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MATERIAL CHARACTERIZATION IN SUPPORT OF IMPLEMENTATION OF THE
MECHANISTIC-EMPIRICAL PAVEMENT DESIGN GUIDE
A THESIS SUBMITTED TO THE GRADUATE DIVISION OF THE
UNIVERSITY OF HAWAIʻI AT MĀNOA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
MASTER OF SCIENCE
IN
CIVIL ENGINEERING
AUGUST 2012
By
Jayanth Kumar Rayapeddi Kumar
Thesis Committee:
Adrian Ricardo Archilla, Chairperson
Phillip Ooi
Lin Shen
ii
ABSTRACT
Use of the Mechanistic-Empirical Pavement Design Guide (MEPDG) and its associated
software requires a large number of inputs about traffic loading, environmental conditions, and
material characteristics. Except for very important projects, for which many of the material
characteristics may be determined directly from laboratory tests, practical implementation of the
MEPDG for routine pavement design projects requires the development of a database containing
properties for the most commonly used materials within the state.
In the analysis of flexible pavements in the MEPDG, the dynamic modulus (|E*|) and
resilient modulus (Mr) are the primary input parameters used to characterize the elastic response
of Hot Mix Asphalt (HMA) mixtures and base course (unbound granular) materials, respectively.
In addition to the elastic properties of the materials used in the mechanistic analysis of the
pavement structures, the MEPDG relies on deterioration model parameters to relate empirically
the mechanistic pavement responses (strains) on different points of the pavement structure to
distresses such as rutting (permanent deformation), cracking, and roughness.
This study focuses on measuring in the laboratory the resilient moduli of two types of
base course materials and the elastic and permanent deformation characteristics of three types of
HMA materials.
The continuous demand of aggregates for maintenance and rehabilitation (M&R) of
existing pavements and to a lesser degree for construction of new ones as well as the increasing
need to reduce the disposal of construction waste is putting pressure on agencies to find ways to
increase the recycling of materials such as Recycled Asphalt Pavement (RAP) into the pavement
structure. Experiences around the world indicate that Foamed Asphalt (FA) base course
mixtures, which are a typically produced by stabilizing Reclaimed Asphalt Pavement (RAP) with
iii
foamed (expanded) asphalt, have shown improved performance relative to unbound base
materials. Hence in this study, one of the base materials considered is a Foamed Asphalt (FA)
base mixture. The other base material studied is a virgin aggregate base course material. The
resilient moduli of both materials were studied at different density levels. The results of the study
showed that the Mr of FA mixtures is in general between 2.5 and 5 times (corresponding to
lowest and highest levels of bulk stress respectively) higher than the Mr of virgin aggregates
(Type B) at 98% and 100% of maximum dry density, whereas at 102% of maximum dry
density, the Mr of FA mixtures is in general between 2.8 and 1.8 times of maximum dry density
(corresponding to lowest and highest levels of bulk stress respectively) higher than the Mr of
virgin aggregates. Further, it was observed that the Mr of FA mixtures increased with increases
in bulk stress, and the Mr decreased with increases in octahedral shear stress. On the other hand,
the Mr of the virgin base course material increase mostly with the octahedral shear stress and to a
much lesser degree also increased with the bulk stress.
For HMA, this study focuses on comparing the test results of dynamic modulus and
permanent deformation tests performed in the laboratory on unmodified, polymer modified
asphalt (PMA) mixes (modified with Elvaloy RET©) , and mixes reinforced with FORTA fibers.
The laboratory experiments included testing two replicates of HMA specimens of each type at
three target air voids. The results of the tests show that the mixes prepared using the PMA binder
show relatively better resistance to rutting at high temperatures and low frequencies. For the
mixes prepared using fibers, it was observed that the rate of failure in a permanent deformation
test remains relatively constant irrespective of the of air voids of the specimen. The effect of the
fibers is to hold the coated particles together under these unfavorable conditions, thus providing
a level of safety for mixes compacted with high air voids.
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ACKNOWLEDGMENTS
I would like to express my deepest gratitude to Dr. Adrian Ricardo Archilla, my research
advisor, for giving me the opportunity to pursue a graduate program at the University of Hawaii
at Manoa (UH). Further, thanks to Dr. Archilla for providing invaluable technical and moral
support during the course of my graduate study at UH.
Sincere thanks to Dr. Phillip Ooi and Dr. Lin Shen for agreeing to participate in my
graduate thesis committee and providing helpful comments.
Heartfelt thanks to Dr. Jonathan E.D Richmond for helping me to get into the University
of Hawaii at Manoa for graduate studies.
Thanks to Hawaii Department of Transportation for providing all the assistance for my
graduate studies at UH.
Special thanks to Jaw W. Glover Ltd, Grace Pacific Corporation, FORTA Corporation,
Alakona Corporation, and Hawaiian Cement – Halawa Quarry for providing the materials used
in this study.
Special thanks to Richard S. Gribbin of Jas W. Glover Ltd for helping me in more than
one ways for timely completion of my thesis.
Sincere thanks to Mitchell Pinkerton of the University of Hawaii at Manoa for all his help
during the course of my laboratory studies.
Thanks to Dr. Arudi Rajagopal, Dr. Luis G. Dias Vasquez, Letizia de Lannoy, Chao
Huang, Diego Munar, Angel Panezo, Steve Havel, and Amir Mohammadipour for helping me
during the course of my graduate stay at UH.
Thanks to my parents, brother, wife, and a number of friends for being there at all times.
v
TABLE OF CONTENTS
ABSTRACT ................................................................................................................................... ii
ACKNOWLEDGMENTS ........................................................................................................... iv
TABLE OF CONTENTS ............................................................................................................. v
LIST OF FIGURES ................................................................................................................... viii
LIST OF TABLES ..................................................................................................................... xiv
CHAPTER 1 INTRODUCTION AND OBJECTIVES ............................................................ 1
1.1 Introduction ........................................................................................................................... 1
1.2 Problem Statement ................................................................................................................ 4
1.3 Research Objectives .............................................................................................................. 6
CHAPTER 2 Literature Review ................................................................................................. 8
2.1 Introduction ........................................................................................................................... 8
2.2 Foamed Asphalt Mixture ...................................................................................................... 8
2.2.1 Asphalt Foaming Technology ........................................................................................ 9
2.2.2 Factors Affecting Foamed Asphalt Mixtures ............................................................... 10
2.2.2.1 Asphalt Properties ................................................................................................. 11
2.2.2.2 Aggregate Properties ............................................................................................. 13
2.2.2.3 Mixing Moisture Content ...................................................................................... 15
2.2.2.4 Curing Conditions ................................................................................................. 17
2.2.2.5 Mixing Temperature ............................................................................................. 18
2.3 Polymer Modification ......................................................................................................... 18
2.4 Polymer Modifier Used in this Study ................................................................................. 19
2.5 Fiber Reinforced Asphalt Concrete Mixtures ..................................................................... 19
2.6 Fibers Used in this Study .................................................................................................... 20
2.7 MEPDG Material Input Parameters .................................................................................... 21
2.8 Dynamic Modulus |E*| ........................................................................................................ 23
2.9 Resilient Modulus ............................................................................................................... 29
2.9.1 Factors Affecting Mr of New Unbound Granular Materials ....................................... 30
2.9.1.1 Aggregate Physical State ...................................................................................... 31
2.9.1.2 State of Stress ........................................................................................................ 33
vi
2.9.1.3 Structure/Type of Material .................................................................................... 35
2.9.2 Resilient Modulus Models for New Unbound Granular Material ............................... 36
2.9.3 Recent Studies on Mr of Foamed Asphalt Mixes ........................................................ 42
2.9.3.1 Discussion ............................................................................................................. 46
2.10 Repeated Load Axial Test (RALT) .................................................................................. 47
CHAPTER 3 Laboratory Experiments ................................................................................... 52
3.1 Background ......................................................................................................................... 52
3.2 Material Sources ................................................................................................................. 52
3.2.1 Base Course Materials ................................................................................................. 52
3.2.2 Hot Mix Asphalt .......................................................................................................... 53
3.3 Base Course Material Information ...................................................................................... 54
3.3.1 Gradation Analysis of Aggregates ............................................................................... 54
3.3.2 Maximum Dry Density and Optimum Moisture Content ............................................ 57
3.4 Test Specimen Preparation for Resilient Modulus Testing ................................................ 58
3.5 Resilient Modulus Testing .................................................................................................. 60
3.6 Hot Mix Asphalt Mixtures Information .............................................................................. 72
3.6.1 Gradation Analysis of Aggregates ............................................................................... 73
3.6.2 Asphalt Binder ............................................................................................................. 74
3.6.3 Preparation of modified binder .................................................................................... 74
3.6.4 Mixing and Compaction Temperatures of Unmodified and Modified Binder ............ 76
3.6.5 Fibers Used in the Study .............................................................................................. 78
3.7 Test Specimen Preparation for Dynamic Modulus and Permanent Deformation Testing . 80
3.8 Dynamic Modulus Testing .................................................................................................. 90
3.9 Repeated Load Axial Test (RALT) .................................................................................. 107
CHAPTER 4 Summary and Conclusions ............................................................................... 115
4.1 Resilient Modulus of Base Course Materials ................................................................... 115
4.2 Dynamic Modulus and Permanent Deformation of HMA Mixtures ................................ 116
4.2.1 Dynamic Modulus of HMA Mixtures ........................................................................ 116
4.2.2 Flow Number Test on HMA Mixtures ....................................................................... 117
4.3 Contributions of the Study ................................................................................................ 118
References .................................................................................................................................. 119
vii
Appendix A: Base Course Material ChartS ........................................................................... 130
Appendix B: Dynamic Modulus Charts .................................................................................. 138
Appendix C: Permanent Deformation Charts ....................................................................... 164
viii
LIST OF FIGURES
Figure 1-1 Current Pavement Design Practices in the United States (FHWA, 2007) .................... 2
Figure 1-2 Schematic Representation of MEPDG Process (Coree et al., 2005) ............................. 3
Figure 2-1 Asphalt Foaming Technology (Construction Equipment, 2005) .................................. 9
Figure 2-2 Relationship Between Foaming Properties ................................................................. 12
Figure 2-3 Desired Aggregate Grading Zones for Foamed Asphalt ............................................. 15
(Redrawn after Akeroyd & Hicks, 1988) ...................................................................................... 15
Figure 2-4 Elvaloy RET Pellets (Photo courtesy: Archilla (2008)) ............................................ 19
Figure 2-5 FORTA fibers (HMA blend) ....................................................................................... 20
Figure 2-6 Asphalt Material Properties – Asphalt Mix Input Values for Level 1 Analysis ......... 22
Figure 2-7 Asphalt Material Properties – Asphalt Mix Input Values for Level 1 Analysis ......... 23
Figure 2-8 Typical Stress-Strain curve obtained during dynamic modulus testing of viscoelastic
materials ................................................................................................................................. 24
Figure 2-9 Dynamic modulus test data (Archilla, 2008) .............................................................. 26
Figure 2-10 Master Curve constructed at a reference temperature of 69.8 °F (Archilla, 2008) ... 27
Figure 2-11 Typical stress-strain behavior of unbound granular materials subjected to traffic-type
loading ................................................................................................................................... 29
Figure 2-12 Stresses Applied in a Triaxial Test............................................................................ 34
Figure 2-13 Range of resilient moduli values (Long and Ventura 2004). .................................... 43
Figure 2-14 HMA permanent deformation behavior .................................................................... 48
Figure 3-1 Gradation analysis of RAP compared with HDOT requirements for ¾” maximum
nominal untreated base .......................................................................................................... 55
Figure 3-2 Gradation analysis of virgin aggregates from Hawaiian Cement – Halawa Quarry
compared with HDOT requirements for 1-1/2” maximum nominal untreated base ............. 56
Figure 3-3 RAP Gradation and desired aggregate grading for FA ............................................... 57
Figure 3-4 Moisture-density relationship of base course materials .............................................. 58
Figure 3-5 Compacted specimen connected to vacuum supply line ............................................. 59
Figure 3-6 Specimen ready for testing .......................................................................................... 60
Figure 3-7 Test specimen inside the testing chamber along with sample LVDTs ....................... 61
Figure 3-8 Example of dynamic modulus data collection ............................................................ 62
ix
Figure 3-9 Effect of bulk stress on resilient modulus for virgin aggregates compacted at three
different densities ................................................................................................................... 63
Figure 3-10 Effect of bulk stress on resilient modulus of FA mixtures compacted at three
different densities ................................................................................................................... 63
Figure 3-11 Mr vs. deviator stress for specimens compacted at different densities using virgin
aggregates .............................................................................................................................. 65
Figure 3-12 Mr vs. deviator stress for specimens compacted at different densities using virgin
aggregates at low (3 psi), intermediate (5 psi), and high (20 psi) confining stress level ...... 66
Figure 3-13 Mr vs. deviator stress for specimens compacted at different densities using FA
mixtures ................................................................................................................................. 67
Figure 3-14 Mr vs. Bulk Stress for Coral sample ......................................................................... 71
Figure 3-15 Mr vs. deviator stress at different confinement stresses for Coral material .............. 72
Figure 3-16 Gradation information for laboratory produced HMA mixtures ............................... 73
Figure 3-17 Gradation information for plant produced HMA mixtures ....................................... 74
Figure 3-18 Evaloy®RET Pebbles (left) and mixing Elvaloy to Unmodified PG64-16 binder
(right) ..................................................................................................................................... 75
Figure 3-19 Fibers in its manufactured condition ......................................................................... 79
Figure 3-20 The setup used to fluff the fibers............................................................................... 79
Figure 3-21 Fibers after fluffing ................................................................................................... 79
Figure 3-22 Steps involved in preparation of test specimens ....................................................... 80
Figure 3-23 Mechanical mixer used for mixing HMA samples ................................................... 82
Figure 3-24 HMA mixture produced using virgin asphalt in the plant ......................................... 83
Figure 3-25 HMA mixture prepared in the laboratory using virgin asphalt ................................. 83
Figure 3-26 HMA mixture prepared in the laboratory using polymer modified asphalt .............. 83
Figure 3-27 HMA mixture prepared in the laboratory using virgin asphalt and FORTA-FI fibers
............................................................................................................................................... 84
Figure 3-28 A specimen extruded after compaction in a Rainhart SGC ...................................... 85
Figure 3-29 Specimen being cored (left) and sawed (right) to required size ................................ 86
Figure 3-30 Cored and sawed specimen ....................................................................................... 86
Figure 3-31 Gauge point fixing jig ............................................................................................... 87
Figure 3-32 Test specimen ready for dynamic modulus testing ................................................... 88
x
Figure 3-33 IPC Global Simple Performance Tester .................................................................... 90
Figure 3-34 Specimen assembly inside the testing chamber ........................................................ 91
Figure 3-35 An example of repeated attempts to glue the gauge point(s) for a specimen ........... 92
Figure 3-36 Example of dynamic modulus data collection .......................................................... 93
Figure 3-37 Master curves for VPPM at three different air voids ................................................ 95
Figure 3-38 Master curves for VLPM at three different air voids ................................................ 97
Figure 3-39 Master curves for PMALPM at three different air voids .......................................... 98
Figure 3-40 Master curves of all specimens for VPPM at three different air voids ..................... 99
Figure 3-41 Master curves for FRACLPM at three different air voids ...................................... 100
Figure 3-42 Comparison of master curves for mixes prepared using polymer modified binder and
compacted at different air voids .......................................................................................... 101
Figure 3-43 Master curve comparison among the three types of laboratory prepared mixtures
compacted at target Va=3% ................................................................................................. 102
Figure 3-44 Master curve comparison among the three types of laboratory prepared mixtures
compacted at target Va=5% ................................................................................................. 103
Figure 3-45 Master curve comparison among the three types of laboratory prepared mixtures
compacted at target target Va=7% ....................................................................................... 104
Figure 3-46 Comparison of dynamic modulus values for three different types of HMA mixtures
at 40 °F at 10 Hz .................................................................................................................. 105
Figure 3-47 Unconfined Dynamic Modulus Master Curves for FORTA Evergreen Control, 1
lb/Ton and 2 lb/Ton Mixtures (Kaloush et al, 2008) ........................................................... 106
Figure 3-48 Specimen assembly inside the testing chamber ...................................................... 107
Figure 3-49 Deformed specimen at the end of flow number test (Specimen ID shown in this
figure is VPPM5) ................................................................................................................. 108
Figure 3-50 Screenshot of the Permanent Deformation test output ............................................ 109
Figure 3-51 Example of the accumulation of permanent strain and fitting of three parameter
model proposed by Archilla et al (2007) for Specimen ID VLPM6 ................................... 110
Figure 3-52 Example of fitting the power model for Specimen ID VLPM6 .............................. 111
Figure 3-53 Comparison of flow number vs. air voids for different types of laboratory produced
HMA mixtures ..................................................................................................................... 113
xi
Figure A-1 Mr vs. deviator stress at different confinement stresses for specimens compacted
using virgin aggregates at 98% of dmax (Specimen ID: HCH1) .......................................... 131
Figure A-4 Mr vs. deviator stress at different confinement stresses for specimens compacted
using virgin aggregates at 98% of dmax (Specimen ID: HCH2) .......................................... 131
Figure A-2 Mr vs. deviator stress at different confinement stresses for specimens compacted
using virgin aggregates at 100% of dmax (Specimen ID: HCH1) ........................................ 132
Figure A-5 Mr vs. deviator stress at different confinement stresses for specimens compacted
using virgin aggregates at 100% of dmax (Specimen ID: HCH2) ........................................ 132
Figure A-3 Mr vs. deviator stress at different confinement stresses for specimens compacted
using virgin aggregates at 102% of dmax (Specimen ID: HCH1) ........................................ 133
Figure A-6 Mr vs. deviator stress at different confinement stresses for specimens compacted
using virgin aggregates at 102% of dmax (Specimen ID: HCH2) ........................................ 133
Figure A-7 Mr vs. deviator stress at different confinement stresses for specimens compacted
using FA mixtures at 98% of dmax (Specimen ID: FA1) ..................................................... 134
Figure A-10 Mr vs. deviator stress at different confinement stresses for specimens compacted
using FA mixtures at 98% of dmax (Specimen ID: FA2) ..................................................... 134
Figure A-8 Mr vs. deviator stress at different confinement stresses for specimens compacted
using FA mixtures at 100% of dmax (Specimen ID: FA1) ................................................... 135
Figure A-11 Mr vs. deviator stress at different confinement stresses for specimens compacted
using FA mixtures at 100% of dmax (Specimen ID: FA2) ................................................... 135
Figure A-9 Mr vs. deviator stress at different confinement stresses for specimens compacted
using FA mixtures at 102% of dmax (Specimen ID: FA1) ................................................... 136
Figure A-12 Mr vs. deviator stress at different confinement stresses for specimens compacted
using FA mixtures at 102% of dmax (Specimen ID: FA2) ................................................... 136
Figure A-13 Mr vs. deviator stress at different confining stresses for specimens compacted using
virgin aggregates at different density levels ........................................................................ 137
Figure B-1 Master Curve for Specimen ID: VPPM1.................................................................. 139
Figure B-2 Master Curve for Specimen ID: VPPM2.................................................................. 140
Figure B-3 Master Curve for Specimen ID: VPPM3.................................................................. 141
Figure B-4 Master Curve for Specimen ID: VPPM4.................................................................. 142
xii
Figure B-5 Master Curve for Specimen ID: VPPM5.................................................................. 143
Figure B-6 Master Curve for Specimen ID: VPPM6.................................................................. 144
Figure B-7 Master Curve for Specimen ID: VLPM1 ................................................................. 145
Figure B-8 Master Curve for Specimen ID: VLPM2 ................................................................. 146
Figure B-9 Master Curve for Specimen ID: VLPM3 ................................................................. 147
Figure B-10 Master Curve for Specimen ID: VLPM3B ............................................................. 148
Figure B-11 Master Curve for Specimen ID: VLPM4 ............................................................... 149
Figure B-12 Master Curve for Specimen ID: VLPM5 ............................................................... 150
Figure B-13 Master Curve for Specimen ID: VLPM6 ............................................................... 151
Figure B-14 Master Curve for Specimen ID: FRACLPM1 ........................................................ 152
Figure B-15 Master Curve for Specimen ID: FRACLPM2 ........................................................ 153
Figure B-16 Master Curve for Specimen ID: FRACLPM3 ........................................................ 154
Figure B-17 Master Curve for Specimen ID: FRACLPM4 ........................................................ 155
Figure B-18 Master Curve for Specimen ID: FRACLPM5 ........................................................ 156
Figure B-19 Master Curve for Specimen ID: FRACLPM6 ........................................................ 157
Figure B-20 Master Curve for Specimen ID: PMALPM1.......................................................... 158
Figure B-21 Master Curve for Specimen ID: PMALPM2.......................................................... 159
Figure B-22 Master Curve for Specimen ID: PMALPM3.......................................................... 160
Figure B-23 Master Curve for Specimen ID: PMALPM4.......................................................... 161
Figure B-24 Master Curve for Specimen ID: PMALPM5.......................................................... 162
Figure B-25 Master Curve for Specimen ID: PMALPM6.......................................................... 163
Figure C-1 Fitting the power model for Specimen ID VPPM1 .................................................. 165
Figure C-2 Fitting the power model for Specimen ID VPPM2 .................................................. 165
Figure C-3 Fitting the power model for Specimen ID VPPM3 .................................................. 166
Figure C-4 Fitting the power model for Specimen ID VPPM4 .................................................. 166
Figure C-5 Fitting the power model for Specimen ID VPPM5 .................................................. 167
Figure C-6 Fitting the power model for Specimen ID VPPM6 .................................................. 167
Figure C-7 Fitting the power model for Specimen ID VLPM1 .................................................. 168
Figure C-8 Fitting the power model for Specimen ID VLPM2 .................................................. 168
Figure C-9 Fitting the power model for Specimen ID VLPM3B ............................................... 169
Figure C-10 Fitting the power model for Specimen ID VLPM4 ................................................ 169
xiii
Figure C-11 Fitting the power model for Specimen ID VLPM5 ................................................ 170
Figure C-12 Fitting the power model for Specimen ID VLPM6 ................................................ 170
Figure C-13 Fitting the power model for Specimen ID PMALPM1 .......................................... 171
Figure C-14 Fitting the power model for Specimen ID PMALPM2 .......................................... 171
Figure C-15 Fitting the power model for Specimen ID PMALPM3 .......................................... 172
Figure C-16 Fitting the power model for Specimen ID PMALPM4 .......................................... 172
Figure C-17 Fitting the power model for Specimen ID PMALPM5 .......................................... 173
Figure C-18 Fitting the power model for Specimen ID PMALPM6 .......................................... 173
Figure C-19 Fitting the power model for Specimen ID FRACLPM1 ........................................ 174
Figure C-20 Fitting the power model for Specimen ID FRACLPM2 ........................................ 174
Figure C-21 Fitting the power model for Specimen ID FRACLPM3 ........................................ 175
Figure C-22 Fitting the power model for Specimen ID FRACLPM4 ........................................ 175
Figure C-23 Fitting the power model for Specimen ID FRACLPM5 ........................................ 176
Figure C-24 Fitting the power model for Specimen ID FRACLPM6 ........................................ 176
xiv
LIST OF TABLES
Table 3-1 Maximum Dry Density and Optimum Moisture Content values ................................. 58
Table 3-2 Mr coefficients calculated using the NCHRP 1-37A model ........................................ 69
Table 3-3 Mr coefficients calculated using the NCHRP 1-37A model ........................................ 72
Table 3-4 Mixing and compaction temperature range for asphalt binders ................................... 78
Table 3-5 Results of theoretical specific gravity .......................................................................... 81
Table 3-6 Characteristics of HMA specimens .............................................................................. 89
Table 3-7 Conditioning time for different testing temperature ..................................................... 91
Table 3-8 Data quality statistics requirements in dynamic modulus test...................................... 92
Table 3-9 Dynamic modulus master curve parameters and shift factors ...................................... 96
Table 3-10 Permanent deformation parameters and Flow Number ............................................ 112
1
CHAPTER 1
INTRODUCTION AND OBJECTIVES
1.1 Introduction
Pavement design is an effort to determine the number and thickness of layers, and
material composition within a pavement structure in order to cater to a given amount of traffic in
a cost-effective way. Several different design procedures are followed by different highway
agencies in the United States. These methods range from the simple empirical methods to the
complex mechanistic-empirical methods. Some of the examples of empirical methods include the
design method followed by the California Department of Transportation (Caltrans) and the 1993
AASHTO pavement design procedure. The Hawaii Department of Transportation (HDOT) uses
the Caltrans procedure to design pavements. The result of a survey conducted by Federal
Highway Administration (FHWA) (FHWA, 2007) is illustrated in Figure 1-1. As can be seen
from the figure, the 1993 AASHTO Guide for Design of Pavement Structures has been the
primary pavement design tool for most highway agencies, which is based on the empirical
equations derived from the AASHO road test performed in the late 1950s near Ottawa, Illinois.
