Validation of a Mathematical-Based Model for the Rheological
Characterization of Asphalt Mixtures
FERNANDO MARTINEZ, MARINA CAUHAPE , LUIS ZORZUTTI, SILVIA ANGELONE
Road Laboratory, Institute of Applied Mechanics and Structures,
National University of Rosario,
Riobamba & Berutti, (2000) Rosario,
ARGENTINA
Abstract: - Asphalt mixtures are viscoelastic materials whose behavior is highly dependent on temperature and
loading frequency. The influence of these factors is described through master curves constructed at a given
reference temperature based on the principle of frequency-temperature superposition. These curves are used as
inputs in asphalt pavement design procedures based on mechanistic principles and related to their in-service
pavement performance. This paper proposes the application of the Kramers-Kronig (K-K) relations to
characterize the rheological properties of asphalt materials using a mathematical approach. Due to the
complexity of the integration of the K-K relations, an approximate solution of the K–K relations was used to
develop a Mathematical-Based Model to predict the master curves for the Dynamic Modulus |E*| and the Phase
Angle f. This model was validated using the experimental results of two different asphalt mixtures with
different characteristics. The results indicate that the model is accurate, and could be an effective approach to
mathematically predict the master curves of the asphalt mixture viscoelastic properties in a wide range of
temperatures and frequencies.
Key-Words: - Asphalt Mixtures, Rheology, Viscoelastic Properties, Master Curves, Kramers-Kronig Relations
Received: November 21, 2022. Revised: August 29, 2023. Accepted: October 8, 2023. Published: November 8, 2023.
1 Introduction
The knowledge of the mechanical properties of
asphalt mixtures is an important issue in the analysis
of pavement structure response and the prediction of
performance based on mechanistic principles.
Because of the complex nature of this kind of
material resulting from the combination of an
asphalt binder and the aggregate skeleton, linear
viscoelastic (LVE) characterization is usually
considered. For asphalt mixtures, the relationship
between applied stress and resulting strain depends
on loading frequency and temperature and can be
fully described using the complex modulus E*.
Two components of the complex modulus E* are
the Dynamic Modulus |E*| and the Phase Angle at
a given temperature and loading frequency.
Laboratory measurements of |E*| and are
commonly done at different temperature and
frequency combinations using different
experimental configurations, [1], [2], [3], [4], [5].
Several mathematical functions have been
proposed to model the dynamic modulus master
curve to be used in pavement design procedures.
Among them, the symmetrical or standard
logistic sigmoidal, non-symmetrical or generalized
logistic sigmoidal, power, and polynomial functions
are the most used by different researchers, [6], [7],
[8], [9], [10]. Also, for the time-temperature shift
factor aT, several functions describing the
temperature dependency of this parameter have been
considered.
In addition, other models have been proposed to
construct simultaneously both the dynamic modulus
and phase angle master curves, [11], [12], [13], [14],
[15].
These master curves are usually constructed by
fitting the selected mathematical function to the
measured data at various temperatures and
frequencies, and the coefficients defining the
function and the time-temperature shift factor aT are
simultaneously solved by performing a nonlinear
minimization algorithm, [16].
The master curve construction of |E*| uses a
mathematical model with a shift factor equation,
without constructing the master curve of ; or
constructing the master curves of both |E*| and
utilizing two mathematical models, respectively,
which are independent of each other with either
different parameters and/or shift factor equations,
[17].
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An important LVE requirement is the Kramers-
Kronig (K-K) relations to ensure that various LVE
functions are equivalent and the model is causal,
[18]. If this requirement is ignored, the parameters
of the models or the time-temperature shift factor aT
for various LVE functions may be different, which
is not consistent with the LVE theory, [19]. Since
physical causality induces relationships between
|E*| and , these two rheological properties are
mathematically interrelated at any frequency, and
they share the same shift factor equation with the
same parameters, which should be determined based
on the test data.
Xi and Luo have used the Kramers–Kronig
relations to construct the master curves of asphalt
materials, [20]. In this paper, two forms of exact K–
K relations were employed in numerical form to
construct the master curves of the dynamic modulus
and the phase angle of asphalt binders and asphalt
mixtures.
Other authors have applied K-K relations to
wave propagation in anelastic media, [21]. It is
shown in this paper the consistency of the K-K
relations applied to experimental data of rocks.
The effect of humidity on LVE properties of
asphalt mixtures has been evaluated using K-K
relations in constructing master curves, [22].
Researchers have developed a simple procedure
for the validation of laboratory measurements of
Young’s modulus of solid specimens at seismic
frequencies using the K-K relations, [23].
This paper proposes a Unified Model for
constructing the master curves of |E*| and based
on an approximate solution of the K-K relations that
satisfies the LVE theory. This Unified Model was
validated using the experimental |E*| and results
of two different asphalt mixtures with different
characteristics as is explained in the next sections.
The model will be applied in the Virtual Asphalt
Mixtures project (VirAM) that is being carried out
at the National University of Rosario, Argentina.
VirAM is a new and innovative concept for
asphalt mixtures that is in development as a set of
mathematical models, equations, and data combined
and connected to mimic and represent real asphalt
mixtures as a software application.
2 Theoretical Background
The Kramers-Kronig relations (K-K) for the
viscoelastic parameters are presented in a couple of
equations as follows, whose detailed derivations can
be found in the literature, [24].
󰇛󰇜
󰇛󰇜


