATA AND CORRESPONDING RESOURCES 

 

Referenc

es 

Lo
c 

Type of 
Material 

Grain 
Size 

Distributi

on 

Atterbe

rg 

Limits 

Compacti

on 

Hydraulic 
Conductivi

ty 

Shear 
Strengt

h 

CB
R 

Resilie

Modul

nt 

us 

 
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2
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5
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9
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,

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A
C

 
,

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C

 
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,
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N

 
,
I

M

 
,

N
M

WI 

M
N 

IL 

Aggregate 
Class 5 
(MN) 

Blend 

(50%RCA 
50% Class5) 

RAP 
RCA 
RPM 

RPM 

RPM 

60%RCA+4
0% RAP 

100% RAP 

1 

1 

7 
7 
2 

1 

1 

1 

1 

 

 

 
 
 

1 

 

 

 

1 

1 

7 
7 
2 

1 

1 

 

1 

1 

1 

7 
7 
2 

 

 

 

 

CO 

RAP 

11 

11 

11 

11 

RAP CBC#1 
RAP CBC#2 
RAP CBC#3 
RAP pitrun 

RAP 

M
T 

V
A 

FL 

RAP 

DGABC 

RAP 

RCA 

RAP 

NJ 

M
N  

3 
3 
3 
3 

4 

3 

1 
1 

1 

4 

3 
3 
3 
3 

 

 

 
 

 

 

 
 
 
 

5 

 

 
 

 

 

3 
3 
3 
3 

 

3 

1 
4 

4 

4 

8 

 

 

 
 
 

 

 

6 

 

 

 
 
24 
24 

 

3 

 
3 

 

 

 

 

 
 
 

 

1 

 

1 

 

 
 
 
 

26 

2 

96 
96 
4 

1 

1 

6 

6 

45 

 
 
 
 

16 

21 

 

 
 

 

 

 

1 
4 

4 

16 

R 
Valu
e 

 

 

 
 
 

 

 

 

 

11 

 
 
48 
48 

 

 

 
 

 

 

Table 1 (cont’d) 

 

 

g
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5
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(

TN 

RAP 

MD 

RAP 

VA 

RAP 

MN 

RAP 

RCA 

NM 

RAP 

MN 

RAP 

FL 

RAP 

FL 

RAP 

WA 

RAP 

TX 

RAP 

MN 

RAP 

WI 

RAP 

WI 

RAP 

RCA 

1 

7 

4 

1 

2 

3 

 

 

1 

1 

1 

 

1 

1 

1 

 

 

4 

 

 

 

 

 

 

 

 

 

 

 

 

3 

7 

4 

1 

2 

1 

3 

 

8 

5 

1 

 

2 

1 

1 

 

7 

 

 

 

 

 

 

 

5 

 

 

 

1 

1 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

9 

 

PD=11 

2 

4 

16 

9 

3 

PD=3 

8 

 

 

 

 

 

 

 

20 

5 

PD= 6 

7 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

9 

Table 1 (cont’d) 

 

CA, 

TX, NJ, 
MI, CO, 

MN 

MN 

RAP 

RCA 

RAP 

RCM 

WI 

RPM 

MN 

RAP 

MN 

RAP 

UT 

RAP 

RI 

RAP 

MN 

RAP 

MN 

RAP 

 
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4 

4 

 

 

 

 

 

 

 

 

 

4 

4 

 

 

 

 

 

 

 

 

 

 

 

 

 

4 

4 

 

 

 

 

1 

1   

 

 

 

 

 

 

12 

11 

 

7 

5 

4 

 

 

 

 

 

 

4 

4 

 

4 

1 

 

6 

4 

7 

5 

 

4 

4 

 

 

1 

11 

12 

4 

7 

 

7 

 

 

 

 

 

 

6 

4 

 

 

 

10 

Table 1 (cont’d) 

 

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l
a
t
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T

RAP 

 

RCA 

RCA 

NJ 

Eastern 
USA 

IL 

RCA 

MN 

RCA 

TX, IA, 

MN 

RCA 

CA, 

CO, MI, 

MN, 
WI, TX 

RCA 

WI 

RCA 

MN 

RCA 

1 

2 

3 

4 

5 

7 

1 

3 

United 
States 

of 

America 

RCA 

RAP 

47 

92 

 

 

 

 

 

 

 

 

3 

3 

31 

 

 

2 

3 

4 

5 

7 

1 

6 

47 

126 

8 

8 

 

 

 

 

7 

1 

3 

32 

57 

1 

1 

8 

8 

4 

4 

 

 

 

 

 

 

 

13 

24 

3 

3 

 

 

 

 

 

 

 

 

3 

3 

 

 

 

 

 

 

 

 

 

5 

66 

24 

38 

153 

0 

316* 

107 

Notes: *: It only represents resilient modulus of RAPs or RAP blends. Strains were not counted for this 
number. PM= Recycled pavement material; CBC= Crushed base course; RCM= Recycled concrete 
material; DGABC= Dense graded aggregate base course; PD= Permanent Deformation; CBR= California 
Bearing Ratio; R-Value= Measures the response of compacted aggregates to a vertically applied pressure 
under specific conditions. 
 
 

 

11 

CHAPTER 1. PHYSICAL PROPERTIES OF RAP AND RCA 

1.1.  GRADATION CHARACTERISTICS 

Gradation  of  the  aggregates  affects  the  engineering  properties  of  granular  materials  such  as 

hydraulic conductivity, shear strength, stiffness, and frost-susceptibility (Saeed 2008). Original 

aggregate type, milling operations, and the crushing methods affect the gradation of RAP and RCA 

(Cosentino and Kalajian 2001). 

The  first  material  characteristics  for  the  database  was  selected  as  the  index  properties,  which 

mainly consists of the gradation of aggregates. Gradation characteristics database include gravel, 

sand,  silt  and  clay  contents,  effective  diameter  sizes  (D60,  D30  and  D10),  and  coefficient  of 

uniformity (Cu) and coefficient of curvature (Cc). Approximately 190 different aggregate materials 

including blends with natural aggregate were included in the gradation database.  

It was observed that the gradations of RAPs were generally similar to natural aggregates; however, 

depending on the method used, RAPs were likely to contain lower fines content (Chesner et al. 

1998). Per MnDOT guideline and applications, RAPs can be considered as a Class 7 aggregate 

based on their comparable gradation curves whereas RCA can be considered as Class 5 aggregate 

based on their comparable gradation curves (LRRB 2016).  

Asphalt content (~ 4.5% - 6%) and trapped air between asphalt coating and aggregate particles 

cause lower specific gravity values for RAP than that of natural aggregates (Cosentino et al. 2003). 

RCA also has a relatively lower specific gravity than natural aggregates due to the presence of 

mortar in RCA matrix (Snyder et al. 1994). This is well shown in our database when comparing 

the specific gravities of the recycled materials with natural aggregates (Appendix A and Table 2). 

 

12 

The Gs of RAP ranges from 2.19 to 2.87 with the median value of 2.4 while Gs of RCA is between 

2.12 and 2.7 with the median value of 2.39. 

94.1% is the highest gravel percent reported for RCA in Mahedi and Cetin (2020) while Edil et al. 

(2017) reported the lowest gravel content (31.8%) for RCA. On the other hand, Alam et al. (2010) 

showed 4% gravel content for a RAP material which was the lowest gravel percent in the database. 

Locander (2009) reported the highest gravel percent for a RAP material which contained 75% 

gravel. Finally, the median gravel percent of RAP and RCA is reported to be 45% (Guthrie et al. 

2007) and 51% (Diagne et al. 2015), respectively. 

The highest sand content in RCA was reported to be 64.9% (Edil et al. 2012a) while Mahedi and 

Cetin (2020) used a RCA with 4.9% sand which was the lowest sand percent in the database. The 

highest and lowest sand contents for RAP materials were 97% and 28.1%, respectively. At last, 

the median value of sand content is 54% and 46.3% for RAP and RCA, respectively.  

12.8% is the highest fines percent for RCA (Edil et al 2012a) while 0.1% is the lowest fines percent 

as reported in Mahedi and Cetin (2020). On the other hand, RAP’s lowest fines content is 0% in 

Alam et al. (2010) study while Camargo et al. (2013) reported highest fines content in RAP with 

11%.  In  summary,  the  median  value  of  fines  percent  is  1%  and  2.8%  for  RAP  and  RCA, 

respectively.   

Table 2. summarizes the gradation table in Appendix A by providing maximum, minimum and 

median value of RAPs and RCAs according to the database. 

Appendix A reports the specific gravities and gradation characteristics (sand and fines percent are 

shown along with D10, D30, D60, Cc and Cu) of the materials for each study. According to Appendix 

A, all of the RAPs and RCAs are classified as coarse-grained soils. Since most of the materials 

 

13 

had fines content lower than 12%, they were all classified either well-graded gravel (GW) and 

poorly graded gravel (GP) or well-graded sand (SW) and poorly graded sand (SP)-SW.  

Table 2. INDEX PROPERTY RANGES OF RCA AND RAP 

Characteristic

s 

Lower 
Limit 

RAP 
Median 

45 
54 
1 

% Gravel 
% Sand 
% Fines 

3 
28.1 
0 
5x10-1/ 
10-1/ 
D10 (mm/inch) 
1.96x10-2 
3.9x10-3 
D30 (mm/inch)  8x10-2/ 
3.1x10-3  1.5/ 6x10-2 
1.5x10-

D60 (mm/inch) 

1/ 

5.9x10-3  

5 
0.21 
2.19 

4.82/ 

1.89x10-1  

10.65 
1.2 
2.395 

Cu 
Cc 
Gs 

Upper 
Limit 
68.1 
97 
11 
1/  

3.93x10-2  

4.9/  
1.9x10-1 
10.4/ 

4.09x10-1 

Lower 
Limit 
31.8 
4.9 
0.1 
10-1/  

3.9x10-3  
2x10-1/ 
7.9x10-3 
6x10-1/ 
2.36x10-2  

40 
8 
2.87 

2.1 
0.14 
2.12 

RCA 
Median 

51 
46.3 
2.8 

2.3x10-1/  
9x10-3  
1.2/  

4.72x10-2 

Upper 
Limit 
94.1 
64.9 
12.8 

4.3x10-1/ 
1.7x10-2  

6.5/ 

2.56x10-1 

6.8/  

2.67x10-1 

16.3/ 

6.42x10-1  

32 
1.4 
2.39 

66 
6 
2.7 

Notes: 52 gravel, sand and fines contents data were collected for RAPs from different sources, while 30, 
27 and 27 data were used to determine the lowest, median and highest values of D10, D30 and D60 for RAPs, 
respectively. 35 Cu, 37 Cc, and 38 Gs data were available to derive lower,median and upper limits of RAPs. 
34 gravel, sand and fines contents data were collected for RCAs from different sources, while 19, 17 and 
17  data  were  used  to  determine  the  lowest,  median  and  highest  values  of  D10,  D30  and  D60 for  RCAs, 
respectively. 29 Cu, 29 Cc, and 32 Gs data were available to derive lower,median and upper limits of RCAs. 
 
1.2.  COMPACTION CHARACTERISTICS  

The general trend of Proctor compaction tests shows that RAP and RCA have lower maximum dry 

unit  weight  than  natural  aggregates  (Figure  1,  Figure  2,  Figure  3  and  Figure  4).    Table  3 

summarizes the compaction characteristics (MDU and OMC) of RCA and RAP materials collected 

for the database. MDU of RAP ranges between 17.2 kN/m3 (110 pcf) and 24.1 kN/m3 (155 pcf) 

with the median value of 19.6 kN/m3 (126 pcf). The limits of MDU for RCA is 18.3 kN/m3 (118 

pcf) and 21.7 kN/m3 (140 pcf) with the median of 19.7 kN/m3 (127 pcf). OMC of RAPs ranges 

between 4% and 10.7% with the median to be 6.05% while OMC of RCA ranges between 6.1% 

and 14.8% with the median of 10.8%. Figures 3 and 4 show that the voids in RAP matrix cannot 

 

14 

be filled effectively because of low fines contents which yields to a lower maximum dry unit 

weight (Locander 2009; Blankenagel and Guthrie 2006). 

RAP possesses hydrophobic properties due to the asphalt coating around aggregate particles and 

this contributes RAP materials to have lower optimum water content (Figure 5 and Figure 6). On 

the other hand, RCA shows hydrophilic properties due to concrete mortar residues thus a higher 

optimum  moisture  content  is  reported  as  a  result  of  higher  water  absorption  capacity  of  RCA 

(Figure 7 and Figure 8) (Edil et al. 2012a, Nokkaew et al. 2012, Sayed et al. 1993, Rahardjo et al. 

2010). In addition, the hydration and cementation of dehydrated cement particles in RCA may 

cause a reduction in the dry unit weight of RCA. Furthermore, higher fines contents in RCA cause 

a higher optimum water content due to an increase in the surface area and absorption capacity of 

aggregate and cement particles (Jayakody et al. 2012). On the other hand, lower maximum dry 

unit weights of RAP may be due to their lower specific gravities caused by asphalt content and 

low fines contents (Guthrie et al. 2007, Locander 2009).  

The reduction in the maximum dry unit weight (MDU) of recycled aggregate-natural aggregate 

mixtures is directly proportional to the RAP and RCA contents in the mixtures (Taha et al. 1999). 

Higher rate of reductions in the maximum dry unit weights were observed with an increase in 

recycled aggregate contents in the mixtures (Bennert et al. 2000). Moreover, using more RAP 

content in the RAP-natural aggregate mixtures caused further reductions in the optimum water 

content (Locander 2009) while use of a higher amount of RCA in the RCA-natural aggregate 

mixtures  caused  an  increase  in  the  optimum  moisture  content  (OMC)  (Bennert  et  al.  2000). 

According to our database, the compaction results were mostly obtained from materials compacted 

at modified Proctor compaction energy. Therefore, it is recommended to use modified Proctor 

compaction data for analyses. 

 

15 

Table 3. COMPACTION CHARACTERISTICS RANGES OF RCA AND RAP 

RAP 
Median 

Upper 
Limit 

Lower 
Limit 

RCA 
Median 

Upper 
Limit 

Characteristics 

MDU 

(kN/m3)/(pcf) 

OMC (%) 

Lower 
Limit 

4 

17.2 (110)  19.6 (126)  24.1 (155)  18.3 (118)  19.7 (127)  21.7 (140) 

Notes: MDU=Maximum dry density, OMC=optimum moisture content. 46 and 35 MDU and OMC data 
were collected for RAPs and RCAs, respectively. 
 

6.05 

10.7 

6.1 

10.8 

14.8 

Figure 1. MAXIMUM DRY UNIT WEIGHT (MDU) VERSUS RAP CONTENT 

Notes: CBC= Crushed base course; DGABC= Dense graded aggregate base course; CR3= County Road 
3; VA= Virgin aggregate 

 

Figure 2. MAXIMUM DRY UNIT WEIGHT (MDU) VERSUS RAP CONTENT (WHISKER PLOT) 

 

 

16 

Figure 3. MAXIMUM DRY UNIT WEIGHT (MDU) VERSUS RCA CONTENT 

Notes: DGABC= Dense graded aggregate base course; VA= Virgin aggregate 
 

 

Figure 4. MAXIMUM DRY UNIT WEIGHT (MDU) VERSUS RCA CONTENT (WHISKER PLOT) 

 

 

Figure 5. OPTIMUM MOISTURE CONTENT (OMC) VERSUS RAP CONTENT 

Notes: CBC= Crushed Base Course; DGABC= Dense Graded Aggregate Base Course; CR3= County 
road 3; VA= Virgin aggregate 

 

 

17 

Figure 6. OPTIMUM MOISTURE CONTENT (OMC) VERSUS RAP CONTENT (WHISKER PLOT) 

 

 

Figure 7. OPTIMUM MOISTURE CONTENT (OMC) VERSUS RCA CONTENT 

Note: VA= Virgin aggregate; DGABC= Dense graded aggregate base course 
 

 

Figure 8. OPTIMUM MOISTURE CONTENT (OMC) VERSUS RCA CONTENT (WHISKER PLOT) 

 

 

18 

It is stated by Kim et al. (2007) that gyratory compactor provided better results to simulate the in-

situ conditions. Figure 9 shows that the gratory compaction results simulate the actual field results 

better than the Proctor compaction results in terms of moisture content and dry unit weight  (Kim 

et al. 2007). 

Figure 9. THE EFFECT OF COMPACTION METHOD ON THE DEGREE OF THE COMPACTION 

 

 

Binding quality improves between aggregate particles due to softening of asphalt binder at higher 

temperatures.  Therefore,  the  compaction  characteristics  of  RAP  changes  with  temperature 

(Soleimanbeigi and Edil 2015b). For example, the dry unit weight of the specimens increased 

about  3.5%  when  compacted  at  49°C  (120°F)  than  the  ones  compacted  at  21°C  (70°F) 

(Montemayor 1998, as cited in Cosentino and Kalajian 2001).  

1.3.  PLASTICITY CHARACTERISTICS  

Most of the plasticity index of RAP and RCA were reported as non-plastic (NP) (Locander 2009, 

Ullah and Tanyu 2019, Edil et al. 2012a, Mijic et al. 2019, Ullah et al. 2018, Edil et al. 2012b, 

Guthrie et al. 2007, and Cetin et al. 2020. Attia and Abdelrahman (2010a) tested the liquid limit 

(LL) of 100% RAP and 75% RAP and reported LL to be 26 and 25, respectively. They also 

 

19 

reported LL to be 19, 20, 25 and 30 for different 50% RAPs mixed with Class 5 aggregate. Class 

5 is a typical base course material classification used in pavements by MnDOT. More detailed 

information about Class 5 can be found at MnDOT grading and base manual (MnDOT 2016). 

 

 

 

 

20 

CHAPTER 2. MECHANICAL AND HYDRAULIC PROPERTIES 

OF RAP AND RCA 

 
Index properties, the aggregate type, and asphalt/mortar content of RAP and RCA affect their 

engineering  properties  significantly  (Thakur  and  Han  2015  and  Hiller  et  al.  2011).  Thus,  it  is 

important  to  study  the  components  and  the  engineering  properties  of  the  aggregates  for 

constructing high-quality pavements as recycled aggregates are obtained from different sources 

(Gonzalez and Moo-Young 2004). Some specifications (AASHTO 2002, Greenbook 2009, ASTM 

2016) limit the content of an impurity, e.g., crushed clay brick, unless its presence improves the 

engineering  properties  of  aggregate  base  course  (Edil  et  al.  2012a).  Hydraulic  conductivity, 

stiffness, strength, shear strength and permanent deformations are discussed and summarized in 

this section.  

2.1. HYDRAULIC CONDUCTIVITY 

One of the main functions of aggregate base layers is to provide an adequate drainage and prevent 

capillary action to increase the service life of pavements (Cedergren 1988). An increase in the pore 

water pressure in the aggregate base layers causes a reduction in the stiffness of aggregate base 

layers  (Edil  et  al.  2012a).  Hydraulic  properties  of  aggregates  are  affected  by  gradation 

characteristics (e.g. sand, fines content and D10). Fine particles fill up the voids and reduce drainage 

properties of aggregates (Cosentino et al. 2003). Saturated hydraulic conductivity (ksat) and soil-

water characteristics curve (SWCC) are the two parameters that should be evaluated for pavement 

designs (Nokkaew et al. 2012). Saturated hydraulic conductivity is a quantitative measure of a 

saturated soil's ability to transmit water when subjected to a hydraulic gradient and it is used as a 

 

21 

parameter  for  drainage  design  while  SWCC  can  be  used  to  determine  the  matric  suction  of 

aggregates at different moisture contents then it can be used to predict the modulus of aggregate 

base layers (Gupta et al. 2004, Ba et al. 2013). 

As  mentioned  in  the  previous  section,  RAP  shows  hydrophobic  properties  while  RCA  shows 

hydrophilic properties (Edil et al. 2012a; Rahardjo et al. 2010). Due to the hydrophobicity of RAP, 

it tends to have higher ksat than RCA (Nokkaew et al. 2012). Thus, if the gradations are similar, 

RAP tends to provide a better drainage layer than RCA (Edil et al. 2012a; Hoppe et al. 2015). 

