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Habtamu Zelelew, Matthew Corrigan, Satish Belagutti, and Jeevan RamakrishnaReddy
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Duplication of this paper for publication or sale is strictly prohibited without prior1written permission of the Transportation Research Board2
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4
Comparative Evaluation of the Stiffness Properties of5
Warm-Mix Asphalt Technologies and |E*| Predictive Models67
8
Habtamu Zelelew, PhD (Corresponding Author)9ESC Inc, FHWA10
Office of Pavement Technology111200 New Jersey Ave., SE12Washington, DC 20590,13Phone: (202) 366-660614
e-mail: habtamu.zelelew.ctr@dot.gov1516
Matthew Corrigan, P.E.17Federal Highway Administration18Office of Pavement Technology19
1200 New Jersey Ave., SE20Washington, DC 2059021Phone: (202) 366-154922
e-mail: matthew.corrigan@dot.gov2324
Satish Belagutti25ESC Inc, FHWA TFHRC26
6300 Georgetown Pike, McLean, VA 2210127Phone: (202) 493-310328
e-mail: satish.belagutti.ctr@dot.gov2930
Jeevan RamakrishnaReddy31ESC Inc, FHWA TFHRC32
6300 Georgetown Pike, McLean, VA33Phone: (202) 256-592834
e-mail:jeevan.ramakrishnareddy.ctr@dot.gov353637
No. of Words = 3235 + 8*500 = 7235 < 750038
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Transportation Research Board Committee40AFK30: Characteristics of Nonasphalt Components of Asphalt Paving Mixtures41
42For Presentation at the 91
stAnnual Meeting43
44
October 31 20114546
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ABSTRACT1
Warm-mix Asphalt (WMA) has gained popularity due to rising energy costs and potential2
reductions in carbon dioxide and carbon dioxide equivalent emissions. In this paper, a3
comprehensive laboratory evaluation of WMA technologies stiffness properties and comparison4
of three |E*| predicting models (Witczak 1-37A, Witczak 1-40D, and Hirsch) are presented. A5
total of nine WMA technologies were included; six foaming processes (Accu-Shear, Advera
,6
Aspha-min, Aquablack
, Low Emission Asphalt (LEA), and Gencor), two chemical additives7
(Evothermand Rediset
), and an organic additive (Sasobit
). The rheological properties of the8
asphalt binders were characterized using the dynamic shear rheometer device at four test9
temperatures (4.4, 21.1, 37.8, and 54.4C) and multiple frequencies (0.016 to 25 Hz). The asphalt10
mixture performance tester was used to capture the stiffness properties of the asphalt mixtures11
using four temperatures (4.4, 21.1, 37.8, and 54.4C) and six frequencies (25, 10, 5, 1, 0.5, and12
0.1 Hz). The stiffness properties of the WMA technologies as well as their control13
binders/mixtures were evaluated through the use of master curves (both shear modulus and14
dynamic modulus). Compared to the control binder and mixture specimens, lower stiffness15
values were observed for the WMA technologies. Overall, reasonable |E*| predictions of the16
plant produced WMA technologies were obtained when the Hirsch model was utilized followed17
by the Witczak 1-40D model and the Witczak 1-37A model.18
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KEYWORDS: Warm-mix asphalt, shear modulus, dynamic modulus, and |E*| predictions20
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INTRODUCTION1
In recent years, Warm-mix Asphalt (WMA) has gained popularity due to rising energy2
costs, potential reductions in carbon dioxide and carbon dioxide equivalent emissions, and the3
need for sustainable materials. WMA is the name given to a variety of technologies that allow4
producing asphalt mixtures to lower temperatures at which the material is mixed, compacted, and5
placed on the roadways. Some WMA technologies have potential benefits in reducing the binder6