(1)
󰇛󰇜
󰇛󰇜


(2)
where |E*()|, () are the dynamic modulus and
phase angle, respectively; is the angular
frequency; and u is the dummy variable.
Due to the difficulties in solving the integrals in
an exact form, an approximate solution was
proposed by, [25]:
󰇛󰇜
󰇟󰇛󰇜󰇠
󰇟󰇛󰇜󰇠
(3)
If the master curve for |E*| is constructed
according to the conventional symmetrical or
standard logistic sigmoidal, the following equation
applies:

󰇟󰇛󰇜󰇠
with f = loading frequency (f = /2), = value of
the lower asymptote of the |E*| master curve; =
difference between the upper and lower asymptotes;
and = shape coefficients; and aT = time-
temperature shift factor of |E*| and .
The time-temperature shift factor aT was adopted
as an Arrhenius equation in the form:
󰇛󰇜
(5)
with K = Arrhenius factor; T = test temperature
(°K); and TR = reference temperature (°K).
Based on Eq. (4), the master curve model of
was derived according to the approximate Kramers-
Kronig relations presented in Eq. (3):
󰇛󰇜
󰇛󰇟󰇛󰇜󰇠󰇜
󰇟󰇛󰇜󰇠
(6)
Because the relationship between and |E*|
proposed by Booij and Thoone in Eq. (3) is an
approximation, a linear function was added to obtain
potentially more accurate predictions. The new
expression for results:
󰇛󰇜󰇛󰇜
󰇛󰇟󰇛󰇜󰇠󰇜
󰇟󰇛󰇜󰇠
(7)
with c1 and c2 = adjustment factors.
The set of Eqs. (4) and (7) are the Mathematical-
Based Model (M-B Model) proposed in this paper.
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3 Materials and Procedures
3.1 Asphalt Mixtures
In this study, two types of hot asphalt mixtures
(HMA) were designed according to the
recommendations of the Road Authority in
Argentina to be used as base or surface courses in
flexible pavements. These mixtures are two dense-
graded asphalt concretes with a Nominal Maximum
Aggregate Size equal to 19 mm fabricated with the
same type of granitic aggregates but two different
asphalt binders, respectively.
One of these mixtures was elaborated using a
conventional non-modified asphalt binder, and it
was identified as AC30. The other one was
fabricated using a modified asphalt binder with
SBS, and it was identified as PmB. The samples
were compacted according to the Marshall Mix
Design procedure with 75 blows per face. In both
cases, the asphalt content was 5.5%. Two samples
of each mixture were tested. The average main
volumetric properties of these mixtures are
presented in Table 1.
3.2 Dynamic Tests
The dynamic tests were experimentally carried out
with the Indirect Tension (IDT) mode with
haversine loading under controlled stress conditions
using a servo-pneumatic machine following a
similar procedure as in the EN 12697-26 Standard,
Annex F: Test applying cyclic indirect tension to
cylindrical specimens (CIT-CY).
The test frame is enclosed in a temperature