Mokwa  and  Peebles  (2005)  and  Cosentino  et  al.  (2003)  reported  an  increase  in  hydraulic 

conductivity with higher RAP content in the RAP-natural aggregate mixtures. Kang et al. (2011) 

also showed 100% RAP had a higher hydraulic conductivity than natural aggregates. On the other 

hand, Wu et al. (2012) indicated that the hydraulic conductivity of base course materials decreased 

by the addition of RAP. After porosity analysis using X-ray scanning, it turned out that the 80% 

RAP had less air voids than the crushed aggregate specimens which may have been the cause for 

observing  low  hydraulic  conductivity.  According  to  Bennert  and  Maher  (2005),  RAP-natural 

aggregate  blends  with  an  increase  in  RAP  content  from  25%  to  75%  lowered  the  hydraulic 

conductivity of the mixture to almost less than 3.5x10-6 m/s (4.2x10-2  ft/hr) while 100% RAP had 

a hydraulic conductivity value of approximately 5.64x10-5 m/s (6.7x10-1 ft/hr). Kang et al. (2011) 

showed that addition of 25% RAP in aggregates improved the saturated hydraulic conductivities 

of the aggregate mixtures since RAP was a coarser material than that of natural aggregates used in 

that particular study. However, with a further increase in RAP contents, the saturated hydraulic 

conductivities  of  the  mixtures  reduced.  It  was  concluded  that  a  reduction  in  the  hydraulic 

 

22 

conductivity may have been due to the that dense packing of the RAP-natural aggregate mixtures. 

Thus, it lowered the saturated hydraulic conductivity of the mixtures.  

Figure 10. HYDRAULIC CONDUCTIVITY VERSUS RAP CONTENT 

 

Bennert and Maher (2005) showed that RCA-natural aggregate blends with an increase in RCA 

content  from  25%  to  75%  of  total  weight  lowered  the  hydraulic  conductivity  of  the  blend  to 

approximately 50% while the hydraulic conductivity of the RCA was 10-6 m/s (0.000145 ft/hr). 

According  to  Kang  et  al.  (2011),  hydraulic  conductivity  of  natural  aggregates  increased  with 

addition of RCA up to 50% by weight. However, further addition of RCA caused a reduction in 

hydraulic  conductivity.  The  RCA  alone  had  higher  hydraulic  conductivity  than  that  of  natural 

aggregate,  while  the  50%  RCA-50%  natural  aggregate  mixture  had  the  highest  hydraulic 

conductivity with in all blends. 

 

23 

Figure 11. HYDRAULIC CONDUCTIVITY VERSUS RCA CONTENT 

 

 

To evaluate the relationship between hydraulic conductivity and gradation of RAP materials, Figure 12 is 

presented with 8 data of hydraulic conductivity of 100% RAP from different studies. D10 and percent fines 

are expected to have major influence on hydraulic conductivity. Low D10 means higher fine particles, which 

is expected to clog the pores in the material matrix and reduce air voids. Thus, it causes lower hydraulic 

conductivity. However, Figure 12 confirms that hydraulic conductivity of RAP increases when D10 

values increases with few exceptions (e.g. D10 = 0.4 mm). 

Figure 12. HYDRAULIC CONDUCTIVITY VERSUS D10 OF 100% RAP 

 

 

24 

According  to  Figure  13,  there  is  a  decreasing  trend  for  the  hydraulic  conductivities  of  RAP 

materials as fines content increases.  

Figure 13. HYDRAULIC CONDUCTIVITY VERSUS FINES CONTENT OF 100% RAP 

 

Figure 14 shows the relationship between hydraulic conductivity of different RAP blends and their 

corresponding  fines  contents.  The  hydraulic  conductivities  of  different  crushed  base  course 

materials  mixed  with  RAP  materials  at  20%  and  50%  RAP  were  collected  from  Mokwa  and 

Peebles (2005).  

Hydraulic conductivity of 100% RAP ranges between 1.8x10-7 m/s (2.1x10-3 ft/hr) and 1.1x10-3 

m/s (1.7x10-1 ft/hr) with the median of 6. 9x10-5 m/s (1x10-2 ft/hr) according to our database. 

Figure 14. HYDRAULIC CONDUCTIVITY VERSUS FINES CONTENT OF DIFFERENT RAP 

 

 

25 

BLENDS 

In Figure 15, there are 11 different hydraulic conductivity data of 100% RCA with corresponding 

fines content. On the other hand, no trend was observed between hydraulic conductivity and fines 

content of the RAP materials. Hydraulic conductivities of RCAs ranged between 1.05x10-6 m/s 

(1.2x10-2 ft/hr) and 1.2x10-3 m/s (1.7x10-1 ft/hr) with the median of 1.7x10-5 m/s (2.5x10-3 ft/hr) 

according to our database. 

Figure 15. HYDRAULIC CONDUCTIVITY VERSUS FINE CONTENT OF 100% RCA 

 

 

2.2. STRENGTH 

The  California  Bearing  Ratio  (CBR)  of  base  materials  is  an  indication  of  their  mechanical 

characteristics under vertical loading (traffic) and is determined as the ratio of the penetration 

resistance of the base material to that of a standard crushed stone. The CBR has been used by 

pavement engineers to characterize the strength of materials for designing pavements (Thakur and 

Han 2015). The minimum CBR values of the aggregate base and subbase layers should be 80 and 

60, respectively (Jayakody et al. 2012; Ooi et al. 2010). In Florida, lime rock Bearing Ratio (LBR) 

which is a modified version of conventional CBR test, is commonly used (Cosentino et al. 2003). 

 

26 

In addition to the specified minimum CBR values, LBR should be at least 100 (LBR = 1.25 x 

CBR) for aggregate base layers (FDOT 2018). 

The database showed that the CBR values of 100 % RAP ranged from 18 to 68 with the median to 

be 28 while CBR of 100% RCA was between 58 to 169 with the median 146. 

 

2.2.1. IMPACTS OF SELECTED INDEX PROPERTIES ON CBR 

Gravel-to-sand  (G/S) ratio and fines contents were selected to investigate their effects on CBR of 

RAP and RCA materials. Figures 16 and 17 reveal that there is not a specific trend between CBR 

of 100% RAP versus fines content and/or gravel to sand ratio; however, it is not possible to draw 

any conclusion due to lack of the data. 

Figure 16. CBR VERSUS GRAVEL TO SAND RATIO OF 100% RAPS 

 

 

27 

 
Figure 17. CBR VERSUS FINES CONTENT OF 100% RAP SAMPLES 

According to Figures 18 and 19, there is also not a specific trend between CBR of 100% RCA and 

fines content or gravel to sand ratio; however, it is not possible to draw any conclusion due to lack 

of data. 

Figure 18. CBR VERSUS GRAVEL TO SAND RATIO OF RCA SAMPLES 

 

 

28 

Figure 19. CBR VERSUS FINES CONTENT OF RCA SAMPLES 

 

 

 
2.2.2. IMPACTS OF RAP/RCA CONTENTS ON CBR 

In general, RAP has lower CBR than natural aggregates. In addition, increasing the RAP content 

in the RAP-natural aggregate mixtures reduces the CBR (Bennert and Maher 2005; Guthrie et al. 

2007). Figure 20 clearly shows that CBR of RAP-natural aggregates decreases with higher RAP 

contents  in  the  mixture.  The  asphalt  coating  around  the  particles  may  be  the  reason  for  CBR 

reduction  in  the  presence  of  RAP  since  asphalt  coating  reduces  the  particle  bonding  and 

interlocking mechanism of aggregate particles (Ooi et al. 2010; Taha et al. 1999). In addition, a 

lower fines content of RAP may leave unfilled voids (open-graded structure), which may result in 

lower CBR (Sayed et al. 1993). Cosentino et al. (2003), Bennert and Maher (2005), Ullah and 

Tanyu (2019), Cosentino and Bleakley (2013) and Guthrie et al. (2007) conducted CBR tests on 

blended RAP-natural aggregate specimens, all of which except Cosentino et al. (2003), reported a 

decrease in CBR with an increase in RAP content. On the other hand, Cosentino et al. (2003) 

observed that the CBR of the mixtures first increased with an increase in RAP content in the blend 

up to a certain level (~RAP content is 80%) and then started decreasing.  

 

29 

Depending on the physical, chemical and morphological characteristics of RAP and/or moisture 

contents used for blends, different trends could be observed in different applications (Thakur and 

Han 2015). Figure 20 reports the type of each material that is blended with RAP. Natural aggregate, 

lime rock (LR), base material, dense graded aggregate base course (DGABC) and fine sand were 

used to blend RAPs. 

Notes: VA= Virgin aggregate; LR= Limerock; DGABC= Dense graded aggregate base course 

Figure 20. CBR VERSUS RAP CONTENT 

 

 

The literature review showed that compacting RAP at a relatively higher temperature increased its 

dry unit weight which led to an increase in the LBR values. For instance, RAP that was compacted 

at 49°C (120°F), the range of LBR was increased from 25-50 to 42-125 (Montemayor 1998). On 

the other hand, higher ambient temperature decreases the LBR of RAP after compaction, while 

higher LBR values were observed at lower ambient temperatures due to asphalt material hardening 

(Cosentino and Kalajian 2001). 

 

30 

It was observed that the CBR of RCA materials (either soaked or unsoaked) had different trends 

in different studies. While lower CBR values were seen for unsoaked RCA materials compared to 

natural aggregates, this trend was opposite when they were soaked (Jayakody et al. 2012). The 

reason of different behaviors of RCA could be due to the presence of dehydrated cement content. 

Relatively higher CBR values can be observed with longer soaking period since more cementitious 

reactions could occur with longer curing periods (Poon et al. 2006; Garach et al. 2015; Bestgen et 

al. 2016). 

To  investigate  the  CBR  behaviors  of  natural  aggregate-RCA  mixtures,  Figure  21  and  22  are 

presented.  These  Figures  show  that  there  is  not  a  discernible  trend  between  CBR  and  RCA 

contents. Figure 22 shows normalized CBR versus RCA content. Normalized CBR is obtained by 

dividing the CBR of each RCA blend by the CBR of 100% RCA of the same study. 

Notes: The CBR value corresponding to 0.1 and 0.2 inches of penetration was used in Bennert and Maher 
(2005) study 

Figure 21. CBR VERSUS RCA CONTENT 

 

 

31 

Figure 22. NORMALIZED CBR VERSUS RCA CONTENT 

Notes: Virgin GAB= Virgin graded aggregate base; DGABC= Dense graded aggregate base course; VA= 
Virgin aggregate 

 

 

2.3. STIFFNESS  

Resilient modulus (Mr) is a fundamental material property used to analyze stiffness of materials 

under  different  conditions  such  as  moisture,  density,  and  stress  level.  The  1993  American 

Association of State Highway and Transportation Officials (AASHTO) flexible pavement design 

method  and  the  current  Mechanistic-Empirical  Pavement  Design  Guide  (MEPDG)  use  Mr to 

define subgrade and base stiffness for pavement systems. Mr is defined as a ratio of applied axle 

deviator stress and axle recoverable strain. Mr of RAP and/or RCA materials depends on several 

factors including moisture content, freeze-thaw cycles, density, stress history, aggregate type, RAP 

or RCA type, gradation, temperature, asphalt content in RAP, type of stabilizing agent and curing 

time (Thakur and Han 2015, Bestgen et al. 2016). 

Mr plays an important role in pavement design. Therefore, most of the studies have reported Mr as 

a stiffness characteristic. In addition to the summary resilient moduli (SMR) values, k1, k2, k3, k6 

 

32 

and k7 were provided in the database. Summary resilient moduli (SMR) were reported at a bulk 

stress of 208 kPa and octahedral stress of 48.6 kPa for base materials as recommended by NCHRP 

1-28A.  

As RAP content increases, Mr gets higher while the plastic strain increases. More than 400 Mr data 

investigating the resilient modulus of RAP, RCA or blends were collected for the database. It also 

includes  the  Mr  data  of  these  materials  that  were  tested  at  different  environmental  conditions 

including different temperatures, freeze-thaw cycles, and moisture contents.  

Overall, it was observed that RAP and RCA in the base course had higher Mr than that of well-

graded  natural  aggregates.  The  SMr  reported  in  the  database  for  RAP  was  between  168  MPa 

(24366 psi) and 400 MPa (58015 psi) with the median value to be 261.5 MPa (37927 psi). The 

SMr of RCA ranged between 123.4 MPa (17897 psi) and 370 MPa (53664 psi) with the median 

value of 183 MPa (26541 psi) according to the database.  

 
 
2.3.1. EFFECTS OF INDEX PROPERTIES ON STIFFNESS OF RCA AND RAP 
 
Figure  23  presents  summary  resilient  modulus  of  RAP  versus  gravel-to-sand  (G/S)  ratio  to 

investigate the effects of index properties on corresponding stiffness. Figure 24 shows that SMr of 

RAP is lower at higher G/S ratios. This indicates that RAP with higher sand content would have 

higher SMr in general (Figure 24).  

 
 

 

33 

Figure 23. SMR AND GRAVEL TO SAND RATIO OF 100% RAPS 

 

 

Figure 24. SMR VERSUS GRAVEL TO SAND RATIO OF 100% RAPS (WHISKER PLOT) 

 
Figure 25 and Figure 26 show that there is no correlation or trend between SMr and fines content 

of RAPs (within the typical ranges observed in this study).  

 

34 

Figure 25. SMR VERSUS FINES CONTENT OF 100% RAPS 

Figure 26. SMR VERUS FINES CONTENT OF 100% RAPS (WHISKER PLOT) 

 

 

The trend between SMr of RCA and corresponding G/S ratios were not as significant as the ones 

observed for RAPs. However, it was observed that an increase in SMr of RCAs when G/S ratio 

was higher.  

 

35 

Figure 27. SMR VERSUS GRAVEL TO SAND RATIO OF 100% RCAS 

 

Figure 28. SMR VERSUS GRAVEL TO SAND RATIO OF 100% RCAS (WHISKER PLOT) 

 

According  to  Figures  29  and  30,  there  is  a  slight  decrease  in  SMr  of  RCAs  as  fines  content 

increases. However, this was not consistent with some other studies such as Bestgen et al. (2016). 

 

36 

Figure 29. SMR VERSUS FINES CONTENT OF 100% RCAS 

 

Figure 30. SMR VERSUS FINES CONTENT OF 100% RCAS (WHISKER PLOT) 

 

The  maximum  dry  unit  weight  (MDU)  and  optimum  moisture  content  (OMC)  of  RAP  from 

different studies were plotted against the corresponding summary resilient modulus (SMr) of the 

corresponding RAP materials (Figures 31 and 33). To better understand these scatter plots, Figures 

32 and 34 are shown as whisker plots. However, no significant trend was observed between MDU 

and SMr of RAP materials (Figure 32). There was a slight decrease in SMr of RAPs with an increase 

in OMC (Figure 33). 

 

37 

Figure 31. SMR VERSUS MAXIMUM DRY UNIT WEIGHT OF 100% RAP 

 

Figure 32. SMR VERSUS MAXIMUM DRY UNIT WEIGHT OF 100% RAP (WHISKER PLOT) 

 

Figure 33. SMR VERSUS OPTIMUM MOISTURE CONTENT OF 100% RAP 

 

 

38 

 

Figure 34. SMR VERSUS OPTIMUM MOISTURE CONTENT OF 100% RAP (WHISKER PLOT) 

D30 and D60 of RAPs were plotted against their corresponding SMr values in Figures 35 and 37, 

respectively. According to Figure 36, RAPs with higher D30 tend to have higher SMr. Similar trend 

was also observed in Figure 38. It shows that SMr of RAPs are higher when they have higher D60 

values. 

Figure 35. SMR VERSUS D30 OF 100% RAP 

 

 

39 

Figure 36. SMR VERSUS D30 OF 100% RAP (WHISKER PLOT) 

 

Figure 37. SMR VERSUS D60 OF 100% RAP 

 

 

Figure 38. SMR VERSUS D60 OF 100% RAP (WHISKER PLOT) 

 

40 

Coefficient of curvature (Cc) should be between 1 and 3 for well-graded gravel and sand. Figures 

39 and 41 show variation of SMr of RAPs with their corresponding Cc values. Based on the data 

collected, it was observed that SMr of RAPs were higher when Cc of RAPs were lower than 1 

(1>Cc) and higher than 3 (Cc>3). It means that poor graded RAP may have higher SMr. Figure 42 

shows that an increase in Cu yields some increase in SMr).  

Figure 39. SMR VERSUS CC OF 100% RAP 

 

 

Figure 40. SMR VERSUS CU OF 100% RAP 

 

41 

Figure 41. SMR VERSUS CC OF 100% RAP (WHISKER PLOT) 

 

 

Figure 42. SMR VERSUS CU OF 100% RAP (WHISKER PLOT) 

RCA materials compacted at higher MDU are likely to have higher SMr values(Figures 43 and 

44). Higher OMC results in a reduction in SMr of RCAs. The OMC of RCA ranged from 6.1% to 

11.9%  while  their  corresponding  SMr  changed  between  370  MPa  (53664  psi)  and  124MPa 

(17984.7  psi)  (Figures  45  and  46).  Figures  47,  48,  49  and  50  shows  that  no  correlations  are 

observed between D30 and D60 characteristics of RCAs and the corresponding SMr values.  

 

42 

The MDU of RCA ranged from 18.9 kN/m3 (121.4 pcf) to 20.9 kN/m3 (134.4 pcf) while their 

corresponding SMr changed between 370 MPa (53664 psi) and 124MPa (17985psi) (Figures 43 

and 44).  

According to Figure 51 and 52, well-graded RCA yields higher SMr than that of poorly-graded 

ones. The SMr of RCA with Cc between 1 and 3 tended to be higher than the ones with Cc (1>Cc) 

smaller than 1 or higher than 3 (Cc>3). Higher Cu values in RCAs could result in higher SMr 

(Figure 54). 

Figure 43. SMR VERSUS MDU OF 100% RCA 

 

 

Figure 44. SMR VERSUS MDU OF 100% RCA (WHISKE PLOT) 

 

43 

Figure 45. SMR VERSUS OPTIMUM MOISTURE CONTENT OF 100% RCA 

 

Figure 46. SMR VERSUS OPTIMUM MOISTURE CONTENT OF 100% RCA (WHISKER PLOT) 

 

 

Figure 47. SMR VERSUS D30 OF 100% RCA 

44 

 

Figure 48. SMR VERSUS D30 OF 100% RCA (WHISKER) 

Figure 49. SMR VERSUS D60 OF 100% RCA 

 

 

Figure 50. SMR VERSUS D60 OF 100% RCA (WHISKER PLOT) 

 

 

45 

Figure 51. SMR VERSUS CC OF 100% RCA 

 

 

Figure 52. SMR VERSUS CC OF 100% RCA (WHISKER PLOT) 

Figure 53. SMR VERSUS CU OF 100% RCA 

 

46 

 

Figure 54. SMR VERSUS CU OF 100% RCA (WHISKER PLOT) 

 

 

2.3.2. TEMPERATURE EFFECTS ON RAP AND RCA STIFFNESS 

RAP  is  sensitive  to  temperature  due  to  its  asphalt  content,  which  is  a  temperature-sensitive 

material.  On  the  other  hand,  RCA  and  natural  aggregates  are  not  as  sensitive  to  temperature 

changes as RAP (Wen et al. 2011; Soleimanbeigi et al. 2015). The SMr of RAP-natural aggregate 

mixtures reduces as temperature increases (Soleimanbeigi et al. 2015). However, Soleimanbeigi 

and Edil (2015b) claimed that RAP could undergo a thermal preloading process. Thus, it would 

have higher stiffness at higher temperatures (Read and Whiteoak 2003, Wen et al. 2011). Thermal 

conditioning  in  this  context  means  inducing  elevated  temperature  to  RAP  during  compaction 

process. The induced elevated temperature increases compressibility of RAP, thus reducing the 

void space in the material. When the temperature drops, the compacted RAP is expected to have 

higher stiffness and strength due to reduction in void space. Therefore, it is important to know the 

proper  thermal  conditioning  for  RAP  during  compaction  when  used  as  a  base  course 

(Soleimanbeigi and Edil 2015b). 

 

47 

Edil et al. (2012a) and Soleimanbeigi et al. (2015) conducted Mr tests on Colorado, Texas and New 

Jersey RAP at 7°, 23°, 35°, 50°C (44.6°, 73.4°, 95° and 122°F) and it was observed that SMr of 

all RAP materials decreased with an increase in temperature (Figure 55). Soleimanbeigi and Edil 

(2015b) showed that SMR of RAP was also affected by the compaction temperature. SMr of RAPs 

increased  when  RAPs  were  compacted  at  higher  temperatures  and  then  cooled  and  tested  for 

resilient modulus as shown in Figure 55. Figure 56 shows the normalized SMr of RAP versus 

different temperatures. SMr of RAP at different temperature was divided by the SMr of RAP at 

23°C (73.4°F) of each RAP study. There was a decreasing trend with higher temperature except 

for  the  New  Jersey  and  Colorado  RAP  from  Soleimanbeigi  et  al.  (2015)  which  had  a  slight 

increasing trend. 