viscosity as well as reducing the short term aging of the mixture during production ( 1, 2).7
Another benefit of WMA is that the improved workability which allows incorporation of higher8
percentages of Reclaimed Asphalt Pavement (RAP) or Reclaimed Asphalt Shingles (RAS) in the9
asphalt mixture (2). There is a widespread concern in pavement community however that the10
reductions in binder viscosity and production temperatures may lead WMA mixtures to exhibit11
lower stiffness properties and consequently prone to rutting as compared to the conventional hot-12
mix asphalt (HMA) mixtures.13
The first trial WMA field projects were constructed in 2004 in Florida and North14
Carolina. To date, over forty-five states and ten Canadian provinces have constructed WMA15
demonstration projects in their jurisdictions (2). Since then, several of WMA technologies have16
emerged in the US market. There is a need to fully understand the properties of WMA17
technologies including their interaction with the asphalt binder and consequently their potential18
affect on pavement performance. In 2005, the Federal Highway Administration (FHWA) in19collaboration with the National Asphalt Pavement Association (NAPA) formed the WMA20
technical working group in order to address these challenges and implement WMA technologies21
successfully.22
The FHWA Office of Pavement Technology introduced the Asphalt Mixture23
Performance Tester (AMPT) equipment for conducting performance-based evaluation of asphalt24
concrete mixtures. The stiffness and deformation properties of asphalt mixes can be evaluated25
using this device respectively through the dynamic modulus and flow number tests. The dynamic26
modulus of an asphalt mixture, identified by |E*|, is a response developed under sinusoidal27
loading conditions tested at multiple frequencies and multiple temperatures. Among others,28
accuracy and repeatability of |E*| measurements can be significantly influenced by the material29
properties and test conditions (e.g., temperature, confinement, rate of loading, tuning/calibration,30
and specimen conditioning). When specimens are tested under higher test temperatures and/or31
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lower loading frequencies, the strain measuring gauge point locations can loosen and1
consequently high variations in the measured |E*| are observed.2
|E*| is also a crucial input to the AASHTOWare DARWin-ME (formerly the3
Mechanistic-Empirical Pavement Design Guide (ME PDG)) which requires laboratory measured4
(Level 1) or predicted (Level 2 and 3) dynamic modulus for estimating pavement performance5
(3). Over the past several years, various HMA |E*| predictive models have been developed (4-9).6
The three most popular models include: the NCHRP 1-37A project (referred in this paper as the7
Witczak 1-37A model) (4); the NCHRP 1-40D project (referred in this paper as the Witczak 1-8
40D model) (5); and the Hirsch model (6). Several studies utilized these models to predict HMA9
|E*| over a range of temperatures, rate of loading, and aging conditions (10-13).10
This paper presents a comprehensive laboratory evaluation of WMA technologies11
stiffness properties. It underscores identifying the effects of WMA technologies on12
binder/mixture stiffness properties. A comparative assessment of the WMA |E*| predicting13
models (Witczak 1-37A, Witczak 1-40D, and Hirsch) is also presented. The study included nine14
WMA demonstration projects in eight states visited by the FHWA Mobile Asphalt Trailer15
Laboratory (MATL) program over the past five years.16
17
OBJECTIVES18
The primary objectives of this study were to:19 Identify the effects of WMA technologies on binder stiffness properties.20 Identify the effects of WMA technologies on mixture stiffness properties.21 Compare the Witczak 1-37A model, the Witczak 1-40D model, and the Hirsch model in22