chamber where the temperature control system can
achieve the required testing temperatures ranging
from 0 °C to 50 °C as displayed in Figure 1.
Displacements were measured along the
horizontal diameter on a gauge length equal to 60
mm using two loose core type miniature LVDTs
mounted on both plane faces of the samples as
shown in Figure 2.
The load capable of producing a measurable
displacement by the recording device was adjusted
at each testing temperature to minimize the induced
damage to the sample. The |E*| and results were
determined for seven frequencies (5, 4, 2, 1, 0.5,
0.25, and 0.1 Hz) and five temperatures (5, 10, 20,
30, and 40°C) having a full rheological
characterization of the asphalt mixtures.
Fig. 1: Testing system
Fig. 2: Detailed view of the LVDT´s
3.3 Calculation of Dynamic Viscoelastic
Properties
Figure 3 shows the variation of the applied loads
and the resulting measured displacements during a
test.
Assuming the plane stress state, the linear
viscoelastic solution for the dynamic modulus |E*|
of an asphalt mixture under the IDT mode results:
󰇛󰇜
(8)
with P0 = amplitude of the applied haversine load;
D0 = amplitude of the resulting horizontal
displacement; t = thickness of specimen; =
Poisson’s ratio; K1 and K2 = coefficients depending
on the specimen diameter and gauge length.
For the adopted gauge length equal to 60 mm
and for specimens with 100 mm diameter, the
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coefficients K1 and K2 result: K1 = 0.256 and K2 =
0.869.
Fig. 3: Applied loads and resulting displacements
The Poisson’s ratio was adopted as a function of
the test temperature in the form:

(9)
where T = testing temperature in °C, [26].
The phase angle results:

(10)
with t = time lag between peak loading and peak
displacement and T = period of the haversine
loading.
For materials with viscoelastic properties, the
range of is between and 90°. For those two
extreme points, = corresponds to a purely
elastic material and = 90° corresponds to a purely
viscous material.
3.4 Obtained Experimental Results
Table 2 shows the obtained experimental results of
the dynamic modulus |E*| in MPa and the phase
angle in Degrees for the AC30 mixture at the
seven frequencies and the five temperatures for the
two tested samples identified as Sample 1 and 2
respectively. In a similar form, Table 3 shows the
same results for samples A and B of the PmB
mixture respectively.
4 Application of the Proposed Model
The six model parameters considered in Eq. (4) and
(7) (, , , , c1 and c2) and the parameter K of the
time-temperature shift factor aT in Eq. (5) were
simultaneously determined by performing a
nonlinear minimization of the error function defined
as:
 




(11)