Figure 55. SMR VERSUS TESTING TEMPERATURE OF 100% RAPS 

 

 

 

48 

 

Figure 56. NORMALIZED SMR VERSUS TEMPERATURE OF 100% RAPS 

On the other hand, Figure 57 shows that RCA is not temperature-dependent. Moreover, Figure 58 

shows the normalized SMr–Temperature data that were tested at different temperatures. The SMr 

of RCA at different temperature was divided by the SMr of the same RCA at 23°C (73.4°F). The 

low  R2  value  in  Figure  58  reveals  that  there  is  no  relationship  between  SMr  of  RCA  and 

temperature conditions during testing.  Figure 59 also shows that SMr of RCA is independent from 

the temperature as the whisker plots do not indicate any visible trend. However, the SMr of RCA 

at 50°C (122°F) had generally lower SMr than that of tested at 7°C (44.6°F). 

Figure 57. SMR VERSUS TEMPERATURE OF 100% RCA 

 

 

49 

Figure 58. NORMALIZED SMR VERSUS TEMPERATURE OF 100% RCA 

 

 

Figure 59. SMR VERSUS TEMPERATURE OF 100% RCA (WHISKER PLOT) 

According to Figure 60, an increase in moisture content of RAPs causes a decrease in SMR. Attia 

and Abdelrahman (2010b) conducted research on Minnesota’s 100% RAP and 50% RAP-natural 

aggregate mixture. In both cases a reduction in SMr was observed as the OMC of the specimens 

increased.  In  addition,  Edil  et  al.  (2012a)  tested  the  RAP  samples  from  Texas  and  Ohio  and 

concluded  that  as  OMC  increased,  SMr  of  these  materials  decreased.  Resilient  modulus  test 

 

50 

following the NCHRP 1-28A, procedure 1A was conducted with test samples at different moisture 

contents, as defined by testing matrix.  

 

Figure 60. SMR VERSUS OMC OF 100% RAPS 

Notes: Samples were compacted at different moisture contents to achieve maximum dry density.  

OMC-2%= 2% dry of OMC; OMC+2%= 2% wet of OMC; ΔMC= Percent change in the OMC, for 

example, ΔMC=+2 in the equation for SMr of OMC+2% 

 

2.3.3. RESILIENT MODULUS BLENDS OF RAP AND RCA WITH NATURAL 

AGGREGATES  

 

The use of a higher amount of RAP and RCA increased the stiffness of the RAP-natural aggregates 

and  RCA-natural  aggregates  mixtures  (Bennert  et  al.  2000).  However,  there  were  several 

exceptions. For instance, Bestgen et al. (2016) did not observe a consistent increase in the SMr of 

the natural aggregates when they were mixed with RCA until RCA contents reached to 75% by 

weight in the mix design.  

 

51 

An increase in RAP content lead to an increase in SMr (Figure 61). The SMr of 100% RAP ranged 

between  170  MPa  (24656.4  psi)  (Kim  et  al.  2005)  and  417  MPa  (60480.7  psi)  (Attia  and 

Abdelrahman 2010a), while the SMr of 100% RCA varied from 164 MPa (23786.2 psi) to 297 

MPa (43076.2 psi). 

Ullah and Tanyu (2019) conducted resilient modulus tests on 3 different RAP (RAP 1, RAP2, and 

RAP3) that were mixed with natural aggregates at 20%, 30%, 40%, 50%, 60% by weight. The SMr 

of natural aggregate in this study was 141.1 MPa (20450 psi). The minerals in parent rock of all 

the RAPs were plagioclase and pyroxene. This study showed that RAP 1 with a high binder content 

(5.6-5.8%) resulted in the highest SMr in RAP-natural aggregate mixture, while RAP 2 with low 

binder content (4.5-4.7%) had the lowest SMr in the blend. Overall, this study claimed that the 

binder contents of RAP samples had a slight impact on the SMR of blends when the blends had 

low RAP percentages and low binder contents. This paper indicated that, parent rock had the most 

impact on SMr on the RAP and RAP-natural aggregate mixtures. For instance, RAP materials with 

plagioclase and pyroxene had a higher SMr than those made of quartz, muscovite, biotite, and 

amphibole.  

 

Attia and Abdelrahman (2010a) tested Minnesota Class 5 (Class 5) and RAP-natural aggregate 

blends consisting of 50% RAP + 50% Class 5, 75% RAP + 25% Class 5, and 100% RAP material. 

Attia and Abdelrahman (2011) determined that RAP-natural aggregate blends were generally less 

sensitive to bulk stress and more sensitive to confining pressure. They showed that materials with 

50% RAP would have SMr of 265 MPa (38435 psi) while  SMr of 75% RAP blends was 210 MPa 

(30458 psi). 100% RAP had a SMr of 400 MPa (58015.1 psi) which was higher than any blends. 

 

52 

Bulk stress in this study was calculated as it is defined in the previous studies. It is the sum of the 

sd and 3 times s3. 

Alam et al. (2010) collected the RAP materials from millings of the 2001 rehabilitation project on 

Mn/ROAD Cell-26 constructed in 1994. This cell was located on the low volume roadway which 

had been subjected to 20,000 vehicles daily (Mulvaney and Worel 2002). These RAP materials 

were mixed with natural aggregates at the following rates by weight 30%, 50%, 70% and 100% 

and were subjected to Mr tests. This study determined that SMr increased with an increase in RAP 

content from 154 MPa (22335.8 psi) at 30% RAP to 270 MPa (39160.2 psi) at 100% RAP. 

Bradshaw  et  al.  (2016)  studied  two  different  types  of  RAP  and  natural  aggregate  blends.  The 

materials included cold recycled RAP blends that were prepared off site and RAP blends that were 

generated in situ during full depth reclamation (FDR). The SMr of the cold recycled RAP blends 

(14– 39% RAP content) was between 120 MPa (17404.5 psi) and 502 MPa (72808.9 psi). The 

possible reason for slightly higher SMr of these blends that those of RAP blends in the literature 

could be the differences in aggregate composition and/or particle shape. The SMr of the FDR-RAP 

blends (57–71% RAP content) ranged from 171 MPa (24802 psi) to 578 MPa (83832 psi) which 

were higher than the SMr of the cold recycled RAP blends. This could be due the higher RAP 

contents  used  in  these  blends.  In  addition,  more  shear  softening  and  permanent  strains  were 

observed for the FDR-RAP mixtures as compared to the cold recycled RAP blends. 

Kang  et  al.  (2011)  tested  recycled  materials  and  natural  aggregates.  RAP  was  collected  from 

highway 61 in Minneapolis. Natural aggregates were collected from a pit south of Jordan, MN. 

RAP and RCA were mixed with natural aggregates at 25%, 50% and 100% by weight. SMr of 

blends in this study increased with an increase in RAP content. However, generally the reported 

 

53 

SMr was smaller than any other study ranging from 90 MPa (13053 psi) at 25% RAP blend to 192 

MPa (27847 psi) at 100% RAP.  

Abdelrahman and Noureldin (2014) conducted research on one source of RAP supplied by the 

Minnesota Department of Transportation (DOT) from a trunk highway. This RAP was blended 

with Class 5 base aggregates (Minnesota DOT) at 50%, 75%, and 100% RAP. According to the 

results, SMr values changed from 289 MPa (41916 psi) at 50% to 262 MPa (38000 psi) at 75% 

RAP mixture. It was reported that the SMr of 100% RAP was 330 MPa (47863 psi) which was the 

highest among all the blends. 

Kim et al. (2005) obtained the reclaimed materials from County Road (CR) 3 in central Minnesota. 

An in situ blend, a mixture of 25%, 50% and 75% RAP and crushed aggregate, pure RAP and pure 

aggregate  materials  were  taken  separately  during  FDR.  This  was  the  only  study  that  reported 

similar SMr for different blends. 100% RAP had SMr of 170 MPa (24656 psi). 

Wu et al. (2012) obtained crushed aggregate (basalt) from POE Asphalt Paving, Inc. (Pullman, 

Wash.) and RAP from the Fairmount Road construction site in Pullman. To eliminate the effect of 

gradation,  one  single  gradation  was  selected  meeting  the  Washington  State  Department  of 

Transportation (DOT) specifications for crushed surfacing base course material for all percentages 

of RAP used in the study. This study showed a constant value for blends from 20% to 60% around 

200 MPa (29008 psi) whereas 80% RAP blend had a SMr of 550 MPa (79771 psi) which was 

considered an outlier. 

 

Bennert  and  Maher  (2005),  conducted  Mr  tests  on  RAP  and  RCA  blended  with  dense  graded 

aggregate base course (DGABC) material from the Central region of New Jersey since the quarried 

material did not exist naturally in southern New Jersey. The ratios of blends for testing were 25%, 

 

54 

50% and 75% along with the 100% RAP or RCA and 100% DGABC. It reported an increasing 

trend with higher RAP contents from 25% (202 MPa- 29225 psi) to 50% (234 MPa- 33895 psi) 

and from 75% (214 MPa- 31009 psi) to 100% RAP (268 MPa- 38870 psi). SMr of 50% RAP was 

observed to be higher than that of blend mixed with 75% RAP. 

Hasan  et  al.  (2018)  collected  the  subgrade  soils  and  the  RAP  from  the  interstate  40  (I-40) 

construction site at the mile post of 141 near Albuquerque, New Mexico and the RAP material 

was supplied from the stockpile. They reported SMr of 175MPa (25382 psi) at 25% RAP and SMr 

of 290 MPa (42061 psi) at 75% RAP. 

Bennert et al. (2000) conducted research on 25%, 50%, 75% and 100% RAP blended with dense 

graded  aggregate  base  course  (DGABC)  in  the  state  of  New  Jersey.  This  study  reported  an 

increasing trend in SMr as RAP content increased. It also showed that the 25% RAP blend had 187 

MPa (27122 psi) stiffness which was 300 MPa (43555 psi) for 100% RAP. 

 

Figure 61. SMR VERSUS RAP CONTENT 

 

 

55 

Figure 62 shows the normalized SMr of each RAP blend to the SMr of the corresponding RAP 

alone and it is observed that SMr of RAP mixtures increase with an increase in RAP contents. 

Figure 63 also confirms this trend more clearly.   

Figure 62. NORMALIZED SMR VERSUS RAP CONTENT 

 

 

Figure 63. SMR VERSUS RAP CONTENT (WHISKER PLOT) 

 

56 

Furthermore, Figure 64 shows that RCA content and SMr relationship is not very straight forward 

as the one observed between the RAP content and SMr. According to Bestgen et al. (2016), the 

presence  of  higher  CaO  content  in  RCA  materials  led  to  higher  SMr  values  than  the  natural 

aggregates. CaO initiates the cementitious reaction in the aggregate matrix which can improve the 

mechanical properties of RCA materials. However, database contained 18 different RCA-natural 

aggregate mixtures and it was observed that each of these mixtures had different trends. Bestgen 

et al. (2016) tested four different natural aggregate materials with two different RCAs. RCAs were 

mixed with natural aggregates at 25%, 50%, 75% and 100% ratios by weight. Overall, the mixtures 

presented a slight increase in SMr when 25% RCA was increased to 50%. All of the mixtures 

showed an increase trend in SMr with RCA content going from 25% to 75% with a few exceptions.  

RCA had higher SMr than the RCA-natural aggregate mixtures and the natural aggregates alone. 

Nevertheless, overall trend was that 100% RCA had a higher summary resilient modulus than any 

other mixtures and natural aggregates (Figure 65). Figure 66 shows the normalized SMr values of 

each blend of RCA (Normalized SMr means the ratio of the SMr value of each RCA blend to the 

corresponding SMr value of 100% RCA).  

Figure 67 indicates that no specific trends are observed between the SMr of 50% and 75% RCA-

natural aggregate blends. The number of available data for SMr of RCA was lower than those 

available  for  RAP.  For  100%  RCA  and  50%  RCA,  23  and  11  data  points  were  available, 

respectively. The lowest number of available data was 10 for 25% and 75% RCA blends. Overall, 

Figure 67 also confirms that 100% RCA has a higher resilient modulus than any blends and natural 

aggregates. 

 

57 

Figure 64. SMR VERSUS RCA CONTENT 

Figure 65. SMR VERSUS RCA CONTENT 

 

 

 

Figure 66. NORMALIZED SMR AND RCA CONTENT 

 

58 

Figure 67. SMR VERSUS RCA CONTENT (WHISKER PLOT) 

 

 

2.4. PERMANENT DEFORMATION  

The permanent deformation failure is attributed to the vertical compressive strains of geomaterials 

under  repeated  loading  conditions  which  lead  to  failure  mechanisms  in  the  flexible  pavement 

systems (Bennert et al. 2000, Thompson and Smith 1990). Permanent deformation is determined 

by  performing  a  cyclic  triaxial  test  in  which  the  confining  pressure,  deviatoric  stress  and  the 

number of cycles are predetermined.  

Increasing the number of loading cycles leads to an increase in the permanent deformation of 

pavement foundation materials regardless of the aggregate type. A relatively higher permanent 

deformations were observed with an increase in the RAP content of the RAP-natural aggregate 

mixtures (Kim and Labuz 2007, Thakur and Han 2015). On the other hand, an increase in the RCA 

content of the RCA-natural aggregate mixtures caused a relatively lower permanent deformation 

(Bennert et al. 2000). In general, RCA showed the lowest permanent deformation among RCA, 

 

59 

RAP and natural aggregate while RAP showed the highest permanent deformation (Bennert et al. 

2000; Edil et al. 2012a). Having the highest permanent deformation in RAP may have been the 

progressive  breakdown  of  its  asphalt  binder  (Bennert  et  al.  2000).  Moreover,  viscous  creep 

behavior of asphalt material could be one of the reasons for the high plastic deformation of RAP 

(Edil et al. 2012a). The permanent deformation of 100% RAPs ranged from 1.05% (Attia 2010) to 

5.63% (Bennert and Maher 2005) while these values were between 0.1% (Bestgen et al. 2016) and 

0.83% for RCAs (Edil et al. 2012a). 

Different  trends  have  been  observed  between  RAP,  RCA,  and  natural  aggregate  due  to  their 

different  gradation  characteristics  (e.g.  fines  contents).  Virgin  aggregate  could  show  lower 

permanent deformation than RCA due to its lower fines content (Bestgen et al. 2016). Fines content 

can  significantly  affect  the  permanent  deformation  while  it  has  no  considerable  effect  on  the 

resilient  moduli  of  aggregates.  A  relatively  higher  fines  content  leads  to  a  higher  permanent 

deformation of aggregates (Mishra and Tutumluer 2012). Moreover, repetitive load may break 

hydrated  cement  particles  thus  reduce  the  angularity  of  RCA  which  finally  leads  to  a  higher 

permanent deformation in RCA than those observed for natural aggregates (Bestgen et al. 2016).  

According  to  Thompson  and  Smith  (1990),  permanent  deformation  plays  an  important  role  in 

determining the pavement performance. Bennert et al. (2000), Attia (2010), Garg and Thompson 

(1996), Kim and Labuz (2007) and Wen and Wu (2011) showed that permanent deformation of 

RAP-natural aggregate mixtures increased with an increase in the RAP content (Figure 68).  

Particle sizes of the RCAs and RAPs are important since the presence of larger aggregates in the 

material matrix tend to lead to higher strength and the resistance against deformation (Gray 1962, 

Kazmee et al. 2016). Moreover, the thicker base layers result in the lower permanent deformation 

due to the improved stress distribution (Cetin et al. 2010, Schaertl 2010).   

 

60 

It  was  also  observed  that  temperature  is  very  crucial  for  RAPs  permanent  deformation 

performances. An increase in temperature yields an increase in the permanent deformation or RAP 

materials because of the temperature-sensitivity of RAP (Edil et al. 2012a; Soleimanbeigi et al. 

2015). On the other hand, the temperature has little to no effect on the permanent deformation 

performances of RCA and natural aggregates (Edil et al. 2012a). 

Figure 68. PERMANENT STRAIN VERSUS RAP CONTENT 

 

 

Figure 69. PERMANENT STRAIN VERSUS RCA CONTENT 

 

 

 

61 

2.5. SHEAR STRENGTH 

Shear strength is the maximum shear stress that a soil can sustain. Attia (2010) identified shear 

strength as an important property for unbound materials when used under a thin HMA layer that 

is  subjected  to  high  shear  stresses.  Shear  strength  is  a  function  of  normal  or  confining  stress, 

friction angle, and cohesion for a particular material. Cosentino et al. (2003), Bennert and Maher 

(2005), Attia (2010), Bejarano (2001), Garg and Thompson (1996), and Kim and Labuz (2007) 

evaluated  shear  strength  parameters  (friction  angle  and  cohesion)  of  the  RAP-blended  natural 

aggregate materials. Results of this study showed that the friction angle (φ) and the cohesion (c) 

of 100 % RAP specimen varied from 44° to 52º and 0 kPa (0 psi) to 131 kPa (19 psi), respectively. 

The large variation in the cohesion of RAP may resulted from the variation in the asphalt binder 

content of the RAP used by different researchers. No correlations or trends were observed between 

the φ and the c parameters of RAP-natural aggregate mixtures and the corresponding RAP content 

(Figures 70 and 71). There were less available data regarding shear strength of RCAs. The “c” of 

RCAs ranged from 24.13 kPa (3.5 psi) to 191 kPa (27.7 psi) and the φ of RCAs ranged from 19° 

to 52.7° (Figures 72 and 73).  

The typical ranges for angle of friction  of granular soil materials for GW, GP, SW, SP are 33-40°, 

32-44°, 33-43°, 30-39°, respectively (Swiss Standard SN 670 010b and Koloski et al. 1989) while 

they are between 35° and 51° for muddy shale and stone Mt. granite rocks (Goodman 1980). 

 

 

62 

Figure 70. COHESION VERSUS RAP CONTENT 

Figure 71. FRICTION ANGLE VERSUS RAP CONTENT 

 

 

 

Figure 72. COHESION VERSUS RCA CONTENT 

 

63 

 

 

Figure 73. FRICTION ANGLE VERSUS RCA CONTENT 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

64 

CHAPTER 3. DESIGN METHODS 

One of the most important steps for constructing high-quality and long-lasting pavement systems 

is the determination of surface, aggregate base, and subbase layers’ thickness. While there are 

methods  and  assumptions  for  using  natural  aggregates  as  an  aggregate  base  or  subbase  layer, 

designing pavement systems with recycled (RAP and RCA) can be challenging (Edil 2011). The 

engineering properties of RAP and RCA should be well understood as they play an important role 

in design. AASHTO (1993) and Mechanistic-Empirical Pavement Design Guide (MEPDG) are 

the most commonly used design methods for flexible and rigid pavements (Edil 2011). The focus 

of this research is to improve the inputs for MEPDG design method which is now called Pavement 

ME design. 

 

3.1. PAVEMENT MECHANISTIC EMPIRICAL DESIGN  

AASHTO (1993) and pavement mechanistic-empirical (PMED) are the two most commonly used 

design methods for flexible and rigid pavements (Edil 2011). One of the main reasons to develop 

PMED method was the lack of using the impact of climate and traffic impacts in the most widely 

used  empirical  AASHTO  design  methods.  In  the  PMED  approach,  pavement  performance  is 

evaluated  based  on  mechanistically  determined  critical  stresses,  strains,  temperatures,  and 

moisture levels that are in turn the inputs to empirical prediction models for specific pavement 

distresses such as rutting, fatigue cracking, thermal cracking, and roughness for flexible pavements 

and cracking, faulting, and roughness for rigid pavements. Accurate characterization of the traffic, 

climate,  and  material  input  parameters  is  therefore  important  to  ensure  that  the  theoretical 

 

65 

computation of pavement stresses, strains, temperatures, and moisture levels are accurate at the 

critical locations within the system (Schwartz et al. 2015).  

Plastic deformation is taken into account in the Pavement ME, which is a mechanistic-empirical 

approach in contrast to the AASHTO (1993) design method which is an empirical approach. There 

are several parameters such as the modulus values of layers, climate zone, traffic conditions, the 

designed  service  life  of  the  pavement,  and  failure  criteria  to  be  considered  to  create  the  most 

suitable design. Resilient modulus values should be obtained from laboratory or field tests for 

conventional and recycled aggregates. Finally making iterations for specific materials along with 

other related conditions leads to determining the design thicknesses (Edil 2011). For performance 

evaluation of pavement systems, required parameters for the analysis can be obtained for RAP, 

RCA, natural aggregates, and the RAP-natural aggregate and RCA-natural aggregate mixtures. 