predicting plant produced WMA |E*|.23
In order to achieve these objectives, laboratory tests were conducted using the Dynamic Shear24
Rheometer (DSR) and AMPT devices respectively to capture the rheological properties of25
asphalt binders and characterize the stiffness properties of the asphalt mixtures.26
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MATERIALS1
The WMA technologies included six foaming processes (Accu-Shear, Advera
, Aspha-2
min, Aquablack
, Low Emission Asphalt (LEA), and Gencor), two chemical additives3
(Evotherm and Rediset
), and an organic additive (Sasobit
). The base binder grade ranged4
from PG 58-34 to PG 76-22. Ten mix designs meeting the respective state DOT specification5
were included, eight Superpave mixes containing 9.5 mm, 12.5 mm, 19 mm, and 25 mm and two6
19 mm Hveem mixes. The project locations covered a wide range of traffic levels as the design7
gyrations (Ndesign) ranged from 55 to 125. All binder tests were conducted at the AMRL-8
accredited Asphalt Binder Testing Laboratory (ABTL) operated by the FHWA Office of9
Pavement Technology. The mixture volumetrics and AMPT performance tests were performed10
by the Mobile Asphalt Mixture Testing Laboratory (MAMTL).11
12
BINDER TESTING13
The AASHTO T164 Standard Method of Test for Quantitative Extraction of Asphalt14
Binder from Hot Mix Asphalt (HMA) test protocol was used for extraction of asphalt binders15
from the plant produced asphalt mixture specimens. In addition, the ASTM D5404 Standard16
Practice for Recovery of Asphalt from Solution Using the Rotary Evaporatortest protocol was17
utilized to recover the asphalt binder specimens. This test method recommends using18
Trichloroethylene solvent for extraction and recovery process. However, the FHWA binder19
laboratory has been using an 85% toluene and 15% of ethanol mixture for extraction and20
recovery process. The rheological properties of the extracted and recovered asphalt binders were21
then measured following the AASHTO T315 Standard Method of Test for Determining the22
Rheological Properties of Asphalt Binder Using a Dynamic Shear Rheometer (DSR) test23
protocol. The DSR testing consisted of 25 mm parallel plate geometry and 1 mm gap setting. The24
asphalt binder sources included lab blended and plant supplied specimens. The Silverson high25
shear mixer was used to blend the base binder and the WMA technology in the laboratory. The26
specified dosage rates of the WMA technology was added gradually into the base binder.27
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Test Results1
Shear Modulus Master Curve2
The frequency sweep tests were conducted to evaluate the stiffness properties of the3
control binders and binders containing WMA technologies. The binder specimens were tested4using test temperatures of 4.4, 21.1, 37.8, and 54.4 C over a wide range of loading frequencies5
0.1 to 157.1 rad/s (i.e., 0.016 to 25 Hz). As described later, the asphalt mixture dynamic modulus6
tests were also conducted using the same set of test temperatures. Each of the frequency sweep7
test data was then shifted to a reference temperature of 21.1 C and fitted with generalized8
logistic function developed by Pellinen, Witczak, and Bonaquist (14).9
Figures 1 and 2 present the comparison of shear modulus |G*| master curves for the10
control binder and WMA technologies included in the study. Asphalt binders with higher |G*|11
mostly improve shear deformation resistance. It is shown in these figures that the asphalt binders12
containing the organic additive Sasobitmeasured high stiffness. The Accu-Shear
and Rediset
13
technologies measured slightly higher stiffness as compared to their control binders primarily at14