The AASHO road test was limited to: a) one specific geographic location, b) moderate traffic
levels, and c) limited structural conditions and materials typically found in the region. According
to Lekarp, Isacsson, & Dawson (2000a), the empirical design procedures have limitations with
regard to adapting to the growing needs of the transportation system. This has led research
efforts to develop mechanistic design procedures, which analyze the response of materials under
different traffic and environmental conditions. Similar limitations could be attributed to other
empirical procedures such as the HDOT procedure of designing pavements.
2
Figure 1-1 Current Pavement Design Practices in the United States (FHWA, 2007)
The Guide for Mechanistic-Empirical Design of New and Rehabilitated Pavement
Structures and its associated software1 developed through a comprehensive research effort by the
National Cooperative Highway Research Program initiative NCHRP Project 1-37A is a state-of-
the-art pavement design tool that has attempted to overcome the limitations of the empirical
pavement design procedures.
A schematic representation of the Mechanistic-Empirical Pavement Design Guide
(MEPDG) process for flexible pavements is illustrated in Figure 1-2.
1 Hereon referred to as Mechanistic-Empirical Pavement Design Guide (MEPDG)
12%
63%
13%
8% 4%
AASHTO 1972
AASHTO 1993
State Design Procedure
AASHTO/State Design Procedure
Other
3
Figure 1-2 Schematic Representation of MEPDG Process (Coree et al., 2005)
As can be seen in Figure 1-2, there are three major components in the MEPDG: (a) Input
Data, (b) Analysis, and (c) Output. The analysis part of the MEPDG represents the major change
in the way pavement design is performed compared to the HDOT and other empirical
procedures. The mechanistic part of the MEPDG refers to the application of principles of
engineering mechanics to determine pavement responses (stress, strain, and deflection) to wheel
loads and/or climatic effects and the empirical part uses transfer functions to convert the
pavement responses to predict pavement distresses.
An important feature of the MEPDG software is the hierarchical approach with regard to
traffic, material characteristics, and environmental inputs. Three levels of design – Level 1 to
Level 3 – are available for determining the input values.
Level 1 provides site and/or material specific inputs for the segment or project through
direct testing or measurements. This level of input provides more precise and accurate
information compared to the other two levels of design. Level 1 is used when there is a need for
designing pavements that require higher level of reliability. Level 2 input values are typically
determined using correlations with other relatively simpler testing procedures. Level 3 provides
4
the lowest level of accuracy. The input values for level 3 are usually default values from the
MEPDG.
The characterization of pavement construction materials is one of the most important
inputs in designing pavements using the MEPDG. As pointed by Yoder and Witczak (1975), for
any pavement design procedure to be completely rational, three elements must be fully
considered: (1) the theory used to predict the assumed failure or distress parameter, (2) the
evaluation of the materials properties applicable to the selected theory, and (3) the determination
of the relationship between the magnitude of the parameter in question to the performance level
desired. The MEPDG considers the aforementioned elements.
The pavement inputs for the MEPDG is extremely extensive compared to other pavement
design procedures. For an effective and efficient implementation of the MEPDG, it is necessary
to develop a database either through testing of materials or compile information of design inputs
of locally used materials. This research attempts to contribute to the development of database by
testing Hot Mix Asphalt materials and base course materials.
1.2 Problem Statement
First: Construction of new pavements or maintenance and rehabilitation (M&R) of in-service
pavements is an on-going process because pavements deteriorate with passage of time. This fact
leads to two concerns: a) growing demand for construction aggregates and b) increase in amount
of construction waste2. For instance, construction and maintaining a freeway pavement of one
lane-mile can use 7,000 to 12,000 tons of raw materials (The Bridge, 2009). With the production
of construction aggregates estimated to increase from 2.0 billion tons to 2.5 billion tons by 2020
(FHWA, 2004), there is concern about the availability of new aggregates. One alternative to
2 The definition of construction waste is deferred until Section 2.3.
5
address the aforesaid challenges is to recycle pavements and use the waste as a substitute
material in road construction. The process of pavement recycling has proved to be economically
beneficial and environmentally sustainable to building long-lasting roads (Kennedy, Tam, &
Solaimanian, 1998, Saeed, 2008). The reusable material that results from removing and/or
reprocessing asphalt pavements is known as Reclaimed Asphalt Pavement (RAP). Some of these
include its use a substitute for new aggregate in Hot Mix Asphalt (HMA), granular base
(stabilized and otherwise), and subbase. RAP contains asphalt and aggregates, which when
properly crushed and screened can be used in a number of paving applications. Although the
benefits of using RAP have resulted in virtually all states recycling the material (Wilburn &
Goonan, 1998), the percent of RAP in recycled mixtures is kept to relatively low values because
of the inability to accurately characterize binder properties (Al-Qadi, Elseifi, & Carpenter, 2007).
A number of studies have shown performance, economic, and environmental benefits of using
RAP in paving applications, and there is a general agreement that pavements constructed using
RAP have proven to perform well to be used in various applications in building asphalt
pavements (Al-Qadi et al., 2007). One type of material produced by stabilizing RAP is Foamed
Asphalt (FA) base course mixtures.
One of the primary input parameters for base course materials in the MEPDG is the
material’s resilient modulus. Several past research efforts have found that the resilient modulus
of FA mixtures is higher compared to virgin material from those studies (Long and Ventura,
2004, Huan et al., 2010). However, no studies have been performed on FA mixtures to evaluate
its stiffness at different compaction levels. Also, the resilient modulus of base course materials
being one of the input parameters in the pavement design will affect the performance of
pavements. Hence, determining the Mr of a particular type of material at different densities
6
would allow highway agencies to select the minimum level of field compaction required for that
type of material in a pavement design. As a result, a rationale for agreeable levels of pay factors
and penalties could be decided by knowing the achievable, target, and actual densities in the
field. The limited supply of FA mixture that was available was used to evaluate the material’s
resilient modulus property at three different densities. This study also included resilient modulus
testing of virgin aggregates compacted at three densities. This research aims to perform the
comparative analysis and estimate the model parameters which can further be used as inputs in
the MEPDG to compute pavement distress information.
Second: This study is also concerned with the characterization of three types of HMA materials.
The availability of different alternatives to enhance the performance of HMA mixtures has been
available for several decades. The use of modified binder (polymer modified, crumb rubber
modified, and so on) has proven to improve the rutting and fatigue cracking performance of the
HMA mixtures compared to unmodified mixture (Archilla, 2008, ARTS, 2010, Shih et al. Xiao
et al.). Similarly, the addition of fibers such as FORTA fibers to HMA mixture has shown
improved results vis-à-vis resistance to rutting and fatigue cracking (Kaloush et al., 2008). This
study aims to estimate the dynamic modulus parameters, and flow number and permanent
deformation parameters of HMA mixtures. The parameters can be used as input parameters in
the MEPDG to compute and compare pavement distresses.
1.3 Research Objectives
The main objectives of this study are to:
1. Estimate the dynamic modulus and permanent deformation parameters of three types of
laboratory produced and one type of plant produced HMA mixtures. The laboratory
7
produced mixtures include (a) mixes prepared using unmodified binder, (b) mixes
prepared using polymer modified binder, and (c) mixes prepared using unmodified binder
which are blended with fibers.
2. Estimate the resilient modulus parameters of two types of base course materials. The two
types of materials include: (a) virgin aggregates and (b) foamed asphalt (FA) mixtures.
8
CHAPTER 2
LITERATURE REVIEW
2.1 Introduction
This chapter begins with a review of different types of materials characterized in this
study. Section 2.2 discusses the history and technology of FA mixtures and foaming technology.
Next, a brief introduction to polymer modified asphalts and the types of modifier used in this
study are introduced in Sections 2.3 and 2.4. Further, the types of fibers and past research
experience about blending HMA mixtures with fibers is presented in Sections 2.5. Section 2.6
gives a brief introduction to the type of fibers used in this study. Later in Section 2.7 through
Section 2.9, material input parameters and testing protocols for HMA and base course materials
at Level 1 accuracy are briefly described. Finally, the characterization of HMA mixtures using
the permanent deformation test is introduced.
2.2 Foamed Asphalt Mixture
Foamed Asphalt mixture refers to a mixture of pavement construction aggregates and
foamed asphalt. A wide variety of aggregates can be used to produce FA mixtures. However,
Reclaimed Asphalt Pavement (RAP) is typically stabilized using foamed asphalt to produce FA
mixturs. The history and technology of asphalt foaming is explained in the following section.
Foamed asphalt mixtures used in base course layers of pavements have shown a lot of
promise for restoring existing pavements and producing a surface with less cost compared to
using new material (Kendall, Baker, Evans, & Ramanujam, 1999). The use of RAP may reduce
the cost of production of foamed asphalt mixtures, because, firstly, the need to quarry and
9
transport new aggregates is avoided, and secondly, RAP contains binder, thereby reducing the
amount of asphalt required to produce the mix (Muthen, 1998, Raffaelli, 2004).
Saeed, Hall, & Barker (2008) mention that poor performance of granular base materials
contribute to the reduced life and costly maintenance of pavements. Therefore, to achieve an
economical pavement design, the properties of granular materials need to be evaluated
thoroughly.
2.2.1 Asphalt Foaming Technology
Asphalt foaming technology is a process where cold water in a proportion of between 1
and 5% by the mass of asphalt binder is injected together with compressed air into hot asphalt
(140º – 170 ºC) in a specially designed expansion chamber to produce foamed asphalt, as shown
in Figure 2-1.
Figure 2-1 Asphalt Foaming Technology (Construction Equipment, 2005)
Air Water
Foamed
Bitumen
Hot
Bitumen
10
When the injected water comes in contact with hot asphalt, the water vaporizes resulting
in spontaneous foaming, which is trapped in thousands of tiny asphalt bubbles producing foamed
asphalt. The foamed asphalt binder is typically added to aggregates in a proportion of less than
3% by the mass of dry aggregates to form FA mixtures. The tiny asphalt bubbles that are formed
during the mixing process disperse throughout the aggregate by adhering to the finer particles to
form a mastic. Typically, a small quantity of filler (cement or hydrated lime) is added to assist in
dispersing the asphalt and improving the retained strength after exposure to moisture. The
quantity of filler material is usually restricted to 1.0% in order for the mixture to be classified
as asphalt stabilized (TG2, 2009). Chiu & Lewis (2002) suggested that the use of cement content
in excess of 2.0% by mass would result in a negative effect on the fatigue properties of the
stabilized layer.
The possibility of using foamed asphalt as a stabilizing agent was originally conceived by
Prof. Ladis Csanyi in 1957 of the Iowa State University. The process consisted of injecting steam
into hot asphalt. This process was, however, impractical for in situ foaming operations, because
of the need for steam producing equipment such as steam boilers. In 1968, Mobil Australia
acquired the patent rights for Prof. Csanyi’s idea, modified the original process by adding cold
water into hot asphalt in an expansion chamber to produce foam. This process was more practical
and economical to use (TG2 2009).
2.2.2 Factors Affecting Foamed Asphalt Mixtures
The performance of foamed asphalt mixtures are determined based on asphalt and
aggregate properties, mixing moisture conditions, mixing temperature, and curing conditions.
11
2.2.2.1 Asphalt Properties
The foamed asphalt binder is a result of a temporary change in the viscosity of binder by
addition of a small percentage of water along with compressed air to hot asphalt. The viscosity is
greatly reduced allowing an increase in the surface area per unit mass, which allows for a
uniform dispersion of the foamed binder onto the aggregates. The two primary properties that
influence asphalt foaming are: a) Expansion Ratio and b) Half-Life (Muthen, 1998, TG2, 2009,
Wirtgen, 2004).
Expansion Ratio (ER) is a measure of the viscosity of the foam, which determines its
dispersion potential in the mix. Mathematically, it is the ratio of maximum volume of the foam to
the final volume of the binder once the foam is dissipated. Half-Life 21 is a measure of the
stability of the foam, which provides an indication of the rate of its collapse (Muthen, 1998,
TG2, 2009, Wirtgen, 2004). It is the time (in seconds) for the foam to collapse to half of its
maximum volume. Figure 2-2 illustrates a typical relationship between the percentage of
foamant water added and expansion ratio and half-life. The following paragraphs explain the
factors that influence the asphalt foaming properties.
12
Figure 2-2 Relationship Between Foaming Properties
(Redrawn using data from Alakona, 2008)
Foamant Water: It can be seen from Figure 2-2 that increasing the percentage of water injected
into the foaming chamber increasing the expansion ratio. The increase in the ER is because of
the increase in the size of asphalt bubbles when water and air comes in contact with hot asphalt.
The increase in the size of bubbles reduces the film thickness, making it less stable, which results
in reduction in half-life. Adequate foam dispersion for effective stabilization is possible when the
amount of foamant water is selected considering an acceptable trade-off between maximum
expansion ratio and half-life (Muthen, 1998, TG2, 2009, Wirtgen, 2004).
Asphalt Content: Unlike in HMA mixtures, the process of determining optimum asphalt content
for FA mixtures is not straightforward. This is because the FA mixtures are prepared using a
known quantity of asphalt and water. According to Muthen ((1998), “in foamed-asphalt mixes
the optimum bitumen content often cannot be clearly determined as it can in the case of hot-mix
5
5.5
6
6.5
7
7.5
7
8
9
10
11
12
13
14
15
16
17
1 1.5 2 2.5 3 3.5
Hal
f-lif
e (
seco
nd
s)
Exp
ansi
on
Rat
io
% Water (Foamant Water)
Expansion Ratio
Half-life
13
asphalt. The range of binder contents (BC) that can be used is limited by the loss in stability of
the mix at the upper end of the range and by water susceptibility at the lower end. It appears that
one significant parameter is the ratio of binder content to fines content, i.e. the viscosity of the
binder-fines mortar plays a significant role in mix stability”.
Asphalt Grade: Lee (1981) mentions that there was no substantial difference between measured
properties of FA produced using different grades of asphalt. Sakr & Manke (1985) conclude that
viscosity or binder cohesion has relatively lesser effect compared to aggregate interlock in the
stability of foamed asphalt mixes.
Asphalt Temperature: The inverse relationship between temperature and viscosity logically leads
to reduced viscosity and therefore increase in the size of asphalt bubbles when water comes in
contact with hot asphalt. The temperature of asphalt should be above 160° C and less than 195°
C to achieve satisfactory foaming (Wirtgen, 2004, TG2, 2009).
2.2.2.2 Aggregate Properties
Typically, RAP is used as aggregates. However, a wide variety of new aggregates can
also be used to produce foamed asphalt mixtures (Muthen, 1998). Bowering & Martin (1976)
indicate that certain aggregates may require treatment with lime and gradation adjustments for
satisfactory performance of the mix. The type and size of aggregates play an important role in
the performance of FA. The importance of RAP gradation on the performance of FA has been
well documented by several researchers over the last few decades. Csanyi (1957), Bowering et
al. (1984), and Lee (1981), suggested a minimum of 3 percent passing No. 200 sieve (referred to
14
as fines in this research) as a basic requirement for good performance of foamed asphalt mixes.
The Wirgten Cold Recycling manual (2004), Ruckel, Acott, & Bowering (1982), and Kendall et
al. (1999) suggested a minimum of 5 percent passing No. 200 sieve in order for foamed asphalt
to mix with and coat the RAP fines to achieve a good end product. Lee (1981), Kendall et al.
(1999), and Ramanujam & Jones (2000) suggested an upper limit of 35-40, 15, and 20 percent
respectively. The Technical Guideline on Bituminous Stabilised Materials published by the
Asphalt Academy (TG, 2009) mentions the Optimum Mixing Moisture Content (OMMC) varies
with the gradation and, in particular, the size of fraction smaller than 0.075 mm. Therefore, the
guide suggests an ideal range of 6 to 10% of mass of material passing No. 200 sieve to achieve
desirable density. Akeroyd & Hicks (1988) suggested three aggregate grading zones (as shown in
Figure 2-3) to select the size of aggregates to enable them to perform satisfactorily in the mix.
Zone A points to the desired grading zone, while Zone B and Zone C refers to the gradation
being either too fine or too coarse respectively, and therefore need to be stabilized by either
adding coarse or fine material correspondingly.
15
Figure 2-3 Desired Aggregate Grading Zones for Foamed Asphalt
(Redrawn after Akeroyd & Hicks, 1988)
2.2.2.3 Mixing Moisture Content
The mixing and compacting moisture content is an important consideration in the design
criteria of foamed asphalt mixes. During the mixing stage, moisture helps to break up
agglomeration of aggregates so that they are uniformly distributed throughout the mix. Unlike
new aggregates, where the Optimum Moisture Content (OMC) is determined using a standard
test procedure, the functional nature of moisture in FA during mixing and compaction stages has
resulted in a different rationale about the procedure to determine the optimum moisture content.
Brennen, Tia, Altschaeffl, & Wood (1983) after studying the consequences of varying
moisture before mixing with the foamed binder concluded that too little moisture reduces the
dispersion of the foam, and therefore workability and compaction of the mix, while too much
moisture increases the curing time and reduces the strength and density of the mix. Chiu (2002)
0.0
75
0.1
50
0.3
00
0.6
00
1.1
8
2.3
6
4.7
5
6.7
9.5
13.2
19.5
26.5
32.5 53
0
10
20
30
40
50
60
70
80
90
100
Sieve Size (mm)
Perc
en
t P
assin
g
Zone A
Zone C
Zone B
16
used the AASHTO T180 procedure to determine the optimum moisture content. However, 90%
of OMC was used during the mixing process. Ruckel et al. (1982) and Wirtgen (2004) also
recommend that OMC be derived from the moisture-density relationship using AASHTO T180
procedure. Lee (1981) and Bissada (1987) found that the optimum mixing moisture content
occurred between 65% and 85% of the modified AASHTO T180 procedure.
Because of the functional influence of moisture on foamed asphalt mixes, some
researchers have proposed to specifically address the issue of determining optimum moisture
content during mixing and compaction separately.
Castedo-Franco, Beaudoin, Wood, & Altschaeffl (1982) considered the idea of optimum
fluid content, which is the sum of asphalt content and moisture content, approximately equal to
the aggregate’s OMC as determined by ASTM D 698 to provide the best compaction.
A relationship considering percentage of fines and OMC was used by Sakr & Manke
(1985), as shown in the following equation.
BCPFOMCMMC 39.04.048.192.8 (3.20)
Where:
MMC = Compaction Moisture Content
OMC = Optimum Moisture Content as determined by AASHTO T180 specification
PC = Percentage of fines of the aggregate passing the #200 sieve
BC = Bitumen (Asphalt) Content, percentage by dry weight of aggregates
It was found that there was no significant difference in mix properties using the OMC
(which is 10% to 20% higher than MMC) and compacting moisture content (Sakr & Manke,
17
1985). Therefore, to prevent the waiting time for the mix to reach compaction moisture content,
it was suggested MMC be used for both mixing and compaction.
2.2.2.4 Curing Conditions
The effect of curing or removing moisture from FA has been extensively reported over
the years by several researchers. The Wirtgen (2004) manual suggests two separate curing
durations based on the size of specimen. For 100 mm diameter specimens, it is suggested to cure
samples by placing them on a smooth flat tray in a forced-draft oven for 72 hours at 40° C. In
case of 150 mm diameter specimens, the manual recommends each specimen be cured separately
in a sealed plastic bag at 40° C for 48 hours. Bowering (1970) reported the moisture content in
FA samples to reach between 0 and 4 percent by curing the samples in an oven at 60° C for 3
days. It 1976 Bowering & Martin concluded that there was little or no effect on the performance
of FA at temperatures ranging from 23° C to 60° C. However, Muthen (1998) reports the
concerns of binder softening and aging at 60° C, which might change the dispersion
characteristics during curing. Lee (1981), using laboratory results, also concluded that curing had
no impact on the strength gained by foamed asphalt mixes. Contradicting this argument, Ruckel
et al. (1982) reported there was effect of curing on FA’s strength. Three different curing times: a)
1 day in mold b) 1 day in mould + 1 day at 40° C, and c) 1 day in mould + 3 days at 40° C to
simulate short, intermediate, and long term field curing effects respectively were also suggested.
From the past research it can be observed that there is no consensus about both the procedure of
curing FA samples in the laboratory. Jenkins (2000) supports this view stating “it is difficult to
ascertain the type and level of laboratory curing required to simulate field curing for a given
material in a specific environment”.
18
2.2.2.5 Mixing Temperature
The temperature of aggregates influences the determination of foamant water from the
Expansion Ratio/Half-Life chart (TG2, 2009). Bowering & Martin (1976) found the optimum
mixing temperature of aggregates for FA lies between 13° C to 23° C, depending on the
aggregate type, and temperatures below this resulted in poor quality of mixes.
2.3 Polymer Modification
The modification of unmodified binder to enhance its properties has been in practice for
over 5 decades (Asphalt Institute, 2007). In a survey result summarized in the Asphalt Institute
(2007), it has been noted that the reason for using Polymer Modified Asphalt (PMA) was to
increase the mixture’s resistance to rutting. The use of polymer modified asphalt in producing
HMA mixtures has been reported to reduce pavement cracking caused by thermal stresses and
decrease the rate of accumulation of permanent deformation (Dwyer and Betts, 2011, Bouldin
and Collins, 1992; Lu and Isacsson, 1999). A comprehensive study by Archilla (2008)
comparing the dynamic modulus and permanent deformation of HMA mixtures prepared using
unmodified and polymer modified binder has shown that the mixtures prepared using polymer
modified binder performed better compared to the unmodified mixes. The results from Archilla
(2008) show that the potential benefits of using polymer in modifying unmodified asphalt are
that it stiffens the binder at high temperatures without affecting the stiffness of asphalt at low
temperatures. This property enhancement is particularly beneficial because the resulting
modified binder is resistant to permanent deformation at high temperatures.
19
2.4 Polymer Modifier Used in this Study
The polymer modifier used in this study is Elvaloy® RET, which is obtained in the form
of pellets as illustrated in Figure 2-4. Elvaloy® RET is produced by DuPont (DuPont 2008) and
is a reactive elastomeric terpolymer (hence the RET in the name). It is claimed to be effective
when used with a wide range of asphalts, at proportion levels as low as 1−2% by weight of
asphalt. In this study, the unmodified asphalt binder is modified using 1% by weight of asphalt.
Figure 2-4 Elvaloy RET Pellets (Photo courtesy: Archilla (2008))
2.5 Fiber Reinforced Asphalt Concrete Mixtures
Several studies have shown that blending fibers with HMA mixtures have improved the
performance of control mixtures against rutting and fatigue cracking (Bueno et al, 2003, Lee et
al, 2005, Kaloush, 2008). The study performed by Kaloush et al. (2008) is of interest because the
same fibers are used in this study. Kaloush et al. (2008) studied the effect of FORTA fibers
(1lb/ton and 2lb/ton by weight of mix) on the performance of HMA mixtures and compared the
test results with HMA mixtures prepared using unmodified binder. Results from their study have
shown a significant increase in the flow number compared to control mixes, and a higher fatigue
20
life compared to control mixes. It was found that FORTA fibers at 1lb/ton showed the best
performance with regard to accumulation of permanent strain in flow number test and higher
moduli values at high temperatures in dynamic modulus test. Specifically, the FN for 1lb/ton mix
was 115 times higher compared to the control mix.
2.6 Fibers Used in this Study
FORTA fibers have been used in HMA mixtures to improve the performance of the blend
against rutting and fatigue cracking. The fibers comprise of polypropylene and aramid fibers in
different proportions depending on the type of blend. The HMA blend of FORTA fibers are used
in this study. Figure 2-5 shows the fibers in its manufactured state.
Figure 2-5 FORTA fibers (HMA blend)
21
2.7 MEPDG Material Input Parameters
The material input parameters for HMA material include the time-temperature dependent
dynamic modulus (|E*|) and Poisson’s ratio (). The general input parameters include layer
thickness which is used to predict pavement responses. The screenshot of the MEPDG software
for HMA material at Level 1 accuracy is shown in Figure 2-6. Further explanation about
dynamic modulus is presented in Section 2.8.
In case of base course materials, the material input parameters required to compute
pavement response are resilient modulus (Mr) and Poisson’s ratio (. Both these parameters are
used for quantifying stress dependent stiffness of base course materials under moving loads. The
screenshot of the MEPDG software for HMA material at Level 1 is shown in Figure 2-7. Further
explanation about resilient modulus is presented in Section 2.8.