 

 

 

 

 

 

 

 

 

 

 

 

66 

CHAPTER 4. SELECTED PRACTICES OF STATE DOTS 

The materials which do not meet the specifications, which state DOTs have established, cannot be 

used due to high failure risk (NCHRP-838). As more DOTs understand the importance of RAPs 

and RCAs, they tend to develope guidelines for RAP and RCA usage in pavements as they can be 

more economical and readily available. This literature review illustrates the practical aspects of 

the use of RAP and RCA in pavement design by different state DOTs and how each guideline 

slightly differs from each other. Caltrans, MnDOT, MoDOT, WiDOT allow RAP and RCA to be 

used as a base course material in pavements if they meet the requirements for gradation and quality 

characteristics. MDOT and IDOT only allow RCA in base applications eventhough IDOT recently 

starts considering the use of RAP in such applications as well. More detailed information about 

DOT spesifications is discussed below. 

4.1. CALIFORNIA DOT 

In California, RAP and RCA base applications are allowed up to 100% since 2006 but before then 

their  usage  was  limited  to  50%.  Recycled  aggregates  must  meet  the  grading  and  quality 

specifications  stated  for  natural  aggregate  in  the  Caltrans  Standard  Specifications  (CalRecycle 

2014). 

Aggregate base and subbase applications of the recycled aggregates are discussed in Sections 25 

and 26 of the Caltrans Standard Specifications published in 2015 (Caltrans 2015). Clean broken 

stone,  crushed  gravel,  natural  rough  surfaced  gravel,  sand,  and  reclaimed  processed  Portland 

cement concrete (PCC) can be used as subbases and aggregate bases. The subbase aggregates must 

meet the gradation ranges of Class 1, Class 2, or Class 3 as shown in Table 4 (section 25 of Caltrans 

2015). In addition, the aggregates must have adequate quality characteristics presented in Table 5 

 

67 

depending on its class. The aggregates used as base materials should meet the requirements of 

gradations and quality characteristics of Class 2 or Class 3 aggregates shown in Tables 6, 7, 8, and 

9. 

Contract  compliance  is  a  larger  range  than  the Operating  Range and  is  used  to  adjust  fort  not 

having to shut the job down or pay a fine.  If the gradation is outside of the Operating Range but 

within  the Contract  Compliance requirements,  this  material  can  continue  to  be  used  for  the 

remainder of the day. It should be noted, that even if within the Contract Compliance requirements, 

changes still need to be made by the next day to ensure the material is within Operating Range, or 

construction will be stopped until requirements are met. If a test results indicate the material is still 

outside the Contract Compliance requirements, Caltrans generally has the right to ask for removal 

or a payment deduction.  

Table 4. AGGREGATE GRADATION FOR SUBBASE APPLICATIONS (CALTRANS 2015) 

Table 5. AGGREGATE QUALITY CHARACTERISTICS FOR SUBBASE APPLICATIONS 

 

 

(CALTRANS 2015) 

 

 
 
 
 
 
 
 

68 

 

Table 6. CLASS 2 AGGREGATE GRADATION FOR AGGREGATE BASE APPLICATIONS 

(CALTRANS 2015) 

 

 

Table 7. CLASS 2 AGGREGATE QUALITY CHARACTERISTICS FOR AGGREGATE BASE 

APPLICATIONS (CALTRANS 2015) 

 

Table 8. CLASS 3 AGGREGATE GRADATION FOR AGGREGATE BASE APPLICATIONS 

(CALTRANS 2015) 

 

 
Table 9. CLASS 3 AGGREGATE QUALITY CHARACTERISTICS FOR AGGREGATE BASE 

APPLICATIONS (CALTRANS 2015) 

 

 

4.2. ILLINOIS DOT 

Sections 311 and 351 of the IDOT Standard Specifications for Road and Bridge Construction 

published  in  2016  allows  crushed  concrete  produced  from  Portland  cement  concrete,  crushed 

gravel and crushed stone for the aggregate base and subbase courses (IDOT 2016). According to 

section  1004,  20  different  aggregate  classes  are  defined  for  different  applications  (Table  10). 

 

69 

Crushed concrete must have adequate gradation requirements of CA6 or CA10 aggregates for 

aggregate base applications (Table 11) (IDOT 2016). 

As stated in Section 1004, coarse aggregate quality control specifications are established by Illinois 

DOT (Table 12). Crushed concrete should be evaluated as class D for checking its quality in terms 

of Illinois Test Procedure (ITP) 96 (LA abrasion test) and must be evaluated as a class C for Illinois 

Test Procedure (ITP) 203 which is used for the determination of deleterious particles in coarse 

aggregate. According to the Los Angeles (LA) abrasion limit, abrasion loss should be less than 

45% and instead of the given limit for deleterious materials (2%), the content of other deleterious 

should be limited to 7% with no more than 5% RAP (IDOT - Bureau of Materials and Physical 

Research). The California bearing ratio should be 80 for the aggregate base applications of typical 

materials but there is no requirement for crushed concrete (IDOT 2016). 

Per Section 303, IDOT allows RAP usage in constructing an aggregate subgrade improvement 

which can contain coarse aggregate or reclaimed asphalt pavement. Crushed RAP , from either 

full depth or single lift removal, may be mechanically blended with aggregate gradations CS 01, 

CS 02 and RR 01 but the total product must contain RAP at 40% or less. The size of RAP particles 

must be less than 4 inches and well graded. RAP with 100% passing 1-1/2 inch sieve and being 

well graded, may be used as a capping aggregate on the top 3 inches when aggregate gradations 

CS 01, CS 02 or RR 01 are used in lower lifts. The RAP used for aggregate subgrade improvement 

shall  be  selected  according  to  the  current  Bureau  of  Materials  and  Physical  Research  Policy 

Memorandum, “Reclaimed asphalt pavement (RAP) for aggregate applications. 

 

 

 

 

70 

 

 

 

Table 10. GRADATION RANGES OF DIFFERENT AGGREGATES (IDOT 2016) 

Table 11. TYPICAL AGGREGATES FOR VARIOUS APPLICATIONS (IDOT 2016) 

 

 

 
 
 
 
 
 
 
 
 
 
 
 
 

71 

Table 12. COARSE AGGREGATE QUALITY CONTROL SPECIFICATIONS (IDOT 2016) 

4.3. MINNESOTA DOT 

 

 

RAP  and  RCA  are  both  allowed  in  Section  2211  of  the  MnDOT  Standard  Specifications  for 

construction published in 2018 to be used as aggregate base course (MnDOT 2018). In Section 

3138, aggregates are classified based on their quality characteristics and they should meet the 

quality requirements of one of those classes (Table 13). In addition, RAP and RCA should meet 

the quality requirements, which are the same for all aggregate classes (Table 14) (MnDOT 2018). 

When the RAP content  is more than 10% of the blend by volume, the gradation of RAP and 

aggregate blend must meet the specified gradation for the aggregate class (McGarrah 2007). RAP 

and  natural  aggregate  must  be  blended  at  the  crushing  site,  not  at  the  job  site  with  stockpiles 

aggregates (McGarrah 2007).  

Almost all concrete pavements in Minnesota are recycled as dense-graded base aggregate material 

(Gonzalez and Moo-Young 2004). Fine-grained (< #4 sieve) RCA particles must be removed to 

avoid the drainage issues. Moreover, open-graded RCA can be mixed with natural aggregates to 

reduce the heavy metal leaching (Snyder 1995, as cited in Gonzalez and Moo-Young 2004). 

Per  Section  3138,  depending  on  the  project,  the  blends  of  natural  aggregates  and  recycled 

aggregates with less than 25% recycled aggregates used as a pavement aggregate base material 

 

72 

should meet the gradations specified for different aggregate classes (Table 15) (MnDOT 2018). If 

25% or more up to 75% recycled aggregates are used in the blends, the mixture should meet the 

gradation criteria provided in Table 16. In addition, if 75% or more recycled concrete is used, the 

mixture should meet the gradation criteria shown in Table 17 (MnDOT 2018). 

Table 13. QUALITY REQUIREMENTS FOR VIRGIN AGGREGATES (MNDOT 2018) 

 

 

Table 14. QUALITY REQUIREMENTS FOR RECYCLED AGGREGATES (MNDOT 2018) 

 

 
 
 
 
 
 
 
 
 
 
 
 

73 

 

Table 15. GRADATION OF BASE AGGREGATE CONTAINING LESS THAN 25% RECYCLED 

AGGREGATES (MNDOT 2018) 

Table 16. GRADATION OF BASE AGGREGATE CONTAINING 25% OR MORE RECYCLED 

AGGREGATES and 75% OR LESS RECYCLED CONCRETE (MNDOT 2018) 

 

 

 

 
 
 
 
 
 
 
 
 
 

74 

 

Table 17. GRADATION OF BASE AGGREGATE CONTAINING MORE THAN 75% RECYCLED 

CONCRETE (MNDOT 2018) 

 

 

4.4. MISSOURI DOT 

The use of reclaimed asphalt and concrete aggregates as base aggregates are allowed in Sections 

304 and 1007 of the MoDOT Standard Specifications for Highway Construction published in 2018 

if they meet the gradation specifications of Type 1 (Table 18), Type 5 (Table 19), and Type 7 

(Table 20) (MoDOT 2018). Section 1007 limits deleterious materials of Type 1, Type 5, and Type 

7 aggregates to be less than 15%. Deleterious materials should be distributed uniformly along with 

sand, silt, and clay contents. Plasticity index (PI) of particles passing No. 40 sieve should not be 

more than 6 (MoDOT 2018). In addition to Types 1, 5, and 7 aggregates, durable stones containing 

no more than 10% (by weight) of earth, sand, shale, and non-durable rock are allowed for aggregate 

base applications according to Section 303. The maximum size depends on the layer thickness. 

For example, the maximum size should be about 12 and 9 inches for 18-inch and 12-inch rock 

base respectively (MoDOT 2018).  

 

 

 

 

75 

 

Table 18. GRADATION CRITERIA OF TYPE 1 AGGREGATE (MODOT 2018) 

Table 19. GRADATION CRITERIA OF TYPE 5 AGGREGATE (MODOT 2018) 

 

 

 

 

Table 20. GRADATION CRITERIA OF TYPE 7 AGGREGATE (MODOT 2018) 

 

 

4.5. WISCONSIN DOT 

Aggregates, breaker run, crushed gravel, crushed stone, pit run, reclaimed asphalt, and crushed 

concrete can be used for different aggregate base applications according to Section 301 of the 

WisDOT Standard Specifications published in 2018 (Table 21). Reclaimed asphalt is only suitable 

for dense 1 ¼-inch aggregate base type while crushed concrete is suitable for dense ¾-inch, dense 

1 1/4 -inch, and dense 3-inch aggregate base types (WisDOT 2018). Base course materials cannot 

contain any deleterious materials such as shale, soft or porous rock fragments, coal, and organic 

particles.  

Per section 301, reclaimed asphalt aggregates should contain at least 75% of reclaimed asphaltic 

pavement or surfacing. Crushed concrete aggregate should contain at least 90% crushed concrete 

 

76 

without  any  steel  reinforcements  or  any  other  impurities.  In  addition,  asphaltic  pavement  and 

surfacing material content should be lower than 10% in crushed concrete aggregate.  

Crushed natural aggregates and recycled aggregates can be mixed at various percentages to create 

reprocessed  materials  or  blended  materials.  Every  single  aggregate  of  blended  materials  must 

satisfy the specified aggregate base physical properties criteria (Table 22), and final blend must 

meet the specified gradation (WisDOT 2018). Per section 305, dense graded aggregates such as 

crushed stone, crushed gravel and crushed concrete (except reclaimed asphalt) should meet the 

gradations provided in Table 23. For reclaimed asphalt, gradation is primarily assessed visually, 

e.g., reclaimed asphalt 100% passing 1 ¼-inch sieve may be used for 1 ¼-inch aggregate base 

application (WisDOT 2018). 

Per section 301, crushed concrete can contain up to 12% of glass, 7% of foundry slag, 75% of steel 

mill slag, 8% of bottom ash, and 7% of pottery cull (by weight). However, all of the by-products 

should not have any deleterious materials (WisDOT 2018). 

Table 21. SUITABILITY OF VARIOUS AGGREGATE BASE MATERIALS (WISDOT 2018) 

 

 

 

 

 

77 

 

 

Table 22. AGGREGATE BASE PHYSICAL PROPERTIES (WISDOT 2018) 

 

 

Table 23. GRADATION REQUIREMENTS OF DENSE-GRADED AGGREGATE BASE 

MATERIALS EXCEPT FOR RECLAIMED ASPHALT (WISDOT 2018) 

 

 

78 

 

4.6. MICHIGAN DOT 

Sections 302 and 902 of the MDOT Standard Specifications for Construction published in 2012 

allows  the  crushed  concrete  along  with  natural  aggregate  and  iron  blast  furnace  slag  as  base 

materials if they meet the gradation (Table 24) and quality (Table 25) specifications for Class 

21AA, 21A, 22A, and 23A dense-graded aggregates. Dense-graded aggregates can be mixed with 

fine-grained aggregates to meet the specifications. Crushed concrete should not contain more than 

5% of brick, wood, plaster or asphalt by particle count but steel reinforcement pieces are allowed 

as long as they meet the specified gradation of stated dense-graded aggregate Classes.  

Crushed concrete can be used as long as there is an additional granular layer of at least 12 inches 

(with class I, II, IIA, or IIAA aggregates – Table 26) between the dense-graded aggregate base and 

an underdrain, which the dense-graded aggregate base drains into. In addition, a geotextile liner or 

geomembrane can be used as an alternative to granular layer between the dense-graded aggregate 

base and the underdrain (MDOT 2012). 

Table 24. GRADING REQUIREMENTS FOR DENSE-GRADED AGGREGATES (MDOT 2012) 

Loss by

Washing (MTM
108) % Passing

No. 200

4-8
4-8
4-8
9-16

 

Series/Class

Sieve Analysis (MTM 109) Total Percent Passing

¾ in

-
-

-

90-100

21 AA
21 AA
22 A
23 A

1½ in
100
100
-
-

1 in
85-100
85-100

100
100

 

½ in
50-75
50-75

-
-

⅜ in

-
-

65-85
60-85

No. 4

-
-
-
-

No. 8 No. 30
20-45
20-45
30-50
25-60

-
-
-
-

 

 

 

 

 

79 

Table 25. PHYSICAL REQUIREMENTS FOR DENSE-GRADED AGGREGATES (MDOT 2012) 

Series/Class

21 AA
21 AA
22 A
23 A

Crushed 

Material, % min

(MTM 117)

95
25
25
25

Loss, % max, Los 
Angeles Abrasion

(MTM 102)

50
50
50
50

 

Table 26. GRADING REQUIREMENTS FOR GRANULAR MATERIALS (MDOT 2012) 

 

 

 

 

 

 

80 

 

CHAPTER 5. INPUTS FOR PAVEMENT MECHANISTIC-

EMPIRICAL DESIGN (PMED) 

 

In order to produce reliable and accurate results, the PMED relies on a high level of detailed 

information  about  input  parameters  for  materials,  traffic  and  climate.  Determining  all  these 

parameters requires extensive testing and data collection efforts, and it can be difficult to devote 

the resources to that if the information is not part of an already existing data set. As an alternative, 

the PMED software allows users to enter this information in a hierarchical fashion, meaning that 

the user has the option to provide different levels of detail, then the program adjusts these inputs 

accordingly.  Level  1  input  needs  more  precise  information  from  field  and  laboratories  which 

should lead to the most accurate pavement distress analyses while level 3 input provides the least 

precise pavement distress predictions.  

For instance, traffic data in its simplest form could simply be an estimate of vehicle traffic volumes. 

Since the PMED process relies on traffic data to calculate pavement loads, the software would 

need to convert this into a load factor by assuming a typical distribution of vehicle types. However, 

if you had actual traffic counts for a project site, including vehicle class information, this would 

allow an additional level of input in the hierarchy. Assumptions would still need to be made about 

the  spectrum  of  actual  loads  based  on  equivalency  factors  (ESALs  or  Equivalent  Single  Axle 

Loads). At the top of the hierarchy, you would need to collect vehicle weight data near the site to 

determine  the  actual  load  distribution,  in  addition  to  monitoring  vehicle  counts.  This  can  be 

achieved by detailed analyses of Weigh-In-Motion (WIM) data. This is the one example of the 

most comprehensive data and increases the precision of the design assumptions. However, the 

PMED process can still function at lower levels of detail. 

 

81 

During PMED analyses in this study, the design inputs of pavement surface layers and subgrade 

layers are kept constant to be able to investigate impact of the properties of RCA and RAP base 

layers on predicted pavement distresses. All analyses were conducted at 90%  reliability level. 

Table 27 summarizes the general inputs used for PMED analyses.  

Table 27. GENERAL INPUTS 

Input 

Value 
20 years 
15000 psi 

Design Period 
SMr of Subgrade 
Subgrade Gradation 
Groundwater Depth (ft) 
Flexible Pavement Input 
Binder Grade 
Base Poisson’s Ratio 
HMA Poisson’s Ratio 
Rigid Pavement Input 
PCC Unit Weight (pcf)  
PCC Poisson’s Ratio  
Notes: SMr=Summary resilient modulus, HMA= Hot mix asphalt, PCC= Portland cement 
concrete. 

Super Pave PG 58-34 

A-1-b 
10 

0.35 
0.35 

150 
0.15  

 

Three different traffic volumes were considered for pavement design analyses (e.g. low, medium, 

and high traffic). Table 28 shows the traffic data used in Pavement ME analyses along with surface 

layer  and  base  layer  thicknesses  which  were  selected  per  recommendations  of  Schwartz  et  al. 

(2011). 

 

 

 

 

 

 

 

 

82 

Inputs 

Table 28. TRAFFIC INPUTS 

Low Traffic  Medium Traffic  High Traffic 

1000 

7500 

25000 

AADTT 
Number of Lanes in Design Direction 
Percent of Trucks in Design Direction (%) 
Percent of Trucks in Design Lane (%) 
Operational Speed (mph) 
Asphalt Thickness in flexible pavement 
(in) 
Base Thickness in flexible pavement (in) 
PCC Thickness for rigid pavement (in) 
Base Thickness in rigid pavement (in) 
Notes: AADTT= Average Annual Daily Truck Traffic, PCC=Portland cement concrete. 
 
In order to investigate the effects of RAP and RCA properties on pavement distress predictions 

3 
50 
55 
50 
3 
10 
9 
6 

2 
50 
75 
50 
2 
8 
8 
4 

3 
50 
50 
50 
4 
12 
11 
8 

when used as base layer materials, the lowest, the highest and median values of summary resilient 

modulus  (SMr),  gradation,  hydraulic  conductivity,  optimum  moisture  content  (OMC)  and 

maximum dry unit weight (γdmax) of these materials were collected from the database. A summary 

of these input is also shown in Appendix C and D. The highest and the lowest values are obtained 

from  the  database  for  each  characteristic  shown  in  Tables  29  while  the  median  values  are 

calculated  from  all  the  available  data  for  each  characteristic  in  the  database.  For  instance,  the 

lowest SMr of RAP was reported to be 24,366 psi by Edil et al. (2012a) thus other inputs shown 

in Table 3 were chosen from that paper accordingly. On the other hand, the highest SMr of RAPs 

was 58,015 psi from Attia and Abdelrahman (2010a) and other inputs were collected from the 

same paper as well.  

 

 

 

 

83 

Varied 

Sand 
Percent 

Gravel 
Percent 

Parameter 
(SMr, psi) 

Table 29. BASE INPUTS INVESTIGATING SMR EFFECT OF RAP 
OMC 
(%) 
5.2 
6.1 
5.5 

MDU 
(pcf) 
138 
126 
134 

24366 
37927 
58015 

(%) 
49.3 
45 
51 

(%) 
50.4 
54 
48.6 

(%) 
0.4 
1 
0.4 

Fines 
Content 

Hydraulic 
conductivity 

(ft/hr) 
2.73 
0.71 

- 

Data Value 

Lowest* 
Median 
Highest** 

Notes: SMr=Summary resilient modulus, MDU= Maximum dry unit weight, OMC= Optimum 
moisture content. *Edil et al. (2012a), **Attia and Abdelrahman (2010a) 
 
The lowest SMr of RCA was reported to be 17,898 psi by Cetin et al. (2020) thus other inputs 

shown in Table 30 are chosen from that report accordingly. The highest SMr of RCAs was 53,664 

psi from Diagne et al. (2015) and other inputs were collected from the same paper as well. 