the low reduced frequency ranges (i.e., below 10 Hz). The other WMA technologies (Advera,15
Aspha-min, and Evotherm
) measured comparably similar stiffness values as their control16
binders when the lower reduced frequency range is considered. For the PA0986 project, the LEA17
and Gencor technologies demonstrated higher stiffness as compared to the control binder when18
the high reduced frequency ranges are considered. The differences in the stiffness properties19
amongst these WMA technologies could be explained from the differences in base binder,20
dosage rates, the WMA technology used, and the inherent variability in the DSR test procedures.21
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(a) (b)1
2
(c) (d)3
4
FIGURE 1 Shear modulus master curve; (a) MO0672, (b) CO0777, (c) WY0778, and (d) TX0985.5
1.E+00
1.E+02
1.E+04
1.E+06
1.E+08
1.E+10
1 .E-0 6 1 .E -0 4 1 .E -0 2 1 .E+0 0 1.E+02 1 .E+0 4 1 .E+0 6 1.E+08
ShearModulus,
|G*|(Pa)
Reduced Frequency (Hz) (TRef= 21.1 C)
PG 70-22
Sasobit
Aspha-min
1.E+00
1.E+02
1.E+04
1.E+06
1.E+08
1.E+10
1 .E-0 6 1 .E -0 4 1 .E -0 2 1 .E+0 0 1.E+02 1 .E+0 4 1 .E+0 6 1.E+08
ShearModulus,
|G*|(Pa)
Reduced Frequency (Hz) (TRef= 21.1 C)
PG 58-28
Advera
Sasobit
Evotherm
1.E+00
1.E+02
1.E+04
1.E+06
1.E+08
1.E+10
1 .E-0 6 1 .E -0 4 1 .E -0 2 1 .E+0 0 1.E+02 1 .E+0 4 1 .E+0 6 1.E+08
ShearM
odulus,
|G*|(Pa)
Reduced Frequency (Hz) (TRef= 21.1 C)
PG 58-34
Advera
Sasobit
1.E+00
1.E+02
1.E+04
1.E+06
1.E+08
1.E+10
1 .E-0 6 1 .E -0 4 1 .E -0 2 1 .E+0 0 1.E+02 1 .E+0 4 1 .E+0 6 1.E+08
ShearM
odulus,
|G*|(Pa)
Reduced Frequency (Hz) (TRef= 21.1 C)
PG 70-22
Rediset
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(a) (b)1
2
(c)3
4
FIGURE 2 Shear modulus master curve; (a) PA0986, (b) LA1088, and (c) IN1099.5
1.E+00
1.E+02
1.E+04
1.E+06
1.E+08
1.E+10
1 .E-0 6 1 .E -0 4 1 .E -0 2 1 .E+0 0 1.E+02 1 .E+0 4 1 .E+0 6 1.E+08
ShearModulus,
|G*|(Pa)
Reduced Frequency (Hz) (TRef= 21.1 C)
PG 64-22
Advera
Sasobit
LEA
Gencor
1.E+00
1.E+02
1.E+04
1.E+06
1.E+08
1.E+10
1 .E-0 6 1 .E -0 4 1 .E -0 2 1 .E+0 0 1.E+02 1 .E+0 4 1 .E+0 6 1.E+08
ShearModulus,
|G*|(Pa)
Reduced Frequency (Hz) (TRef= 21.1 C)
PG 64-22
Accu-Shear
1.E+00
1.E+02
1.E+04
1.E+06
1.E+08
1.E+10
1 .E-0 6 1 .E -0 4 1 .E -0 2 1 .E+0 0 1.E+02 1 .E+0 4 1 .E+0 6 1.E+08
ShearM
odulus,
|G*|(Pa)
Reduced Frequency (Hz) (TRef= 21.1 C)
PG 64-22
Accu-Shear
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ASPHALT CONCRETE MIXTURE TESTING1
Specimen Preparation2
Plant produced asphalt mixtures for dynamic modulus specimens were sampled from3
haul trucks. Asphalt specimens were immediately fabricated without reheating or additional4oven conditioning to eliminate additional mixture aging. The asphalt mixtures were then5
compacted to 8.5% air voids in the gyratory compactor in order to achieve the 7.0+0.5%6
targeted air voids for the cored and trimmed test specimen. The performance test specimens7
were cored from the center 100 mm of a 150 mm diameter specimen and the sample ends8
were trimmed from a height of 180+ mm down to 150 mm. The MATL mix design9
replication (MDR) samples were oven conditioned for 4 hours at 135C.10
11
Dynamic Modulus Test12
Four test replicates per sample were used for performance testing. Since the dynamic13
modulus test is non-destructive at low temperatures, the same set of four replicates were14
tested at the three lower temperatures (4.4, 21.1, and 37.8C), while another set of four15
replicates were tested at the high temperature (54.4C). Six loading frequencies were used16
25, 10, 5, 1, 0.5, and 0.1 Hz. The dynamic modulus tests were performed from the lowest17
temperature to the highest temperature and from the highest frequency to the lowest18
frequency. The axial stress needed in the unconfined test to produce a target microstrain of19