22
Figure 2-6 Asphalt Material Properties – Asphalt Mix Input Values for Level 1 Analysis
23
Figure 2-7 Asphalt Material Properties – Asphalt Mix Input Values for Level 1 Analysis
2.8 Dynamic Modulus |E*|
Dynamic modulus is a property necessary to accurately predict the in-situ pavement
responses to varying speeds and temperatures throughout the pavement’s cross-section. The
primary stiffness property of HMA materials used in the Guide for Mechanistic-Empirical
Design of New and Rehabilitated Pavement Structures is the dynamic modulus.
The effects of temperature and frequency under continuous sinusoidal loading for linear
viscoelastic materials such as HMA mixtures is defined by its dynamic modulus (|E*|).
24
According to NCHRP Report 547, dynamic modulus is defined as “the ratio of the amplitude of
the sinusoidal stress (at any given time, t, and angular load frequency, ω), σ = σ0 sin(ωt), and the
amplitude of the sinusoidal strain ε = ε0 sin(ωt −φ), at the same time and frequency, that results
in a steady-state response”. A graphical illustration of the stress and strain versus time in a
dynamic modulus test is presented in Figure 2-8.
(2.1)
Where σ = stress, = strain, Φ = phase angle, degrees, σo = peak (maximum) stress, = peak
(maximum) strain, t = time, seconds
Figure 2-8 Typical Stress-Strain curve obtained during dynamic modulus testing of viscoelastic
materials
Mathematically, the dynamic modulus is defined as the norm value of complex modulus.
It can be expressed as:
(2.2)
σo sin(ωt)
εo sin(ωt −φ)
φ/ω
εo σo
25
The phase angle (ϕ) is used to describe the viscous properties of asphalt materials. In
Equation 2.1, the value of ϕ = 0 for purely elastic material and ϕ = 90° for purely viscous
material. HMA material exhibits more of elastic behavior at low temperatures and high
frequencies, and more of viscous behavior at high temperatures and low frequencies. In general,
the dynamic modulus of HMA is a function of temperature, rate of loading, age, and mixture
characteristics such as asphalt binder stiffness, aggregate gradation, asphalt binder content, and
air voids.
The dynamic modulus values at different temperatures and frequencies are required as
input parameters in the MEPDG design process. To determine the |E*| values at different
temperatures and frequencies, the test is performed using either the AASHTO TP62 or AASHTO
TP79 procedure. The difference between the two test procedures is that the AASHTO TP62
procedure was to test HMA specimens for dynamic modulus. On the other hand, the AASHTO
TP79 procedure describes test methods for measuring the dynamic modulus and flow number of
HMA mixes. The test consists of subjecting a cylindrical HMA specimen to a uniaxially applied
sinusoidal stress pattern while measuring the deformation. The test can be performed with or
without the effect of confining pressure. Although the test using AASHTO TP62 procedure
provides the dynamic modulus values at different temperatures and frequencies, the |E*| values
required for a pavement design at temperatures and frequencies other than the tested values need
to be determined. Therefore, a system to interpolate these values is required for predicting
dynamic modulus at any combination of temperature and loading. The interpolation is achieved
using the time-temperature superposition principle, which allows horizontal shifting of test
points at a given temperature and frequency onto a “Master Curve” constructed at a reference
26
temperature. In the MEPDG, the reference temperature used is 70 °F. Figure 2-9 and Figure 2-10
illustrate the use of time-temperature superposition principle to construct a Master Curve.
Figure 2-9 Dynamic modulus test data (Archilla, 2008)
10,000
100,000
1,000,000
10,000,000
0.00001 0.0001 0.001 0.01 0.1 1 10 100 1000 10000 100000
Time of loading (s)
|E*|
(p
si)
129.2F
113.0F
100.4F
69.8F
39.9F
27
Figure 2-10 Master Curve constructed at a reference temperature of 69.8 °F (Archilla, 2008)
Figure 2-9 illustrates the results from a dynamic modulus test on an HMA specimen for
temperatures ranging from 40 ºF (4.4ºC) to 104ºF (40ºC) and time of loading ranging from 0.04
seconds to 10 seconds. The data presented in the figure indicate the influence of temperature and
frequency on the stiffness of the mix, which was explained earlier. The Master Curve developed
using the time-temperature superposition principle is illustrated in Figure 2-10. The master curve
is useful because the dynamic modulus values at any combination of temperature and frequency
can be predicted with it. The amount of shifting the original test data onto the Master Curve and
its sign are temperature dependent. The shift factor is formally defined as:
(2.3)
Where
10,000
100,000
1,000,000
10,000,000
0.00001 0.0001 0.001 0.01 0.1 1 10 100 1000 10000 100000
Time of loading (s)
|E*|
(p
si)
129.2F
113.0F
100.4F
69.8F
39.9F
Master Curve
28
t = time of loading at a given temperature of interest,
tr = time of loading at the reference temperature (i.e., after shifting),
f = frequency of loading at a given temperature of interest (1/t), and
fr = frequency of loading at the reference temperature (1/tr).
By taking the logarithm of equation (2.3), the following equation is obtained:
(2.4)
Once all the data points at different frequencies are shifted to a reference temperature, the
following equation used in the MEPDG is used to construct the Master Curve.
(2.5)
Where , , , and are the model parameters
According to the MEPDG CHRP 1-37A, 2004), the parameters and depend on the
aggregate gradation, asphalt binder content, and air voids. The parameters and , which control
the shape of the master curve, depend on the characteristics of asphalt binder and the magnitude
of and
One of the equations that have been used to model the shift factor as a function of
temperature is:
(2.6)
Where A, B, C are model parameters and Ti is the temperature.
29
While Equation (2.5) describes the time dependency of the modulus at the reference
temperature, the shift factors describe the temperature dependency of the modulus.
2.9 Resilient Modulus
The deformation behavior of base course materials under traffic-type loading is
characterized by recoverable (resilient) strain and permanent (plastic) strain , which is
illustrated in Figure 2-11. According to Huang (1993), if a small load compared to the strength of
the material is applied a number of times, the recoverable deformation is nearly completely
recoverable and the material can be considered elastic, and the modulus based on the recoverable
strain under repeated loads is called the resilient modulus.
Figure 2-11 Typical stress-strain behavior of unbound granular materials subjected to traffic-type
loading
Resilient modulus is a measure of the stiffness of a material. In other words, it is the
elastic modulus (E) of a material for rapidly applied loads like those experienced by pavements.
Axial Strain (in./in.)
Dev
iato
r S
tres
s (σ
d =
σ1 –
σ3)
Total Strain (εt)
Resilient Strain (εr)
Plastic
Strain
(εp)
εt = εr + εp
30
Typically, the Mr of a material is used to characterize base, subbase, and subgrade materials for
the purpose of pavement design and evaluation. The resilient modulus of a material provides a
basic relationship between stress and deformation of pavement materials for the structural
analysis of layered pavements. Mathematically, it is calculated using the Equation 2.7.
r
drM
(2.7)
Where:
Mr = Resilient Modulus of the material
d = 31 = Deviator Stress
r = Resilient (recoverable) Strain
1 = Axial Stress
3 = Confining Stress
2.9.1 Factors Affecting Mr of New Unbound Granular Materials
Several research efforts to characterize resilient modulus of granular materials show a
nonlinear and time-dependent elastoplastic response under repeated loads, simulating the actual
traffic. According to Li and Selig (1994), the resilient modulus behavior is affected by three
factors. These factors are: soil3 physical state, state of stress, and structure/type of material. In
case of visco-elastic materials such as foamed asphalt mixes, in addition to the state of stress, Mr
is influenced by loading rate and temperature (Muthen, 1998).
3 To be consistent in the terminology used in this research, ‘soil’ is hereafter referred to as ‘aggregate’.
31
The models developed to predict resilient modulus should include all the significant
factors for higher reliability. The following paragraphs give a background to the factors affecting
resilient modulus of unbound granular material used in pavement construction. Because of its
relevance to this research, particular emphasis is given to the physical state and state of stress of
UGMs.
2.9.1.1 Aggregate Physical State
The physical state of aggregates is related to four factors: moisture content )(w , dry
density )( dry , degree of saturation S , and temperature.
Moisture Content and Degree of Saturation: Moisture content has two separate effects on the
material (NCHRP 1-37A, 2004): a) decrease in effective stress and therefore stiffness because of
pore-water pressure and b) destruction of cementation between particles. It has been reported by
(Lekarp, Isacsson, & Dawson, 2000b) that higher moisture content lowers the stiffness of
unbound granular material. Several field and laboratory studies performed to address the issue of
moisture changes on resilient modulus have led to conclusion that moisture content or degree of
saturation (a parameter defined by moisture content) affects the resilient modulus of unbound
granular materials (Hicks & Monosmith, 1971, Heydinger, Xie, Randolph, & Gupta, 1996).
The relationship between the first three physical state parameters is shown in Equation
2.8 and Equation 2.9.
1dry
wsG
wS
(2.8)
32
e
wGS s
(2.9)
Where:
S = degree of saturation (%)
Gs = Specific gravity of the aggregate
w = moisture content (%)
w = unit weight of water
dry = dry unit weight
e = void ratio
Density: Density is a result of volume change. Therefore, void ratio may be used as an
alternative for dry density (NCHRP 1-37A, 2004). This argument was further supported by
Archilla et al (2007), who reported better correlation between Mr and void ratio as opposed to
density. It is known that increasing density results in improving the stiffness of unbound granular
material under static loading. However, the influence of density on stiffness has been less
thoroughly researched and hence remains rather ambiguous (Lekarp et al, 2000b).
Temperature: The effect of temperature becomes important in predicting rM of frozen materials.
For thawed materials, it has no significant influence (NCHRP 1-37A, 2004). Unlike new
aggregates, foamed asphalt mixes being visco-elastic are influenced by temperature. The
performance properties of FA were superior compared to hot-mix asphalt mixes at temperatures
higher than 30º C (Muthen, 1998). Nataatmadja (2002) concluded a 30-44% decrease in stiffness
when the temperature increased from 10º C to 40º C. The temperature sensitivity of resilient
33
modulus between foamed asphalt and hot-mix asphalt mixes was studied by Saleh (2006). It was
found from the study, which was conducted at 10º C, 15º C, and 25º C, there was higher decrease
in Mr of HMA at 25C, while foamed asphalt mixes maintained high resilient modulus value at
that temperature. However, the indirect tensile test procedure was used to determine the Mr
values. In a laboratory concluded study, Fu & Harvey (2007) investigated effect of temperature
on foamed asphalt mixes. It was reported that the bulk stress dominated the effects of deviator
stress (or octahedral stress), and is largely independent of temperature. The study also observed
interaction between deviator stress and temperature. It was concluded that resilient modulus of
FA depends on temperature. Kim, Lee, & Heitzman (2008) concluded from the dynamic
modulus test results performed on RAP mixed with foamed asphalt between 1 and 3% at 4.4º C
that coarser RAP materials with small amount of residual asphalt exhibited smaller dynamic
values. However, it was found that finer RAP materials with higher amounts of harder binder
amount at 37.8º C exhibited higher modulus values.
2.9.1.2 State of Stress
The importance of state of stress has been reported since the 1960s. It has been agreed
without doubt that stress level has the most significant impact on the resilient modulus of
unbound granular materials (Lekarp et al., 2000b). The degree of influence that Bulk Stress
and Octahedral Stress oct have on the resilient modulus has been historically reported by
several researchers (Monismith, Seed, Mitry, & Chan, 1967, Uzan, 1985, Lekarp et al., 2000b).
Figure 2-12 illustrates the stresses applied on a specimen in a triaxial test. As shown in the
Figure, 1 is the major principal stress, 2 and 3 are intermediate and minor principal stresses
34
respectively, and is the Shear Stress. The Bulk Stress (Equation 2.10) and Octahedral Stress
(Equation 2.11) are calculated using major and minor principal stresses.
Bulk Stress = 321 (2.10)
Octahedral Stress oct = 2
32
2
31
2
21 )()()(3
1 (2.11)
Figure 2-12 Stresses Applied in a Triaxial Test
(Redrawn after NCHRP, 1997)
The increase in confining pressure and sum of principal stresses results in increase in the
resilient modulus of the material. Particularly, the effect of confining stress has been found to
have more influence compared to deviator or shear stress on the material stiffness (Lekarp et al.,
2000b).
3321 3 d
Total Axial Stress, 1
(Major Principal Stress)
31 d
(Deviator Stress)
3
32
3 = Confining Pressure
(Minor Principal Stress)
Shear Stress = = 0
35
2.9.1.3 Structure/Type of Material
The structure/type of material is related to four factors that have a bearing on the stiffness
of unbound granular material. The four factors are: compaction method, gradation, particle
shape, and nature of bonds between particles and their sensitivity to moisture.
Compaction Method: The resilient modulus is directly related to the compaction effort, which
means increase in compaction increases stiffness. The increase in stiffness varies with different
materials and the moisture content at which the samples are compacted (Nazarian, Pezo, &
Picornell, 1996, Pezo, Claros, Hudson, & Stokoe II, 1992).
Gradation: The stiffness of material, to some extent, is reported to be influenced by the
gradation of aggregates. Hicks & Monismith (1971) observed some reduction in resilient
modulus with increase in fines. However, Muthen (1998) states increase in resilient modulus
with increase in fines in foamed asphalt mixtures. Saleh (2006), using results from a laboratory
study, concluded that coarse gradations resulted in higher modulus compared to finer gradations.
Particle Shape: Several researchers have reported that crushed material having angular to
subangular shaped particles result in higher resilient modulus compared to uncrushed aggregates
(Hicks & Monismith, 1971, Barksdale & Itani, 1989, Heydinger et al., 1996).
As the properties of materials continuously keep changing due to the effects of chemical
forces, physical forces, climatic variations, and onset of fracture or deformation (NCHRP 1-37A,
2004), a good understanding of the deformational behavior of pavement construction materials
36
under varying traffic and climatic conditions is a prerequisite in mechanistic approach to design
pavements.
2.9.2 Resilient Modulus Models for New Unbound Granular Material
As explained in the previous section, there are several factors that affect the resilient
modulus of unbound granular materials. Of all the factors, the effect of stress is recognized as the
most important factor. As a result, constitutive models including the effects of state of stress
have been proposed by many researchers over the years. The Mr models computed based on state
of stress can be basically divided into three categories.
The first category is expressing the resilient modulus as a function of minor principal
stress or sum of principal stresses. Dunlap (1963) proposed a model in which confining stress
)( 3 was used as the independent variable. Seed, Mitry, Monismith, & Chan, (1967) formulated
a model (commonly known as the K-θ model) considering bulk stress (θ) as the stress attribute.
Equations 2.12 and 2.13 present the Dunlap (1963) and Seed et al. (1967) models respectively.
2
31
k
a
arp
pkM
(2.12)
2
1
k
a
arp
pkM
(2.13)
Where 21,kk = regression parameters, ap = atmospheric pressure, 3 = minor principal or
confining stress, = bulk stress
37
The second category of models uses only shear stress (expressed in terms of deviator
stress) to predict resilient modulus. Moosazadeh & Witczak (1981) and Pezo, Kim, Stokoe, &
Hudson, (1992) used deviator stress in a power model (Equation 2.14).
2
1
k
dr kM (2.14)
Where:
21,kk = regression parameters
d = deviator stress
The simplicity of K model has made it extremely useful in computing the stiffness of
granular materials. However, May and Witczak (1981) noted the field resilient modulus is not
only influenced by bulk stress as suggested in K model, but also by shear or deviator stress.
Since then, several researchers have proposed the third category of models known as the three-
parameter models, which includes the effects of both confining stress (expressed in terms of
bulk, minor principal, and octahedral stress ]3[ oct ) and shear stress (expressed in terms of
deviator stress or octahedral shear stress ][ oct ).
The general form of a three-parameter model is as shown in Equation 2.15 (Ooi, Archilla,
& Sandefur, 2004).
32 )]([)]([1
KK
ar sgcfpKM (2.15)
Where:
)(cf = function of confinement
38
)(sg = function of shear
321 ,, KKK = regression constants
The deficiency of not considering shear stress effect in the K model was addressed
by Uzan (1985), who modified it by including bulk stress and deviator stress. The effect of shear
stress is captured using deviator stress, which is directly related to maximum shear stress )( max
applied to the specimen (i.e., 2max d ).
Pezo (1993) found it was necessary to include deviator stress in the analysis. However,
the parameters of the K model were considered statistically not significant since deviator
stress is hidden in the prediction variable, bulk stress. This problem was overcome by replacing
bulk stress with confining stress in the Uzan (1985) model.
The Uzan (1985) and Pezo (1993) equations are shown in Equation 2.16 and 2.17
respectively.
32
1
K
a
d
K
a
arpp
pKM
(2.16)
32
31
K
a
d
K
a
arpp
pKM
(2.17)
Where:
ap = atmospheric pressure
d = 31 = deviator stress
3 = confining or minor principal stress
39
Witczak and Uzan (1988) modified Equation 2.17 by replacing the deviator stress with
octahedral shear stress )( oct (calculated using Equation 2.11) because it considers stresses in all
three orthogonal directions. The modified model is shown in Equation 2.18.
32
1
K
a
oct
K
a
arpp
pKM
(2.18)
There are two limitations in Uzan (1985), Witczak and Uzan (1988), and Pezo (1993)
models according to Ni, Hopkins, Sun, & Beckham (2002). Firstly, these three models predict
0rM when 03 K and rM when 03 K . Secondly, when there is no confinement
(i.e., 0321 ), rM is predicted to be zero. These two limitations were overcome by Ni
et al. (2002) using the following equation.
32
11 31
K
a
d
K
a
arpp
pKM
(2.19)
Ooi et al. (2004) found the following two models fit the data better compared to the
previous models.
32
111
K
a
d
K
a
arpp
pKM
(2.20)
32
111
K
a
oct
K
a
arpp
pKM
(2.21)
40
The Mechanistic-Empirical Pavement Design Guide (NCHRP 1-37A, 2004) recommends
the use of a new model (Equation 2.22) to predict the variations of rM with changes in degree of
saturation.
ropt
SSKEXP
aba
r MM opts )).((110
(2.22)
41
Where:
rM = Resilient Modulus at degree of saturation S (in decimal)
roptM = Resilient Modulus at maximum dry density and optimum moisture content
optS = Degree of saturation at maxd and OMC (in decimal)
sK = Material constant which can be obtained by regression
a = minimum of )(log roptr MM
b = maximum of )(log roptr MM
= location parameter – obtained as a function of a and b by imposing the condition of a zero
intercept; )ln( ab meaning the ratio of )(log roptr MM = 1 at optimum
optSS = Variation in degree of saturation (in decimal)
According to the MEPDG, roptM is calculated using the following equation.
32
11
K
a
oct
K
a
aroptpp
pkM
(2.23)
Where:
321 ,, KKk = regression constants
Assuming constants K2 and K3 are independent of water content or degree of saturation,
substituting roptM from Equation 2.23 in Equation 2.22 gives the following two formulations.
32
110 1
)).((1
K
a
oct
K
a
a
SSKEXP
aba
rpp
pkM opts
(2.24)
42
Or
32
11
K
a
oct
K
a
arpp
pKM
(2.25)
Where:
1
)).((1
1 10 kK opts SSKEXP
aba
Hence, K1 is a function of degree of saturation
2.9.3 Recent Studies on Mr of Foamed Asphalt Mixes
Numerous laboratory studies have been conducted to determine the resilient modulus of
FA. Some of the recent ones are presented below. When available, the Mr values from different
studies are presented. The importance of presenting the Mr values is described in section 2.9.7.1.
Resilient behavior of foamed asphalt mixtures was investigated using the triaxial set up
by Jenkins (2000). Foamed asphalt stabilized material was compacted by adding “sufficient
material” in the gyratory compactor to produce 100 mm high specimens after a certain number of
gyrations. Three such samples were place on top of one another without tack coat or any
adhesives to achieve a height of 300 mm required for triaxial testing. Compacted specimens were
cured using different procedures simulating an initial cure equivalent to early trafficking
conditions and medium-term cure for a moderate climate. Testing was performed at 25º C. It was
observed that the behavior of FA without cement resembled that of granular material, i.e. stress
dependent. The stress dependent behavior was found to be less evident or insignificant with a)
the addition of cement in the mix, b) foamed asphalt contents reaching 4% or higher, and c)
specimens tested without conditioning cycles.
43
Long and Ventura (2004) studied the stiffness behavior of FA produced using different
foamed asphalt contents on laboratory compacted specimens. Specimens (150 mm height and
300 mm diameter) were compacted in usually 3 lifts on the vibratory compaction table to
selected levels of density. Because it was difficult to achieve high densities, specimens were
sometimes compacted with 4 lifts with improved tamping on each lift. The compacted samples
were cured at ambient temperature for 28 days in the laboratory. Plastic strain triaxial tests (not
resilient modulus dynamic triaxial tests) were performed on specimens to determine the Mr. The
plastic strain dynamic triaxial test performed to determine the permanent deformation behavior
was used to calculate the Mr of the mixes. The range of resilient modulus values is presented in
Figure 2-13. It was observed from the figure that addition of foamed asphalt to the parent
material resulted in slight reduction in the Mr of the mixture compared to that of the parent
material. The addition of cement to the foamed asphalt stabilized mixture shows increase in Mr.
Figure 2-13 Range of resilient moduli values (Long and Ventura 2004).
Nataatmadja (2001) tested indirect tensile modulus of foamed asphalt specimens prepared
using varying asphalt contents and compacted with 50 and 75 blows per face using Marshall
Res
ilie
nt
Mod
ulu
s
44
compaction and gyratory compaction with different curing types and time. Each specimen was
tested under three different curing conditions: a) immediately after compaction, b) after oven
curing, and c) after soaking. The magnitude of modulus values for specimens cured at 60ºC for 3
days, 40ºC for 3 days, and at the end of 28 days at ambient (25ºC) temperature are in the order of
around 15,000 Mpa, 6,000 Mpa, and 8,000 Mpa respectively. The Mr value of the air-cured
specimen at the end of three days was around 4,000 Mpa, which is because the specimens are
more susceptible to moisture resulting in relatively low modulus as compared with the other two
methods. Test results for samples tested immediately after compaction have shown highest
resilient modulus corresponding to about 2.2% of asphalt content. The gyratory specimens,
however, seemed less sensitive to asphalt content variation. It was also seen that the modulus
values for specimens compacted with 75 blows were lower compared to the ones compacted
using 50 blows.
Chiu and Huang (2010) performed Mr testing of foamed asphalt stabilized mixes using
Indirect Tensile Stiffness Modulus (ITSM) test. The specimens were cured for 72 hours at 40 ºC.
Resilient modulus test results on the four mix types (in the order presented in the table) was
found to be 7027, 10489, 5943, and 8028 Mpa respectively.
45
Saleh (2004b) investigated the effect of asphalt source and grade and the type of fines on
the Mr of FA. Two groups of aggregates were used to produce the foamed asphalt mixtures. Fly
ash and cement was used to adjust the fine fraction of the aggregates in order for the gradation to
comply with the midpoint of the “ideal” zone, which is illustrated in Figure 3. The first group
was produced using aggregates passing 20mm, fly ash, and 2% cement, while the second group
was identical to the first, except that no cement was used. Both mixes were produced using OMC
and 3.5% asphalt content. All specimens were cured for 7 days at room temperature (19°C),
except that the second group of specimens was further oven-dried. Resilient modulus testing was
performed using the repeated load ITSM test at room temperature. It was found from the test
results that the modulus values were comparable with or in excess of that of asphalt concrete.
The investigation also revealed that addition of 2% cement had a significant effect on the value
of Mr.
Fu & Harvey (2007) investigated the potential interaction between temperature sensitivity
and stress states on foam asphalt mix stiffness using a cyclic triaxial test. No active filler was
used to produce the mixes, so the effects of foamed asphalt as the only stabilizer could be
captured. Different combinations of confining pressure and deviator stress at relatively small
temperature variation (between 10º C and 22º C) for different specimens were tested in a
chamber with no temperature control. It was found that Mr of FA was influenced by both stress
state and temperature. The study proposed a modified model (Equation 2.26), based on Witczak
and Uzan (1988), to predict resilient modulus of unbound granular material.