Table 30. BASE INPUTS INVESTIGATING SMR EFFECT OF RCA 
Varied 

Gravel 
Percent 

Sand 
Percent 

Fines 
Content 

MDU 
(pcf) 

OMC 
(%) 

Data 
Value 

Parameter 
(SMr, psi) 

17898 
26542 
53664 

(%) 
38.3 
50.8 
47.2 

(ft/hr) 
0.06 
Lowest* 
0.2 
Median 
Highest** 
0.35 
Notes: SMr=Summary resilient modulus, MDU= Maximum dry unit weight, OMC= Optimum 
moisture content. *Cetin et al. (2020), **Diagne et al. (2015) 
 
The lowest fines content of RAP was reported to be 0% by Alam et al. (2010) thus other inputs 

(%) 
54.6 
45.5 
48.6 

(%) 
7.1 
3 
1.8 

11.1 
10.8 
6.1 

123 
127 
134 

Hydraulic 
conductivity 

shown in Table 31 are chosen from that report accordingly. The highest fines content of RAPs was 

11% from Camargo et al. (2013) and other inputs were collected from the same paper as well. 

Table 31. BASE INPUTS INVESTIGATING FINES CONTENT EFFECT OF RAP 

MDU 
(pcf) 

OMC 
(%) 

Hydraulic 
conductivity 

(ft/hr) 

SMr (psi) 

Data 
Value 

Varied 

Parameter 

(Fines 

content, %) 

Gravel 
Percent 

Sand 
Percent 

(%) 
3 
45 
46 

(%) 
97 
54 
43 

0 
1 
11 

39349 
Lowest* 
37927 
Median 
Highest** 
44962 
Notes: SMr=Summary resilient modulus, MDU= Maximum dry unit weight, OMC= Optimum 
moisture content. *Alam et al. (2010), **Camargo et al. (2013) 
 

- 
126 
136 

- 
6.1 
7.5 

0.71 

- 

- 

 

84 

The lowest fines content of RCA was reported to be 0.1% by Mahedi and Cetin (2020) thus other 

inputs shown in Table 32 are chosen from that report accordingly. The highest fines content of 

RCAs was 15% from Chen et al. (2013) and other inputs were collected from the same paper as 

well. 

Table 32. BASE INPUTS INVESTIGATING FINES CONTENT EFFECT OF RCA 

Data 
Value 

Varied 

Parameter 

(Fines 

content, %) 

Gravel 
Percent 

Sand 
Percent 

MDU 
(pcf) 

OMC 
(%) 

Hydraulic 
conductivity 

(ft/hr) 

SMr (psi) 

(%) 
68.8 
50.8 
41 

(%) 
31.1 
45.5 
44 

0.1 
3 
15 

Lowest* 
26542 
Median 
Highest** 
27412 
Notes: SMr=Summary resilient modulus, MDU= Maximum dry unit weight, OMC= Optimum 
moisture content. *Mahedi and Cetin (2020), **Chen et al. (2013) 
 

14.4 
10.8 
11.9 

127 
127 
121 

- 
0.2 
- 

- 

The lowest gravel content of RAP was reported to be 3% by Alam et al. (2010) thus other inputs 

shown in Table 33 are chosen from that report accordingly. The highest gravel content of RAPs 

was 68.1% from Garg and Thompson (1996) and other inputs were collected from the same paper 

as well. 

Table 33. BASE INPUTS INVESTIGATING GRAVEL CONTENT EFFECT OF RAP 

Data 
Value 

Sand 
Percent 

(%) 

Fines 
content 

(%) 

MDU 
(pcf) 

OMC 
(%) 

Hydraulic 
conductivity 

(ft/hr) 

SMr (psi) 

Varied 

Parameter 
(Gravel 
Percent, 

%) 
3 
45 
68.1 

97 
54 
28.1 

39349 
Lowest* 
37927 
Median 
Highest** 
31702 
Notes: SMr=Summary resilient modulus, MDU= Maximum dry unit weight, OMC= Optimum 
moisture content. *Alam et al. (2010), **Garg and Thompson (1996) 
 
The lowest gravel content of RCA was reported to be 31.8% by Edil et al. (2012a) thus other inputs 

- 
126 
135 

0 
1 
3.8 

- 
6.1 
6 

0.71 

- 

- 

shown in Table 34 are chosen from that report accordingly. The highest gravel content of RCAs 

 

85 

was 94.1% from Mahedi and Cetin (2020) and other inputs were collected from the same paper as 

well. 

Varied 

Parameter 
(Gravel 
Percent, 

%) 
31.8 
50.8 
94.1 

Table 34. BASE INPUTS INVESTIGATING GRAVEL CONTENT EFFECT OF RCA 

Data 
Value 

Sand 
Percent 

(%) 

Fines 
content 

(%) 

MDU 
(pcf) 

OMC 
(%) 

Hydraulic 
conductivity 

(ft/hr) 

SMr (psi) 

Lowest* 
Median 
Highest** 
Notes: SMr=Summary resilient modulus, MDU= Maximum dry unit weight, OMC= Optimum 
moisture content. *Edil et al. (2012a), **Mahedi and Cetin (2020) 
 

11.2 
10.8 
12.6 

64.9 
45.5 
4.9 

27412 
26542 

125 
127 
118 

3.3 
3 
1 

0.2008 

- 

- 

- 

The lowest sand content of RAP was reported to be 28.1% by Garg and Thompson (1996) thus 

other inputs shown in Table 35 are chosen from that report accordingly. The highest sand content 

of RAPs was 97% from Alam et al. (2010) and other inputs were collected from the same paper as 

well. 

Varied 

Parameter 

(Sand 
Percent, 

%) 
28.1 
54 
97 

Table 35. BASE INPUTS INVESTIGATING SAND CONTENT EFFECT OF RAP 

Data 
Value 

Gravel 
Percent 

(%) 

Fines 
content 

(%) 

MDU 
(pcf) 

OMC 
(%) 

Hydraulic 
conductivity 

(ft/hr) 

SMr (psi) 

68.1 
45 
3 

31702 
Lowest* 
37927 
Median 
Highest** 
39349 
Notes: SMr=Summary resilient modulus, MDU= Maximum dry unit weight, OMC= Optimum 
moisture content. *Garg and Thompson (1996), **Alam et al. (2010) 
 
The lowest sand content of RCA was reported to be 4.9% by Mahedi and Cetin (2020) thus other 

135 
126 
- 

6 
6.1 
- 

3.8 
1 
0 

0.71 

- 

- 

inputs shown in Table 36 are chosen from that report accordingly. The highest sand content of 

RCAs was 64.9% from Edil et al. (2017) and other inputs were collected from the same paper as 

well. 

 

86 

Table 36. BASE INPUTS INVESTIGATING SAND CONTENT EFFECT OF RCA 

Data 
Value 

Gravel 
Percent 

(%) 

Fines 
content 

(%) 

MDU 
(pcf) 

OMC 
(%) 

Hydraulic 
conductivity 

(ft/hr) 

SMr (psi) 

Varied 

Parameter 

(Sand 
Percent, 

%) 
4.9 
45.5 
64.9 

94.1 
50.8 
31.8 

Lowest* 
26542 
Median 
Highest** 
27412 
Notes: SMr=Summary resilient modulus, MDU= Maximum dry unit weight, OMC= Optimum 
moisture content. *Mahedi and Cetin (2020), **Edil et al. (2017) 
 
The lowest D60 of RAP was reported to be 2.3 mm by Edil et al. (2012a) in a RAP sample from 

12.6 
10.8 
11.2 

118 
127 
125 

- 
0.2 
- 

1 
3 
3.5 

- 

Minnesota  thus  other  inputs  shown  in  Table  37  are  chosen  from  that  report  accordingly.  The 

highest D60 of RAPs was 10.4 mm from Wu et al. (2012) and other inputs were collected from the 

same paper as well. 

Table 37. BASE INPUTS INVESTIGATING D60 EFFECT OF RAP 

Gravel 
Percent 

Sand 
Percent 

Fines 
content 

Varied 

Parameter 
(D60, in) 
0.090 
0.19 
0.409 

SMr 
Data 
(psi) 
Value 
26107 
Lowest* 
37927 
Median 
Highest** 
29008 
Notes: SMr=Summary resilient modulus, MDU= Maximum dry unit weight, OMC= Optimum 
moisture content. *Edil et al. (2012a), **Wu et al. (2012) 
 

MDU 
(pcf) 
134 
126 
- 

OMC 
(%) 
6.7 
6.05 

(ft/hr) 
0.013 
0.71 

(%) 
71.2 
54 
32 

(%) 
26.3 
45 
67 

(%) 
2.5 
1 
1 

- 

- 

Hydraulic 
conductivity 

The lowest D60 of RCA was reported to be 1.7 mm by Edil et al. (2012a) thus other inputs shown 

in Table 38 are chosen from that report accordingly. The highest D60 of RCAs was 16.3 mm from 

Edil et al. (2012a) and other inputs were collected from the same paper as well. 

 

 

 

 

87 

(%) 
3.3 
3 
2.1 

Hydraulic 
conductivity 

(ft/hr) 

- 
0.2 
- 

Table 38. BASE INPUTS INVESTIGATING D60 EFFECT OF RCA 

Varied 

Gravel 
Percent 

Sand 
Percent 

Fines 
content 

(%) 
31.8 
45.5 
21.6 

(%) 
31.8 
50.8 
76.3 

OMC 
(%) 
11.2 
10.8 
9.2 

MDU 
(pcf) 
125 
127 
127 

Parameter 
(D60, in) 
0.067 
0.268 
0.642 

SMr 
Data 
(psi) 
Value 
27412 
Lowest* 
26542 
Median 
Highest* 
23786 
Notes: SMr=Summary resilient modulus, MDU= Maximum dry unit weight, OMC= Optimum 
moisture content. *Edil et al. (2012a) 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 

88 

CHAPTER 6. DISTRESSES  

The following pavement distresses were analyzed via PMED software: 1) for flexible pavements-

International Roughness Index (IRI), rutting, and fatigue distresses, 2) for rigid pavements-IRI, 

joint faulting,  transverse cracking.  

Target failure values at a reliability level of 90% for different pavement distresses for flexible 

pavements are summarized in Table 39. IRI values greater than 170 in/mile were marked as a 

failure in this study per suggestions of Elbheiry et al. (2011) and this value was determined as the 

terminal IRI.  0.75 inches were determined as a target values for failure for total rutting distresses 

(Ceylan  et  al.  2015).  Table  40  represents  the  target  values  of  distresses  for  rigid  pavements. 

Terminal IRI and joint faulting distresses for rigid pavements were chosen as 172 in/mile and 0.12 

inches, respectively. 

Table 39. PAVEMENT DISTRESS TYPES AND TARGET VALUES FOR FLEXIBLE PAVEMENT 

Parameter 

Target value 

Reliability (%) 

170 
Terminal IRI (in/mile) 
Total Pavement Rutting (in) 
0.75 
Notes: IRI= International Roughness Index; AC= Asphalt Concrete 
 

90 
90 

90 
90 

Table 40. PAVEMENT DISTRESS TYPES AND TARGET VALUES FOR JCPC 

Parameter 

Target value 

Reliability (%) 

Terminal IRI (in/mile) 
Mean Joint Faulting (in) 
Notes: IRI= International Roughness Index  

172 
0.12 

In this section, distress analysis is done using the inputs indicated in Section 2 focusing on two 

distresses which might be affected by the base properties, IRI and total pavement deformation. 

 

 

 

89 

6.1. INTERNATIONAL ROUGHNESS INDEX (IRI) FOR FLEXIBLE 

PAVEMENTS  

The international roughness index (IRI) is a standard measure of pavement smoothness and ride 

quality  (Izevbekhai  and  Akkari  2011).  The  terminal  IRI  value  was  defined  to  be  170  in/mile 

(Elbheiry  et  al.  2011).  The  initial  IRI  value  was  determined  to  be  63  in/mile  which  was  in 

accordance with the suggestions provided by Izevbekhai and Akkari (2011); Ceylan et al. (2015). 

6.1.1. IMPACT OF SUMMARY RESILIENT MODULUS (SMR) ON IRI 

The predicted IRI values using the inputs mentioned in Table 29 and Table 30 are shown in Figure 

74 for RAP and Figure 75 for RCA in flexible pavements. Both Figure 74 and Figure 75 show that 

higher traffic and base layers with lower SMr yield higher IRI damage to the flexible pavements 

indicating that stiffness of the base layers have an impact on IRI distress. However, it does not 

seem to cause high differences in terms of IRI performance and none of the results exceeded the 

terminal IRI values. Thus, it can be claimed that any SMr values presented in the database can be 

used comfortably for pavement design analyses if IRI is the main design criteria.  

 
Figure 74. IRI VERSUS DIFFERENT SMR OF RAP 

 

 

90 

 

 
Figure 75. IRI VERSUS DIFFERENT SMR OF RCA 

 6.1.2. IMPACT OF FINES CONTENT ON IRI 

The predicted IRI values using the inputs mentioned in Table 31 and Table 32 are shown in Figure 

76  for  RAP  and  Figure  77  for  RCA  in  flexible  pavements.  Results  showed  that  higher  fines 

contents in RAP (ranging between 0%-11%) and RCA (ranging between 0.1%-15%) used as a 

base  course  material  had  higher  IRI  values  in  flexible  pavements  (Figure  76  and  Figure  77). 

However, none of the results exceeded the terminal IRI values indicating that any fines content 

values presented in the database can be used comfortably for pavement design analyses if IRI is 

the main design criteria. In addition, higher volume of traffic yielded higher IRI values regardless 

of fines content of RAP and RCA materials. 

Figure 76. IRI VERSUS DIFFERENT FINES CONTENT OF RAP IN FLEXIBLE PAVEMENT 

 

 

91 

 

Figure 77. IRI VERSUS DIFFERENT FINES CONTENT OF RCA IN FLEXIBLE PAVEMENT 

 

6.1.3. IMPACT OF GRAVEL CONTENT ON IRI 

The predicted IRI values using the inputs mentioned in Table 33 and Table 34 are shown in Figure 

78 for RAP and Figure 79 for RCA in flexible pavements. Results showed that higher gravel 

content in RAP (ranging between 3%-68.1%) and RCA (ranging between 31.8%-94.1%) materials 

seemed to increase IRI values slightly (almost negligible). As expected, higher traffic volume 

resulted  in  higher  IRI  values.  Moreover,  none  of  the  results  exceeded  the  terminal  IRI  values 

indicating that any gravel content values presented in the database can be used comfortably for 

pavement design analyses if IRI is the main design criteria. 

Figure 78. IRI VERSUS DIFFERENT GRAVEL CONTENT OF RAP IN FLEXIBLE PAVEMENT 

 

 

92 

Figure 79. IRI VERSUS DIFFERENT GRAVEL CONTENT OF RCA IN FLEXIBLE PAVEMENT 

 

6.1.4. IMPACT OF SAND CONTENT ON IRI 

The predicted IRI values using the inputs mentioned in Table 35 and Table 36 are shown in Figure 

80 for RAP and Figure 81 for RCA in flexible pavements. Figure 80 and Figure 81 show that there 

is a small decrease in IRI values when RAP (ranging between 28.1%-97%) and RCA (ranging 

between 4.9%-64.9%) base materials have relatively higher sand contents However, this change 

was very small and can be assumed negligible. Moreover, none of the results exceeded the terminal 

IRI  values  indicating  that  any  sand  content  values  presented  in  the  database  can  be  used 

comfortably for pavement design analyses if IRI is the main design criteria. 

Figure 80. IRI VERSUS DIFFERENT SAND CONTENT OF RAP IN FLEXIBLE PAVEMENT 

 

 

93 

Figure 81. IRI VERSUS DIFFERENT SAND CONTENT OF RCA IN FLEXIBLE PAVEMENT 

 

6.1.5. IMPACT OF D60 ON IRI  

The predicted IRI values using the inputs mentioned in Table 37 and Table 38 are shown in Figure 

82 for RAP and Figure 83 for RCA in flexible pavements. Impacts of D60 of the RAP and RCA 

materials were also investigated to determine whether there was a relationship between D60 of these 

materials and predicted IRI. As shown in Figures 82 and 83, no trend is observed between D60 and 

IRI values while higher traffic volume causes higher IRI values as expected. 

Figure 82. IRI VERSUS DIFFERENT D60 OF RAP IN FLEXIBLE PAVEMENT 

 

 

94 

Figure 83. IRI VERSUS DIFFERENT D60 OF RCA IN FLEXIBLE PAVEMENT 

 

6.2. INTERNATIONAL ROUGHNESS INDEX (IRI) FOR RIGID 

PAVEMENTS  

6.2.1. IMPACT OF SMR ON IRI 

The predicted IRI values using the inputs mentioned in Table 29 and Table 30 are shown in Figure 

84 for RAP and Figure 85 for RCA in rigid pavements. Results showed that traffic volume had a 

significant impact on IRI of rigid pavements while SMr of the RAP and RCA materials did not 

seem to impact the rigid pavements IRI performances.  

Figure 84. IRI VERSUS DIFFERENT SMR OF RAP IN RIGID PAVEMENT 

 

 

95 

Figure 85. IRI VERSUS DIFFERENT SMR OF RCA IN RIGID PAVEMENT 

 

 

6.2.2. IMPACT OF FINES CONTENT ON IRI 

The predicted IRI values using the inputs mentioned in Table 31 and Table 32 are shown in Figure 

86 for RAP and Figure 87 for RCA in rigid pavements. Figure 86 shows that an increase in fines 

content in RAP material (ranging between 0%-11%) caused a slight decrease in IRI values for 

rigid  pavements.  On  the  other  hand,  an  opposite  trend  was  observed  for  RCA  material  as  an 

increase in fines content (ranging between 0.1%-15%) resulted in higher IRI values. Moreover, 

Figures 86 and 87 show that all IRI values exceeded the terminal IRI value for RAP except the 

ones subjected to lower traffic volume while RCA IRI values satisfied this threshold performance 

for medium traffic level as well.  

 

96 

Figure 86. IRI VERSUS DIFFERENT FINES CONTENT OF RAP IN RIGID PAVEMENT 

 

Figure 87. IRI VERSUS DIFFERENT FINES CONTENT OF RCA IN RIGID PAVEMENT 

 

6.2.3. IMPACT OF GRAVEL CONTENT ON IRI 

The predicted IRI values using the inputs mentioned in Table 33 and Table 34 are shown in Figure 

88 for RAP and Figure 89 for RCA in rigid pavements. Figures 88 and 89 show that IRI values 

decrease when RAP (ranging between 3%-68.1%) and RCA (ranging between 31.8%-94.1%) with 

higher gravel contents are used as base materials.  In addition, it was observed that terminal IRI 

values were exceeded when the lowest and median gravel contents were used under high and 

medium level traffic volumes.  This suggests determining the gravel content of RAP and RCA 

materials before their use as a base material for rigid pavement design.  

 

97 

Figure 88. IRI VERSUS DIFFERENT GRAVEL CONTENT OF RAP IN RIGID PAVEMENT 

 

Figure 89. IRI VERSUS DIFFERENT GRAVEL CONTENT OF RCA IN RIGID PAVEMENT 

 

 

6.2.4. IMPACT OF SAND CONTENT ON IRI 
 
The predicted IRI values using the inputs mentioned in Table 35 and Table 36 are shown in Figure 

90 for RAP and Figure 91 for RCA in rigid pavements. Figure 90 shows that IRI values of RAP 

are significantly impacted when sand content is increased from the lowest (28.1%) to median sand 

content while such impact is not observed between IRI values predicted via median and the highest 

sand contents (97%). Such a trend was not observed for RCA (Figure 91). These results claim that 

sand contents of RAP bases could be a critical parameter to be checked before conducting rigid 

pavement design.    

 

98 

Figure 90. IRI VERSUS DIFFERENT SAND CONTENT OF RAP IN RIGID PAVEMENT 

 

 

Figure 91. IRI VERSUS DIFFERENT SAND CONTENT OF RCA IN RIGID PAVEMENT 

 

6.2.5. IMPACT OF D60 ON IRI  

The predicted IRI values using the inputs mentioned in Table 37 and Table 38 are shown in Figure 

92 for RAP and Figure 93 for RCA in rigid pavements. Results for both RAP and RCA showed 

that an increase in D60 from the lowest (0.090 inch in RAP and 0.067 inch in RCA) to median 

value (0.19 inch in RAP and 0.268 inch in RCA) did not seem to impact the IRI performance of 

rigid pavements while it was improved significantly when D60 was the highest value presented in 

 

99 

the database. These results indicated that agencies may prefer to use RAP and RCA materials with 

higher D60 values.     