10015 was used. The dynamic modulus |E*| was calculated by dividing the maximum peak-20
to-peak stress by the recoverable peak-to-peak strain.21
22
Test Results23
Dynamic Modulus Master Curve24
The dynamic modulus test data was used to construct master curves for each of the25
test specimen at a reference temperature of 21.1C. The data was then shifted along the26
frequency axis to form a single |E*| master curve using the sigmoidal function given in ME27
PDG (3).28
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Figures 3 through 5 present comparison of |E*| master curves of the control HMA and1
WMA mixtures for all the projects included in the study. Overall, the |E*| master curve plots2
exhibited similar shape/trend for a wide range of frequencies. The stiffness properties of all3
of the asphalt mixtures presented in these figures decreased with an increase in test4
temperature and increased with an increase in loading frequency. Asphalt mixtures with5
higher |E*| mostly improve stability and rutting resistance. In general, compared to the6
control HMA mixtures, lower stiffness values were observed for the WMA technologies7
prepared with foaming processes followed by the chemical additives. The reduction in8
stiffness is more pronounced for the asphalt mixtures with Advera
and Aspha-min9
technologies and therefore these mixes may be more susceptible to rutting. This is a concern10
during the early life of the pavement if high temperatures are encountered and heavy traffic11
loading is placed on the pavement before it can age and stiffen in place on the roadway. The12
WMA mixtures containing organic additive Sasobitexhibited higher stiffness, particularly13
at lower and intermediate frequency ranges. In these figures, the MATL mix design14
replicates (MDR) mixtures measured relatively higher stiffness (except for MO0987 project)15
as compared to the plant produced HMA mixtures due to additional oven conditioning (416
hours at 135C). The differences in the stiffness properties of these WMA mixtures could be17
explained through, among others, the differences in volumetric properties, binder rheological18
properties, WMA dosage rates, aggregate shape properties (e.g., angularity and texture),19
production temperatures, and plant aging.20
21
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(a)1
(b)2
(c)3
FIGURE 3 Dynamic modulus master curve; (a) MO0672, (b) CO0777, and (c) WY0778.4
1.E+01
1.E+02
1.E+03
1.E+04
1.E+05
1.E-06 1.E-04 1.E-02 1.E+00 1.E+02 1.E+04 1.E+06 1.E+08
DynamicModulus,|
E*|(MPa)
Reduced Frequency (Hz) (TRef= 21.1 C)
HMA
WMA (Sasobit)
WMA (Aspha-min)
1.E+01
1.E+02
1.E+03
1.E+04
1.E+05
1.E-06 1.E-04 1.E-02 1.E+00 1.E+02 1.E+04 1.E+06 1.E+08
DynamicModulus,|
E*|(MPa)
Reduced Frequency (Hz) (TRef= 21.1 C)
HMA
WMA (Advera)
WMA (Sasobit)
WMA (Evotherm)
1.E+01
1.E+02
1.E+03
1.E+04
1.E+05
1.E-06 1.E-04 1.E-02 1.E+00 1.E+02 1.E+04 1.E+06 1.E+08
DynamicModulus,|
E*|(MPa)
Reduced Frequency (Hz) (TRef= 21.1 C)
HMA
WMA (Advera)
WMA (Sasobit)
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(a)1
(b)2
(c)3
4
FIGURE 4 Dynamic modulus master curve; (a) MN0884, (b) TX0985, and (c) PA0986.5
1.E+01
1.E+02
1.E+03
1.E+04
1.E+05
1.E-06 1.E-04 1.E-02 1.E+00 1.E+02 1.E+04 1.E+06 1.E+08
DynamicModulus,|
E*|(MPa)
Reduced Frequency (Hz) (TRef= 21.1 C)
HMA Wear
HMA Nonwear
WMA (Evotherm) Wear
WMA (Evotherm) Nonwear
1.E+01
1.E+02
1.E+03
1.E+04
1.E+05
1.E-06 1.E-04 1.E-02 1.E+00 1.E+02 1.E+04 1.E+06 1.E+08
DynamicModulus,|
E*|(MPa)
Reduced Frequency (Hz) (TRef= 21.1 C)
HMA
WMA (Rediset 2)
WMA (Rediset 10)
WMA (Rediset 12)
1.E+01
1.E+02
1.E+03
1.E+04
1.E+05
1.E-06 1.E-04 1.E-02 1.E+00 1.E+02 1.E+04 1.E+06 1.E+08
DynamicModulus,|
E*|(MPa)
Reduced Frequency (Hz) (TRef= 21.1 C)
HMA
HMA (MDR)
WMA (Advera)
WMA (Sasobit)
WMA (LEA)