(2.26)
Tk
oct
oct
Tk
oct TMrTMr
54
00
0,,
46
Where:
),,( octr TM = Resilient modulus of foamed asphalt at temperature T stress state ),( oct
In a triaxial test, 3/)23(0 octp and 23 octd
)(0 TMr = ),,( 00 octr TM
00 , oct = Bulk stress and octahedral shear stress, respectively, for a reference stress state where
0p = 103.4 and 02pd
)(),( 54 TkTk = Material and temperature dependent constants
Huan et al. (2010) determined the resilient modulus on foamed asphalt mixtures using the
repeated load triaxial. The aggregate mixture consisted of 75% Crushed Rock Base and 25%
Crushed Limestone, treated with 1% hydrated lime. The specimens were compacted at 0%, 3%,
and 5% foamed asphalt content. The results of the test show the mixture with 0% asphalt content
had the highest Mr value, between 235 and 570 Mpa, compared to Mr of mixes stabilized with
3% and 5% foamed asphalt.
2.9.3.1 Discussion
A number of studies have evaluated the resilient modulus of foamed asphalt mixtures
using different variables. However, none of the studies have evaluated the influence of density
on the Mr of the FA material.
It can be seen that, depending on the variation in the factors affecting the Mr of FA, the
range of resilient modulus values are between 235 Mpa and about 15000 Mpa. The range of
values seems to be unrealistically large. The higher end of the stiffness values are closer to the
47
stiffness values that is generally exhibited by HMA mixtures. Further investigation to have more
confidence in the range of stiffness values for FA mixtures seems warranted.
Of all the past research efforts presented in this review, three studies (Saleh 2004,
Nataatmadja 2001, Chiu and Huang 2010) use ITSM test to measure resilient modulus. It is
known that, among several factors that influence the resilient modulus, the stress level has been
found to show the most significant impact on the resilient properties of granular materials
(Lekarp et al. 2000). Furthermore, the effect of bulk stress on weakly bonded materials such as
FA has been found to be fairly sensitive (Fu and Harvey 2007). Since ITSM test protocol neither
applies confinement to the specimen nor can control stress state of the specimen, the measured
stiffness and the actual stiffness of the material in all three studies may not be the identical.
2.10 Repeated Load Axial Test (RALT)
The result of repeated loading on the pavement, which accumulates over time, causes
permanent deformation or rutting. As defined by Mallick and El-Korchi (2009):
“the one-dimensional densification-consolidation rutting, resulting from a decrease
in air voids, occurs with volume change and is vertical deformation only (primary rutting),
whereas the two-dimensional rutting is caused by shear failure and is accompanied by both
vertical and lateral movement of material (secondary and tertiary rutting)”.
The test is performed by applying a repeated haversine pulse load of 0.1 seconds with a
rest period of 0.9 seconds. The typical permanent deformation behavior of HMA, when subjected
to repeated axial load in the laboratory and under specific environmental conditions, is
represented in Figure 2-14.
48
Figure 2-14 HMA permanent deformation behavior
There are typically three stages of permanent deformation. The first stage or the primary
stage is related to volumetric change, characterized by a high and decreasing rate of change. The
secondary stage is characterized by decrease in incremental permanent strain. The tertiary stage
is characterized by no volumetric change and an increasing rate of shear deformation until failure
occurs (Mallick and El-Korchi, 2009).
The beginning of the tertiary stage (or the point between the secondary and tertiary stage)
is designated as the flow number (FN). The FN is defined as the number of cycles at which the
tertiary permanent strain begins.
The permanent deformation damage model adopted by the MEPDG considers test data
only for the primary and secondary stages of permanent deformation with the first stage being
considered only an extrapolation of the secondary stage. The model is a modified version of the
widely used power law model and it is expressed in the form:
(2.27)
Primary Secondary Tertiary
Flow Point
Load Repetitions
Pe
rman
en
t Str
ain
49
where
p is the accumulated plastic strain at N repetitions of load,
r is the resilient strain of the
asphalt concrete (
r is a function of |E*| and the stress level), T is the pavement temperature, k1,
k2, and k3 are non linear regression coefficients, and
r1,r2, and r3, are field calibration factors.
A log-log chart relationship between the number of load repetitions and permanent strain
is typically expressed using the classical power model as shown in Equation 2.10.
(2.28)
Where, a and b are regression constants, which depends on the material and test conditions, and
N is the number of load repetitions.
Without the calibration factors, Equation 2.9 can be rewritten as:
(2.29)
For a given temperature, Equation 2.29 is simply equivalent to Equation 2.28.
Concerns regarding the limitation of Equation 2.29 were expressed by several researchers
including Mohammed et al. (2006) and Archilla (2008). The concern is that the mixture
properties such as binder viscosity, volume of effective binder content, and maximum air voids
are only taken into account by their effects on the elastic response of the material.
The approach used to estimate the FN by the IPC Global Universal Testing Software is
based on the moving average periods as proposed in Appendix D of NCHRP Report No. 513
(Bonaquist et al, 2003). This procedure is based on data smoothing techniques and provides an
acceptable FN. However, the estimated FN can affected by noise in the data and thus could be
different for the same specimen if different moving average periods are used for smoothing.
Since the estimated FN is used to determine the data to fit the power model (Equation 2.11), the
50
importance of estimating relatively accurate FN cannot be overemphasized. As mentioned
earlier, the FN values reported by the IPC Global Universal Testing Software may not be
accurate in some cases. Therefore, to provide a unifying criterion to calculate the FN of a mix,
Archilla et al. (2007) proposed the following model (Equation 2.30) in order to determine
mathematically the location of the inflection point (the Flow Number).
(2.30)
where εp is the permanent strain after N load repetitions, and and are model parameters
estimated by non-linear regression.
Once the model parameters and are estimated for a given specimen, the FN for that
specimen and permanent strain at FN can be estimated using the following expressions (Equation
2.31 and Equation 2.32).
(2.31)
(2.32)
As mentioned previously, the widely used power model (Equation 2.28) uses the
secondary and primary stage to estimate the model parameters. Further, the parameter estimates
can be affected by the number of initial observations that are included in the estimation.
Therefore, the dataset was trimmed between the initial observation (estimated using a technique
explained in the next paragraph) and FN. The FN is estimated using Equation 2.31. For
51
determining the number of observations to be included (or excluded) from the primary stage in
the estimation process, the test data for each specimen was trimmed down by eliminating the first
10% of the data in the series. A rationale and justification for this procedure is provided in (Diaz
et al. 2008). Once the data range is determined, fitting of Equation 2.28 and Equation 2.29 to
estimate k1 and k3, respectively, becomes simple. Figure 2-15 illustrates the data of the
permanent deformation test for one of the specimens after trimming together with power model.
Figure 2-15 Example of fitting of power model to trimmed data (Specimen ID: VLPM6)
100
1000
10000
100000
1000000
1 10 100 1000
Pe
rman
en
t St
rain
(
p)
Number of Load Repetitions
Test Points
Power (Model)
52
CHAPTER 3
LABORATORY EXPERIMENTS
3.1 Background
This chapter focuses on all the laboratory tests and testing details performed on base
course materials and Hot Mix Asphalt (HMA) for surface courses used in this study. The
laboratory tests performed on base course materials include: (a) Gradation analysis, (b) Modified
Proctor test, and (c) Resilient Modulus test. For the HMA, the laboratory tests performed are (a)
the Dynamic Modulus test and (b) the repeated load axial permanent deformation test. The
availability of materials and equipment limited to some extent the experimental plan for how and
what should be investigated, particularly for the foamed asphalt material. The following sections
provide information about the materials being characterized and the testing procedures used in
this study.
3.2 Material Sources
3.2.1 Base Course Materials
The experimental plan for base course materials included 2 different types of aggregates
namely, (a) virgin and (b) recycled. Virgin aggregates (Type B) were collected from the
Hawaiian Cement – Halawa Quarry in Aiea, Honolulu, Hawaii. A limited amount of recycled
material (foamed asphalt mixture) (~300 lbs) was delivered to the University of Hawaii at Manoa
pavement engineering laboratory by Alakona Corporation, Honolulu, Hawaii. The FA mixture
used in this study was produced using 100% RAP, stabilized using 2% of foamed (expanded)
asphalt, and 1% of Portland cement as filler.
53
3.2.2 Hot Mix Asphalt
In order to evaluate the potential effects of the use of polymer modified asphalt or fiber
reinforcement, testing was performed on sets of six specimens of an unmodified control mix, a
polymer modified mix, and a fiber reinforced mix. For each mix, two specimens were compacted
at three different target air voids. The mix design adopted was used recently by Grace Pacific
Corporation (GPC) in a paving project. GPC provided the samples of the same aggregates and
the same asphalt binder used in that project, which were used in the preparation of specimens in
the laboratory. In addition, testing was performed on six specimens (2 replicates at three target
air voids) of another unmodified mix produced at a local asphalt plant. The four types of
mixtures tested in this study along with their designation are:
1. Plant produced mixtures prepared using virgin asphalt binder: VPPM
2. Laboratory produced mixtures prepared using virgin asphalt binder: VLPM
3. Laboratory produced mixtures prepared using polymer modified asphalt binder:
PMALPM
4. Laboratory produced mixtures prepared using unmodified binder and fibers: FRACLPM
The aggregates used in the preparation of HMA samples in the laboratory were from Ameron
Kapaa quarry from the island of Oahu, Hawaii. In case of plant produced mixes, while the coarse
aggregates were from Ameron Kapaa quarry from the island of Oahu, Hawaii, the fine
aggregates were from Ameron Puunene quarry from the island of Maui, Hawaii. The unmodified
asphalt binder used in this study is from Asphalt Hawaii.
The required amount of mix to compact the VPPM specimens was collected from Jas W.
Glover Ltd (JWG), Honolulu, Hawaii. As indicated before, the remaining three types of
54
mixtures were laboratory mixed and laboratory compacted using material provided by Grace
Pacific Corporation (GPC), Honolulu, Hawaii.
The details of the base course and the HMA component materials and various tests
performed are provided in the following sections.
3.3 Base Course Material Information
In this section, the details of two tests performed on base course materials are provided.
First, the gradation analysis of aggregates is presented. Next, the Modified Proctor test
performed to determine the optimum moisture content and maximum dry density is explained.
3.3.1 Gradation Analysis of Aggregates
The gradation analysis of RAP was performed using the AASHTO T27 procedure.
According to AASHTO T27, the aggregate sample used for sieve analysis is dried at 110 °C.
However, the RAP sample used for gradation analysis in this study was oven dried at only 60 °C
for 48 hours prior to sieving. The reason for using a lower temperature to dry the RAP material is
because it contains asphalt binder, which could soften and help create lumps. The presence of
lumps could result in misrepresentation of actual gradation if the lumps are not broken during
sieving. For virgin aggregates, the gradation analysis provided by Hawaiian Cement Halawa –
Quarry was used. The gradation analysis results for RAP along with the minimum and maximum
requirements for 3/4” maximum nominal aggregate size allowed by the HDOT for untreated base
course materials is presented in Figure 3-1. Correspondingly, the gradation data collected from
Hawaiian Cement – Halawa (HCH) quarry along with the minimum and maximum requirements
for 1-1/2” maximum nominal aggregate size allowed by the HDOT for untreated base course
55
materials is presented in Figure 3-2. Figure 3-2 also includes the gradation analysis test data
performed using the AASHTO T11 procedure (typically known as wet sieve analysis) to
determine the actual percentage of virgin material passing the #200 sieve.
Figure 3-1 Gradation analysis of RAP compared with HDOT requirements for ¾” maximum
nominal untreated base
2"
1-1
/2"
1"
3/4
"
1/2
"
#4
#8
#16
#20
#40
#50
#100
#200
0
10
20
30
40
50
60
70
80
90
100
Perc
en
t P
assin
g
Sieve Designation
Reclaimed Asphalt Pavement
HDOT Minimum Specif ication
HDOT Maximum Specif ication
56
Figure 3-2 Gradation analysis of virgin aggregates from Hawaiian Cement – Halawa Quarry
compared with HDOT requirements for 1-1/2” maximum nominal untreated base
Based on the dry sieve analysis results, both virgin material and RAP gradation fall
within the HDOT requirements for untreated base course material. However, for the virgin
material, the wet sieve analysis results indicate that the material did not meet the HDOT
specifications.
The RAP material used in this study is also compared with the gradation requirements
recommended by Akeroyd and Hicks (1988), which is widely considered by several researchers
to provide the limits of desired gradation of RAP for producing foamed asphalt mixtures. Figure
3-3 illustrates the gradation analysis of RAP superimposed on the grading requirements
recommended by Akeroyd and Hicks. As can be seen from the figure, the material falls within
Zone A, which indicates the material is in the “ideal” grading limits for foamed asphalt
stabilization.
2"
1-1
/2"
1"
3/4
"
1/2
"
3/8
"48
16
30
50
100
200
0
10
20
30
40
50
60
70
80
90
100P
erc
en
t P
assin
g
Sieve Designation
Hawaiian Cement - Halawa Quarry
Hawaiian Cement - Halawa Quarry (wet sieve analysis)
HDOT Minimum Specif ication
HDOT Maximum Specif ication
57
Figure 3-3 RAP Gradation and desired aggregate grading for FA
(Redrawn after Akeroyd and Hicks, 1988)
3.3.2 Maximum Dry Density and Optimum Moisture Content
The maximum dry density (γdmax) and optimum moisture content (OMC) of both
materials were determined using the standard AASHTO T180 – Method D procedure. The OMC
and maximum dry density values are presented in Figure 3-4. Table 3-1 summarizes the test
results.
2"
1"
3/4
"
1/2
"
3/8
"
1/4
"
No.4
No.8
No.1
6
No.2
0
No.3
0
No.4
0
No.5
0
No.1
00
No.2
00
50.0
25
.0
19.0
12.5
9.5
6.3
4.7
50
2.3
60
1.1
80
0.8
50
0.6
00
0.4
25
0.3
00
0.1
50
0.0
75
0
10
20
30
40
50
60
70
80
90
100 P
erc
en
t P
assin
g
Sieve Size (mm)
RAP
Zone C
Zone A
Zone B
Zone A: Ideal Materials Zone B: Suitable Materials Zone C: Unsuitable Materials
58
Figure 3-4 Moisture-density relationship of base course materials
Table 3-1 Maximum Dry Density and Optimum Moisture Content values
Material Maximum Dry Density
(kg/m3)
Maximum Dry
Density (lb/f3)
Optimum Moisture
Content (%)
Hawaiian Cement – Halawa 2098 131.0 11.2
Reclaimed Asphalt Pavement
(RAP) 2032 126.9 8.1
3.4 Test Specimen Preparation for Resilient Modulus Testing
The resilient modulus of base course materials included compaction and testing the
materials at three different densities; 98%, 100%, and 102% of the maximum dry density. The
specimens were tested using the repeated load triaxial resilient modulus in accordance with
AASHTO T307; except that the number of load repetitions applied during each testing sequence
was reduced. The nominal maximum size of the virgin aggregates and RAP, which is used to
1,900
1,925
1,950
1,975
2,000
2,025
2,050
2,075
2,100
2,125
4.00 5.00 6.00 7.00 8.00 9.00 10.00 11.00 12.00 13.00 14.00 15.00 16.00 17.00 18.00
Dry
Den
sit
y (
kg
/m3)
Moisture Content (%)
Reclaimed Asphalt Pavement
Hawaiian Cement - Halawa Quarry
59
produce foamed asphalt mixtures, was found to be 50 mm and 19.0 mm respectively. Based on
AASHTO T307, the dimensions of the cylindrical test specimen for testing the virgin material
and FA was required to be compacted using a vibratory hammer in a split mold with a target
diameter of a 150 mm and a height between 305 mm and 318 mm.
Further, since there was no prior experience with in characterization of foamed asphalt
mixtures, and because of limited availability of FA, it was decided to reduce the size of the test
specimens so as to compact two replicates at three target densities. Accordingly, each specimen
using FA was compacted using a vibratory hammer in a split mold with a target diameter of 100
mm and a height of 203.2 mm. All the specimens compacted using FA mixtures were cured at 40
°C for 2 days.
All specimens were compacted in accordance with the AASHTO T307 procedure. Figure
3-5 shows a compacted specimen ready to be placed inside the cell prior to testing. The
compacted specimen inside the testing chamber placed in the loading frame is shown in Figure
3-6.
Figure 3-5 Compacted specimen connected to vacuum supply line
60
Figure 3-6 Specimen ready for testing
3.5 Resilient Modulus Testing
The resilient modulus testing was performed using the IPC Global Universal Testing
System (UTS) consisting of a hydraulic axial stress and a pneumatic confining stress loading
system, and a computer-controlled data acquisition system (CDAS) connected to a personal
computer. The machine is capable of applying repeated cycles of a haversine-shaped load pulse
of 0.1 seconds with a 0.9 seconds rest period. The deformation produced in the sample during
testing is captured by two external sample Linear Variable Differential Transducers (LVDTs)
and a system LVDT that is attached to the actuator that provides the system deformation. The
test specimen placed inside the testing chamber along with sample LVDTs is shown in Figure 3-
7.
61
Figure 3-7 Test specimen inside the testing chamber along with sample LVDTs
The resilient modulus test was performed in accordance with the AASHTO T307
procedure. A total of 15 combinations (from Table 2 of AASHTO T307) of deviator and
confining stresses were applied to the compacted sample. The two stages of the resilient
modulus test are: (a) Conditioning and (b) Measuring stress and strains to calculate Mr.
Conditioning: AASHTO T307 requires between 500 and 1000 repetitions of the conditioning
deviator stress. The reason for applying conditioning sequence is to eliminate the effects of the
initial loading versus reloading. Further, the conditioning also helps in reducing the effects of
any imperfect contact between the top platen, base plate, and the test specimen. However, in
order to prevent damage of the compacted specimens, all tests were performed by applying 50
cycles of deviator stress.
Measuring stress and strains to calculate Mr: Following the conditioning cycles, the resilient
modulus testing was performed by applying 50 cycles at each combination of confining stress
and deviator stress. Repeated cycles of haversine-shaped load pulse of 0.1s with a rest period of
Sample LVDT
62
0.9s were applied for both conditioning and testing. Mr was calculated as the average of the
ratios of the deviator stress to resilient strain for the last five cycles (46-50). Figure 3-8 shows a
screen shot during a typical testing procedure.
Figure 3-8 Example of dynamic modulus data collection
The repeated load triaxial resilient modulus tests were performed to evaluate the behavior
of virgin aggregates and FA mixtures when compacted at three different density levels. The
effect of bulk stress at each combination of the loading sequence on the resilient modulus of
virgin aggregates and FA specimens compacted at three different densities was observed. For
brevity, the results of one specimen from each of the three densities are presented in Figure 3-9
and Figure 3-10. The figures show resilient modulus of three specimens plotted against the bulk
63
stress (θ = 3σ3 + σd), where σ3 = the confining pressure and σd = the deviator stress on a log-log
graph. As can be seen from the figure, Mr increases with increase in density.
Figure 3-9 Effect of bulk stress on resilient modulus for virgin aggregates compacted at three
different densities
Figure 3-10 Effect of bulk stress on resilient modulus of FA mixtures compacted at three
different densities
1000
10000
100000
10 100 1000
Resi
lient
Mod
ulus
(ps
i)
Bulk Stress (psi)
Hawaiian Cement - Halawa Quarry @ 98% of Max. Dry Density
Hawaiian Cement - Halawa -Quarry @ 100% of Max. Dry Density
Hawaiian Cement - Halawa Quarry @ 102% of Max. Dry Density
10000
100000
10 100 1000
Resi
lient
Mod
ulus
(ps
i)
Bulk Stress (psi)
FA @ 98% of Max. Dry Density
FA @ 100% of Max. Dry Density
FA @ 102% of Max. Dry Density
64
When granular materials are subjected to triaxial state of stress, deviator stress is found to
have an important effect on the material’s resilient modulus. Witczak and Uzan (1988) found
that for granular materials tested in a triaxial stress state, the deviator stress has two contrary
effects on the stiffness of the material; first, increase in deviator stress will result in an increase
in bulk stress (θ=3σ3+σd), which leads to increase in the stiffness of the material and second, an
increase in deviator stress also increases the octahedral shear stress, which tends to decrease the
modulus. Further, Hicks and Monismith (1971) reported a “slight softening of the granular
material at low deviator stress levels and a slight stiffening behavior at higher levels of deviator
stress”.
Figures 3-11 shows the effect that deviator stress on the resilient modulus of the
specimens compacted at 98%, 100%, and 102% of the maximum dry density using virgin
aggregates. The figure is constructed using the average values of Mr and deviator stress from two
replicate specimens. For these specimens, regardless of the compaction level, it is clear that a
higher compaction level translates into a higher resilient modulus for the same stress level. The
effect of deviator stress on Mr for each specimen of virgin aggregates is presented individually in
Appendix A, where the same trends observed in Figure 3-11 arte observed.
65
Figure 3-11 Mr vs. deviator stress for specimens compacted at different densities using virgin
aggregates
Figure 3-12 shows the same information as Figure 3-11 except that data for two of the
confining stresses are not included. This figure is presented to illustrate the effect that confining
stress has on the modulus of virgin aggregates, which is not obvious from Figure 3-11. As can be
observed in the figure, except at the low level of confining stress (3 psi) for specimens
compacted at 102% of maximum dry density, where the modulus shows a “slight” softening
behavior and subsequently increases marginally with increase in deviator stress, the Mr values
increase with confining stress for specimens compacted at all densities. A figure illustrating the
effect of all 5 different levels of confining stress on the modulus is presented in Appendix A.
5000
10000
15000
20000
25000
30000
35000
40000
45000
50000
0 5 10 15 20 25 30 35 40 45 50
Resil
ien
t M
od
ulu
s (
psi)
Deviator Stress (psi)
HCH @ 98%
HCH @ 100%
HCH @ 102%
66
Figure 3-12 Mr vs. deviator stress for specimens compacted at different densities using virgin
aggregates at low (3 psi), intermediate (5 psi), and high (20 psi) confining stress level
Figure 3-13 shows the variation of resilient modulus with deviator stress at each
confining stress level for foamed asphalt mixture specimens compacted at percent of maximum
densities of 98, 100, and 102% respectively. This figure is again constructed using the average
values of Mr and deviator stress from two replicate specimens. For these specimens, an increase
in the modulus is observed with increase in deviator stress at all confining stress levels for
specimens compacted at 98% of maximum dry density. For the specimens compacted at 100% of
maximum dry density, a slight increase in modulus with deviator stress is observed. Furthermore,
for the specimens compacted at 102% of maximum dry density, it is observed that the resilient
modulus decreases with increase in deviator stress at all confining levels.
5000
10000
15000
20000
25000
30000
35000
40000
45000
50000
0 5 10 15 20 25 30 35 40 45 50
Resil
ien
t M
od
ulu
s (
psi)
Deviator Stress (psi)
HCH @ 98%; Confining stress = 3 psi
HCH @ 100%; Confining stress = 3 psi
HCH @ 102%; Confining stress = 3 psi
HCH @ 98%; Confining stress = 10 psi
HCH @ 100%; Confining stress = 10 psi
HCH @ 102%; Confining stress = 10 psi
HCH @ 98%; Confining stress = 20 psi
HCH @ 100%; Confining stress = 20 psi
HCH @ 102%; Confining stress = 20 psi
67
For the specimens compacted at 102% of maximum dry density, at low and intermediate
level of confining stress (σ3 = 3, 5, and 10 psi), the modulus values show a “slight” softening
behavior and subsequently increase marginally with increase in deviator stress. It is also
observed from the figure that at the higher confining stresses (10, 15 and 20 psi) the trend lines
with deviator stress tend to cross for the 100% and 102% compaction levels. The relative
position of the crossing point also appears to depend on the confining stress.
The relationship between deviator stress and Mr for all the specimens is individually
presented in Appendix A.
Figure 3-13 Mr vs. deviator stress for specimens compacted at different densities using FA
mixtures
10000
20000
30000
40000
50000
60000
70000
80000
90000
100000
110000
120000
0 5 10 15 20 25 30 35 40 45 50
Resil
ien
t M
od
ulu
s (
psi)
Deviator Stress (psi)
FA @ 98%; Conf ining stress = 3 psi
FA @ 100%; Conf ining stress = 3 psi
FA @ 102%; Conf ining stress = 3 psi
FA @ 98%; Conf ining stress = 5 psi
FA @ 100%; Conf ining stress = 5 psi
FA @ 102%; Conf ining stress = 5 psi
FA @ 98%; Conf ining stress = 10 psi
FA @ 100%; Conf ining stress = 10 psi
FA @ 102%; Conf ining stress = 10 psi
FA @ 98%; Conf ining stress = 15 psi
FA @ 100%; Conf ining stress = 15 psi
FA @ 102%; Conf ining stress = 15 psi
FA @ 98%; Conf ining stress = 20 psi
FA @ 100%; Conf ining stress = 20 psi
FA @ 102%; Conf ining stress = 20 psi
68
To evaluate the effects of deviator stress and octahedral shear stress on Mr of virgin
aggregates and FA mixtures, the coefficients of the three-parameter model was determined using
the following equation.