Figure 92. IRI VERSUS DIFFERENT D60 OF RAP IN RIGID PAVEMENT 

 

Figure 93. IRI VERSUS DIFFERENT D60 OF RCA IN RIGID PAVEMENT 

 

6.3. Total Rutting on Flexible Pavements 

6.3.1. IMPACT OF SMR ON TOTAL RUTTING 

Figure 94 and Figure 95 show that the summary resilient modulus (SMr) of RCA and RAP has an 

impact on the total rutting of the pavement system. It was observed that changes in SMr of both 

 

100 

RAP (ranging between 24366 psi-58015 psi) and RCA (ranging between 17898 psi-53664 psi) had 

a same rate of decrease in total rutting distress predictions. 

Figure 94. TOTAL RUTTING VERSUS DIFFERENT SMR OF RAP 

 

Figure 95. TOTAL RUTTING VERSUS DIFFERENT SMR OF RCA 

 

 

6.3.2. IMPACT OF FINES CONTENT ON TOTAL RUTTING 

According to Figure 96 and Figure 97, total rutting of pavements (running Pavement ME with 

input shown in Tables 31 and 32) increase significantly with an increase in fines contents of both 

RAP (ranging between 0%-11%) and RCA (ranging between 0.1%-15%) materials. This indicates 

 

101 

that extra attention should be paid for fines content of these materials even though none of the 

cases exceeded the terminal total rutting thresholds.  

Figure 96. TOTAL RUTTING VERSUS DIFFERENT FINES CONTENT OF RAP 

 

 

Figure 97. TOTAL RUTTING VERSUS DIFFERENT FINES CONTENT OF RCA 

 

 

6.3.3. IMPACT OF GRAVEL CONTENT ON TOTAL RUTTING 

Figures 98 and 99 show that RCAs and RAPs with higher gravel content resulted in higher total 

rutting distresses in both RAP (ranging between 3%-68.1%) and RCA (ranging between 31.8%-

 

102 

94.1%). However, all the cases were below the total rutting criteria of 0.75 in (input data used for 

Pavement ME is shown in Tables 33 and 34). 

 

Figure 98. TOTAL RUTTING VERSUS DIFFERENT GRAVEL CONTENT OF RAP 

 

Figure 99. TOTAL RUTTING VERSUS DIFFERENT GRAVEL CONTENT OF RCA 

 

 

6.3.4. IMPACT OF SAND CONTENT ON TOTAL RUTTING 

Unlike gravel and fines content, both RAPs (ranging between 28.1%-97%) and RCAs (ranging 

between 4.9%-64.9%) with higher sand content yielded lower total rutting distresses (Figure 100 

 

103 

and Figure 101). In addition, all cases were below the rutting failure criteria for these analyses 

(input data used for Pavement ME is shown in Tables 35 and 36). 

 

Figure 100.  TOTAL RUTTING VERSUS DIFFERENT SAND CONTENT OF RAP 

 

Figure 101. TOTAL RUTTING VERSUS DIFFERENT SAND CONTENT OF RCA 

 

 

6.3.5. IMPACT OF D60 ON TOTAL RUTTING 

Figure  102  shows  that  higher  D60  for  RAP  materials  tend  to  slightly  increase  total  rutting  of 

pavements (input data used for Pavement ME is shown in Table 37). On the other hand, the median 

 

104 

D60 value presented in the database yielded to the lower total rutting distress predictions for RCA 

material (Figure 103) (input data used for Pavement ME is shown in Table 38). Overall, both 

Figures 102 and 103 show that any data used from the database in the analyses resulted in total 

rutting values lower than that of total rutting failure criteria.    

 

 

 

Figure 102. TOTAL RUTTING VERSUS DIFFERENT D60 OF RAP 

 

Figure 103. TOTAL RUTTING VERSUS DIFFERENT D60 OF RCA 

 

 

105 

6.4. MEAN JOINT FAULTING  

Transverse joint faulting is one of the main types of distresses in rigid pavements affecting its 

serviceability. Joint faulting is defined as the difference in elevation between adjacent joints at a 

transverse joint and it is developed due to a combination of repeated heavy axle loads, insufficient 

load transfer between the adjacent slabs, free moisture in the pavement structure, and erodible base 

or subgrade material. When there is an excess moisture in a pavement with an erodible base or 

underlying fine-grained subgrade material, repeated vehicle loadings will cause the mixture of 

water and fines materials to be removed from beneath the leave slab corner and ejected to the 

surface through the transverse joint or along the shoulder. This process is called pumping which 

will eventually cause a void below the leave slab corner. Additionally, some of the fines that are 

not ejected will be deposited under the approach slab corner, making the approach slab to rise. 

This material building up beneath the approach corner and losing support due to a void under the 

leave corner can result in significant faulting at the joint (especially for rigid pavement without 

dowels). As mentioned above it is clear that properties of base materials may have a great impact 

on joint faulting distresses of rigid pavements. Therefore, sensitivity analyses were conducted to 

determine whether the values collected in the database provide results that are under threshold 

limits for joint faulting distress (0.12 inches) for rigid pavement design analyses.  

6.4.1. IMPACT OF SMR ON MEAN JOINT FAULTING  

Figures 104 and 105 show that SMr of either RAP or RCA materials have any impact on joint 

faulting distress predictions for rigid pavements while they are directly impact by an increase in 

traffic volumes. (input data used for Pavement ME is shown in Tables 29 and 30).   

 

 

106 

Figure 104. MEAN JOINT FAULTING VERSUS DIFFERENT SMR OF RAP 

 

Figure 105. MEAN JOINT FAULTING VERSUS DIFFERENT SMR OF RCA 

 

 

6.4.2. IMPACT OF FINES CONTENT ON MEAN JOINT FAULTING  

Figure  106  shows  that  RAP  material  with  the  highest  fines  content  (11%)  resulted  in  a  slight 

decrease in joint faulting distresses under medium and high traffic volumes. On the other hand, 

Figure  107  shows  that  joint  faulting  distresses  increased  slightly  when  fines  content  of  RCA 

increased from the lowest (0.1%) fines content values to medium fines content (input data used for 

Pavement ME is shown in Tables 31 and 32).  

 

 

107 

Figure 106. MEAN JOINT FAULTING VERSUS DIFFERENT FINES CONTENT OF RAP 

 

Figure 107. MEAN JOINT FAULTING VERSUS DIFFERENT FINES CONTENT OF RCA 

 

6.4.3. IMPACT OF GRAVEL CONTENT ON MEAN JOINT FAULTING  

Both Figures 108 and 109 show that using the highest gravel content for both RAP (68.1%) and 

RCA (94.1%) materials yielded a slight decrease in joint faulting distresses for rigid pavements 

under all traffic conditions (input data used for Pavement ME is shown in Tables 33 and 34). 

 

108 

 

Figure 108. MEAN JOINT FAULTING VERSUS DIFFERENT GRAVEL CONTENT OF RAP 

 

Figure 109. MEAN JOINT FAULTING VERSUS DIFFERENT GRAVEL CONTENT OF RCA 

 

 

6.4.4. IMPACT OF SAND CONTENT ON MEAN JOINT FAULTING  

For  both  RAP  and  RCA  materials,  it  was  observed  that  an  increase  in  sand  content  (ranging 

between 28.1%-97.0% for RAP and 4.90%-64.9% for RCA) in these materials caused a consistent 

increase in joint faulting distresses under all traffic conditions (input data used for Pavement ME 

is shown in Tables 35 and 36). Figure 110 and 111 are derived from running Pavement ME using 

inputs from Table 35 and 36.  

 

109 

 

Figure 110. MEAN JOINT FAULTING VERSUS DIFFERENT SAND CONTENT OF RAP 

 

Figure 111. MEAN JOINT FAULTING VERSUS DIFFERENT SAND CONTENT OF RCA 

 

6.4.5. IMPACT OF D60 ON MEAN JOINT FAULTING  

Both Figures 112 and 113 show that joint faulting distresses decrease slightly when the highest 

D60 values from the database are used for both RAP (0.409 inch) and RCA (0.642 inch) materials 

(input data used for Pavement ME is shown in Tables 37 and 38).    

 

110 

Figure 112. MEAN JOINT FAULTING VERSUS DIFFERENT D60 OF RAP 

 

Figure 113. MEAN JOINT FAULTING VERSUS DIFFERENT D60 OF RCA 

 

 

 

 

 

 

 

 

 

 

111 

CHAPTER 7. CONCLUSIONS/RECOMMENDATIONS  

Extensive literature review was conducted on RAP and RCA used as base or subbase materials. In 

addition, data for the RAP and RCA mixtures with natural aggregates was collected as well. The 

relationships  between  summary  resilient  modulus  (SMr),  California  Bearing  Ratio  (CBR), 

hydraulic conductivity, permanent deformation and index characteristics of these materials were 

investigated. Sensitivity analysis was conducted to determine how these input properties of the 

100%  RAP  and  RCA  could  affect  pavement  distress  predictions  for  both  flexible  and  rigid 

pavement via using AASHTOware Pavement ME software. Based on the analyses of dataset and 

the results of PMED the following conclusions can be drawn: 

•  Gravel contents of RAPs range from 3% to 68% with the median of 45% while the gravel 

contents of RCA are between 32 % and 94 % with the median to be 51%. Thus, RCA tends 

to be slightly coarser than RAP. 

•  Sand contents of RAP are between 28% and 97% with the median to be 54%. The lower 

limit of sand content is 4.9% and the upper limit of sand content is 65% in RCA with the 

median value of 46%. 

•  Fines contents in most of the RAP and RCA contents are below 12%. Fines content of RAP 

ranged between 0% and 11% with the median of 1% while it ranged from 0.1% to 13% 

with the median of 2.8% for RCA. 

•  Specific gravities of RAPs fall between 2.19 to 2.87 with the median of 2.395 while these 

values are between 2.12 and 2.7 with the median of 2.39 for the RCAs. 

•  Maximum dry unit weight (MDU) of RAPs ranges from 17.2 kN/m3 (110 pcf) to 24.1 

kN/m3 (155 pcf) with the median of 19.6 kN/m3 (126 pcf). MDU of RCAs falls between 

 

112 

18.3 kN/m3 (118 pcf) and 21.7 kN/m3 (139 pcf) with the median value to be 19.7 kN/m3 

(127 pcf). 

•  Optimum moisture content (OMC) of RAP and RCAs ranges between 4-10.7% and 6.1-

14.8%, respectively. 

•  Summary resilient modulus (SMr) of RAPs ranges from 168 MPa (24366 psi) to 400 MPa 

(58015 psi) with the median value of 262 MPa (37927 psi). The SMr of RCA is between 

123 MPa (17897 psi) and 370 MPa (53664 psi) with the median value of 183 MPa (26542 

psi). 

•  The permanent deformation of 100% RAPs ranges from 1.05% to 5.63%. The permanent 

deformation of 100% RCAs is between 0.1% and 0.83%. RCA shows the lowest permanent 

deformation  among  RCA,  RAP  and  natural  aggregates  while  RAP  shows  the  highest 

permanent deformation. 

•  CBR of RAP is between 18 and 68 with the median of 28 while CBR of RCA ranges 

between 58 and 169 with the median to be 146. 

•  Angle of friction (φ) and the cohesion (c) of 100 % RAP specimen vary from 44° to 52º 

and 0 kPa to 131 kPa, respectively. 

•  The cohesion (c) of RCAs range from 24 kPa to 191 kPa and angle of friction (φ) of RCAs 

range from 19° to 52.7°. 

•  No trend was observed between CBR and gravel-to-sand ratio (G/S) or fines content in 

both RCA and RAP. 

•  Hydraulic conductivity of RAPs falls between 1.8x10-7 m/s (2.12x10-3 ft/hr) and 1.14x10-

3 m/s (13.46 ft/hr) with the median value to be 6.89x10-5 m/s (8.14x10-1 ft/hr). Hydraulic 

 

113 

conductivity of RCA ranges from 1.05x10-6 m/s (1.24x10-2 ft/hr) to 1.2x10-3 m/s (14.17 

ft/hr) with the median value to be 1.7x10-5 m/s (2.00x10-1 ft/hr). 

• 

It is observed that higher D10 values results in higher hydraulic conductivity and higher 

fines contents yield smaller hydraulic conductivity for RAP and RCA materials. 

•  SMr of RAPs and RCAs increases with higher G/S ratio while fines contents have no effect 

on SMr of RAPs and RCAs. 

•  There is an increasing trend in SMr of RAPs with higher D30 and D60 values. 

•  RAPs with higher values of Cc and Cu will have higher SMr. 

•  RCAs with higher Cu tends to have higher SMr. 

•  As  temperature  increases  SMr  of  RAPs  decreases  except  when  thermal  preloading  is 

applied. On the other hand, SMr of RCA is independent from both compaction and testing 

temperature conditions. 

•  SMr of RAPs decrease as optimum moisture content (OMC) of RAPs increases. 

•  Higher permanent deformation of natural aggregates is observed with addition of RAP 

which needs to be considered when designing a pavement with RAP.  

•  As RCA content increases in RCA-natural aggregate blends, OMC increases as well while 

MDU of the blends decreases. 

•  According  to  PMED  results,  summary  resilient  modulus  (SMr)  of  base  has  the  highest 

influence on the pavement performance among other material inputs for base. 

•  While with higher traffic volume, higher base and asphalt layer or PCC thicknesses were 

applied, more damage was observed with higher AADTT values. 

•  There is an increasing trend in total rutting with higher fines contents in RAP and RCA. 

•  There is a decreasing trend in rutting with higher SMr in both RAP and RCA.  

 

114 

•  As sand content increases, the rutting of the pavement decreases in both RAP and RCA.  

•  While fines content gets higher, the IRI increases as well in both RCA and RAP in flexible 

pavements. 

•  No special trend was observed in different D60 values with total rutting. 

•  No trend was observed between D60 and IRI in RCA and RAP in both flexible and rigid 

pavements. 

•  Mean joint faulting and IRI control the rigid pavement design located in high traffic and in 

some cases medium traffic volume as they always fail in all cases for both RAP and RCA. 

•  All cases with low traffic volume satisfy the target value defined for rigid pavements so it 

is safe to design JCPC pavements with RAP and RCA used as base course materials for 

low traffic roads without much experiment or data needed. 

•  All cases in flexible pavement pass the IRI and total rutting criteria. However, in some 

cases such as high fines content, low sand, and high gravel content for RCA in medium 

and high traffic areas, they come close to the target values defined. 

•  Overall, there is a high chance that flexible pavements with a period design of 20 years can 

provide adequate performance in all types of traffic volume. However, it is recommended 

that before designing flexible pavement, one can measure gradations and then summary 

resilient modulus as they have the major influence on total rutting and IRI. 

The main part of the project was to collect engineering and index properties data from RAP and 

RCA and the whole database is summarized in the Table 41.  

 

 

 

115 

Table 41. SUMMARY OF DATABASE 

 

Characteristics 

% Gravel 
% Sand 
% Fines 

D10 (mm/in) 

D30 (mm/in) 

D60 (mm/in) 

Cu 
Cc 
Gs 

MDU 

(kN/m3/pcf) 
OMC(%) 

SMr (MPa/psi) 

CBR (%) 
Hydraulic 
conductivity 
(m/s/ft/hr) 

Lower 
Limit 
3 (52) 
28.1 (52) 
0 (52) 
10-1/ 
3.9x10-3 

(30) 
8x10-2/ 
3.1x10-3 

(27) 

1.5x10-1/ 
5.9x10-3  

(27) 
5 (35) 
0.21 (37) 
2.19 (38) 
17.2/ 110 

(46) 
4 (46) 
168/ 

24366.3 

(32) 
18 (12) 
1.8x10-7/ 
2.12x10-3 

(23) 

RAP 
Median 
45 (52) 
54 (52) 
1 (52) 
5x10-1/ 
1.96x10-2 

(30) 
1.5/ 
6x10-2 
(27) 
4.82/ 

1.89x10-1 

(27) 

10.65 (35) 
1.2 (37) 
2.395 (38) 
19.61/ 126 

(46) 

6.05 (46) 
261.5/ 

37927.368 

(32) 
28 (12) 
6.89x10-5/ 
8.14x10-1 

(23) 

Upper 
Limit 
68.1 (52) 
97 (52) 
11 (52) 

1/ 

3.93x10-2 

(30) 
4.9/ 

1.9x10-1 

(27) 
10.4/ 

4.09x10-1 

(27) 
40 (35) 
8 (37) 
2.87 (38) 
24.12/ 155 

(46) 

10.7 (46) 

400/ 

58015.1 

(32) 
68 (12) 
1.14x10-3/ 
1.35x10 

(23) 

Lower 
Limit 
31.8 (34) 
4.9 (34) 
0.1 (34) 
10-1/ 
3.9x10-3 

(19) 
2x10-1/ 
7.9x10-3 

(17) 
6x10-1/ 
2.36x10-2 

(17) 

2.1 (29) 
0.14 (29) 
2.12 (32) 
18.3/ 118 

(35) 

6.1 (35) 
123.4/ 

17897.657 

(18) 
58 (4) 

1.05x10-6/ 
1.24x10-2 

(12) 

RCA 
Median 
51 (34) 
46.3 (34) 
2.8 (34) 
2.3x10-1/ 
9x10-3 
(19) 
1.2/ 

4.72x10-2 

(17) 
6.8/ 

2.67x10-1 

(17) 
32 (29) 
1.4 (29) 
2.39 (32) 
19.7/ 127 

(35) 

10.8 (35) 

183/ 

26541.9 

(18) 
146 (4) 
1.7x10-5/ 
2.01x10-1 

(12) 

Upper 
Limit 
94.1 (34) 
64.9 (34) 
12.8 (34) 
4.3x10-1/ 
1.7x10-2 

2.56x10-1 

(19) 
6.5/ 

(17) 
16.3/ 

6.42x10-1 

(17) 
66 (29) 
6 (29) 
2.7 (32) 
21.7/ 140 

(35) 

14.8 (35) 

370/ 
53664  
(18) 
169 (4) 
1.2x10-3/ 
1.42x10 

(12) 

Notes: Numbers provided in parantheses for each data represent the corresponding sample size 
 

 

 

116 

 
 
 

 

 

 

 

 

 

 

APPENDICES

 

117 

  APPENDIX A. 