with N = number of test data points;
measured dynamic modulus;
 modeled
dynamic modulus;
measured phase angle;
and
modeled phase angle.
The nonlinear minimization of the error was
implemented using the Solver function in an Excel
spreadsheet. The resulting values of those
parameters are listed in Table 4.
For both asphalt mixtures, the coefficient c1 is
close to unity and c2 is close to zero, so the entire
proposed linear correction function is close to unity.
Thus, the approximate solution proposed in Eq. (3)
is a very good alternative to solve the mathematical
difficulty for the exact integration of Eq. (2).
Figure 4 shows the master curve of |E*| and
Figure 5 presents the master curve of , both at the
reference temperature equal to 20°C for the AC30
mixture. Figure 6 and Figure 7 show the same
master curves but for the PmB mixture.
Fig. 4: Master curve of |E*| for the AC30 mixture
Fig. 5: Master curve of for the AC30 mixture
Applied Load
Po
Time
Displacement
Do
Time
tT
100
1000
10000
100000
0.00001 0.001 0.1 10 1000 100000
Dyn Mod |E*| (MPa)
Reduced frequency fR (Hz)
Measured
Modeled
Reference Temperature = 20°C
0
10
20
30
40
50
0.00001 0.001 0.1 10 1000 100000
Phase angle (°)
Reduced frequency fR (Hz)
Measured
Modeled
Reference Temperature = 20°C
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Table 1. Volumetric properties of the tested mixtures
%AC
Gmb (g/dm3)
Gmm (g/dm3)
Vb (%)
Va (%)
VMA (%)
VFB (%)
AC30
5.5
2.376
2.477
13.07
4.08
17.15
76.22
PmB
5.5
2.374
2.476
13.06
4.12
17.18
76.02
AC: Asphalt Content; Gmm: Theoretical Maximum Specific Gravity; Gmm: Bulk Specific Gravity; Vb: Bitumen Volume;
Va: Air Voids Volume; VMA: Voids in the Mineral Aggregate; VFB: Voids Filled with Bitumen
Table 2. Experimental |E*| and results for the AC30 mixture
5°C
10°C
20°C
30°C
40°C
|E*|

|E*|

|E*|

|E*|

|E*|

Sample 1
5 Hz
13480
22.1
9421
26.0
4730
35.1
2234
40.7
853
40.3
4 Hz
13044
23.0
9082
26.4
4339
35.0
1992
39.5
698
41.1
2 Hz
11135
23.2
7584
28.3
3414
35.1
1674
36.3
550
39.3
1 Hz
9513
24.0
6347
29.8
2698
37.2
1229
37.0
465
36.2
0.5 Hz
8479
26.0
5152
31.4
1891
39.0
824
38.0
436
33.1
0.25 Hz
7234
28.9
4154
33.3
1620
38.0
700
35.1
344
32.0
0.1 Hz
5570
30.4
2995
35.2
1167
36.6
625
32.6
221
31.0
Sample 2
5 Hz
14847
19.6
10174
23.0
5870
32.1
1919
38.2
1020
37.7
4 Hz
14179
18.6
9951
24.5
5464
32.1
1831
37.1
1021
35.6
2 Hz
12470
20.0
8295
25.7
4127
34.8
1338
37.4
767
33.4
1 Hz
10823
20.9
6690
27.4
3096
34.1
970
38.3
648
32.5
0.5 Hz
9413
22.7
5244
29.6
2382
37.2
822
36.5
569
35.1
0.25 Hz
8122
24.6
4194
32.3
1798
37.4
800
34.1
349
33.4
0.1 Hz
6235
27.3
2910
33.2
1280
36.1
612
31.8
276
31.2
|E*| in MPa, in Degrees
Table 3. Experimental |E*| and results for the PmB mixture
5°C
10°C
20°C
30°C
40°C
|E*|

|E*|

|E*|

|E*|

|E*|

Sample A
5 Hz
13551
12.9
9928
16.2
4855
23.1
2337
27.9
1154
28.0
4 Hz
13272
13.6
9737
16.3
4736
23.1
2239
27.2
1063
31.8
2 Hz
11738
13.8
8546
17.6
3942
24.5
1802
27.6
861
28.1
1 Hz
10624
14.6
7513
18.6
3266
26.0
1574
26.7
642
28.6
0.5 Hz
9343
15.7
6467
20.4
2724
27.1
1376
26.5
578
26.5
0.25 Hz
8293
16.7
5623
21.2
2318
27.6
1150
26.9
456
26.3
0.1 Hz
6926
18.1
4705
22.9
1772
29.3
876
27.4
361
24.4
Sample B
5 Hz
14352
13.2
10419
18.6
4754
24.6
3224
29.9
1424
31.6
4 Hz
13946
13.3
10185
19.6
4631
24.1
3092
28.9
1355
29.1
2 Hz
12502
14.4
8846
20.3
3684
24.6
2390
29.4
1192
28.1
1 Hz
11223
15.2
7630
21.4
3029
25.9
1943
30.0
1078
26.7
0.5 Hz
9994
15.7
6489
22.4
2489
26.3
1763
29.0
930
26.5
0.25 Hz
8897
16.8
5567
23.8
2034
26.4
1298
30.3
690
26.8
0.1 Hz
7430
18.4
4420
25.7
1696
27.4
890
29.8
567
25.2
|E*| in MPa, in Degrees
Table 4. Resulting parameters for the M-B Model
K