WMA (Gencor)
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(a)1
(b)2
(c)3
4
FIGURE 5 Dynamic modulus master curve; (a) MO0987, (b) LA1088, and (c) IN1090.5
1.E+01
1.E+02
1.E+03
1.E+04
1.E+05
1.E-06 1.E-04 1.E-02 1.E+00 1.E+02 1.E+04 1.E+06 1.E+08
DynamicModulus,|
E*|(MPa)
Reduced Frequency (Hz) (TRef= 21.1 C)
HMA
HMA (MDR)
WMA (Aquablack 6)
WMA (Aquablack 7)
WMA (Aquablack 8)
WMA (Aquablack 10)
1.E+01
1.E+02
1.E+03
1.E+04
1.E+05
1.E-06 1.E-04 1.E-02 1.E+00 1.E+02 1.E+04 1.E+06 1.E+08
DynamicModulus,|
E*|(MPa)
Reduced Frequency (Hz) (TRef= 21.1 C)
HMA 12.5mm
HMA (MDR) 12.5mm
WMA (Accu-Shear) 12.5mm
HMA 19mm
HMA (MDR) 19mm
WMA (Accu-Shear) 19mm
1.E+01
1.E+02
1.E+03
1.E+04
1.E+05
1.E-06 1.E-04 1.E-02 1.E+00 1.E+02 1.E+04 1.E+06 1.E+08
DynamicModulus,|
E*|(MPa)
Reduced Frequency (Hz) (TRef= 21.1 C)
HMA
WMA (Accu-Shear 1)
WMA (Accu-Shear 2)
WMA (Accu-Shear 3)
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|E*| PREDICTIONS1
This paper also included predictions of |E*| through the use of the Witczak 1-37A,2
Witczak 1-40D, and Hirsch models. Detailed explanation of the model equations can found3
elsewhere (4, 5, and 6). The inputs to the Witczak 1-37A model include mixture volumetrics,4
aggregate gradation, binder viscosity, and loading frequency. The mixture volumetrics include5
air voids and effective binder content. The gradation parameters include percent passing on the6
0.075 mm (No. 200) sieve, cumulative percent retained on the 19 mm (3/4 in.) sieve, cumulative7
percent retained on the 9.5 mm (3/8 in.) sieve, and cumulative percent retained on the 4.76 mm8
(No. 4) sieve. The inputs to the Witczak 1-40D model are similar to the inputs to the Witczak 1-9
37A model. The Witczak 1-40D model was intended to improve the Witczak 1-37A model and10
therefore, the binder viscosity and loading frequency parameters are replaced by the binder shear11
modulus |G*| and the binder phase angle. In this study, the binder frequencies at which |G*|12
measured were multiplied by a factor of 0.159 to calculate the mixture frequencies used in the13
Witczak 1-40D model. For the Hirsch model, the binder |G*|, voids in mineral aggregates, and14
voids filled with asphalt are incorporated. For this model, the loading frequency of the binder is15
the same as that for the mixture. These models were originally developed using HMA mixture16
material properties. The |E*| predictive capability of these models using plant produced WMA17
mixture data is presented below.18
1920
COMPARISON OF MEASURED AND PREDICTED |E*|21
Figure 6 presents the comparison of laboratory measured and predicted |E*| using the22
three models in arithmetic and logarithmic scales. A total of 570 data points were used involving23
only WMA mixtures tested at four temperatures and six loading frequencies. In order to meet24
one of the stated objectives, the control HMA mixtures (both plant produced and MATL mix25
design replication) were not included in the |E*| prediction analysis. In these figures, over-26
prediction of |E*| was observed when the Witczak 1-37A and 1-40D models were utilized. The27
over-prediction is pronounced with higher modulus values that correspond to the asphalt28
mixtures tested at high loading frequencies and low test temperatures. In the logarithmic scale,29
the Hirsch model predicted |E*| with the highest coefficient of determination (R2=0.9005) and30
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the lowest error (Se/Sy=0.3154) followed by the Witczak 1-40D model (R2=0.8453 and1
Se/Sy=0.3934) and the Witczak 1-37A model (R2=0.8074 and Se/Sy=0.4388). Better predictions2
were obtained using the Witczak 1-37A model following the Hirsch model when the arithmetic3
scale is considered. These findings are consistent with the model developers with high4