TABLE 42. GRADATION CHARACTERISTICS OF RCA-RAP DATABASE 

Ref 

Loc 

Type of 
Material 

Gravel 
(%) 

Sand 
(%) 

Fine 
(%) 

Classification - 

USCS 

Classification  - 

AASHTO 

D10 
(mm) 

D30 
(mm) 

D60 
(mm) 

Cu 

Cc 

Gs 

 
)
a
2
1
0
2
(
 
.
l
a
 
t
e
 
l
i
d
E

Aggregate 
Class 5 
Blend 
RAP 
RCA 

RCA 

RPM 
RCA 
RAP 
RCA 
RAP 
RCA 
RAP 
RCA 
RAP 
RCA 
RAP 
RMP 
RAP 

22.9 

32.7 
26.3 
31.8 

68.5 

49.3 
40.9 
31.7 
50.6 
36.8 
76.3 
41 
43.2 
32.1 
41.2 
50.9 
55.7 
30.9 

MN 

MI 

CO 

CA 

TX 

OH 

NJ 

WI 

67.6 

63.8 
71.2 
64.9 

28.3 

50.4 
46.3 
67.7 
47.1 
61.4 
21.6 
44.9 
49.5 
66.2 
54.6 
48.4 
43.6 
68.5 

9.5 

3.4 
2.5 
3.3 

3.2 

0.4 
12.8 
0.7 
2.3 
1.8 
2.1 
1 
7.3 
1.7 
4.3 
0.7 
0.6 
0.5 

GW-GM 

SP 
SP 
SW 

GP 

SW 
SC 
SP 
GW 
SW 
GW 
SW 

SW-SM 

SW 
SP 
GW 
GW 
SP 

119 

A-1-b 

A-1-b 
A-1-a 
A-1-a 

A-1-a 

A-1-b 
A-1-b 
A-1-a 
A-1-a 
A-1-a 
A-1-a 
A-1-a 
A-1-a 
A-1-a 
A-1-b 
A-1-a 
A-1-b 
A-1-b 

0.1 

0.2 
0.3 
0.1 

0.4 

0.4 
0.1 
0.4 
0.3 
0.3 
0.4 
0.7 
0.2 
0.5 
0.2 
1 
0.5 
0.6 

0.4 

0.6 
0.7 
0.4 

4.1 

1.7 
0.6 
0.9 
1.7 
1.3 
6.5 
2.5 
1.2 
1.6 
0.5 
2.8 
2.1 
1.4 

1.7 

2.8 
2.3 
1.7 

12.3 

6.5 
4.9 
3.3 
6.8 
4.2 
16.3 
7.9 
5.3 
3.8 
5.1 
5.9 
8.7 
3.6 

21 

13 
7 
21 

35 

17 
66 
9 
22 
13 
38 
11 
34 
7 
28 
6 
18 
6 

1.4 

0.5 
0.7 
1.4 

3.9 

1.1 
1.1 
0.7 
1.4 
1.2 
6 
1.1 
1.7 
1.3 
0.3 
1.3 
1 
0.9 

2.57 

 

2.41 
2.39 

2.37 

2.39 
2.28 
2.23 
2.32 
2.56 
2.27 
2.34 
2.24 
2.43 
2.31 
2.37 
2.35 
2.37 

Appendix A. (cont’d) 

 
t
e
 
l
i
d
E

 
.
l
a

 
)
b
2
1
0
2
(

 
)
c
2
1
0
2
(

 
t
e
 
l
i
d
E

 
.
l
a

 
r
e
u
l
m
u
t
u
T

 
.
l
a
 
t
e

 
)
5
1
0
2
(

 
)
9
0
0
2
(
 
r
e
d
n
a
c
o
L

 
d
n
a
 
a
w
k
o
M

 
)
5
0
0
2
(
 
s
e
l
b
e
e
P

 

 

WI 

RPM 

46 

43 

11 

GW-GM 

A-1-a 

MN 

RPM 

IL 

blend 

RAP 

CO 

RAP 

40 

73 

49 

55 
64 
54 
59 
45 
56 
59 
59 
67 
67 
75 

52 

25 

50 

43.6 
35.1 
43.6 
40.1 
54.4 
43 
40.2 
40 
32.2 
31.8 
24.1 

8 

2 

1 

1.4 
0.9 
2.4 
0.9 
0.6 
1 
0.8 
1 
0.8 
1.2 
0.9 

SW-SM 

A-1-a 

GW 

SW 

GW-GP 
GW-GP 
GW-GP 
GW-GP 
SW-SP 
GW-GP 
GW-GP 
GW-GP 
GW-GP 
GW-GP 
GW-GP 

 

 

 
 
 
 
 
 
 
 
 
 
 

MT 

CBC#1 
unmixed 
CBC#1 
20%RAP 
CBC#1 
50%RAP 

52.46 

41.58 

5.96 

GW-GP 

A-1-a (6A) 

54.98 

42.39 

1.82 

GW-GP 

A-1-a(5A) 

49.28 

49.01 

1.71 

SW-SP 

A-1-a(5A) 

 

 

 

 

 

 

 

 

 

 

1.2 

0.9 

4.9 

2.8 

20 

16.6 

1 

5.5 

6.1 

1.5 

 
 
 
 
 
 
 
 
 
 
 

 

 

 

 
 
 
 
 
 
 
 
 
 
 

 

 

 

 
 
 
 
 
 
 
 
 
 
 

 

 

 

 
 
 
 
 
 
 
 
 
 
 

 

 

 

 
 
 
 
 
 
 
 
 
 
 

 

 

 

 

 

 

 

2.25 
2.36 
2.3 
2.33 
2.39 
2.39 
2.37 
2.34 
2.36 
2.26 
2.29 

2.67 

2.67 

2.59 

119 

Appendix A. (cont’d) 

 

 

CBC#2 
unmixed 
CBC#2 
20%RAP 
CBC#2 
50%RAP 
CBC#3 
unmixed 
CBC#3 
20%RAP 
CBC#3 
50%RAP 

Pitrun 
unmixed 
Pitrun 

20%RAP 

Pitrun 

50%RAP 
FL RAP 

unprocessed 

FL RAP 

Hammermill 

FL RAP 
Tubgrinder 

RAP1 

(Plagioclase 

and 

Pyroxene) 

 
)
8
0
0
2
(
 
d
e
e
a
S

 
)
9
1
0
2
(
 
u
y
n
a
T
 
d
n
a
 

 

 

FL 

VA 

Virgin 
aggregate 

45 

43 

12 

SM-SC 

h
a
l
l

U

 

20%RAP1 

30%RAP1 

46 

45 

44 

53 

1 

SW 

45.6 

47.8 

9.4 

8.2 

SW-SP 

SW-SP 

120 

 

 

 

 

55.8 

41.59 

2.61 

GW-GP 

A-1-a (6A) 

54.35 

43.55 

53.74 

42.37 

2.1 

1.7 

GW-GP 

A-1-a (6A) 

GW-GP 

A-1-a(5A) 

55.5 

39.35 

5.15 

GW-GP 

A-1-a(5A) 

52.31 

45.68 

2.01 

GW-GP 

A-1-a(5A) 

58.48 

40.09 

1.43 

GW-GP 

A-1-a(5A) 

41.79 

40.74 

57.66 

38.23 

1.05 

1.62 

53.08 

38.04 

1 

 

 

 

 

 

 

 

 

 

SP 

GP 

GW 

GW/SW 

SW 

SP 

Spec. Borrow 

Spec. Borrow 

Spec. Borrow 

A-1-a 

A-1-a 

A-1-a 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

2.7 

2.66 

2.59 

2.68 

2.66 

2.59 

0.4 

0.4 

0.53 
0.28-
0.32 
0.35 

0.35 

 

1.6 

2 

2.5 

1.3-2 

1.9 

0.9 

0.7 

17 

15 

12 

5.1-6 
3.75-
5 
5 

42.5 

0.37 

2.72 

37.5 

0.66 

2.63 

22.6 

17.1 
10-
14.3 
14-
14.3 

0.98 
1.2-
2.2 
1.5-
2.1 
0.5 

2.61 

 

 

 

7 

 

 

2.95 

0.5 

2 

5.1 

10.2 

1.5 

2.85 

 

 

 

 

 

 

 

 

 

 

 

 

Appendix A. (cont’d) 

40%RAP1 

50%RAP1 

60%RAP1 

RAP2 

(Plagioclase 

and 

Pyroxene) 

RAP5 

(Plagioclase 

and 

Pyroxene) 

RAP11 

(Muscovite, 

Quartz, 

Biotite and 
Amphibo) 

 

DGABC 

RAP 

RCA 

100% 

aggregate 

CR 3 

25% RAP 
from CR 3 
50% RAP 
from CR 3 

60 
60 

60 

17 

27 

35 

 

 

NJ 

MN 

 
t
e
 
t
r
e
n
n
e
B

 
)
0
0
0
2
(
 
.
l
a

 
)
5
0
0
2
(
 
.
l
a
 
t
e
 
m
K

i

 

45 

46 

46 

39 

47.8 

47.8 

48.8 

60 

26 

73 

42 

57 

33 
59 

56 

7.2 

6.2 

5.2 

SW-SP 

SW-SP 

SW-SP 

1 

1 

1 

7 
1 

4 

SW 

SW 

SW 

GW 
GW 

GW 

74.5 

8.5 

SW-SP 

67 

6 

SW-SP 

61.5 

3.5 

SW 

121 

 

 

 

 

 

 

 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

0.5 

1.5 

4.5 

9 

1 

2.82 

0.32 

1.1 

3 

9.3 

1.26 

2.87 

0.5 

1.7 

5 

10 

1.1 

2.6 

0.18 
1 

0.18 

2.1 
3.1 

1.5 

9 
8 

11 

50 
8 

61 

2.7 
1.2 

1.1 

0.14 

0.42 

2.6 

18.5 

0.19 

0.85 

3.5 

18.4 

0.36 

2.3 

4.3 

11.9 

 

 

 

 
 

 

 

 

 

Appendix A. (cont’d) 

 

75% RAP 
from CR 3 

40 

58 

2 

SW 

 

 

g
n
o
D
d
n
a
 

 

 
)
4
1
0
2
(

g
n
a
u
H

TN 

RAP 

41 

58 

1 

SW-SP 

 

 

RAP 1 

46.3 

51.8 

1.83 

SW 

A-1-a 

RAP2 

37.8 

61.3 

0.93 

SW 

A-1-a 

RAP3 

45.7 

54.1 

0.13 

SP 

A-1-a 

MD 

RAP4 

40.7 

59 

0.33 

SW 

A-1-a 

RAP5 

44 

54.8 

1.19 

SW 

A-1-a 

RAP6 

45.3 

54.2 

0.47 

SW 

A-1-a 

122 

 
)
9
1
0
2
(
 
.
l
a
 
t
e
 
c
i
j
i

M

 

0.7 

2.7 

4.9 

7 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

14 

1.79 

2.25 

10.6 

1.26 

2.36 

5.6 

1.03 

2.25 

8.28 

1.58 

2.44 

11.7 

1.36 

2.29 

11.2 

1.32 

2.48 

Appendix A. (cont’d) 

 

 

 

 

 

 

 

 

RAP7 

47.6 

52 

0.39 

SW 

A-1-a 

RAP 1 as is 

45 

53.5 

1.5 

SW 

A-1-a 

RAP 2 as is 

40 

57.8 

2.2 

SW 

A-1-a 

VA 

Virgin 
aggregate 

as is 

Virgin 
aggregate 

Eng. 

Natural 
aggregate 

46 

42 

12 

SW-SM 

A-1-a 

48 

45.7 

6.5 

SW-SM 

A-1-a 

22.9 

67.6 

9.5 

GW-GM 

A-1-b 

MN 

RCA 

31.8 

64.9 

3.3 

SW 

A-1-a 

RCA  
blend 

32.7 

63.8 

3.4 

SP 

A-1-b 

123 

 
)
8
1
0
2
(
 
.
l
a
 
t
e
 

h
a
l
l

U

 
)
7
1
0
2
(
 
.
l
a
 
t
e
 
l
i
d
E

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

6.87 

1.26 

2.4 

10.65 

1.43 

2.43 

9 

1.36 

2.6 

93 

1.1 

2.85 

31 

2.6 

2.81 

21 

1.4 

2.57 

21 

1.4 

2.39 

13 

0.5 

 

Appendix A. (connt’d) 

 

 

RAP 

26.3 

71.2 

2.5 

SP 

A-1-a 

 

 

 

7 

0.7 

2.41 

Subgrade 

soil 

4 

91.5 

4.5 

SW 

A-2-6 

0.2 

0.8 

1.8 

9 

1.7 

 
)
8
1
0
2
(
 
.
l
a
 
t
e
 

n
a
s
a
H

 
t
e
 
a
l
a
p
p
u
P

 
)
2
1
0
2
(
 
.
l
a

 
i
g
i
e
b
n
a
m
i
e
l
o
S

 
l
i
d
E
 
d
n
a

 
)
a
5
1
0
2
(

 
.
l
a
 
t
e
 
o
g
r
a
m
a
C

 
)
3
1
0
2
(

 

 

NM 

RAP 

48 

51.7 

0.3 

SP 

30% RAP 

44.8 

50.7 

4.50 

SP 

TX 

RAP 

48 

48 

4 

GP 

WI 

RAP 

20 

78 

2 

SW 

WI 

RPM 

46 

43 

11 

GW-GM 

 

 

 

 

 

124 

 

 

 

 

5 

0.98 

 

 

 

 

2.39 

 

0.5 

0.98 

9 

18 

0.2 

0.4 

0.9 

9 

22.5 

0.2 

 

 

 

 

 

 

 

 

 

 
Appendix A. (cont’d) 

CA 

TX 

NJ 

MI 

CO 

TX 

NJ 

MN 

RCA 

RAP 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

2.3 

2.1 

4.3 

3.2 

0.7 

1 

0.7 

2.5 

 
)
5
1
0
2
(
.
l
a
 
t
e
 
i
g
i
e
b
n
a
m
i
e
l
o
S

 

 

 

 

 

 

 

 

 

 

125 

A-1-a 

0.31 

A-1-a 

0.43 

A-1-b 

0.18 

A-1-a 

0.4 

A-1-a 

0.35 

A-1-a 

0.72 

A-1-a 

1 

A-1-a 

0.3 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

22 

1.4 

2.32 

38 

6 

2.27 

28 

0.3 

2.31 

35 

3.9 

2.37 

9 

0.7 

2.23 

11 

1.1 

2.34 

6 

1.3 

2.37 

7 

0.7 

2.41 

Appendix A. (cont’d) 

25%RCM 

40 

59 

1 

SP 

MN 

50% RCM 

75% RCM 

41 

42 

58 

57 

100% RCM 

48 

51 

1 

1 

1 

SP 

SP 

SP 

 

 

 

 

0.6 

1 

5 

8.3 

0.3 

0.5 

0.9 

0.42 

0.9 

5 

5 

10 

0.3 

11 

0.3 

0.4 

0.8 

7 

17.5 

0.22 

MN 

RAP Trunk 
highway 10 

RAP TH 

19-MM 101 
field 50-50 

RAP TH 

19-MM 104 
field 50-50 

RAP TH 22 
field 50-50 

51 

48.6 

0.4 

GP 

A-1-b 

0.6 

2 

7 

11.7 

0.95 

22 

76.6 

1.4 

SP 

A-1-b 

0.32 

0.6 

1.8 

5.6 

0.6 

24 

73.9 

2.1 

41 

57.7 

1.3 

SP 

SP 

126 

A-1-b 

0.25 

0.6 

2 

8 

0.72 

A-1-b 

0.42 

1.3 

5 

11.9 

0.8 

 

 

 

 

 

 

 

 

 
)
1
1
0
2
(
 
l
a
 
t
e
 

g
n
a
K

 
)
a
0
1
0
2
(
 
n
a
m
h
a
r
l
e
d
b
A
 
d
n
a
 
a
i
t
t

A

 

Appendix A. (cont’d) 

 

 

UT 

RI 

 
)
7
0
0
2
(
 
.
l
a
 
t
e
 
e
i
r
h
t
u
G

 
)
6
1
0
2
(
 
l
a
 
t
e
 
w
a
h
s
d
a
r

B

 

50% RAP 

TH 10 

+50% Class 

5 lab 

75% RAP 

TH 

10+25% 
Class 5 lab 

41.5 

56.85 

1.65 

SP 

A-1-b 

0.32 

0.95 

5 

15.6 

0.56 

46.25 

52.72 

1.03 

SP 

A-1-b 

0.4 

1.3 

6.5 

16.2 

0.065 

RAP 1 

45 

46.5 

8.5 

SW-SM 

A-1-a 

0.127 

0.889 

5.08 

RAP 2 

45 

54 

1 

SW 

A-1-a 

0.508 

1.651  4.826 

Base1 

55 

35.5 

9.5 

GWGM 

A-1-a 

0.08382  1.016  9.652 

Base2 

44 

46.5 

9.5 

SP-SM 

A-1-a 

0.08382 

1.27 

4.826 

RAP1, 23% 

3 

97 

0 

SW-SP 

A-1-a 

RAP2, 14% 

3 

97 

0 

SW-SP 

A-1-a 

 

 

 

 

 

 

127 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

2.47 

2.47 

2.64 

2.68 

 

 

Appendix A. (cont’d) 

 

 

RAP3, 23% 

9 

91 

0 

SW-SP 

A-1-a 

RAP FDR 
no treat 

7 

93 

RAP4, 26% 

5 

95 

Rap 5, 19% 

15 

85 

RAP 6 , 

39% 

8 

92 

0 

0 

0 

0 

SW-SP 

A-1-a 

SW-SP 

A-1-a 

SW-SP 

A-1-a 

SW-SP 

A-1-a 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 
r
e
h
a

 
)
5
0
0
2
(

M
 
d
n
a
 
t
r
e
n
n
e
B

 

 
 
 

RAP 

49 

50.9 

0.1 

SW 

NJ 

RCA 

71 

26.2 

2.8 

GW 

 

 

0.516 

0.08 

0.15 

10.85  1.22 

0.29 

0.2 

0.6 

52.95  4.71 

128 

 

 

 

 

 

 

 

Appendix A. (cont’d) 

 
)
6
1
0
2
(
 
.
l
a
 
t
e
 

n
e
g
t
s
e
B

 
)
2
1
0
2
(
 
.
l
a
 
t
e
 
r
e
u
l
m
u
t
u
T

 
.
l
a
 
t
e
 
n
a
j
a
r
a
t
a
N

 
)
9
1
0
2
(

 
n
i
t
e
C
 
d
n
a
 
i
d
e
h
a

 
)
0
2
0
2
(

M

 

 

 

A
S
U
n
r
e
t
s
a
E

G1 

G2 
G3 
G4 

RCA 1 
RCA 2 

RCA 

75% RCA 

IL 

50% RCA 

RCA 
RCA 

line 
RCA 

Passing lane 
RCA Center 

Driving lane 

RCA1 

RCA2 

RCA1 

RCA 2 

MN 

TX 

IA 

MN 

RCA 

 

 
 
 
45 
40 

55 

55 

55 

 

55 

37 

52 

 

 
 
 
45 
55 

37 

36 

35 

 

43 

61 

46 

93.4 

68.8 

48.8 

82 

94.1 

5.8 

31.1 

51.1 

17.8 

4.9 

 

 
 
 
10 
5 

8 

9 

10 

 

2 

2 

2 

0.8 

0.1 

0.1 

0.2 

1 

 

 
 
 
SP 
SP 

GP 

GP 

GP 

GW 

GW 

GW 

GW 

GP 

GP 

SP 

GW 

GP 

129 

A-1-a 

0.1 

1.8 

10 

5 
10 
6.8 
6.5 
5 

7.5 

7.5 

0.05 
0.08 
0.1 
0.11 
0.11 

0.3 
1 
0.3 
0.6 
0.28 

0.23 

2.5 

0.1 

2.5 

A-1-a(0) 
A-1-a(0) 
A-1-a(0) 
A-1-a(0) 
A-1-a(0) 

 

 

 

 

 

 

 

A-1-a 

A-1-a 

A-1-a 

A-1-a 

A-1-a 

0.075 

2.5 

7.5 

 

0.4 

0.35 

0.32 

 

 

 

 

 

 

1.9 

0.8 

1.4 

 

 

 

 

 

 

8 

4 

8 

 

 

 

 

 

 

 
 
 
59 
45 

32 

75 

 

 

 

 

 

2.1 

32 

7.9 

7.6 

2.1 

 

 
 
 
0.5 
0.14 

 

 
 
 
 
 

3.6 

2.41 

8.3 

11 

 

 

 

 

1.1 

3.6 

0.6 

1.8 

1.4 

 

 

2.7 

2.26 

2.13 

2.5 

2.44 

2.41 

2.33 

2.36 

2.12 

 
Appendix A. (cont’d) 

CA 
CO 
MI 
MN 
TX 

 

h
s
e
r
F
 
I

W

 

k
c
o
t

S
 
I

 
e
l
i

P

RCA 
RCA 
RCA 
RCA 
RCA 

RCA 

RCA 

 
 
 
 
 

 

 

 
 
 
 
 

 

 

 
 
 
 
 

 

 

SP 
SM 
GP 
SP 

GP-GM 

GP 

SP 

W

WI 

RCA 

51 

47.2 

1.8 

GW 

 
 
 
 
 

 

 

 

 
 
 
 
 

 

 

 
 
 
 
 

 

 

 
 
 
 
 

 

 

 
 
 
 
 

 

 

 
 
 
 
 

 

 

2.6 
2.6 
2.7 
2.7 
2.6 

2.7 

2.6 

0.17 

1.2 

7 

41.67  1.25 

2.41 

MN 

Coarse 
RCA 

Fine RCA 
RCA+ RAP 

61.7 

38.3 
41 

34.9 

54.6 
50.4 

3.4 

7.1 
8.6 

GW 

SW-SM 
SP-SM 

A-1-a 

A-1-a 
A-1-a 

 

 
 

 

 
 

 

 
 

34.49  1.75 

33.93  1.12 
49.41  0.98 

2.64 

2.64 
2.52 

WA 

RAP 

67 

32 

1 

GP 

 

0.45 

4.9 

10.4 

23 

5.13 

 

130 

 
)
3
1
0
2
(
 
.
l
a
 
t
e
 

n
e
h
C

 
t
e
 
e
n
g
a
i
D

 
)
5
1
0
2
(
 
.
l
a

 
.
l
a
 
t
e
 
n
i
t
e
C

 
)
0
2
0
2
(

 
)
2
1
0
2
(
 
.
l
a
 
t
e
 

u
W

 

Appendix A. (cont’d) 

 

m
a
l
A

 
.
l
a
 
t
e

 
)
0
1
0
2
(

MN 

RAP 100% 

4 

96 

0 

SP-SW 

 

 

 

 

 

 

 

APAC 

Melbourne 
Crushed 

 