c1
c2
Error
AC30
22730
1.442
3.379
-0.369
-0.404
1.196
-0.199
1.03
PmB
26592
1.531
3.340
-0.406
-0.307
1.151
-0.203
1.28
Figure 8 shows a comparison of measured and
modeled values in the Black space (|E*| - ) for the
AC30 mixture, and Figure 9 presents the same
comparison but for the PmB mixture. The measured
values are tightly located around the model curve.
Therefore, the proposed model can characterize
the Linear Viscoelastic behavior of both considered
asphalt mixtures in the frequency domain quite
accurately.
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5 Overall Performance of the Model
Measured and modeled values were compared to
examine the scattering of the data along the line of
equality (LOE). For the AC30 mixture, Figure 10
shows the comparison of measured and modeled
|E*| values in an arithmetic space, while Figure 11
shows the same comparison in a logarithmic space.
Fig. 6: Master curve of |E*| for the PmB mixture
Fig. 7: Master curve of φ for the PmB mixture
Fig. 8. Black space for the AC30 mixture
Fig. 9: Black space for the PmB mixture
Fig. 10: Measured vs. Modeled |E*| values for the
AC30 mixture (arithmetic space)
Fig. 11: Measured vs. Modeled |E*| values for the
AC30 mixture (logarithmic space)
Figure 12 shows the comparison of measured
and modeled values. Figure 13, Figure 14, and
Figure 15 show the same comparisons for the PmB
mixture.
For the |E*| values and the two mixtures
considered in this study, the data points are located
along the line of equality in a narrow band and
distributed on both sides without a remarkable bias.
Phase angle data points are also located along the
line of equality but are slightly more scattered.
100
1000
10000
100000
0.00001 0.001 0.1 10 1000 100000
Dyn Mod |E*| (MPa)
Reduced frequency fR (Hz)
Measured
Modeled
Reference Temperature = 20°C
0
10
20
30
40
50
0.00001 0.001 0.1 10 1000 100000
Phase angle (°)
Reduced frequency fR (Hz)
Measured
Modeled
Reference Temperature = 20°C
0
10
20
30
40
50
100 1000 10000 100000
Phase angle (°)
Dynamic modulus |E*| (MPa)
Measured
Modeled
Reference Temperature = 20°C
0
10
20
30
40
50
100 1000 10000 100000
Phase angle (°)
Dynamic modulus |E*| (MPa)
Measured
Modeled
Reference Temperature = 20°C
0
5000
10000
15000
20000
0 5000 10000 15000 20000
|E*|Modeled (MPa)
|E*|
Measured
(MPa)
LOE
100
1000
10000
100000
100 1000 10000 100000
|E*|Modeled (MPa)
|E*|
Measured
(MPa)
LOE
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However, in all cases, the modeled values are
tightly clustered around the line of equality, which
indicates that these modeled dynamic modulus and
phase angle values are in good match with the
measured values.
To evaluate the overall performance of the
model, the correlation of the measured and modeled
values was assessed using goodness-of-fit statistics
according to the subjective criteria proposed by,
[27], [28], as shown in Table 5. The statistics
include the correlation coefficient, R2, and Se/Sy
relationship (standard error of estimate
values/standard deviation of measured values).
Se/Sy is a measure of the accuracy of the estimates,
and R2 represents the accuracy of the model. Both
parameters have been used to standardize the results
in a subjective goodness classification.
Fig. 12: Measured vs. Modeled values for the
AC30 mixture
Fig. 13: Measured vs. Modeled |E*| values for the
PmB mixture (arithmetic space)
Table 6 presents the evaluation of the model in
modeling the |E*| and values according to these
criteria for the results of the AC30 and the PmB
mixtures.
Table 5. Criteria for goodness-of-fit statistical
parameters
Criteria
R2
Se/Sy
Excellent
≥ 0.90
≤ 0.35
Good
0.70 – 0.89
0.36 – 0.55
Fair
0.40 – 0.69
0.56 – 0.75
Poor
0.20 – 0.39
0.76 – 0.89
Very Poor
≤ 0.19
≥ 0.90
Fig. 14: Measured vs. Modeled |E*| values for the
PmB mixture (logarithmic space)
Fig. 15: Measured vs. Modeled values for the
PmB mixture
The resulting evaluation according to this
classification is Excellent, with R2 greater than
0.945 in all cases and Se/Sy values significantly
smaller than 0.35.
Table 6. Evaluation of the goodness-of-fit for the
model
Parameter
R2
Se/Sy
Evaluation
AC30
mixture
|E*|
0.990
0.105
Excellent
log |E*|
0.996
0.095
Excellent