correlation coefficient and low error in logarithmic scale for the Witczak 1-40D and Hirsch5
models (5, 6). Comparisons of the predictive models amongst various WMA technologies (i.e.,6
foam, chemical, and organic) are also shown in Figure 7.7
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1
(a)2
3
(b)4
5
(c)6
FIGURE 6 Comparison of measured and predicted |E*| in arithmetic and logarithmic7
scales; (a) Witczak 1-37A, (b) Witczak 1-40D, and (c) Hirsch.8
0
5000
10000
15000
20000
25000
30000
35000
0 5000 10000 15000 20000 25000 30000 35000
Predicted|E*|(MPa)
Measured |E*| (MPa)
R2 = 0.8106Se/Sy = 0.4352
10
100
1000
10000
100000
10 100 1000 10000 100000
Predicted|E*|(MPa)
Measured |E*| (MPa)
R2 = 0.8074Se/Sy = 0.4388
0
5000
10000
15000
20000
25000
30000
35000
0 5000 10000 15000 20000 25000 30000 35000
Predicted|E*|(MPa)
Measured |E*| (MPa)
R2 = 0.5984Se/Sy = 0.6338
10
100
1000
10000
100000
10 100 1000 10000 100000
Predicted|E*|(MPa)
Measured |E*| (MPa)
R2 = 0.8453Se/Sy = 0.3934
0
5000
10000
15000
20000
25000
30000
35000
0 5000 10000 15000 20000 25000 30000 35000
Predicted|E*|(MPa)
Measured |E*| (MPa)
R2 = 0.8854Se/Sy = 0.3386
10
100
1000
10000
100000
10 100 1000 10000 100000
Predicted|E*|(MPa)
Measured |E*| (MPa)
R2 = 0.9005Se/Sy = 0.3154
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(a)1
(b)2
(c)3
FIGURE 7 |E*| Comparison of measured and predicted |E*| for various WMA4
technologies; (a) Witczak 1-37A, (b) Witczak 1-40D, and (c) Hirsch.5
10
100
1000
10000
100000
10 100 1000 10000 100000
Predicted|E*
|(MPa)
Measured |E*| (MPa)
Foam
Chemical
Organic
Line of Equality
10
100
1000
10000
100000
10 100 1000 10000 100000
Predicted|E*|(MPa)
Measured |E*| (MPa)
Foam
Chemical
Organic
Line of Equality
10
100
1000
10000
100000
10 100 1000 10000 100000
Predicted|E*|(MPa)
Measured |E*| (MPa)
Foam
Chemical
Organic
Line of Equality
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Accuracy of the |E*| Predictive Models1
The accuracy of the predictive models was determined by calculating the |E*| percent2
error (e) which equals the difference between predicted and measured |E*| divided by the3
predicted |E*|. For each test temperature and loading frequency, the |E*| percent error was4
computed and presented into seven groups: (a) e< 0%, (b) 0%
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(a) (b)1
2
(c) (d)3
FIGURE 8 Summary of predicted |E*| percent error (e); (a) 4.4C, (b) 21.1C, (c) 37.8C, and (d) 54.4C.4
0
20
40
60
80
e < 0% 0 < e 10% 10 < e 20% 20 < e 30% 30 < e 40% 40 < e 50% e > 50%
Percent(%)
Predicted |E*| Percent Error Range
Witczak 1-37A
Witczak 1-40D
Hirsch
0
20
40
60
80
e < 0% 0 < e 10% 10 < e 20% 20 < e 30% 30 < e 40% 40 < e 50% e > 50%
Percent(%)
Predicted |E*| Percent Error Range
Witczak 1-37A
Witczak 1-40D
Hirsch
0
20
40
60
80
e < 0% 0 < e 10% 10 < e 20% 20 < e 30% 30 < e 40% 40 < e 50% e > 50%
Percent(%)
Predicted |E*| Percent Error Range
Witczak 1-37A
Witczak 1-40D
Hirsch
0
20
40
60
80
e < 0% 0 < e 10% 10 < e 20% 20 < e 30% 30 < e 40% 40 < e 50% e > 50%
Percent(%)
Predicted |E*| Percent Error Range
Witczak 1-37A
Witczak 1-40D
Hirsch
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SUMMARY AND CONCLUSION1
This paper presents a comprehensive laboratory evaluation of WMA technologies2
stiffness properties and comparisons of three |E*| predictive models (Witczak 1-37A,3
Witczak 1-40D, and Hirsch). It included nine WMA demonstration projects; six foaming4
processes (Accu-Shear, Advera
, Aspha-min
, Aquablack
, Low Emission Asphalt (LEA),5
and Gencor); two chemical additives (Evotherm and Rediset
); and an organic additive6
(Sasobit). The rheological properties of the asphalt binders were characterized using the7
dynamic shear rheometer device at four test temperatures (4.4, 21.1, 37.8, and 54.4C) and8