32
11
K
a
oct
K
a
arPP
pKM
Where:
Pa = normalizing stress (atmospheric pressure = 14.68 psi)
σ1, σ2, and σ3 = principal stresses, and σ2 = σ3
σd = deviator stress = σ1 - σ3
θ = bulk stress = (σ1 + σ2 + σ3) = (3σ3 + σd)
τoct = octahedral shear stress =
K1, K2, and K3 are material specific regression constants.
Using the above equation, the coefficients of bulk stress and octahedral shear stress, and
its statistical significance in the model are determined. Table 3-2 presents the results.
69
Table 3-2 Mr coefficients calculated using the NCHRP 1-37A model
Specimen ID K1
p-value
(K1)
K2
p-value
(K2)
K3
p-value
(K3)
R2
FA1 @ 98 2887.61 2.03E-27 0.39 2.04E-09 -0.09 3.42E-01 0.97
FA2 @ 98 3022.21 1.25E-26 0.39 1.31E-08 -0.18 1.14E-01 0.96
Average FA @ 98 2954.91 0.39 -0.14
FA1 @100 3312.90 3.22E-26 0.47 3.67E-09 -0.29 2.79E-02 0.97
FA2 @ 100 3362.65 8.75E-27 0.39 1.01E-08 -0.26 3.14E-02 0.96
Average FA @ 100 3337.77 0.43 -0.27
FA1 @ 102 3662.43 1.14E-24 0.44 2.20E-07 -0.57 2.94E-03 0.91
FA2 @ 102 3645.89 5.15E-26 0.43 1.96E-08 -0.43 4.08E-03 0.95
Average FA @ 102 3654.16 0.44 -0.50
HCH1 @ 98 575.57 8.46E-22 0.09 1.34E-01 1.75 9.81E-07 0.95
HCH2 @ 98 595.97 2.54E-25 0.08 2.57E-02 1.54 2.91E-09 0.98
Average HCH @ 98 585.77 0.09 1.65
HCH1 @ 100 667.78 4.90E-23 0.16 5.03E-03 1.42 1.10E-06 0.96
HCH2 @ 100 694.08 6.36E-23 0.09 1.05E-01 1.62 3.46E-07 0.96
Average HCH @ 100 680.93 0.13 1.52
HCH1 @ 102 1051.43 1.70E-24 0.07 9.67E-02 1.34 2.53E-07 0.96
HCH2 @ 102 1091.80 6.28E-25 0.06 1.34E-01 1.33 1.18E-07 0.96
Average HCH @ 102 1071.6 0.07 1.34
From the summary of regression coefficients presented in Table 3-2, the following
observations are made:
70
1. The resilient modulus of virgin aggregates and FA mixtures show an increasing trend
with increase in bulk stress at increasing levels of compaction.
2. For virgin aggregates, a higher compaction level translates into a higher resilient modulus
for the same deviator stress. However, for FA mixture specimens, an increase in the
modulus is observed with increase in deviator stress at all confining stress levels for
specimens compacted at 98% of maximum dry density. For the specimens compacted at
100% of maximum dry density, a slight increase in modulus with deviator stress is
observed. Furthermore, for the specimens compacted at 102% of maximum dry density, it
is observed that the resilient modulus decreases with increase in deviator stress at all
confining levels.
3. The coefficient K2 in NCHRP 1-37A equation, which is the exponent for the bulk stress
term, is positive. This indicates increase in bulk stress increases the stiffness of virgin
aggregates and FA mixture.
4. The coefficient K3 in NCHRP 1-37A equation, which is the exponent for the shear stress
term, is negative for FA mixture, suggesting the stiffness of FA mixture decreases with
increase in octahedral shear stress. This behavior is analogous to the observations made
by Witczak and Uzan (1988) as explained earlier. Further, it can be seen from the p-
values of coefficient K3 that the octahedral shear stress is not statistically significant for
specimens compacted at 98% of maximum dry density.
5. The sign of the coefficient K3 in NCHRP 1-37A equation is positive for specimens
compacted using virgin aggregates, which means an increase in octahedral shear stress
increases the resilient modulus of the material. This observation is contrary to the widely
held belief that, for unbound materials, the coefficient K3 should be negative (NCHRP 1-
71
37A 2004, FHWA, 2002, George, 2004, Hossain, 2008). The sign of coefficient K3 has
been reported to be positive by several researchers including Heydinger et al. (1996) and
Bennert and Maher (2005). Studies performed by Song (2009) in the same laboratory at
the University of Hawaii at Manoa has also reported positive coefficient values for the
octahedral shear stress term in the NCHRP 1-37A model on Mr tests performed on
granular materials using the AASHTO T307 procedure. Results of a Mr test performed
by Dr.Adrian Ricardo Archilla of the University of Hawaii on a coral sample using the
AASHTO T307 procedure is presented below (Figure 3-14, Figure 3-15, Table 3-3). As
can be seen from the table, the coefficient of octahedral shear stress, K3, is positive.
Figure 3-14 Mr vs. Bulk Stress for Coral sample
y = 9356.6x0.4258
R² = 0.8454
10000
100000
10 100 1000
Re
silie
nt
Mo
du
lus
(psi
)
Bulk Stress (psi)
72
Figure 3-15 Mr vs. deviator stress at different confinement stresses for Coral material
Table 3-3 Mr coefficients calculated using the NCHRP 1-37A model
Specimen ID K1
p-value
(K1)
K2
p-value
(K2)
K3
p-value
(K3)
R2
Coral 1755.79 1.40E-24 0.17 1.28E-03 0.96 8.47E-06 0.96
3.6 Hot Mix Asphalt Mixtures Information
This section provides a detailed description of the materials used to compact specimens
for dynamic modulus and permanent deformation tests. First, the aggregate gradation used to
produce HMA mixtures is presented. Next, the asphalt binder used in the preparation of HMA
mixtures is discussed. Later, the modification process for producing polymer modified binder is
reviewed. The particulars of mixing and compaction temperature for unmodified and modified
10000
20000
30000
40000
50000
60000
70000
80000
90000
0 10 20 30 40 50
Re
silie
nt
Mo
du
lus
(psi
)
Deviator Stress (psi)
Confining stress = 3 psi
Confining stress = 5 psi
Confining stress = 10 psi
Confining stress = 15 psi
Confining stress = 20 psi
73
binder are presented. Lastly, the type of FORTA-FI fibers and the procedure followed to blend
the fibers with HMA mixture is discussed.
3.6.1 Gradation Analysis of Aggregates
This study included HMA mixtures prepared using two gradations for surface course in
Hawaii. As mentioned in section 3.2.2, the mix design and materials used in this study was
provided by paving contractors in Hawaii. Neither of the gradations is as a result of a mix design
procedure performed as a part of this study. Figure 3-16 and Figure 3-17 presents the two
gradation blend information collected from the local contractors on a 0.45 power chart. Figure 3-
16 is the gradation used for preparing mixes in the laboratory. The gradation conforms to the
requirements of the HDOT specification for mix type IV for surface courses and also falls within
the control points of the 12.5 mm Superpave mix. Figure 3-17 shows the gradation used in
producing plant produced mixes. The gradation curve falls within the requirements of the 19.0
mm Superpave mix.
Figure 3-16 Gradation information for laboratory produced HMA mixtures
1"
3/4
"
1/2
"
3/8
"
#4
#8
#16
#30
#50
#100
#200
0
10
20
30
40
50
60
70
80
90
100
Perc
en
t P
assin
g
Sieve Designation
Gradation for Laboratory Produced Mix
HDOT Mix Type IV - Minimum Specif ication
HDOT Mix Type IV - Maximum Specif ication
12.5 mm Superpave Control Points - Lower
12.5 mm Superpave Control Points - Upper
74
Figure 3-17 Gradation information for plant produced HMA mixtures
3.6.2 Asphalt Binder
Unmodified PG64-16 binder distributed to JWG by Asphalt Hawaii was used to produce
VPPM. For the two types of HMA mixtures prepared in the laboratory, one is an unmodified
PG64-16 binder distributed to GPC by Asphalt Hawaii, which is used to prepare VLPM, and the
other is the polymer modified asphalt binder which was used to prepare PMALPM. The polymer
modified binder was prepared by modifying the PG64-16 binder distributed to GPC by Asphalt
Hawaii with 1.0% of DuPont’s Elvaloy®RET and mixed with 0.3% (by weight of binder)
polyphosphoric acid. The latter is added to act as a catalyst of the reaction between Elvaloy RET
and the binder.
3.6.3 Preparation of modified binder
The Evaloy®RET manufacturers recommend two procedures for modification using
Elvaloy: (a) with a catalyst and (b) without a catalyst. The procedure used in this study is
1"
3/4
"
1/2
"
3/8
"
#4
#8
#16
#30
#50
#100
#200
0
10
20
30
40
50
60
70
80
90
100
Perc
en
t P
assin
g
Sieve Designation
Gradation for Plant Produced Mix
19.0 mm SuperPave Control Points - Lower
19.0 mm SuperPave Control Points - Upper
75
modification of the unmodified binder using the catalyst. First, the unmodified binder to be
modified is heated in a heating pot at a temperature of 185 ºC. Once the sample becomes less
viscous, a lab mixer is set inside the softened binder to rotate at a speed high enough to create a
small vortex. Care was taken to ensure air bubbles were not formed. Subsequently, a calculated
amount of Elvaloy pellets (1% of the weight of the unmodified binder) was added at an
approximate rate of 10 g/min. Mixing is continued at the same speed for two hours after adding
all the pellets. Subsequently, polyphosphoric acid in a concentration of 105% is added to the
mixture as a catalyst while the mixing is in progress for an additional 15 to 30 minutes. Next, the
modified binder is transferred to new containers and the lids are tightly covered. The cans are
placed inside an oven set at 185ºC for 3 hours. Finally, the asphalt cans are removed from the
oven, allowed to air-cool for 10 minutes and the lid is opened. The modified binder is now ready
to be used. Figure 3-18 shows the Elvaloy pellets and the hot pot where the modification process
was performed.
Figure 3-18 Evaloy®RET Pebbles (left) and mixing Elvaloy to Unmodified PG64-16 binder
(right)
76
3.6.4 Mixing and Compaction Temperatures of Unmodified and Modified Binder
The mixing and compaction temperature ranges for unmodified binder used to prepare
HMA mixtures were obtained from the temperature-viscosity charts provided by JWG and GPC.
For the modified binder, the mixing and compaction temperature was taken from Archilla
(2008). The same grade of binder (PG64-16) was modified by Archilla (2008) in a study that
evaluated the performance of polymer modified and unmodified HMA mixtures. Given that the
grade of the binder is the same, their mixing and compaction temperatures were similar, and that
the same proportion of polymer was used, it is expected that the mixing and compaction ranges
would be similar to those found by Archilla (2008). The fiber reinforced asphalt concrete
mixture was prepared using unmodified binder. The effect of modifying virgin binder with fibers
was studied by Kaloush et al. (2008). The modification process was done by using only
Polypropylene fibers. It was found that the (a) at lower temperatures the viscosity-temperature
susceptibility relationship did not show any changes compared to original binder and (b) at high
temperatures, higher binder viscosities were observed indicating that the modified binder is less
susceptible to viscosity change with increased temperatures. Although improved properties were
observed at high temperatures, for this study, the variation of the viscosity of the binder with
fibers was not measured, because according to The Asphalt Handbook (MS-2) (Asphalt Institute,
2007), one of the assumptions in performance graded asphalt binder specifications is that the
asphalt binders should exhibit isotropic behavior. With respect to testing asphalt binders
incorporated with fibers, the Asphalt Handbook states:
“Asphalt binders should exhibit isotropic behavior. Isotropic behavior occurs when
specimen loading or particle orientation has no effect on the response. Asphalt binders
77
that incorporate fibers could exhibit anisotropic behavior – meaning the fiber orientation
affects the test response”.
Furthermore, as indicated in section 3.7, all specimens were aged in accordance with
AASHTO R30 in an oven at 135 °C irrespective of the viscosity of the binder. The rationale
behind not using the compaction temperature from the viscosity-temperature charts is because
the temperature ranges obtained from these charts are important to be used during mix design to
achieve equiviscous mixing and compaction in the laboratory. However, in the field, it is
important that the temperatures are high enough (above what is called cessation temperature) to
achieve the required density. The cessation temperature for compaction of HMA in the field is
reported to be 79 °C. It is also reported that the cessation temperature of 79 °C is reported to be a
general rule of thumb and will change from mix to mix depending on the properties of the binder
(West et al, 2010). Although the actual cessation temperatures for the two types of binder used in
this study is not known, the compaction temperature of 135 °C is much higher compared to the
cessation temperature reported by West et al.
Further, it can be seen from the results in the following sections that there were no
problems in achieving the target densities.
Table 3-4 presents the mixing and compaction temperature ranges for the two types of
binders used in this study.
78
Table 3-4 Mixing and compaction temperature range for asphalt binders
Asphalt Binder
Temperature (°C)
Mixing Compaction
Unmodified binder used to produce VPPM 150 - 155 143 – 147
Unmodified binder (PG64-16) used to prepare VLPM 150 - 155 143 – 147
Modified binder (PG64-16 + 1% Elvaloy) 160 - 165 150 – 155
3.6.5 Fibers Used in the Study
FORTA-FI HMA blend fibers are used in this study. In its manufactured condition, the
fibers are clasped together. The fibers were fluffed using a makeshift procedure prior to mixing
them with hot aggregates. This is done to enhance the effect of fibers and improve the
distribution of fibers in the HMA mixture. The procedure involved placing packaged fibers
inside a hollow cylinder, the top of which was then covered using a perforated disc. Next,
compressed air was blown from the top to achieve the desired result. Figure 3-19 through Figure
3-21 shows the fibers in its manufactured condition, the fluffing setup and method, and fluffed
fibers. The fluffed fibers were then weighed as required and mixed with hot aggregates before
asphalt was introduced into the mixing bowl.
79
Figure 3-19 Fibers in its manufactured condition
Figure 3-20 The setup used to fluff the fibers
Figure 3-21 Fibers after fluffing
80
3.7 Test Specimen Preparation for Dynamic Modulus and Permanent Deformation Testing
The dynamic modulus and permanent deformation tests were performed on compacted
HMA samples prepared at three different target air voids (Va); Va=3%, 5%, and 7%. Both tests
require a 100 mm diameter by 150 mm height cored and sawed from 150 mm diameter by 170
mm specimens compacted in the Superpave gyratory compactor. Asphalt mixtures used to
compact cylindrical specimens were prepared in accordance with AASHTO T312. The mixtures
were conditioned according to AASHTO R30 at 135 °C for 4 hours prior to compaction. The
following steps (as shown in Figure 3-22) are followed in preparation of the test specimens.
Figure 3-22 Steps involved in preparation of test specimens
Material quantity calculation: The first step is to determine the amount of material required to
compact a specimen to achieve certain amount of air voids in the test specimen. The amount of
Material Quantity Calculation
Batching
Mixing
Conditioning
Compaction
Coring and Sawing
81
material is determined using the target air voids value and the theoretical specific gravity (Gmm)
of the mixture, which is determined in accordance with AASHTO T209. Subsequently, a
batching sheet is developed to give the following details that will assist in preparing the
compacted specimen.
a) target air voids
b) mass of different types and sizes of aggregates
c) asphalt type and content
d) temperature at which the mixture has to be prepared, and
e) mixture conditioning details
The theoretical specific gravity test was performed using AASHTO T209 procedure. The
results of the tests are presented in Table 3-5. The Gmm test on mixes with fibers was not
performed because it was assumed that the addition of a small percentage of fibers (1 lb per ton
of HMA mixture, which is equivalent to 0.05% by weight of mix) would have a negligible effect.
Therefore, the Gmm of mixes prepared using unmodified binder was used to calculate the
amount of HMA material required to achieve a target density. The amount of fibers to be added
was then determined based on the total mass of the HMA mixture.
Table 3-5 Results of theoretical specific gravity
Material Type Theoretical Specific Gravity
VPPM 2.560
VLPM 2.460
PMALPM 2.452
FRACLPM 2.460 (same as for VLPM)
82
Batching: Based on the mass calculations in the batching sheet, aggregates of different types and
sizes are combined together to achieve the desired gradation and provide enough room for
asphalt to produce a mixture with target air voids, height, and diameter. The batched aggregates
were place inside an industrial oven at 175 °C (350 °F) for a minimum of 5 hours prior to
mixing.
Mixing: Except for VPPM, which is plant produced, all HMA samples were mixed in a
mechanical mixer (as shown in Figure 3-23). The mixing temperature ranges used for different
types of asphalt binder are shown in Table 3-4.
Regardless of the type of binder used, the HMA mixtures prepared in the laboratory had
very similar appearance except for the mixture with fibers. The fibers appear to hold the material
together. Figure 3-24 through Figure 3-27 illustrate the three different types of mixes.
Figure 3-23 Mechanical mixer used for mixing HMA samples
83
Figure 3-24 HMA mixture produced using virgin asphalt in the plant
Figure 3-25 HMA mixture prepared in the laboratory using virgin asphalt
Figure 3-26 HMA mixture prepared in the laboratory using polymer modified asphalt
84
Figure 3-27 HMA mixture prepared in the laboratory using virgin asphalt and FORTA-FI fibers
Conditioning: According to AASHTO R30, all HMA mixed samples were placed in an oven at
135 °C for 4 hours prior to compaction.
Compaction: The conditioned samples were compacted in a 150 mm diameter mold to a height
of 170 mm using a Rainhart SuperPave gyratory compactor. Since the HMA samples were
immediately compacted after conditioning, the samples were not subjected to the compaction
temperature as prescribed in Table 3-4 prior to compaction. The compacted specimens were
then extruded from the mold. Figure 3-28 shows the gyratory compactor used for compaction
and a specimen extruded after compaction.
85
Figure 3-28 A specimen extruded after compaction in a Rainhart SGC
The extruded specimens were clearly labeled and allowed to cool to room temperature.
Next, the bulk specific gravities of the compacted specimens were determined in accordance
with AASHTO T166.
Coring and Sawing: All air-dried samples were cored and sawed to obtain a 150 mm tall by 100
mm diameter test sample. Figure 3-29 shows the coring and sawing machine used to core and
saw the specimens to achieve the required diameter and height. A cored and sawed specimen is
shown in Figure 3-30.
86
Figure 3-29 Specimen being cored (left) and sawed (right) to required size
Figure 3-30 Cored and sawed specimen
Subsequently, the cored and sawed samples were washed under water to remove all loose
debris and allowed to dry in air. Finally, the samples were tested for bulk specific gravity in
accordance with AASHTO T 166. The specimens were now ready for the preparation for the
dynamic modulus test.
87
All specimens were glued with six gauge points using epoxy to hold three LVDTs.
Figure 3-31 shows the gauge point fixing jig used to glue the gauge points. The glued gauge
points were allowed to dry and set for at least 5 hours before removing the specimen from the
gauge point fixing jig. An example of a test specimen ready for testing is shown in Figure 3-32.
Figure 3-31 Gauge point fixing jig
88
Figure 3-32 Test specimen ready for dynamic modulus testing
The steps explained in Section 3.6 were followed to prepare specimens for VLPMs,
PMALPMs, FRACLPMs. In total, 19 specimens were prepared in these three categories. Six
additional specimens were prepared using plant produced HMA mixtures, which belong to
VPPMs. The specimens prepared using plant produced mixtures were heated to 135 °C for 4
hours prior to compaction. A summary of the volumetric characteristics of all the HMA
specimens is presented in Table 3-6. As can be seen from the table, the actual Va and target Va
don’t match all the time. This is primarily because of the variability involved in determining the
theoretical (rice) specific gravity of the loose HMA mixture, which determines the mass of HMA
material required to compact a specimen of known dimension and target air voids. Furthermore,
cored specimens usually have lower air voids compared to the original compacted specimen.
89
Table 3-6 Characteristics of HMA specimens
Specimen ID Mix Type Pb (%) Target
Va (%) Gmm Gmb
Actual
Va (%) VMA VFA
VPPM1 Virgin 5.5% 3.0% 2.560 2.539 0.8% 9.8 91.8
VPPM2 Virgin 5.5% 3.0% 2.560 2.543 0.7% 9.6 93.1
VPPM3 Virgin 5.5% 5.0% 2.560 2.498 2.4% 11.2 78.4
VPPM4 Virgin 5.5% 5.0% 2.560 2.496 2.5% 11.3 77.8
VPPM5 Virgin 5.5% 7.0% 2.560 2.419 5.5% 14.0 60.7
VPPM6 Virgin 5.5% 7.0% 2.560 2.420 5.5% 14.0 60.9
VLPM1 Virgin 6.7% 3.0% 2.460 2.408 2.1% 13.5 84.2
VLPM2 Virgin 6.7% 3.0% 2.460 2.418 1.7% 13.1 86.9
VLPM3 Virgin 6.7% 5.0% 2.460 2.349 4.5% 15.6 71.1
VLPM3B Virgin 6.7% 5.0% 2.460 2.337 5.0% 16.0 68.7
VLPM4 Virgin 6.7% 5.0% 2.460 2.341 4.8% 15.8 69.6
VLPM5 Virgin 6.7% 7.0% 2.460 2.282 7.2% 18.0 59.7
VLPM6 Virgin 6.7% 7.0% 2.460 2.264 8.0% 18.6 57.2
PMALPM1 Polymer Modified 6.7% 3.0% 2.452 2.413 1.6% 13.3 88.0
PMALPM2 Polymer Modified 6.7% 3.0% 2.452 2.417 1.7% 13.1 86.8
PMALPM3 Polymer Modified 6.7% 5.0% 2.452 2.346 4.6% 15.7 70.5
PMALPM4 Polymer Modified 6.7% 5.0% 2.452 2.351 4.4% 15.5 71.5
PMALPM5 Polymer Modified 6.7% 7.0% 2.452 2.286 7.1% 17.8 60.4
PMALPM6 Polymer Modified 6.7% 7.0% 2.452 2.296 6.7% 17.5 61.8
FRACLPM1 Fiber Reinforced 6.7% 3.0% 2.460 2.404 2.3% 13.6 83.2
FRACLPM2 Fiber Reinforced 6.7% 3.0% 2.460 2.403 2.3% 13.6 83.1
FRACLPM3 Fiber Reinforced 6.7% 5.0% 2.460 2.338 5.0% 16.0 69.0
FRACLPM4 Fiber Reinforced 6.7% 5.0% 2.460 2.351 4.4% 15.5 71.4
FRACLPM5 Fiber Reinforced 6.7% 7.0% 2.460 2.271 7.7% 18.4 58.2
FRACLPM6 Fiber Reinforced 6.7% 7.0% 2.460 2.268 7.8% 18.5 57.8
90
3.8 Dynamic Modulus Testing
The dynamic modulus testing was performed using the IPC Global Simple Performance
Tester (SPT), which is shown in Figure 3-33. The SPT is a relatively small, computer-controlled
hydraulic loading and testing machine that can perform tests on compacted HMA specimens
over temperatures ranging from 4 °C to 60 °C. The specimen is seated inside a testing chamber,
which facilitates axial testing of specimens with or without confinement.
Figure 3-33 IPC Global Simple Performance Tester
The compacted HMA specimens were tested for dynamic modulus in accordance with the
AASHTO TP 62: “Standard Method of Test for Determining Dynamic Modulus of Hot Mix
Asphalt (HMA)” procedure. Figure 3-34 shows the sample connected with LVDTs mounted
inside the testing chamber.
91
Figure 3-34 Specimen assembly inside the testing chamber
Each sample was tested at three different temperatures (4.4 °C, 21 °C, and 40 °C) and
seven different frequencies (25, 10, 5, 1, 0.5, 0.1, 0.01 Hz). The conditioning time for each
temperature is presented in Table 3-7.
Table 3-7 Conditioning time for different testing temperature
Testing Temperature 4.4 °C 21 °C 40 °C
Conditioning Time 6 Hours 3 Hours 2 Hours
The test is run starting at the lowest temperature to the highest, and the frequency starts
from the highest to the lowest. In cases where the specimens were prepared using virgin binder,
the gauge points attached to the sample would repeatedly fall off at higher temperatures and
lowest frequency, forcing to stop the test. In such instances, all six gauge points were re-glued on
a different location of the sample and the test was attempted again. Figure 3-35 shows an
92
extreme example in which repeated attempts were necessary because the gauge points kept
coming off from the sample and had to be re-glued to finish the test. The figure also makes it
clear that the glued gauge points came off because of the softening of the binder and not because
of the epoxy.