0.945
0.270
Excellent
PmB
mixture
|E*|
0.993
0.085
Excellent
log |E*|
0.992
0.127
Excellent

0.968
0.237
Excellent
0
10
20
30
40
50
010 20 30 40 50
Modeled (°)
Measured
(°)
LOE
0
5000
10000
15000
20000
0 5000 10000 15000 20000
|E*|Modeled (MPa)
|E*|
Measured
(MPa)
LOE
100
1000
10000
100000
100 1000 10000 100000
|E*|Modeled (MPa)
|E*|
Measured
(MPa)
LOE
0
10
20
30
40
50
010 20 30 40 50
Modeled (°)
Measured
(°)
LOE
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DOI: 10.37394/232013.2023.18.14
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6 Model Sensitivity
Model sensitivity is an important part of
understanding the accuracy and uncertainty of the
proposed Mathematical-Based Model (MBM).
The ability of the model to capture the different
rheological behavior of the two asphalt mixtures
related to the different asphalt binders used in each
case was investigated by comparing the master
curves of |E*| and as shown in Figure 16 and
Figure 17 respectively.
Fig. 16: Compared |E*| master curves
Fig. 17: Compared master curves
The PmB mixture is softer at high
frequencies/low temperatures and stiffer a low
frequencies/high temperatures with a smaller
thermal susceptibility compared to the conventional
AC30 mixture. In addition, the PmB mixture shows
a more elastic behavior compared to the AC30
mixture, with smaller phase angles for the full
frequency range.
Rutting and fatigue cracking performance of
asphalt mixtures can be evaluated using the dynamic
modulus |E*| and phase angle  [29].
A Rutting Factor (RF) and a Fatigue Factor (FF)
can be defined as:
 󰇛󰇜
(12)
 󰇛󰇜
(13)
Higher values of RF indicate stiffer and more
elastic mixtures that have good rutting resistance.
Lower FF is an indication of better performance
against fatigue with softer and elastic asphalt
mixtures.
Rutting usually occurs during summer at high-
temperature conditions and slow vehicle speeds, and
fatigue cracking is a common phenomenon at
intermediate pavement service temperature and
vehicle speed of about 90 Km/h.
For the RF calculation, average values of |E*|
and at 40°C and 0.1 Hz were selected from Table
2 and Table 3 as extreme summer conditions with
very low vehicle speed. For the FF calculation,
average values of |E*| and at 20°C and 5 Hz were
selected from Table 2 and Table 3 as intermediate
pavement service conditions.
Table 7 shows the RF and FF values calculated
for both asphalt mixtures.
Table 7. RF and FF values for the asphalt mixtures
RF (MPa)
FF (MPa)
AC30 mixture
481
2933
PmB mixture
1106
1943
The PmB mixture has a higher Rutting Factor
than the AC30 asphalt, which implies that the PmB
mixture has better resistance to rutting as compared
to the AC30 asphalt mixture. The Fatigue Factor of
the PmB asphalt mixture is smaller as compared to
the AC30 and hence, with a better fatigue resistance.
This behavior is in good agreement with the
well-documented effect of SBS modification on
binders and mixtures with greater resistance to
fatigue and permanent deformation as well as
reducing thermal susceptibility, [30], [31], [32],
[33].
7 Conclusions
A model has been proposed to establish the master
curves of the viscoelastic properties |E*| and of
asphalt mixtures using the approximate Kramers-
Kronig relations and the sigmoidal function with the
same time-temperature shift factor and fitting
parameters.
Dynamic modulus |E*| and phase angle values
at different temperatures and frequencies were