APAC 

Melbourne 

Milled 

24.2 

75.2 

0.6 

SP 

A-1-a 

0.3 

0.91 

3.1 

10.7 

0.9 

2.508 

41.9 

57.6 

0.5 

SW 

A-1-a 

0.5 

2 

5 

9.6 

1.9 

2.524 

 
)
2
1
0
2
(
 
.
l
a
 
t
e
 

o
n
i
t
n
e
s
o
C

 

 

Whitehurst 
Gainesville 

Milled 

FL 

54 

45.6 

0.4 

SP 

A-1-a 

0.4 

1.5 

4.8 

11.2 

0.8 

2.576 

APAC 

Jacksonville 

Crushed 

26.6 

66.6 

6.8 

SP 

A-1-b 

0.1 

0.3 

3 

26.2 

0.4 

2.604 

75% milled 
mel and LR 

 

50% milled 
Melbourne 
and 50% 
LimeRock 

43 

56 

45 

53 

1 

2 

 

 

131 

 

 

0.39 

2 

5 

0.3 

1.8 

6 

 

 

 

 

 

 

Appendix A. (cont’d) 

 

 

25% milled 
Melbourne 
and 75% 
LimeRock 

50 

47 

3 

 

 

0.2 

1.3 

7.1 

 

 

 

0.9 

SP 

A-1-a 

0.27 

0.65 

4.7 

17 

0.3 

2.19 

A-1-b 

0.17 

0.35 

3.3 

19 

0.2 

2.25 

 

 

 

0.15 

0.25 

0.62 

4.1 

0.7 

2.37 

0.2 

0.85 

3.5 

0.35 

2.3 

4.3 

 

 

 

 

 

 

 

 

 

 

132 

 
)
3
0
0
2
(
 
.
l
a
 
t
e
 

o
n
i
t
n
e
s
o
C

100% RAP 
modified 

40 

FL 

80% RAP- 
20% fine 

sand 

60% RAP- 
40% fine 

sand 

 

 

 

 

 

3.1 

4 

25% RAP 
from CR 3 

28 

66 

6 

MN 

50% RAP 
from CR 3 

36 

60 

4 

 
)
7
0
0
2
(
 
z
u
b
a
L
 
d
n
a
 
m
K

i

 

 
 
 
 

 

Appendix A. (cont’d) 

 

75% RAP 
from CR 3 

40 

58 

CA 

RAP 

54 

45 

2 

1 

 

 
)
1
0
0
2
(
 

 

o
n
a
r
a
j
e
B

 

d
n
a
 

 
)
6
9
9
1
(
 

n
o
s
p
m
o
h
T

 

g
r
a
G

IL 

RAP 

68.1 

28.1 

3.8 

 

 

 

 

3
1
0
2
 
.
l
a
 
t
e
 
a
B

CO, TX 

TX RAP 

54 

45.01 

0.99 

SW 

CO RAP 

31 

68.31 

0.69 

SP 

 

 

 

 

 

0.7 

2.7 

4.9 

0.46 

2.1 

7 

 

 

 

0.8 

2.5 

8 

0.4 

0.9 

3.1 

 

 

 

 

 

 

 

 

 

 

 

 

 

2.34 

2.23 

Notes: CBC= Crushed base aggregate; DGABC= Dense graded aggregate base course ; CR= County Road ; RPM= Recycled pavement material ; 
RCM= Recycled concrete material; RAP TH= RAP Trunk Highway ; RAP FDR= Full-depth reclamation. Pyroxene is a group of important rock-
forming  silicate  minerals  of  variable  composition  including  calcium-,  magnesium-,  and  iron-rich  varieties  predominate,  while  Plagioclase 
contains calcium and sodium and is a mixture of albite (Ab), or sodium aluminosilicate (NaAlSi3O8), and anorthite (An), or calcium aluminosilicate 
(CaAl2Si2O8). 
 
 

 

133 

APPENDIX B. 

TABLE 43. RAP DATABASE 
Gravel (%) 

Loc. 

Ref. 

D10 
(mm) 
0.3 

D30 
(mm) 
0.7 

D60 
(mm) 
2.3 

SMr 
(MPa) 
180 

MN 

MI 

CO 

CA 

TX 

OH 

NJ 

WI 

26.3 

49.3 

31.7 

36.8 

41 

32.1 

50.9 

30.9 

Sand (%) 

Fine (%) 

71.2 

50.4 

67.7 

61.4 

44.9 

66.2 

48.4 

68.5 

2.5 

0.4 

0.7 

1.8 

1 

1.7 

0.7 

0.5 

WI 

46 

43 

11 

MN 

CO 

40 

64 

59 
59 

52 

8 

35.1 

40.1 
40 

0.9 

0.9 
1 

 
)
a
2
1
0
2
(
 
.
l
a
 
t
e
 
l
i
d
E

 
.
l
a
 
t
e
 
l
i
d
E

 
)
b
2
1
0
2
(

 
t
e
 
l
i
d
E

 
.
l
a

 
)
c
2
1
0
2
(

 
r
e
d
n
a
c
o
L

 
)
9
0
0
2
(

 

 

CBR 

Density (kN/m3)  OMC (%) 

 

 

 

 

 

 

 

 

 

20.8 

21.5 

20.7 

20.7 

20.3 

19.8 

20.4 

20 

21.2 

6.7 

5.2 

5.7 

6.1 

8 

8.8 

6.5 

7.3 

7.5 

168 

184 

173 

198 

197 

209 

266 

310 

HC (m/s) 
0.00000

11 

0.00023

1 

0.00003

82 
 

0.00003

0.00005

18 

03 

9 

0.00036

0.00005

19 

 

 

257 

19 

20.04 

4.9 

239.64 

211.8 
181.13 

 

 
 

19.35 

19 
18.8 

7.2 

10.7 
8.8 

7.7x10-

4 

0.00074 
0.00073 

6.5 

3.3 

4.2 

7.9 

3.8 

5.9 

3.6 

 

 

 

 
 

0.4 

0.4 

0.3 

0.7 

0.5 

1 

0.6 

 

 

 

 
 

1.7 

0.9 

1.3 

2.5 

1.6 

2.8 

1.4 

 

 

 

 
 

134 

Appendix B. (cont’d) 

 
t
r
e
n
n
e
B

 
.
l
a
 
t
e

 
)
0
0
0
2
(

 

g
n
a
u
H

 

g
n
o
D
d
n
a

 

 
)
4
1
0
2
(

 
a
l
a
p
p
u
P

 
.
l
a
 
t
e

 
)
2
1
0
2
(

 
i
g
i
e
b
n
a
m
i
e
l
o
S

 
l
i
d
E
d
n
a

 

 
)
a
5
1
0
2
(

 

o
g
r
a
m
a
C

 
.
l
a
 
t
e

 
)
3
1
0
2
(

NJ, 
RAP 

60 

TN 

41 

TX 

48 

59 

58 

48 

WI 

20 

78 

1 

1 

4 

2 

WI 

46 

43 

11 

CO 

TX 

NJ 

 

 

 

 

 

 

0.7 

1 

0.7 

0.35 

0.72 

1 

 
t
e
 
i
g
i
e
b
n
a
m
i
e
l
o
S

 
)
5
1
0
2
(
 
.
l
a

 

 
 
 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

135 

1 

3.1 

8 

300.3 

 

 

 

 

286.5 

251 

390 

18.35 

5 

18.73 

7.95 

21.3 

18.7 

309 

22 

21.2 

255 

345 

280 

 

 

 

20.7 

20.3 

20.4 

 

 

 

 

 

 

 

 

6 

5 

7.5 

5.7 

8.1 

6.5 

Appendix B. (cont’d) 

 
d
n
a
 
a
i
t
t

A

 

d
n
a
 
a
i
t
t

A

 
n
a
m
h
a
r
l
e
d
b
A

 

n
a
m
h
a
r
l
e
d
b
A

 
)
a
0
1
0
2
(

 
)
b
0
1
0
2
(

MN 

51 

48.6 

0.4 

0.6 

2 

7 

380 

MN 

51 

48.6 

0.4 

0.6 

2 

7 

380 

 

 

20.82 

5.5 

20.82 

5.5 

 

 

 

d
n
a
 
t
r
e
n
n
e
B

 
r
e
h
a

M

 
)
5
0
0
2
(

NJ 

49 

50.9 

0.1 

0.516 

0.08 

0.15 

268 

18 

 

 

 

 

20.26 

18.22 

5.6 

5.75 

 

 

 

 

0.00004
865 

 

 

 

 

 

21 

22 

 

 

 
.
l
a
 
t
e
 

u
W

 
)
2
1
0
2
(

WA 

 
e
i
r
h
t
u
G

 
.
l
a
 
t
e

 
)
7
0
0
2
(

UT 

RAP 1 

UT 

RAP 2 

 
t
e
 

n
a
s
a
H

 
)
8
1
0
2
(
 
.
l
a

NM 

67 

45 

45 

48 

32 

1 

0.45 

4.9 

10.4 

200 

 

46.5 

54 

8.5 

0.127 

0.889 

5.08 

1 

0.508 

1.651 

4.826 

51.7 

0.3 

0.5 

0.98 

9 

 

 

 

 
t
e
 
m
a
l
A

 
)
0
1
0
2
(
 
.
l
a

 

MN 

3 

97 

0 

 

 

 

271.3 

136 

Appendix B. (cont’d) 

 
o
n
i
t
n
e
s
o
C

 
.
l
a
 
t
e

 
)
3
0
0
2
(

 

o
n
a
r
a
j
e
B

 
)
1
0
0
2
(

 

 

d
n
a
 

g
r
a
G

n
o
s
p
m
o
h
T

 
)
6
9
9
1
(

 
 
.
l
a
 
t
e
 
c
i
j
i

M

 
)
9
1
0
2
(

 

d
n
a
 

h
a
l
l

U

 
)
9
1
0
2
(
 

u
y
n
a
T

 

FL 

40 

59.1 

0.9 

0.27 

0.65 

4.7 

291.39 

32 

18.5 

8.2 

CA 

54 

45 

1 

IL 

68.1 

28.1 

3.8 

MD 
RAP 1 
MD 
RAP2 
MD 
RAP3 
MD 
RAP4 
MD 
RAP5 
MD 
RAP6 
MD 
RAP7 
VA 
RAP1  
VA 
RAP2 
VA 
RAP 5 

46.3 

37.8 

45.7 

40.7 

44 

45.3 

47.6 

46 

39 

26 

51.8 

61.3 

54.1 

59 

54.8 

54.2 

52 

53 

60 

73 

1.83 

0.93 

0.13 

0.33 

1.19 

0.47 

0.39 

1 

1 

1 

310 

218.58 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

0.5 

0.5 

0.32 

2 

1.5 

1.1 

5.1 

4.5 

3 

137 

24.12 

5.5 

21.04 

6 

19.6 

18.5 

17.2 

18.7 

19.2 

19.1 

18.5 

 

 

 

5.7 

6.8 

6.3 

6.8 

7.5 

6.4 

8.2 

 

 

 

0.00000

2 

 

 

0.00009

0.00056

83 

6 

0.00114 
0.00025

1 

7 
 

 

 

0.00006

1 

89 

0.00020

0.00052

57 

1 

0.5 

1.7 

5 

53.5 

57.8 

1.5 

2.2 

 

 

 

 

 

 

 

 

 

 

Appendix B. (cont’d) 
VA 
RAP 
11 
VA 
RAP 1 
as is 
VA 
RAP 2 
as is 

 
)
8
1
0
2
(

 
.
l
a
 
t
e
 

h
a
l
l

U

42 

45 

40 

 
.
l
a
 
t
e
 
l
i
d
E

 
)
7
1
0
2
(

MN 

26.3 

71.2 

2.5 

 
.
l
a
 
t
e
 
a
B

 

2
1
0
2

TX 
RAP 
CO 
RAP 

54 

31 

45.01 

68.31 

0.99 

0.69 

0.8 

0.4 

2.5 

0.9 

8 

3.1 

 
e
n
r
u
o
b
l
e

 

M
C
A
P
A

 

d
e
h
s
u
r

C

 
e
n
r
u
o
b
l
e

 

M
C
A
P
A

 
d
e
l
l
i

M

 
)
2
1
0
2
(
 
.
l
a
 
t
e
 

o
n
i
t
n
e
s
o
C

 

 
 
 
 

24.2 

75.2 

0.6 

0.3 

0.91 

3.1 

41.9 

57.6 

0.5 

0.5 

2 

5 

138 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

19 

19.47 

 

 

 

 

5.5 

5.5 

 

 

 

62.4 

19.16 

5 

 

 

 

 

 

 

 

60 

19.03 

6.2 

0.00003

1 

Appendix B. (cont’d) 

 
t
s
r
u
h
e
t
i
h
W

 
d
e
l
l
i

M

 
e
l
l
i
v
s
e
n
i
a
G

 
e
l
l
i
v
n
o
s
k
c
a
J
 
C
A
P
A

 

d
e
h
s
u
r

C

54 

45.6 

0.4 

0.4 

1.5 

4.8 

26.6 

66.6 

6.8 

0.1 

0.3 

3 

 

N
M

MN 

MN 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

139 

 

 

193 

330 

400 

60 

19.08 

4 

0.00000

13 

68 

19.63 

4.5 

0.00000
018 

 

 

 

20.79 

4 

0.00002
2152 

20.82 

5.5 

 

 

 

 

 

 
t
e
 

g
n
a
K

 
)
1
1
0
2
(
 
.
l
a

 

d
n
a
 

n
a
m
h
a
r
l
e
d
b
A

 
)
4
1
0
2
(
 

n
i
d
l
e
r
u
o
N

 

d
n
a
 
a
i
t
t

A

 

n
a
m
h
a
r
l
e
d
b
A

 
)
1
1
0
2
(

 

APPENDIX C.  

TABLE 44. RCA DATABASE 

Gravel 
(%) 
31.8 
68.5 
40.9 
50.6 
76.3 
43.2 
41.2 

60 

 

 

 

 

Sand 
(%) 
31.8 
28.3 
46.3 
47.1 
21.6 
49.5 
54.6 

56 

 

 

 

 

Fine 
(%) 
3.3 
3.2 
12.8 
2.3 
2.1 
7.3 
4.3 

4 

2.1 

4.3 

2.3 

3.2 

Ref. 

 
)
a
2
1
0
2
(
 
.
l
a
 
t
e
 
l
i
d
E

r
e
n
n
e
B

 
.
l
a
 
t
e
 
t

 
)
0
0
0
2
(

 
t
e
 
i
g
i
e
b
n
a
m
i
e
l
o
S

 
)
5
1
0
2
(
 
.
l
a

 
t
e
 

g
n
a
K

 
)
1
1
0
2
(
 
.
l
a

Loc. 
MN 
MI 
CO 
CA 
TX 
OH 
NJ 

NJ 

Tx 

Nj 

CA 

MI 

MN 
RCM 

SMr (MPa) 

CBR 

D10 
(mm) 
0.1 
0.4 
0.1 
0.3 
0.4 
0.2 
0.2 

D30 
(mm) 
0.4 
4.1 
0.6 
1.7 
6.5 
1.2 
0.5 

D60 
(mm) 
1.7 
12.3 
4.9 
6.8 
16.3 
5.3 
5.1 

189 
171 
175 
178 
164 
163 
208 

0.18 

1.5 

11 

297.6 

0.43 

0.18 

 

 

 

 

 

 

 

 

 

 

188 

160 

 

 

164.844531

2 

Density 
(kN/m3) 
19.5 
20.8 
18.9 
19.9 
19.7 
19.4 
19.8 

19.45 

19.7 

19.8 

19.9 

20.8 

OMC 
(%) 
11.2 
8.7 
11.9 
10.4 
9.2 
11.8 
9.5 

7.5 

9.2 

9.5 

10.4 

8.7 

HC (m/s) 

 
 
 
 
 
 
 

 

 

 

 

 

19.02 

9.4 

0.00001021

2 

 
 
 
 
 
 
 

 

 

 

 

 

 

48 

51 

1 

0.4 

0.8 

7 

 

d
n
a
 
t
r
e
n
n
e
B

 
)
5
0
0
2
(
 
r
e
h
a

M

NJ 

71 

26.2 

2.8 

0.29 

0.2 

0.6 

272.9 

169 

 

 

0.00000105 

 

140 

 
Appendix C. (cont’d) 

 

 

A
S
U
 
n
r
e
t
s
a
E

 
1
 
 

A
C
R

45 

45 

10 

0.11 

0.6 

6.5 

295 

148 

20.2 

9.5 

 

A
S
U
 
n
r
e
t
s
a
E

 
2
 
A
C
R

40 

55 

IL 

55 

37 

5 

8 

0.11 

0.28 

5 

220 

144 

20.1 

9.5 

0.23 

2.5 

7.5 

188 

58 

20 

9.3 

 

 

 

 
)
6
1
0
2
(
 
.
l
a
 
t
e
 

n
e
g
t
s
e
B

 
r
e
u
l
m
u
t
u
T

 
.
l
a
 
t
e

 
)
2
1
0
2
(

 
t
e
 
e
n
g
a
i
D

 
)
5
1
0
2
(
 
.
l
a

WI 

51 

47.2 

1.8 

0.17 

1.2 

7 

370 

61.7 

34.9 

3.4 

38.3 

54.6 

7.1 

93.4 

5.8 

68.8 

31.1 

0.8 

0.1 

 

 

 

 

 

 

 

 

 

 

 

 

127.377075

2 

123.385892

5 

 

 

 
.
l
a
 
t
e
 

n
i
t
e
C

 
)
0
2
0
2
(

 
e
s
r
a
o
C

 

A
C
R

 
e
n
i

F

 

A
C
R

 

d
n
a
 
i
d
e
h
a

M

)
0
2
0
2
(
 

  TX 
RCA
1 
TX 
RCA
2 

n
i
t
e
C

 
 

 

141 

 

 

 

 

 

20.9 

6.1 

0.00003 

19.31 

11.3 

2.67E-06 

19.1 

11.1 

4.85E-06 

19 

10.9 

19.7 

14.4 

 

 

Appedix C. (cont’d) 

IA 
RCA
1 
IA 
RCA 

2 
MN 
RCA 

 

 
)
9
1
0
2
(
 
.
l
a
 
t
e
 

n
a
j
a
r
a
t
a
N

 
)
3
1
0
2
(
 
.
l
a
 
t
e
 

n
e
h
C

 

 

 

A
C
R
N
M

 

 

A
C
R
N
M

 

 

g
n
i
s
s
a
P

 
e
n
a
l

 

A
C
R
N
M

 

 
e
n
i
l
 
r
e
t
n
e
C

 

A
C
R
N
M

 

 
g
n
i
v
i
r

D

 
e
n
a
l

CA 

CO 

MI 
MN 
TX 

48.8 

51.1 

82 

94.1 

17.8 

4.9 

 

 

55 

43 

37 

61 

52 

50 

41 

69 
32 
76 

46 

47 

44 

28 
64 
21 

0.1 

0.2 

1 

 

2 

2 

2 

3 

15 

3 
4 
3 

 

 

 

 

8 

4 

8 

 

 

 
 
 

 

 

 

 

 

 

 

 

0.4 

1.9 

0.35 

0.8 

0.32 

1.4 

 

 

 
 
 

 

 

 
 
 

 

142 

 

 

 

 

 

 

 

 

 

 
 
 

 

 

 

 

 

 

 

 

 

 
 
 

19 

18.4 

18.3 

14.8 

14.3 

12.6 

19.5 

11.2 

21.4 

12 

21 

11.7 

21.7 

13.5 

 

 

 

 

 

 

 

19.8 

18.9 

20.8 
19.5 
19.7 

10.9 

11.9 

8.7 
11.2 
9.2 

0.000019 

0.000016 

0.000026 
0.000018 
0.000008 

Appendix C. (cont’d) 

 
h
s
e
r
F
 
I

W

 

 
e
l
i
p
k
c
o
t

 
I

W

48 

50 

65 

32 

2 

3 

S

MN 

31.8 

64.9 

3.3 

 
.
l
a
 
t
e
 
l
i
d
E

 

7
1
0
2

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

19.4 

10.8 

0.0012 

19.9 

9.9 

0.00071 

 

 

 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 

143 

 
 

 

 

 

 

 

REFERENCES 

 

 

 

 

 

 

144 

REFERENCES 

 

AASHTO  (1993).  Guide  for  Design  of  Pavement  Structures,  American  Association  of  State 

Highway and Transportation Officials, Washington, DC. 

 
AASHTO (2002). Standard Specifications for Highway Bridges, American Association of State 

Highway and Transportation Officials, Washington, DC. 

 
Abdelrahman, M., and Noureldin, E. (2014). Parametric Analysis of Resilient Modulus Modeling 
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