Figure 3-35 An example of repeated attempts to glue the gauge point(s) for a specimen
During the test, several parameters are checked to see if they meet the data quality
statistics requirement. The parameters and corresponding allowable limits are listed in Table 3-8.
Table 3-8 Data quality statistics requirements in dynamic modulus test
Data Quality Parameter Allowable Limit
Deformation Drift 400%
Load Standard Error 10%
Deformation Standard Error 10%
Deformation Uniformity 30%
Phase Uniformity 3 Degrees
Load Drift 3%
93
Figure 3-36 shows a typical screen shot during a test. As can be seen from the figure, the
temperature at which the sample is being tested, dynamic modulus and other parameters listed in
Table 3-8 at different frequencies is recorded. It was ensured that, for each specimen, test data
within the aforementioned allowable limits was used to derive the master curve using the shift
factor. Once the dynamic modulus test was completed at all temperatures and frequencies, the
specimen was removed from the testing chamber, the LVDTs, LVDT holders, and gauge points
were removed from the specimen, and the specimen was prepared for the flow number or
repeated axial load test.
Figure 3-36 Example of dynamic modulus data collection
94
The results from the dynamic modulus test consist of a set of dynamic modulus values
obtained at different temperatures and frequencies. As explained in section 2.8, the master curve
can be used to compute the dynamic modulus values for any desired combination of temperature
and frequency. The dynamic modulus test data from all specimens was used to derive the
“Master Curve” for each specimen using the quadratic equation for the shift factor (Equation
2.6). The dynamic modulus parameters and shift factors are calculated for each specimen. The
results are tabulated in Table 3-9 and the Master Curves for individual specimens are presented
in Appendix B. Master curves developed using these parameters are presented in Figures 3-37
through Figure 3-41. The figures show the master curves for different types of HMA mixtures
used in this study. For brevity, Master Curves for one specimen at three different air voids are
presented.
95
Figure 3-37 Master curves for VPPM at three different air voids
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100
1000
10000
100000
1000000
10000000
1.00E-06 1.00E-05 1.00E-04 1.00E-03 1.00E-02 1.00E-01 1.00E+00 1.00E+01 1.00E+02 1.00E+03 1.00E+04 1.00E+05 1.00E+06
Dy
na
mic
Mo
du
lus
E*
(ps
i)
Frequency (Hz)
VPPM1: Pb=5.5%, Va=0.8%
VPPM4: Pb=5.5%, Va=2.5%
VPPM5: Pb=5.5%, Va=5.5%
96
Table 3-9 Dynamic modulus master curve parameters and shift factors
Specimen Information Dynamic Modulus Parameters and Shift Factors
Sample ID Mix Type Pb
(%)
Target
Va (%)
Actual Va
(%) a b c
VPPM1 Virgin 5.5% 3.0% 0.8% 2.4499 -0.7961 0.6139 4.1120 2.20E-04 -0.1039 6.1977
VPPM2 Virgin 5.5% 3.0% 0.7% 3.2024 -1.2148 0.5192 3.4064 1.86E-04 -0.1006 6.1324
VPPM3 Virgin 5.5% 5.0% 2.4% 4.0469 -1.4948 0.4117 2.5969 -2.26E-05 -0.0808 5.7657
VPPM4 Virgin 5.5% 5.0% 2.5% 3.5585 -1.2857 0.4735 3.0174 2.62E-04 -0.1137 6.6724
VPPM5 Virgin 5.5% 7.0% 5.5% 6.4968 -1.9279 0.3820 0.1224 2.52E-04 -0.1069 6.2468
VPPM6 Virgin 5.5% 7.0% 5.5% 8.3188 -2.1990 0.3777 -1.7090 2.27E-04 -0.1065 6.3398
VLPM1 Virgin 6.7% 3.0% 2.1% 5.2913 -1.7662 0.3813 1.3471 2.76E-04 -0.1121 6.4881
VLPM2 Virgin 6.7% 3.0% 1.7% 4.5099 -1.5705 0.4269 2.1074 3.01E-04 -0.1145 6.5384
VLPM3 Virgin 6.7% 5.0% 4.5% 7.3521 -2.0255 0.3493 -0.6909 4.98E-04 -0.1447 7.6910
VLPM3B Virgin 6.7% 5.0% 5.0% 4.9543 -1.7057 0.4049 1.5869 3.47E-04 -0.1185 6.5942
VLPM4 Virgin 6.7% 5.0% 4.8% 7.9998 -2.1602 0.3573 -1.3853 2.44E-04 -0.1068 6.2824
VLPM5 Virgin 6.7% 7.0% 7.2% 8.4071 -2.1188 0.3799 -1.9033 5.51E-04 -0.1416 7.2103
VLPM6 Virgin 6.7% 7.0% 8.0% 5.0538 -1.5131 0.4263 1.4048 4.43E-03 -0.5667 17.9429
PMALPM1 PMA 6.7% 3.0% 1.6% 2.5919 -1.1184 0.4718 3.9754 3.12E-04 -0.1190 6.7992
PMALPM2 PMA 6.7% 3.0% 1.7% 2.7471 -1.1822 0.4273 3.8449 2.82E-04 -0.1173 6.8271
PMALPM3 PMA 6.7% 5.0% 4.6% 3.4742 -1.3601 0.4365 3.0593 2.92E-04 -0.1171 6.7657
PMALPM4 PMA 6.7% 5.0% 4.4% 2.9967 -1.1645 0.4678 3.5098 2.64E-04 -0.1140 6.6793
PMALPM5 PMA 6.7% 7.0% 7.1% 4.8144 -1.5924 0.3927 1.6264 2.54E-04 -0.1114 6.5480
PMALPM6 PMA 6.7% 7.0% 6.7% 3.8065 -1.3463 0.4286 2.6299 2.57E-04 -0.1115 6.5434
FRACLPM1 Fiber Reinforced 6.7% 3.0% 2.3% 3.3866 -1.3658 0.4641 3.1645 2.64E-04 -0.1101 6.4134
FRACLPM2 Fiber Reinforced 6.7% 3.0% 2.3% 4.9957 -1.6674 0.3987 1.6410 3.45E-04 -0.1215 6.8130
FRACLPM3 Fiber Reinforced 6.7% 5.0% 5.0% 5.4578 -1.6557 0.3909 1.1170 2.94E-04 -0.1162 6.6930
FRACLPM4 Fiber Reinforced 6.7% 5.0% 4.4% 6.6733 -1.8883 0.3755 -0.0342 2.81E-04 -0.1142 6.6140
FRACLPM5 Fiber Reinforced 6.7% 7.0% 7.7% 4.3542 -1.4444 0.4461 2.0833 2.35E-04 -0.1050 6.6140
FRACLPM6 Fiber Reinforced 6.7% 7.0% 7.8% 6.2141 -1.7272 0.3787 0.3053 3.76E-04 -0.1241 6.8463
97
Figure 3-38 Master curves for VLPM at three different air voids
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10000000
1.00E-06 1.00E-05 1.00E-04 1.00E-03 1.00E-02 1.00E-01 1.00E+00 1.00E+01 1.00E+02 1.00E+03 1.00E+04 1.00E+05 1.00E+06
Dy
na
mic
Mo
du
lus
E*
(ps
i)
Frequency (Hz)
VLPM1: Pb=6.7%, Va=2.1%
VLPM3B: Pb=6.7%, Va=5.0%
VLPM6: Pb=6.7%, Va=8.0%
98
Figure 3-39 Master curves for PMALPM at three different air voids
As can be seen from Figure 3-37, Figure 3-38, Figure 3-39, and Figure 3-41, air voids
show considerable influence on the stiffness of each of the mixtures. Furthermore, the effect of
air voids appear to be similar for all laboratory produced mixes. For the plant produced mixes,
which has a coarser gradation with 19.0 mm nominal maximum aggregate size, air voids appears
to have an effect only for the high temperatures and low frequencies (as shown in Figure 3-40).
10
100
1000
10000
100000
1000000
10000000
1.00E-06 1.00E-05 1.00E-04 1.00E-03 1.00E-02 1.00E-01 1.00E+00 1.00E+01 1.00E+02 1.00E+03 1.00E+04 1.00E+05 1.00E+06
Dy
na
mic
Mo
du
lus
E*
(ps
i)
Frequency (Hz)
PMALPM1: Pb=6.7%, Va=1.6%
PMALPM3: Pb=6.7%, Va=4.6%
PMALPM6: Pb=6.7%, Va=7.1%
99
Figure 3-40 Master curves of all specimens for VPPM at three different air voids
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100000
1000000
10000000
1.00E-06 1.00E-05 1.00E-04 1.00E-03 1.00E-02 1.00E-01 1.00E+00 1.00E+01 1.00E+02 1.00E+03 1.00E+04 1.00E+05 1.00E+06
Dy
na
mic
Mo
du
lus
E*
(ps
i)
Frequency (Hz)
VPPM1: Pb=5.5%, Va=0.8%
VPPM2: Pb=5.5%, Va=0.7%
VPPM3: Pb=5.5%, Va=2.4%
VPPM4: Pb=5.5%, Va=2.5%
VPPM5: Pb=5.5%, Va=5.5%
VPPM6: Pb=5.5%, Va=5.5%
100
Figure 3-41 Master curves for FRACLPM at three different air voids
The trend seen in the dynamic modulus Master Curves (Figures 3-38, 3-39, and 3-41) for
the laboratory prepared mixes is consistent with the results obtained by Archilla (2010). That is,
an increase in air voids results in a decrease in dynamic modulus. Figure 3-42 (from Archilla,
2010) shows the comparison of Master Curves for mixes prepared using polymer modified
asphalt with a binder content of 5.8% and compacted at four different air voids (3%, 5%, 7%,
and 9%).
10
100
1000
10000
100000
1000000
10000000
1.00E-06 1.00E-05 1.00E-04 1.00E-03 1.00E-02 1.00E-01 1.00E+00 1.00E+01 1.00E+02 1.00E+03 1.00E+04 1.00E+05 1.00E+06
Dy
na
mic
Mo
du
lus
E*
(ps
i)
Frequency (Hz)
FRACLPM1: Pb=6.7%, Va=2.3%
FRACLPM3: Pb=6.7%, Va=5.0%
FRACLPM6: Pb=6.7%, Va=7.8%
101
Figure 3-42 Comparison of master curves for mixes prepared using polymer modified binder and
compacted at different air voids
A comparison among the three different mix types is presented in Figures 3-43 through 3-
45 for target air voids at 3%, 5%, and 7% respectively.
1,000
10,000
100,000
1,000,000
10,000,000
1.00E-05 1.00E-04 1.00E-03 1.00E-02 1.00E-01 1.00E+00 1.00E+01 1.00E+02 1.00E+03 1.00E+04
|E*|
(p
si)
Reduced Frequency (Hz)
Va = 3%, VFA = 78.1, Pb = 5.8%
Va = 5%, VFA = 67.7, Pb = 5.8%
Va = 7%, VFA = 59.4, Pb = 5.8%
Va = 9%, VFA = 52.7, Pb = 5.8%
102
Figure 3-43 Master curve comparison among the three types of laboratory prepared mixtures
compacted at target Va=3%
10
100
1000
10000
100000
1000000
10000000
1.00E-06 1.00E-05 1.00E-04 1.00E-03 1.00E-02 1.00E-01 1.00E+00 1.00E+01 1.00E+02 1.00E+03 1.00E+04 1.00E+05 1.00E+06
Dy
na
mic
Mo
du
lus
E*
(ps
i)
Frequency (Hz)
VLPM1: Pb=6.7%, Va=2.1%
FRACLPM1: Pb=6.7%, Va=2.3%
PMALPM1: Pb=6.7%, Va=1.6%
103
Figure 3-44 Master curve comparison among the three types of laboratory prepared mixtures
compacted at target Va=5%
10
100
1000
10000
100000
1000000
10000000
1.00E-06 1.00E-05 1.00E-04 1.00E-03 1.00E-02 1.00E-01 1.00E+00 1.00E+01 1.00E+02 1.00E+03 1.00E+04 1.00E+05 1.00E+06
Dy
na
mic
Mo
du
lus
E*
(ps
i)
Frequency (Hz)
VLPM3B: Pb=6.7%, Va=5.0%
FRACLPM3: Pb=6.7%, Va=5.0%
PMALPM3: Pb=6.7%, Va=4.6%
104
Figure 3-45 Master curve comparison among the three types of laboratory prepared mixtures
compacted at target target Va=7%
From Figure 3-43 through Figure 3-45, it is clear that, regardless of air voids, PMA
mixtures are stiffer at high temperatures and low frequencies compared to fiber reinforced
asphalt concrete mixtures and mixtures prepared using virgin binder. It must however be noted
that the PMA mixes had lower air voids. Thus the actual differences at exactly the same air voids
are expected to be slightly smaller. Furthermore, the dynamic modulus master curves at lowest
test temperature (40 °F) at high frequencies cluster over the top of one another. For clearer
understanding of the difference in the behavior of different types of HMA mixtures used in this
study, a separate comparison of dynamic modulus values at different frequencies needs to be
10
100
1000
10000
100000
1000000
10000000
1.00E-06 1.00E-05 1.00E-04 1.00E-03 1.00E-02 1.00E-01 1.00E+00 1.00E+01 1.00E+02 1.00E+03 1.00E+04 1.00E+05 1.00E+06
Dy
na
mic
Mo
du
lus
E*
(ps
i)
Frequency (Hz)
VLPM6: Pb=6.7%, Va=8.0%
FRACLPM6: Pb=6.7%, Va=7.8%
PMALPM6: Pb=6.7%, Va=6.7%
105
performed. For brevity, the actual test data comparing the dynamic modulus values at 10 Hz is
provided in Figure 3-46. The chart at 10 Hz is shown because 10 Hz typically represent the
speeds of vehicles on actual arterial streets.
Figure 3-46 Comparison of dynamic modulus values for three different types of HMA mixtures
at 40 °F at 10 Hz
At low temperature, in order for the mixtures to have better resistance to cracking, it is
desirable to have mixes with less stiffness. Figure 3-46 shows that neither polymer modified
asphalt nor fibers have any effect on the stiffness of the mixture at low temperature (40 °F) and
10 Hz.
The dynamic modulus test results at high temperature on mixes prepared using FORTA
fibers and compacted at intermediate air voids (~5%) show lower stiffness values compared to
the |E*| values observed with the mixes prepared using unmodified binder. For mixes that are
compacted at high air voids (~7%) and tested at high temperature and low frequency, there is no
25
85
49
5
23
05
79
0
16
75
54
8
25
33
51
3
22
51
56
0
16
99
03
8
26
53
79
0
22
44
89
0
16
59
01
8
1000000
1400000
1800000
2200000
2600000
3000000
Va=
3%
Va=
5%
Va=
7%
Dyn
amic
Mo
du
lus
(psi
)
Target Air Voids
Virgin Mix Fiber Reinforced Asphalt Concrete Mix Polymer Modified Asphalt Concrete Mix
106
conclusive difference between the stiffness values for mixes prepared using unmodified binder
and mixes prepared using fibers. The comparison of stiffness values using dynamic modulus
tests on control mix and mixes blended with FORTA fibers (one sample at 1lb/ton and the
second one at 2lb/ton) were performed by Kaloush et al. (2008). In that study, the dynamic
modulus tests were performed on HMA samples compacted at target air voids of 7%. The master
curves constructed using the results of the study are presented in Figure 3-47. As can be seen
from the figure, the dynamic modulus values at low temperature is higher than the |E*| values of
mixes prepared using unmodified binder, and the |E*| values of mixes prepared using 1lb/ton and
2lb/ton fibers at high temperature and low frequencies are lower compared to control mixes.
Figure 3-47 Unconfined Dynamic Modulus Master Curves for FORTA Evergreen Control, 1
lb/Ton and 2 lb/Ton Mixtures (Kaloush et al, 2008)
107
3.9 Repeated Load Axial Test (RALT)
The RALT was performed using the IPC Global Simple Performance Tester (SPT),
which is shown in Figure 3-33. The preparation of the test specimen for the RALT is relatively
simple. The specimen is placed inside a rubber latex membrane and the top and bottom loading
platens are tightly sealed using O-rings. Next, the entire assembly is placed inside the testing
chamber (as shown in Figure 3-48) and the hydraulic system is connected to the bottom loading
platen. In RALT, the steel ball is not placed on top of the top loading platen. The testing chamber
is closed and the temperature control unit is used to set the desired temperature.
Figure 3-48 Specimen assembly inside the testing chamber
The RALT is performed by repeatedly applying a compressive load on the test
specimens. The compressive load applied is in the haversine form with a loading pulse of 0.1
seconds followed by a rest period of 0.9 seconds. The test specimens were conditioned inside the
testing chamber at 54 °C for a period of 3 hours if the test specimen was followed from a
dynamic modulus test or 4 hours if the sample was at the room temperature. A confining stress of
108
138 kPa (20 psi), contact stress of 41.4 kPa (6 psi), and a deviator stress of 828 kPa (120 psi) was
applied to the specimen for the entire duration of the test. The values for different stresses were
selected based on the recommendations from previous research efforts by Witczak (2002) in
NCHRP report No. 465. As documented in Archilla (2008), the test temperature of 54 °C was
selected based on the following factors: (a) according to the Long Term Pavement Performance
(LTPP) bind software, considering 35 weather stations in Hawaii, it was observed that the testing
temperatures between 54 °C and 64 °C would cover most of the situations to which pavements in
Hawaii would be subjected to and (b) the capability of SPT to achieve and maintain 54 °C inside
the testing chamber was considered reasonable. The test was terminated when a maximum of
20,000 cycles was reached or when the sample accumulated a deformation of 100,000 micro
strains. Since this is a destructive test, the specimen is damaged at the end of the test. An
example of how the specimen looks like at the end of a test is shown in Figure 3-49.
Figure 3-49 Deformed specimen at the end of flow number test (Specimen ID shown in this
figure is VPPM5)
109
A sample output from the IPC Global Flow Test software is presented in Figure 3-50.
The figure shows a monotonically increasing total axial strain and axial strain rate on the two y-
axes, and the number of (cycles) repetitions on the x-axis. The vertical line is the flow number
calculated by the IPC Global software. It can be seen that the total axial strain (permanent strain)
displays the typical three stages of a permanent deformation tests. The vertical line provides an
estimate of the boundary between the secondary and tertiary stages, which defines the inflection
point of the permanent deformation curve and which as indicated before is known as the Flow
Number (FN). This number is used as the upper limit of the data used in calculating the
parameters k1 and k3 for Equation 2.31.
Figure 3-50 Screenshot of the Permanent Deformation test output
110
An example showing the accumulation of permanent strain (Test Points) for a specimen
is presented in Figure 3-51. The FN for this specimen reported by the SPT software was 107.
The FN estimated using the three parameter model proposed by Archilla et al (2007) was found
to be 122. It should be noted that the difference in FN values in this example is not “large”.
However, the difference in some cases can be substantial, as can be seen from the FN values in
Table 3-9.
Figure 3-51 Example of the accumulation of permanent strain and fitting of three parameter
model proposed by Archilla et al (2007) for Specimen ID VLPM6
The most widely used power model includes the first two deformation stages and
excludes the tertiary stage. The model parameters can be greatly affected by the consideration
given to the number of initial observations (Test Points) included in the estimation. Since the
data from tertiary stage is excluded from the analysis, it becomes straightforward to accept the
FN as the end point of the secondary stage. The number of initial observations is considered
1000
10000
100000
1000000
1 10 100 1000
Perm
an
en
t S
train
(ε
p)
Number of Load Repetitions
Test Points
FN estimated by SPT Machine
FN estimated using Archilla et al. (2007)
Power (Model)
FN estimated using Archilla et al. (2007) procedure
FN estimated by SPT Machine
Trimmed Data range used to Estimate the Power Model
111
based on the justification provided by Diaz et al (2008). Accordingly, 10% of the initial
observations were excluded and the parameters were estimated. An example showing the actual
data (Test Points), trimmed data, and estimated power model is shown in Figure 3-52. This
procedure was repeated to all specimens and the values are tabulated in Table 3-10. The power
model for trimmed data for all the samples is included in Appendix C.
Figure 3-52 Example of fitting the power model for Specimen ID VLPM6
100
1000
10000
100000
1000000
1 10 100 1000
Pe
rman
en
t St
rain
(
p)
Number of Load Repetitions
Test Points
Power (Model)
112
Table 3-10 Permanent deformation parameters and Flow Number
Specimen Information FN From
SPT
Machine
Equation 2.30 parameters
FN p @ FN
Equation 2.28 parameters Average
k3 r Mix ID Mix Type
Pb
(%)
Target
Va (%)
Actual
Va (%) k1 k3
VPPM1 Virgin 5.5% 3.0% 0.8% 316 3.194 1.01E-04 695.8 346 8820.1 -3.9513 0.321 0.415
2630.6
VPPM2 Virgin 5.5% 3.0% 0.7% 249 2.093 1.01E-04 652.6 265 7279.7 -5.0816 0.509 11208.2
VPPM3 Virgin 5.5% 5.0% 2.4% 432 2.186 5.68E-05 1072.4 449 13304.3 -4.2733 0.480 0.386
2909.5
VPPM4 Virgin 5.5% 5.0% 2.5% 221 3.739 7.96E-05 456.8 237 11555.2 -3.8063 0.292 3270.9
VPPM5 Virgin 5.5% 7.0% 5.5% 196 2.283 3.97E-05 469.8 202 19568.4 -3.8605 0.417 0.476
3394.8
VPPM6 Virgin 5.5% 7.0% 5.5% 138 2.084 2.97E-05 364.6 148 24592.7 -3.9320 0.535 3161.6
VLPM1 Virgin 6.7% 3.0% 2.1% 338 2.782 9.22E-05 776.6 367 9244.5 -4.0782 0.363 0.356
2833.5
VLPM2 Virgin 6.7% 3.0% 1.7% 244 2.988 7.13E-05 533.0 259 12239.3 -3.8824 0.348 2939.7
VLPM3 Virgin 6.7% 5.0% 4.5% Sample damaged while fixing the SPT machine.
VPLM3B Virgin 6.7% 5.0% 5.0% 76 1.811 4.70E-05 509.9 184 13645.5 -4.0703 0.441 0.444
3516.5
VLPM4 Virgin 6.7% 5.0% 4.8% 201 2.124 5.26E-05 470.3 193 14104.7 -4.0514 0.448 3279.0
VLPM5 Virgin 6.7% 7.0% 7.2% 103 3.097 6.87E-05 232.3 114 12843.2 -3.9444 0.364 0.340
4398.0
VLPM6 Virgin 6.7% 7.0% 8.0% 107 3.304 4.30E-05 242.4 122 20842.5 -3.8678 0.316 7356.2
PMALPM1 PMA 6.7% 3.0% 1.6% 1234 5.685 9.70E-05 3112.6 1747 9969.4 -3.7838 0.194 0.203
3118.8
PMALPM2 PMA 6.7% 3.0% 1.7% 3813 5.199 1.62E-04 7023.5 3892 5931.7 -4.0647 0.212 2594.9
PMALPM3 PMA 6.7% 5.0% 4.6% 544 2.582 3.85E-05 1238.2 567 21485.8 -3.9874 0.424 0.406
3097.1
PMALPM4 PMA 6.7% 5.0% 4.4% 516 2.698 5.03E-05 1307.8 611 16748.9 -4.0270 0.388 3237.7
PMALPM5 PMA 6.7% 7.0% 7.1% 150 2.237 2.32E-05 386.5 164 33149.1 -3.9149 0.501 0.422
4624.8
PMALPM6 PMA 6.7% 7.0% 6.7% 194 2.994 3.81E-05 428.1 208 22921.7 -3.7963 0.342 5041.3
FRACLPM1 Fiber Reinforced 6.7% 3.0% 2.3% 289 2.898 8.06E-05 595.1 286 10725.9 -3.9223 0.333 0.340
2971.2
FRACLPM2 Fiber Reinforced 6.7% 3.0% 2.3% 291 3.016 7.84E-05 565.5 276 11155 -3.9199 0.348 2870.3
FRACLPM3 Fiber Reinforced 6.7% 5.0% 5.0% 92 1.811 4.10E-05 629.0 227 15644.4 -4.1539 0.469 0.382
3829.1
FRACLPM4 Fiber Reinforced 6.7% 5.0% 4.4% 268 3.128 7.68E-05 894.6 442 11517.1 -3.9045 0.296 3334.4
FRACLPM5 Fiber Reinforced 6.7% 7.0% 7.7% 236 3.875 5.29E-05 467.4 245 17505.1 -3.8069 0.289 0.306
4991.7
FRACLPM6 Fiber Reinforced 6.7% 7.0% 7.8% 186 3.295 4.35E-05 439.2 220 20579.5 -3.8122 0.324 5087.6
113
As explained in section 2.10, the flow number is the point at which the specimen begins
to fail. Also, as seen from Table 3-10, the FN can be different when calculated using different
models. Flow Number is a good indicator to characterize permanent deformation behavior of
HMA mixes, but it should probably not be used as the sole indicator to characterize the mixes.