experimentally determined using the IDT mode with
haversine loading.
100
1000
10000
100000
0.00001 0.01 10 10000
Dyn Mod |E*| (MPa)
Reduced frequency fR (Hz)
AC30 PmB
Reference Temperature = 20°C
0
10
20
30
40
50
0.00001 0.001 0.1 10 1000 100000
Phase angle (°)
Reduced frequency fR (Hz)
AC30 PmB
Reference Temperature = 20°C
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Modeled and measured |E*| results were
compared in arithmetic and logarithmic spaces.
Phase angle values were compared in an arithmetic
space.
The correlation between modeled and measured
data R2 was greater than 0.945 and the Se/Sy ratio
was smaller than 0.27 for both |E*| and values and
for the two asphalt mixtures considered in this
study. Therefore, the model could be evaluated as
Excellent according to the adopted goodness-of-fit
criteria. The adjustment coefficient c1 is close to
unity and c2 is close to zero so that the entire
proposed linear correction function is close to unity.
Thus, this approximate solution is a very good
alternative to solve the mathematical difficulty for
the exact integration of the Kramers-Kronig
relations.
The ability of the model to distinguish the
different rheological behaviors of different asphalt
mixtures was evaluated by the definition of the
Rutting and Fatigue Factors. The mixture
formulated with a polymer-modified asphalt binder
has a higher Rutting Factor than the asphalt mixture
with the conventional asphalt binder, which implies
that the PmB mixture has better resistance to rutting
as compared to the AC30 asphalt mixture. The
Fatigue Factor of the PmB asphalt mixture is
smaller as compared to the AC30 and hence, with a
better fatigue resistance.
Hence, it can be concluded that the model is able
to capture adequately the different rheological
behavior of the PmB mixture compared to the AC30
mixture. The proposed model is enough accurate,
and it could be an effective approach to
mathematically predict the viscoelastic properties of
master curves in a wide range of temperatures and
frequencies for asphalt mixtures.
This model will be included in the Virtual
Asphalt Mixtures project (VirAM) that is being
carried out at the National University of Rosario,
Argentina. VirAM is a new and innovative concept
for asphalt mixtures that is in development as a set
of mathematical models, equations, and data
combined and connected to mimic and represent
real asphalt mixtures as a software application.
Virtual Asphalt Mixtures could be used to design,
test, and analyze different mixture compositions and
to model the behavior of asphalt pavements under
different traffic and temperature conditions.
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Contribution of Individual Authors to the
Creation of a Scientific Article (Ghostwriting
Policy)
The authors equally contributed to the present study,
at all stages from the formulation of the research
methodology to the conclusions.
Sources of Funding for Research Presented in a
Scientific Article or Scientific Article Itself
The National University of Rosario has provided the
funds for conducting this study.
Conflict of Interest
The authors have no conflicts of interest to declare
that are relevant to the content of this article.
Creative Commons Attribution License 4.0
(Attribution 4.0 International, CC BY 4.0)
This article is published under the terms of the
Creative Commons Attribution License 4.0
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