multiple frequencies (0.016 to 25 Hz). The asphalt mixture performance tester was used to9
capture the stiffness properties of the asphalt mixtures using four temperatures (4.4, 21.1,10
37.8, and 54.4C) and six frequencies (25, 10, 5, 1, 0.5, and 0.1 Hz). The following11
conclusions can be drawn on the basis of the findings presented in this study:12
The Accu-Shearand Redisettechnologies measured slightly higher binder stiffness13as compared to their control binders primarily at low reduced frequency ranges. The14
LEA and Gencor technologies demonstrated higher binder stiffness as compared to the15
control binder at high reduced frequency ranges. The Advera
, Aspha-min, and16
Evothermtechnologies measured comparably similar binder stiffness values as their17
control binder at lower reduced frequency ranges.18
Compared to the control HMA mixtures, lower stiffness values were observed for the19WMA technologies prepared with foaming processes followed by the chemical20
additives. The reduction in stiffness is more pronounced for the asphalt mixtures21
containing Advera and Aspha-min
technologies. The WMA mixtures containing22
organic additive measured higher stiffness.23
The differences in the stiffness properties of the WMA technologies are attributed to,24among others, the differences in binder rheological properties, volumetric properties,25
WMA dosage rates, aggregate structure in the mix, production temperatures, and plant26
aging.27
Overall, reasonable |E*| predictions of the plant produced WMA technologies were28obtained when the Hirsch model was utilized followed by the Witczak 1-40D model29
and the Witczak 1-37A model.30
31
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RECOMMENDATIONS1
A comprehensive statistical analysis is needed to further investigate the effects of various2properties (e.g., volumetrics, binder, aggregate, WMA dosage rates, and aging) on3
binder/mixture stiffness performance.4
Refining the existing |E*| predictive models using WMA material data.5 Additional investigation into the AASHTOWare DARWin-ME predicted pavement6
distresses versus actual field WMA pavement distresses is required to determine if WMA7
pavement performance is similar to HMA.8
The dataset used in this paper can assist researchers and practitioners to calibrate and9validate the AASHTOWare DARWin-ME for designing new and rehabilitated WMA10
pavements.11
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ACKNOWLEDGMENTS1
The success of this study is made possible through the close partnership of the transportation2
community. The FHWA Office of Pavement Technology wishes to express sincere thanks to3
the state Departments of Transportation (Colorado, Indiana, Louisiana, Minnesota, Missouri,4
Pennsylvania, Texas, and Wyoming) and the contractors involved in the projects. The5
authors would also like to acknowledge and extend special thanks to MATL programs6
mixture and binder laboratory technicians.7
8
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REFERENCES1
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B. Warm-mix Asphalt: European Practice. Federal Highway Administration (FHWA),4
FHWA-PL-08-007,2008.5
2. Prowell, B., Hurley, G., and Frank, B. Warm-mix Asphalt: Best Practices. The National6Asphalt Pavement Association (NAPA), 2
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3. Guide for Mechanistic-Empirical Design of New and Rehabilitated Pavement Structures.9NCHRP 1-37A Project. Transportation Research Board of the National Academies,10
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4. Andrei, D., Witczak, M. and Mirza, W. Appendix CC-4: Development of a Revised12Predictive Model for the Dynamic (Complex) Modulus of Asphalt Mixtures.13
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