Figure 3-53 presents a visual plot of actual air voids of each specimen plotted against the
corresponding FN value. Because the FN values had a large range, the y-axis (FN) is plotted on a
log scale.
Figure 3-53 Comparison of flow number vs. air voids for different types of laboratory produced
HMA mixtures
As can be seen from Figure 3-52, the FN values for mixes prepared using unmodified
binder decrease with increase in the air voids. This trend is also true for specimens prepared
using polymer modified mixes. Note that the FN values for mixes prepared using FORTA fibers
10
100
1000
10000
0.0% 1.0% 2.0% 3.0% 4.0% 5.0% 6.0% 7.0% 8.0% 9.0%
Flo
w N
um
be
r
Air Voids (Va)
VPPM VLPM PMALPM FRACLPM
114
are almost constant irrespective of the air voids. In a study by Kaloush et al. (2008) it has been
reported that the FN for mixes with 1lb/ton of fibers was 115 times higher than the FN for mixes
prepared using unmodified binder. It must be noted that the repeated load axial test was
performed using a deviator stress of 15 psi (105 kPa).
Another important indicator of the performance of HMA mixtures is the rate at which the
specimen accumulates the permanent strain. The parameter k3 in the power model (Equation
2.28) indicates the rate at which the sample is accumulating permanent strain.
Logically, the rate at which the specimens accumulate permanent deformation should
increase with increase in air voids. In other words, the denser the material, the smaller is the rate
at which the permanent deformation accumulates. A cursory look at the k3 values in Table 3-10
indicates a noisy trend in many cases.
The average slope (k3) value for polymer modified asphalt concrete mixtures is the
lowest compared to virgin and fiber reinforced concrete mixtures at low air voids (~3%). At
intermediate and higher air voids, the fiber reinforced asphalt concrete mixtures had the lowest
K3 value. Kaloush et al. (2008) reported that for the samples prepared using FORTA fibers (at a
target Va = 7%), the slope of the permanent strain curve for mixes prepared using unmodified
binder was higher compared to the slope of the permanent strain curve for mixes prepared using
fibers.
The plant produced mixtures produced using virgin binder does not show any particular
trend vis-à-vis the rate at which the sample fails.
115
CHAPTER 4
SUMMARY AND CONCLUSIONS
4.1 Resilient Modulus of Base Course Materials
1. The resilient modulus of virgin aggregates and FA mixtures show an increasing trend
with increase in bulk stress at increasing levels of compaction.
2. For virgin aggregates, a higher compaction level translates into a higher resilient modulus
for the same deviator stress. However, for FA mixture specimens, an increase in the
modulus is observed with increase in deviator stress at all confining stress levels for
specimens compacted at 98% of maximum dry density. For the specimens compacted at
100% of maximum dry density, a slight increase in modulus with deviator stress is
observed. Furthermore, for the specimens compacted at 102% of maximum dry density, it
is observed that the resilient modulus decreases with increase in deviator stress at all
confining levels.
3. The coefficient K2 in the NCHRP 1-37A equation, which is the exponent for the bulk
stress term, is positive. This indicates that increases in bulk stress increase the stiffness of
virgin aggregates and FA mixtures.
4. The coefficient K3 in NCHRP 1-37A equation, which is the exponent for the shear stress
term, is negative for FA mixtures, suggesting the stiffness of FA mixtures decrease with
increases in octahedral shear stress.
5. The sign of the coefficient K3 in the NCHRP 1-37A equation is positive for specimens
compacted using virgin aggregates, which means an increase in octahedral shear stress
increases the resilient modulus of the material.
116
6. The results of the study showed that the Mr of FA mixtures is in general between 2.5 and
5 times (corresponding to lowest and highest levels of bulk stress respectively) higher
than the Mr of virgin aggregates at 98% and 100% of maximum dry density, whereas at
102% of maximum dry density, the Mr of FA mixtures is in general between 2.8 and 1.8
times (corresponding to lowest and highest levels of bulk stress respectively) higher than
the Mr of virgin aggregates.
4.2 Dynamic Modulus and Permanent Deformation of HMA Mixtures
The Dynamic modulus tests using AASHTO TP62 were performed on HMA specimens
produced using virgin and polymer modified binder, and HMA mixtures blended with FORTA
fibers. With the caveat that (a) there are some differences in the actual air voids of the compacted
specimens with the same target air voids and (b) a small sample size is used to make the
conclusions, the testing results lead to the following conclusions:
4.2.1 Dynamic Modulus of HMA Mixtures
1. The stiffness of compacted HMA specimens prepared using polymer modified mixes
show an increase in the dynamic modulus values at high temperature (104 °F) and lowest
frequency (0.01 Hz) compared to the mixes prepared with virgin binder or fiber
reinforced asphalt concrete mixes.
2. For the plant produced mixes, which has a coarser gradation with 19.0 mm nominal
maximum aggregate size, air voids appears to have an effect only for the high
temperatures and low frequencies.
117
3. There was no effect of either polymer modification or addition of fibers to the dynamic
modulus values at low temperature and high frequency at all target air voids.
4.2.2 Flow Number Test on HMA Mixtures
1. The FN values of mixes prepared using polymer modified mixes at low and medium air
voids are higher compared to the FN values for other types of laboratory prepared mixes
at same approximate air voids. For higher air voids (~7%), the FN for PMA mixes are
higher than the FN for the mixes prepared using unmodified binder.
2. The FN values for all specimens prepared using fibers are relatively constant at all air
voids.
3. The average slope (k3) value for polymer modified asphalt concrete mixtures is the
lowest compared to virgin and fiber reinforced concrete mixtures at low air voids (~3%).
At intermediate and higher air voids, the fiber reinforced asphalt concrete mixtures had
the lowest K3 value.
4. Between the virgin and fiber reinforced mixtures, the average k3 values for fiber
reinforced asphalt concrete mixes show a relatively lower strain rate compared to
mixtures prepared using virgin binder at corresponding target air voids.
5. The plant produced and laboratory produced mixes using unmodified binder does not
show a particular trend with respect to the rate of accumulation of permanent strain.
6. The FN values estimated by the SPT software is always lower compared to the FN values
estimated using the Archilla et al (2007) procedure. This is because the FN estimated
using SPT software relies on the moving average points for data smoothing, which can be
118
affected by noise in the data, whereas the FN estimated using Archilla et al (2007) fits the
data using non-linear regression and is relatively insensitive to such noise.
4.3 Contributions of the Study
In addition to the above conclusions, the following are additional contributions of this
study.
1. This study has contributed dynamic modulus test results of 25 samples involving
different air voids, two different aggregate gradations, and two different asphalt binder
contents to the existing database of 84 samples that were prepared and tested at two
different aggregate gradations, three different target air voids, and three different asphalt
binder contents by Archilla (2008).
2. Test results of six fiber reinforced HMA specimens at three different target air voids are
added to the existing database of 84 specimens.
3. The dynamic modulus and permanent deformation test results from these 25 samples can
be added to the existing database of 84 samples and used to re-compute the model
estimated by Archilla (2008).
119
REFERENCES
Akeroyd, F.M.L. & Hicks, B. J. (1988). Foamed Bitumen Road Recycling. Highways.
Al-Qadi, I. L., Elseifi, M., & Carpenter, S. H. (2007). Reclaimed Asphalt Pavement – A
Literature Review, FHWA-ICT-07-001, A report of the findings of ICT R27-11,
Determination of Usable Residual Asphalt Binder in RAP, Illinois Center for
Transportation. Distribution.
Alakona. (2008). Foamed Bitumen Mix Design Report, Prepared by Loudon International.
Retrieved from the Alakona Corporation website http://www.alakona.com/pdf/Alakona
Report.pdf.
Archilla, A. R., Diaz, Luis G. and Carpenter, S (2007). Proposed Method to Determine the Flow
Number in Bituminous Mixtures from Repeated Axial Load Tests. Journal of
Transportation Engineering, American Society of Civil Engineers, pp. 610-617.
Archilla, A R., Ooi, Phillip S. K., & Sandefur, K. G. (2007). Estimation of a Resilient Modulus
Model for Cohesive Soils Using Joint Estimation and Mixed Effects. Journal of
Geotechnical and Geoenvironmental Engineering, 133(8), 984.
Archilla,A, R., (2008). Effect of Polymer Modified Asphalt Binders on the Performance of
Asphalt Concrete Mixes Used in Hawaii. Final Report, Honolulu, HI
Archilla, A.R. (2010). Developing Master Curve Predictive Equation Models for Local
Conditions: A Case Study for Hawaii. Association of Asphalt Paving Technologists.
Volume 79.
ARRA. (2001). Basic Asphalt Recycling Manual. US Department of Transportation.
ARTS (2010). Rubber-modified Hot-mix Asphalt Laboratory Performance Study. Retrieved
from http://www.clemson.edu/ces/arts/ARTS_hot-mix_study.pdf
Asphalt Institute (2007). The Asphalt Handbook, Manual Series No. 4 (MS-4), 7th
Edition, The
Asphalt Institute, Lexington, Kentucky.
Barksdale, R. D. (1972). Laboratory evaluation of Rutting in Basecourse materials. Proceedings
of the 3rd International Conference on Structural Design of Asphalt Pavements (pp. 161-
174).
Barksdale, R. D., & Itani, S. Y. (1989). Influence of Aggregate Shape on Base Behavior.
Transportation Research Record: Journal of the Transportation Research Board, National
Research Council, Washington, D.C, (1227), 173-182.
120
Bissada, A. F. (1987). Structural Response of Foamed-asphalt-sand Mixtures in Hot
Environments. Transportation Research Record: Journal of the Transportation Research
Board, National Research Council, Washington, D.C., (1115), 134-149.
Bouldin, M.G. and J.H. Collins (1990). Wheel Tracking Experiments with Polymer Modified and
Unmodified Hot Mix Asphalt, Polymer Modified Asphalt Binders, ASTM STP 1108,
American Society of Testing Materials.
Bowering, R. H. (1970). Properties and Behaviour of Foamed Bitumen Mixtures for Road
Building. Proceedings of the 5th Australian Road Research Board Conference, Canberra,
Australia.
Bowering, R.H. & Martin, C. L. (1976). Foamed bitumen production and application of
mixtures, evaluation and performance of pavements. Proceedings of the Association of
Asphalt Paving Technologists (pp. 453-477).
Bueno, B. S., Silva, W. R., Lima, D. C., Minete, E. (2003). Engineering Properties of Fiber
Reinforced Cold Asphalt Mixes. Technical Note, Journal of Environmental Engineering,
ASCE, Vol. 129, N. 10.
Brennen, M., Tia, M., Altschaeffl, A.G. & Wood, L. E. (1983). Laboratory Investigation of the
Use of Foamed Asphalt for Recycled Bituminous Pavements. Transportation Research
Record: Journal of the Transportation Research Board, National Research Council,
Washington, D.C., (911), 80-87.
Brown, S. F., & Hyde, A. F. L. (1975). Analysis of Pavements with Granular Bases.
Transportation Research Record: Journal of the Transportation Research Board, National
Research Council, Washington, D.C, (537), 49-58.
Castedo-Franco, L.H., Beaudoin, C.C., Wood, E.L. & Altschaeffl, A. G. (1984). Durability
Characteristics of Foamed Asphalt Mixtures. Proceedings of the 29th Annual Canadian
Technical Asphalt Association Conference, Montreal, Canada.
Chiu, C., & Lewis, A. (2002). A Study on Properties of Foamed-Asphalt-Treated Mixes. Journal
of Testing and Evaluation.
Christopher, B. R., Schwartz, C., & Boudreau, R. (2006). Geotechnical Aspects of Pavements.
FHWA NHI-05-037, National Highway Institute, US Department of Transportation.
Construction Equipment. (2005). Foamed Asphalt Offers Impressive Benefits. Retrieved from
http://www.constructionequipment.com/foamed-asphalt-offers-impressive-benefits
Coree, B., Ceylan, Halil., & Harrington D,. (2005) Implementing the Mechanistic-Empirical
Pavement Design Guide: Technical Report. IHRB Project TR-509, IA
121
Csanyi, L. H. (1957). Foamed Asphalt in Bituminous Paving Mixtures. Highway Research
Record, National Research Council, Washington D.C, (160), 108-122.
Drumm, E. C., Reeves, J. S., Madgett, M. R., & Trolinger, W. D. (1997). Subgrade Resilient
Modulus Correction for Saturation Effects. Journal of Geotechnical and Geoenvironmental
Engineering, 123(7), 663.
Dunlap, W. A. (1966). Deformation Characteristics of Granular Materials Subjected to Rapid
Repetitive Loading. PhD thesis, Texas A&M University, College Station, Texas.
Dunlap, W. A. (1963). Resilient deformation characteristics of granular materials. Technical
Report. No. 1, Project 2-8-62-27, Texas Transportation Institute, Texas A&M University,
College Station, Texas.
DuPont (2008). http://www2.dupont.com/Elvaloy/en_US/products/elvaloy_asphalt_
modifiers.html (last accessed, July 2008).
Dwyer, J., & Betts, M. (2011). Polymer-Modified Asphalt: Improving our Nation’s
Infrastructure. Eleventh Annual Freshman Conference, University of Pittsburg, Swanson
School of Engineering.
Ebels, L. J., & Jenkins, K. J. (n.d.). Determination of Material Properties of Bitumen Stabilised
Materials using Tri-axial Testing. Institute for Transport Technology, Civil Engineering
Department, Stellenbosch University, South Africa.
Eller, A., & Olson, R. (2009). Recycled Pavements Using Foamed Asphalt in Minnesota. Office
of Materials & Road Research Minnesota Department of Transportation, Maplewood, MN.
FHWA. (1981). Materials Notebook: Hot and Cold Recycling of Asphalt Pavements. FHWA N.
5080.93.
FHWA. (1997). User Guidelines for Waste and Byproduct Materials in Pavement Construction.
Publication Number: FHWA-RD-97-148.
FHWA (2002). Study of LTPP Laboratory Resilient Modulus Test Data and Response
Characteristics: Final Report. Publication Number: FHWA-RD-02—051.
FHWA. (2004). Transportation Applications of Recycled Concrete Aggregate. FHWA State of
the Practice National Review.
Fu, P., & Harvey, J. (2007). Temperature Sensitivity of Foamed Asphalt Mix Stiffness: Field and
Lab Study. International Journal of Pavement Engineering, 8(2), 137-145.
George, K.P. (2004). Prediction of Resilient Modulus from Soil Index Properties. Publication
Number: FHWA/MS-DOT-RD-04-172.
122
Gidel, G., Hornych, Pierre, & Chauvin, J.-J. (2001). A new approach for investigating the
permanent deformation behaviour of unbound granular material using the repeated load
triaxial apparatus. Bulletin Des Labpratproes Des Ponts Et Chaussees, 233(4359), 5-21.
Gonzalez, A., Cubrinovski, M., Pidwerbesky, B., & Alabaster, D. (2011). Strength and
Deformational Characteristics of Foamed Bitumen Mixes under Suboptimal Conditions.
Journal of Transportation Engineering, (January), 1-10.
Gui-ping, H., & Wing-gun, W. (2008). Effects of moisture on strength and permanent
deformation of foamed asphalt mix incorporating RAP materials. Construction and
Building Materials, 22(1), 30-40.
Haider, S. W., Baladi, G. Y., Lansing, E., & Akram, T. (2008). Development of Guidelines for
Flexible Pavement.
HDOT. (2005). Standard Specifications for Road and Bridge Construction, Hawaii Department
of Transportation, HI.
Heydinger, A. G., Xie, Q. L., Randolph, B. W., Gupta, J. D. (1996). Analysis of Resilient
Modulus of Dense and Open-graded Aggregates. Transportation Research Record: Journal
of the Transportation Research Board, National Research Council, Washington, D.C,
(1547), 1-6.
Hicks, R. G., & Monismith, C. L. (1971). Factors Influencing the Resilient Properties of
Granular Materials. Highway Research Record, (345), 15-31.
Hornych P., Corté J.F., P. J. L. (1993). Etude Des Déformations Permanentes Sous Chargement
Répétés De Trois Ggraves Non Traitées. Bull liaison Labo P et (pp. 45-55).
Hornych, P, & Abd, A. E. (2004). Selection and Evaluation of Models for Prediction of
Permanent Deformations of Unbound Granular Materials in Road Pavements. Document #
SAM-05-DE10, Sustainable and Advanced Materials for Road Infrastructure, Work
Package 5 Performance-based specification.
Hossain, S. (2008). Characterization of Subgrade Resilient Modulus for Virginia Soils and Its
Correlation with the Results of Other Soil Tests. Report No. VTRC 09-R4. Virginia
Transportation Research Council, VA.
Huang, Y. H. (1993). Pavement Analysis and Design (2nd ed.). Upper Saddle River, NJ: Pearson
Prentice Hall.
Jenkins, K J, Long, F. M., & Ebels, L J. (2007). Foamed bitumen mixes = shear performance?
International Journal of Pavement Engineering, 8(2), 85-98.
123
Jenkins, Kim Jonathan. (2000). Mix Design Considerations for Cold and Half-warm Bituminous
Mixes with Emphasis on Foamed Bitumen. PhD dissertation, Department of Civil
Engineering, University of Stellenbosch, South Africa.
Kamal, M. A., Dawson, A. R., Farouki, O. T., Hughes, D. A. B., & Sha’at, A. A. (1993). Field
and Laboratory Evaluation of the Mechanical Behaviour of Unbound Granular Materials in
Pavements. Transportation Research Record: Journal of the Transportation Research
Board, National Research Council, Washington, D.C., (1406), 88-97.
Kandhal, P. S., & Mallick, R. B. (1997). Pavement Recycling Guidelines for State and Local
Governments Participant’s Reference Book. Publication No. FHWA-SA-98-042.
Kaloush, K.E., Biligiri, K, P., Zeiada, W, A., Rodezno, C., Dwivedi, S., Reed, J., & Cary, C.
Evaluation of FORTA Fiber-Reinforced Asphalt Mixtures Using Advanced Material
Characterization Tests – Evergreen Drive, Tempe, Arizona.
Kendall, M., Baker, B., Evans, P., & Ramanujam, J. (1999). Foamed Bitumen Stabilisation.
Southern Region Symposium, Qld Department of Main Roads, Goondiwindi (pp. 1-18).
Kennedy, T. W., Tam, W. O., & Solaimanian, M. (1998). Optimizing Use of Reclaimed Asphalt
Pavement with the Superpave System. Journal of the Association of Asphalt Paving
Technologists, 67, 311-333.
Khedr, S. (1985). Deformation Characteristics of Granular Base Course in Fexible Pavement.
Transportation Research Record: Journal of the Transportation Research Board, National
Research Council, Washington, D.C., (1043), 131-138.
Khoury, N. N., & Zaman, M. M. (2004). Correlation Between Resilient Modulus, Moisture
Variation, and Soil Suction for Subgrade Soils. Transportation Research Record: Journal of
the Transportation Research Board, National Research Council, Washington, D.C., (1874),
99-107.
Kim, Y, Lee, H. D., & Heitzman, M. (2009). Dynamic Modulus and Repeated Load Tests of
Cold In-Place Recycling Mixtures Using Foamed Asphalt. Journal of Materials in Civil
Engineering, 21(6), 279.
Lashine, A.K.F, Brown S.F., P. P. S. (1971). Dynamic Properties of Soils, Dept of Civil
Engineering, University of Nottingham.
Lee, D. Y. (1981). Treating Marginal Aggregates and Soil with Foamed Asphalt. Proceedings of
the Association of Asphalt Paving Technologists.
Lee, S. J., Rust, J. P., Hamouda, H., Kim, Y. R., Borden, R. H. (2005). Fatigue Cracking
Resistance of Fiber-Reinforced Asphalt Concrete. Textile Research Journal, Vol. 75, N.
2, pp. 123-128.
124
Lekarp, F, & Dawson, A. (1998). Modelling Permanent Deformation Behaviour of Unbound
Granular Materials. Construction and Building Materials, 12(1), 9-18.
Lekarp, Fredrick, Isacsson, U., & Dawson, Andrew. (2000a). State of the Art. II: Permanent
Strain Response of Unbound Aggregates. Journal of Transportation Engineering, 126(1),
76-83.
Lekarp, Fredrick, Isacsson, U., & Dawson, Andrew. (2000b). State of the Art. I: Resilient
Response of Unbound Aggregates. Journal of Transportation Engineering, 126(1), 66-75.
Lentz, R. W., Baladi, G. Y. (1981). Constitutive Equation for Permanent Strain of Sand
Subjected to Cyclic Loading. Transportation Research Record: Journal of the
Transportation Research Board, National Research Council, Washington, D.C., (810), 50-
54.
Li, D., & Selig, E. T. (1994). Resilient Modulus for Fine-Grained Subgrade Soils. Journal of
Geotechnical Engineering, 120(6), 939-957. doi: 10.1061/(ASCE)0733-
9410(1994)120:6(939).
Lu X., and U. Isacsson (1999). Chemical and Rheological Characteristics of Styrene-Butadiene-
Styrene Polymer-Modified Bitumens, Transportation Research Record, No. 1661,
National Academy of Sciences, Washington, D.C., pp. 83-92.
Loizos, A. (2007). In-situ characterization of foamed bitumen treated layer mixes for heavy-duty
pavements. International Journal of Pavement Engineering, 8(2), 123-135.
Maccarrone, S., Holleran, G. & Ky, A. (1995). Cold Asphalt Systems as an Alternative to Hot
Mix. 9th AAPA International Asphalt Conference.
May, R. W., Witczak, M. W. (1981). Effective granular modulus to model pavement responses.
Transportation Research Record: Journal of the Transportation Research Board, National
Research Council, Washington, D.C, (810), 1-9.
Mohammad, L., Y. Abu-Farsakh, M., Wu, Z., & Abadie, C. (2003). Louisiana Experience with
Foamed Recycled Asphalt Pavement Base Materials. Transportation Research Record:
Journal of the Transportation Research Board, National Research Council, Washington,
D.C, 1832(1), 17-24.
Monismith, C. L., Seed, H. B., Mitry, F. G., Chan, C. K. (1967). Prediction of pavement
deflections from laboratory tests. Proc., 2nd Int. Conf. Struct. Des. of Asphalt Pavements
(pp. 109-140).
Moosazadeh, J., & Witczak, M. W. (1981). Prediction of Subgrade Moduli for Soil that Exhibits
Nonlinear Behavior. Transportation Research Record: Journal of the Transportation
Research Board, National Research Council, Washington, D.C., (810), 1-9.
125
Morgan, J. R. (1996). The response of granular materials to repeated loading. Proceedings of the
3rd Conference, ARRB (pp. 1178-1192).
Muthen, K. M. (1998). Foamed Asphalt Mixes Mix Design Procedure, Contract Report CR-
98/077, SABITA Ltd & CSIR Transportek. Retrieved from Council for Scientific and
Industrial Research website http://asphalt.csir.co.za/FArefs/Muthen - Mix Design.pdf.
Nataatmadja, A. (2001). Some Characteristics of Foamed Bitumen Mixes. Transportation
Research Record: Journal of the Transportation Research Board, National Research
Council, Washington, D.C, (1767), 120-125.
Nataatmadja, A. (2002). Foamed Bitumen Mix: Soil or Asphalt. 9th International conference on
Asphalt Pavements (pp. 14-21).
Nazarian, S., & Yuan, D. (2003). Variation in Moduli of Base and Subgrade with Moisture. A
paper for possible inclusion in Session Entitled Road/Pavement Design for Seasonal Effects
Sponsored by Committees A2L04 and A2B05 2003 Annual TRB Meeting. Retrieved from
Louisiana Transportation Research Center website www.ltrc.lsu.edu/TRB_82/TRB2003-
001286.pdf.
Nazarian, S., R. Pezo, and M. P. (1996). Testing Methodology for Resilient Modulus of Base
Materials, Research Report 1336-1. Center for Geotechnical and Highway Materials
Research. University of Texas El Paso.
NCHRP 1-28. (1997). Laboratory Determination of Resilient Modulus for Flexible Pavement
Design: Final Report, Transportation Research Board, National Research Council.
NCHRP 1-37A. (2004). Guide for Mechanistic-Empirical Design of New and Rehabilitated
Pavement Structures - Final Report. National Cooperative Highway Research Program
(NCHRP) Project 1-37A, Transportation Research Board, National Research Council.
Ni, B., T.C. Hopkins, L. Sun, T. L. B. (2002). Modeling the Resilient Modulus of Soils.
Proceedings of the 6th International Conference on the Bearing Capacity of Roads,
Railways, and Airfields, Vol. 2, A.A. Balkema Publishers, Rotterdam, the Netherlands (p.
1131–1142).
Nishi M., Yoshida N., Tsujimoto T., O. K. (1994). Prediction of Rut Depth in Asphalt
Pavements. Proceedings of the 4th Int. Conf. on the Bearing Capacity of Roads and
Airfields, Minneapolis, USA (pp. 1007-1019).
Ooi, Phillip S. K, Archilla, a R., & Sandefur, K. G. (2004). Resilient Modulus Models for
Compacted Cohesive Soils. Transportation Research Record: Journal of the Transportation
Research Board, National Research Council, Washington, D.C., (1874), 115-124.
126
Pappin, J. W. (1979). Characteristics of Granular Material for Pavement Analysis, PhD
dissertation, Department of Civil Engineering, University of Nottingham, Nottingham,
England.
Paute, J. L., Hornych, P., and Benaben, J. P. (1996). Repeated Load Triaxial Testing of Granular
Materials in the French Network of Laboratoires des Ponts et Chausse ´es. Flexible
Pavements, Proc., Eur. Symp. Euroflex 1993, A. G. Correia, ed., Balkema, Rotterdam, The
Netherlands (pp. 53-64).
Paute, J. L., Jouve, P., Martinez, J., Ragneau, E. (1988). Mode`le de calcul pour le
dimensionnement des chausse ´es souples. Bull. de Li- aison des Laboratoires des Ponts et
Chaussees, (156), 21-36.
Pezo, R. F. (1993). A General Method of Reporting Resilient Modulus Tests of Soils—A
Pavement Engineer’s Point of View. 72nd Annual Meeting of the Transportation Research
Board, Washington, D.C.
Pezo, R. F., G. Claros, W. R. Hudson, K. H. S. I. (1992). Development of a Reliable Resilient
Modulus Test for Subgrade and Non-granular Subbase Materials for Use in Routine
Pavement Design. Report 1177-4F. Center for Transportation Research, University of
Texas, Austin.
Pezo, R.F. , D.S. Kim, K.S. Stokoe, W.R. Hudson, A. s. (1992). Aspects of a Reliable Resilient
Modulus Testing System. 71st Annual Meeting of the Transportation Research Board,
Washington, D.C.
Raffaelli, D. (2004). Foamed Asphalt Base Stabilization. Technology Transfer Program, UC
Berkeley. Retrieved from University of California Berkeley, Institute of Transportation
Studies, Technology Transfer Program website
www.techtransfer.berkeley.edu/techtopics/2004techtopics.pdf.
Ramanujam, J. M., & Jones, J D. (2007). Characterization of foamed-bitumen stabilisation.
International Journal of Pavement Engineering, 8(2), 111-122.
Ramanujam, J., & Jones, J. D. (2000). Characterisation of Foamed Bitumen Stabilisation, Road
Systems & Engineering Technology Forum. Retrieved from AustStab, Pavement Recycling
and Stabilisation Association website http://www.auststab.com.au/pdf/tp27.pdf.
Ruckel, P.J., Acott, S.M. & Bowering, R. H. (1982). Foamed-asphalt Paving Mixtures:
Preparation of Design Mixes and Treatment of Test Specimens. Transportation Research
Record: Journal of the Transportation Research Board, National Research Council,
Washington, D.C., (911), 88-95.
Saeed, A. (2008). Performance-Related Tests of Recycled Aggregates for Use in Unbound
Pavement Layers. NCHRP 598, Transportation Research Board, Washington D.C.
127
Saeed, A., Hall, J. W. J., & Barker, W. (2008). Performance-Related Tests of Aggregates for Use
in Unbound Pavement Layers. NCHRP Report 453, Transportation Research Board,
National Research Council, Washington, D.C.
Sakr, H.A. & Manke, P. G. (1985). Innovations in Oklahoma Foamix Design Procedures.
Transportation Research Record: Journal of the Transportation Research Board, National
Research Council, Washington, D.C.,, (1034), 26-34.
Saleh, M. & Herrington, P. (2004a). Foamed Bitumen Stabilisation for New Zealand Roads,
Transfund New Zealand Research Report No. 250. 88 pp.
Saleh, M. (2004b). New Zealand Experience with Foam Bitumen Stabilization. Transportation
Research Record: Journal of the Transportation Research Board, National Research
Council, Washington, D.C., (1868), 40-49.
Saleh, M. (2006). Effect of Aggregate Gradation, Mineral Fillers, Bitumen Grade, and Source on
Mechanical Properties of Foamed Bitumen-Stabilised Mixes. Transportation Research
Record: Journal of the Transportation Research Board, National Research Council,
Washington, D.C, (1952), 90-100.
Saleh, M. (2007). Effect of Rheology on the Bitumen Foamability and Mechanical Properties of
Foam Bitumen Stabilised Mixes. International Journal of Pavement Engineering, 8(2), 99-
110.
Saleh, M. (2007). Cost evaluation of foam bitumen and other stabilisation alternatives.
International Journal of Pavement Engineering, 8(2), 157-161.
Schnormeier, R. J. (1988). Recycling Tires into Pavement. Resource Recycling. Retrieved from
www.p2pays.org/ref/03/02379.pdf.
Seed, H. B., Mitry, F. G., Monismith, C. L., Chan, C. K. (1967). Prediction of Fexible Pavement
Deflections from Laboratory Repeated Load Tests. NCHRP Rep. No. 35, National
Cooperative Highway Research Program.
Shaw, P. (1980). Stress-Strain Relationships for Granular Materials under Repeated Loading.
PhD thesis, Department of Civil Engineering , University of Nottingham.
Shenton, M. J. (1974). Deformation of Railway Ballast Under Repeated Loading (Triaxial
Tests). Rapport RP5, British Railways Research Department.
Shih, C., Tia, M., & Ruth, B.E. Evaluation of The Effects of Crumb Rubber and SBR on Rutting
Resistance of Asphalt Concrete. Retrieved from
http://web.anl.gov/PCS/acsfuel/preprint%20archive/Files/41_4_ORLANDO_08-
96_1227.pdf
128
Sweere, G. T. H. (1990). Unbound Granular Bases for Roads. PhD thesis, Delft University of
Technology, The Netherlands.
Tarricone, P. (1993). Recycled Roads. Civil Engineering, Vol. 63, No. 4, 46-49.
TG2. (2009). Technical Guideline: Bitumen Stabilised Materials, A Guideline for the Design and
Construction of Bitumen Emulsion and Foamed Bitumen Stabilised Materials. Asphalt
Academy.
The Bridge. (2009) Retrieved from
http://www.ce.washington.edu/news/TheBridge/Bridge_Sp2009.pdf
Thom, N. H., & Brown, S. F. (1988). The Effect of Grading and Density on the Mechanical
Properties of a Crushed Dolomitic Limestone. Proceedings of the 14th ARRB Conference,
Part 7 (pp. 94-100).
Tseng, K. h, & Lytton, R. L. (1989). Prediction of Permanent Deformation in Flexible
Pavements. Implication of Aggregates in the Design, Construction, and Performance of
Flexibe Pavements, ASTM STP 1016, H.G. Schreuders and C.R.Marek, Eds, American
Society for Testing and Materials, Philadelphia, 154-172.
USEPA. (1998). Characterization of Building-related Construction and Demolition Debris in the
United States. The U.S. Environmental Protection Agency Municipal and Industrial Solid
Waste Division, Office of Solid Waste Report No. EPA530-R-98-010.
Uzan, J. (1985). Characterization of Granular Material. Transportation Research Record:
Journal of the Transportation Research Board, National Research Council, Washington,
D.C, (1022), 52-59.
Van de Ven, M. F. C., Jenkins, K J, Voskuilen, J. L. M., & Beemt, R. V. D. (2007).
Development of (half-) warm foamed bitumen mixes: state of the art. International Journal
of Pavement Engineering, 8(2), 163-175.
Vorobieff, G., Preston, N., & Bitumen, S. (2004). Bitumen Stabilisation – An Australian
Perspective. NZIHT Stabilisation of Road Pavements (pp. 1-19).
Vuong, B. (1994). Evaluation of Back-Calculation and Performance Models Using a Full Scale
Granular Pavement Tested with the Accelerated Loading Facility (ALF). Proceedings of the
4th International Conference on the Bearing Capacity of Roads and Airfields, Minneapolis,
USA (pp. 183-197).
West, R.C., Watson, D.E., Turner, P.A., & Casola, J.R. (2010). Mixing and Compaction
Temperatures of Asphalt Binders in Hot-Mix Asphlat. NCHRP Report No. 648,Washington
D.C.
129
Wilburn, D. R., & Goonan, T. G. (1998). Aggregate from Natural and Recycled Sources,
Economic Assessment of Construction Applications - A Materials Flow Analysis. United
States Geological Survey Circular 1176, United States Department of Interior, Washington,
D.C.
Wirtgen. (2004). Wirtgen Cold Recycling Manual. 2nd Edition, Wirtgen GmbH, Germany.
Witczak, M. W., Uzan, J. (1988). The universal airport pavement design system, Report I of IV:
Granular material characterization. University of Maryland, College Park, Md.
Wolff, H., & Visser, A. T. (1994). Incorporating Elasto-Plasticity in Granular Layer Pavement
Design. Proceedings of the Institution of Civil Engineers Transport (pp. 259-272).
Xiao, F., Amirkhanian, S., & Juang, H. Rutting Resistance of Rubberized Asphalt Concrete
Pavements Containing Reclaiming Asphalt Pavement Mixtures. Retrieved from
http://www.clemson.edu/ces/arts/JMCE_Xiao%20%28resived%294%20%28Rut%20Resist
ance%20of%20CRM%20HMA%20with%20RAP%29.pdf
Yoder,E.J., & Witczak, M.W., (1975)Principles of Pavement Design, Wiley, New York.
130
APPENDIX A: BASE COURSE MATERIAL CHARTS
131
Figure A-1 Mr vs. deviator stress at different confinement stresses for specimens compacted
using virgin aggregates at 98% of dmax (Specimen ID: HCH1)
Figure A-4 Mr vs. deviator stress at different confinement stresses for specimens compacted
using virgin aggregates at 98% of dmax (Specimen ID: HCH2)
5000
10000
15000
20000
25000
30000
35000
40000
45000
50000
0 5 10 15 20 25 30 35 40 45 50
Re
silie
nt
Mo
du
lus
(p
si)
Deviator Stress (psi)
Confining Stress = 3 psi
Confining Stress = 5 psi
Confining Stress = 10 psi
Confining Stress = 15 psi
Confining Stress = 20 psi
5000
10000
15000
20000
25000
30000
35000
40000
45000
50000
0 5 10 15 20 25 30 35 40 45 50
Re
silie
nt
Mo
du
lus
(p
si)
Deviator Stress (psi)
Confining Stress = 3 psi
Confining Stress = 5 psi
Confining Stress = 10 psi
Confining Stress = 15 psi
Confining Stress = 20 psi
132
Figure A-2 Mr vs. deviator stress at different confinement stresses for specimens compacted
using virgin aggregates at 100% of dmax (Specimen ID: HCH1)
Figure A-5 Mr vs. deviator stress at different confinement stresses for specimens compacted
using virgin aggregates at 100% of dmax (Specimen ID: HCH2)
5000
10000
15000
20000
25000
30000
35000
40000
45000
50000
0 5 10 15 20 25 30 35 40 45 50
Resilie
nt
Mo
dulu
s (p
si)
Deviator Stress (psi)
Conf ining Stress = 3 psi
Conf ining Stress = 5 psi
Conf ining Stress = 10 psi
Conf ining Stress = 15 psi
Conf ining Stress = 20 psi
5000
10000
15000
20000
25000
30000
35000
40000
45000
50000
0 5 10 15 20 25 30 35 40 45 50
Re
silie
nt
Mo
du
lus
(p
si)
Deviator Stress (psi)
Confining Stress = 3 psi
Confining Stress = 5 psi
Confining Stress = 10 psi
Confining Stress = 15 psi
Confining Stress = 20 psi
133
Figure A-3 Mr vs. deviator stress at different confinement stresses for specimens compacted
using virgin aggregates at 102% of dmax (Specimen ID: HCH1)
Figure A-6 Mr vs. deviator stress at different confinement stresses for specimens compacted
using virgin aggregates at 102% of dmax (Specimen ID: HCH2)
5000
10000
15000
20000
25000
30000
35000
40000
45000
50000
0 5 10 15 20 25 30 35 40 45 50
Re
silie
nt
Mo
du
lus
(p
si)
Deviator Stress (psi)
Confining Stress = 3 psi
Confining Stress = 5 psi
Confining Stress = 10 psi
Confining Stress = 15 psi
Confining Stress = 20 psi
5000
10000
15000
20000
25000
30000
35000
40000
45000
50000
0 5 10 15 20 25 30 35 40 45 50
Re
silie
nt
Mo
du
lus
(p
si)
Deviator Stress (psi)
Confining Stress = 3 psi
Confining Stress = 5 psi
Confining Stress = 10 psi
Confining Stress = 15 psi
Confining Stress = 20 psi
134
Figure A-7 Mr vs. deviator stress at different confinement stresses for specimens compacted
using FA mixtures at 98% of dmax (Specimen ID: FA1)
Figure A-10 Mr vs. deviator stress at different confinement stresses for specimens compacted
using FA mixtures at 98% of dmax (Specimen ID: FA2)
10000
20000
30000
40000
50000
60000
70000
80000
90000
100000
110000
120000
0 5 10 15 20 25 30 35 40 45 50
Resilie
nt
Mo
dulu
s (p
si)
Deviator Stress (psi)
Conf ining Stress = 3 psi
Conf ining Stress = 5 psi
Conf ining Stress = 10 psi
Conf ining Stress = 15 psi
Conf ining Stress = 20 psi
10000
20000
30000
40000
50000
60000
70000
80000
90000
100000
110000
120000
0 5 10 15 20 25 30 35 40 45 50
Re
silie
nt M
od
ulu
s (p
si)
Deviator Stress (psi)
Confining Stress = 3 psi
Confining Stress = 5 psi
Confining Stress = 10 psi
Confining Stress = 15 psi
Confining Stress = 20 psi
135
Figure A-8 Mr vs. deviator stress at different confinement stresses for specimens compacted
using FA mixtures at 100% of dmax (Specimen ID: FA1)
Figure A-11 Mr vs. deviator stress at different confinement stresses for specimens compacted
using FA mixtures at 100% of dmax (Specimen ID: FA2)
10000
20000
30000
40000
50000
60000
70000
80000
90000
100000
110000
120000
0 5 10 15 20 25 30 35 40 45 50
Re
silie
nt
Mo
du
lus
(p
si)
Deviator Stress (psi)
Confining Stress = 3 psi
Confining Stress = 5 psi
Confining Stress = 10 psi
Confining Stress = 15 psi
Confining Stress = 20 psi
10000
20000
30000
40000
50000
60000
70000
80000
90000
100000
110000
120000
0 5 10 15 20 25 30 35 40 45 50
Re
silie
nt
Mo
du
lus
(p
si)
Deviator Stress (psi)
Confining Stress = 3 psi
Confining Stress = 5 psi
Confining Stress = 10 psi
Confining Stress = 15 psi
Confining Stress = 20 psi
136
Figure A-9 Mr vs. deviator stress at different confinement stresses for specimens compacted
using FA mixtures at 102% of dmax (Specimen ID: FA1)
Figure A-12 Mr vs. deviator stress at different confinement stresses for specimens compacted
using FA mixtures at 102% of dmax (Specimen ID: FA2)
10000
20000
30000
40000
50000
60000
70000
80000
90000
100000
110000
120000
0 5 10 15 20 25 30 35 40 45 50
Re
silie
nt
Mo
du
lus
(p
si)
Deviator Stress (psi)
Confining Stress = 3 psi
Confining Stress = 5 psi
Confining Stress = 10 psi
Confining Stress = 15 psi
Confining Stress = 20 psi
10000
20000
30000
40000
50000
60000
70000
80000
90000
100000
110000
120000
0 5 10 15 20 25 30 35 40 45 50
Re
silie
nt
Mo
du
lus
(p
si)
Deviator Stress (psi)
Confining Stress = 3 psi
Confining Stress = 5 psi
Confining Stress = 10 psi
Confining Stress = 15 psi
Confining Stress = 20 psi
137
Figure A-13 Mr vs. deviator stress at different confining stresses for specimens compacted using
virgin aggregates at different density levels
5000
10000
15000
20000
25000
30000
35000
40000
45000
50000
0 5 10 15 20 25 30 35 40 45 50
Resil
ien
t M
od
ulu
s (
psi)
Deviator Stress (psi)
HCH @ 98%; Confining stress = 3 psi
HCH @ 100%; Confining stress = 3 psi
HCH @ 102%; Confining stress = 3 psi
HCH @ 98%; Confining stress = 5 psi
HCH @ 100%; Confining stress = 5 psi
HCH @ 102%; Confining stress = 5 psi
HCH @ 98%; Confining stress = 10 psi
HCH @ 100%; Confining stress = 10 psi
HCH @ 102%; Confining stress = 10 psi
HCH @ 98%; Confining stress = 15 psi
HCH @ 100%; Confining stress = 15 psi
HCH @ 102%; Confining stress = 15 psi
HCH @ 98%; Confining stress = 20 psi
HCH @ 100%; Confining stress = 20 psi
HCH @ 102%; Confining stress = 20 psi
138
APPENDIX B: DYNAMIC MODULUS CHARTS
139
Figure B-1 Master Curve for Specimen ID: VPPM1
140
Figure B-2 Master Curve for Specimen ID: VPPM2
141
Figure B-3 Master Curve for Specimen ID: VPPM3
142
Figure B-4 Master Curve for Specimen ID: VPPM4
143
Figure B-5 Master Curve for Specimen ID: VPPM5
144
Figure B-6 Master Curve for Specimen ID: VPPM6
145
Figure B-7 Master Curve for Specimen ID: VLPM1
146
Figure B-8 Master Curve for Specimen ID: VLPM2
147
Figure B-9 Master Curve for Specimen ID: VLPM3
148
Figure B-10 Master Curve for Specimen ID: VLPM3B
149
Figure B-11 Master Curve for Specimen ID: VLPM4
150
Figure B-12 Master Curve for Specimen ID: VLPM5
151
Figure B-13 Master Curve for Specimen ID: VLPM6
152
Figure B-14 Master Curve for Specimen ID: FRACLPM1
153
Figure B-15 Master Curve for Specimen ID: FRACLPM2
154
Figure B-16 Master Curve for Specimen ID: FRACLPM3
155
Figure B-17 Master Curve for Specimen ID: FRACLPM4
156
Figure B-18 Master Curve for Specimen ID: FRACLPM5
157
Figure B-19 Master Curve for Specimen ID: FRACLPM6
158
Figure B-20 Master Curve for Specimen ID: PMALPM1
159
Figure B-21 Master Curve for Specimen ID: PMALPM2
160
Figure B-22 Master Curve for Specimen ID: PMALPM3
161
Figure B-23 Master Curve for Specimen ID: PMALPM4
162
Figure B-24 Master Curve for Specimen ID: PMALPM5
163
Figure B-25 Master Curve for Specimen ID: PMALPM6
164
APPENDIX C: PERMANENT DEFORMATION CHARTS
165
Figure C-1 Fitting the power model for Specimen ID VPPM1
Figure C-2 Fitting the power model for Specimen ID VPPM2
y = 1307.5x0.3213
R² = 0.993
100
1000
10000
100000
1000000
1 10 100 1000 10000
Pe
rman
en
t St
rain
(
p)
Number of Load Repetitions
Test Points
Power (Model)
y = 413.59x0.5089
R² = 0.9978
100
1000
10000
100000
1000000
1 10 100 1000 10000
Pe
rman
en
t St
rain
(
p)
Number of Load Repetitions
Test Points
Power (Model)
166
Figure C-3 Fitting the power model for Specimen ID VPPM3
Figure C-4 Fitting the power model for Specimen ID VPPM4
y = 687.85x0.4798
R² = 0.9953
100
1000
10000
100000
1000000
1 10 100 1000 10000
Pe
rman
en
t St
rain
(
p)
Number of Load Repetitions
Test Points
Power (Model)
y = 2287.9x0.292
R² = 0.9959
100
1000
10000
100000
1000000
1 10 100 1000 10000
Pe
rman
en
t St
rain
(
p)
Number of Load Repetitions
Test Points
Power (Model)
167
Figure C-5 Fitting the power model for Specimen ID VPPM5
Figure C-6 Fitting the power model for Specimen ID VPPM6
y = 2063.3x0.4151
R² = 0.9902
100
1000
10000
100000
1000000
1 10 100 1000 10000
Pe
rman
en
t St
rain
(
p)
Number of Load Repetitions
Test Points
Power (Model)
y = 1663.3x0.5354
R² = 0.9993
100
1000
10000
100000
1000000
1 10 100 1000
Pe
rman
en
t St
rain
(
p)
Number of Load Repetitions
Test Points
Power (Model)
168
Figure C-7 Fitting the power model for Specimen ID VLPM1
Figure C-8 Fitting the power model for Specimen ID VLPM2
y = 1045.5x0.3629
R² = 0.9915
100
1000
10000
100000
1000000
1 10 100 1000 10000
Pe
rman
en
t St
rain
(
p)
Number of Load Repetitions
Test Points
Power (Model)
y = 1718x0.3476
R² = 0.9934
100
1000
10000
100000
1000000
1 10 100 1000 10000
Pe
rman
en
t St
rain
(
p)
Number of Load Repetitions
Test Points
Power (Model)
169
Figure C-9 Fitting the power model for Specimen ID VLPM3B
Figure C-10 Fitting the power model for Specimen ID VLPM4
y = 1291.7x0.4386
R² = 0.9848
100
1000
10000
100000
1000000
1 10 100 1000
Pe
rman
en
t St
rain
(
p)
Number of Load Repetitions
Test Points
Power (Model)
y = 1283.9x0.4463
R² = 0.9911
100
1000
10000
100000
1000000
1 10 100 1000 10000
Pe
rman
en
t St
rain
(
p)
Number of Load Repetitions
Test Points
Power (Model)
170
Figure C-11 Fitting the power model for Specimen ID VLPM5
Figure C-12 Fitting the power model for Specimen ID VLPM6
y = 2249.7x0.3644
R² = 0.9993
100
1000
10000
100000
1000000
1 10 100 1000
Pe
rman
en
t St
rain
(
p)
Number of Load Repetitions
Test Points
Power (Model)
y = 4478.3x0.3154
R² = 0.9973
100
1000
10000
100000
1000000
1 10 100 1000
Pe
rman
en
t St
rain
(
p)
Number of Load Repetitions
Test Points
Power (Model)
171
Figure C-13 Fitting the power model for Specimen ID PMALPM1
Figure C-14 Fitting the power model for Specimen ID PMALPM2
y = 2309x0.1936
R² = 0.9929
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y = 1005.8x0.2124
R² = 0.9941
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Figure C-15 Fitting the power model for Specimen ID PMALPM3
Figure C-16 Fitting the power model for Specimen ID PMALPM4
y = 1426x0.4241
R² = 0.9981
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y = 1354.3x0.387
R² = 0.9921
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173
Figure C-17 Fitting the power model for Specimen ID PMALPM5
Figure C-18 Fitting the power model for Specimen ID PMALPM6
y = 2532.4x0.5005
R² = 0.9994
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y = 3571.1x0.3422
R² = 0.993
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Power (Model)
174
Figure C-19 Fitting the power model for Specimen ID FRACLPM1
Figure C-20 Fitting the power model for Specimen ID FRACLPM2
y = 1563.3x0.3333
R² = 0.9856
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y = 1536.6x0.3476
R² = 0.9947
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175
Figure C-21 Fitting the power model for Specimen ID FRACLPM3
Figure C-22 Fitting the power model for Specimen ID FRACLPM4
y = 1089.4x0.4808
R² = 0.9823
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Power (Model)
y = 1508.3x0.33
R² = 0.976
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176
Figure C-23 Fitting the power model for Specimen ID FRACLPM5
Figure C-24 Fitting the power model for Specimen ID FRACLPM6
y = 3500.8x0.2892
R² = 0.9979
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y = 3602x0.3167
R² = 0.9991
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