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Cary and Zapata 1
EVALUATING THE UTILITY OF EXISTING PAVEMENT MANAGEMENT SYSTEM
STATE DEFLECTION DATA FOR USE IN THE IMPLEMENTATION OF THE ME-
PDG FOR ARIZONA
Carlos E. Cary
Graduate Assistant
Department of Civil and Environmental Engineering
Arizona State University
P.O. Box 875306, Tempe, AZ 85287-5306
Phone: (480) 965-3997
Fax: (480) 965-0557
E-mail: [email protected]
and
Claudia E. Zapata, Ph.D.*
Assistant Professor
Department of Civil and Environmental Engineering
Arizona State University
P.O. Box 875306, Tempe, AZ 85287-5306
Phone: (480) 727-8514
Fax: (480) 965-0557
E-mail: [email protected]
*Corresponding author
Submitted for Presentation and Publication in the 88th
Annual Meeting of the Transportation
Research Board
Submit date: August 1st, 2008
Word Count: 4400 + 1500 = 5900
Number of Tables: 3
Number of Figures: 3
TRB 2009 Annual Meeting CD-ROM Paper revised from original submittal.
Cary and Zapata 2
ABSTRACT
The modulus backcalculation from Falling Weight Deflectometers is one of the primary means
for evaluating in-situ resilient properties of pavement materials. When evaluating material
moduli from the same location by using deflection data from different sources, it is highly
probable that different methodologies will lead to differing results.
This study presents a comparative analysis of backcalculated moduli results performed to
quantify the differences between the historic Arizona Department of Transportation - Pavement
Management System (ADOT-PMS) and the Strategic Highway Research Program – Long Term
Pavement Performance (SHRP-LTPP) databases. Pavement sections were selected from
numerous SHRP sites in Arizona, having deflection data available at the same location and in the
same general time frame of the ADOT-PMS test locations.
The results of this study indicated that there was a poor correspondence between
backcalculated layer moduli from both databases. As a general rule, the degree of layer
correspondence improved as layer depths gradually increased (subgrade was the most accurate
comparison).
On the other hand, fairly good correspondence was obtained for all moduli between two
differing backcalculation schemes (MODCOMP v4.2 and MODULUS v6.0). Finally, it was
found that the use of the simple, closed form solution to estimate subgrade moduli from the outer
geophones, gave comparable answers to the more complex backcalculated solutions based upon
total deflection basin results. This gives rise to the possibility that significant reductions in cost
and labor can be achieved in maintaining PMS systems and by utilizing the outer geophone
equation as an implementation approach for the ME-PDG.
INTRODUCTION
The resilient modulus is a fundamental parameter in the design of pavements. Any state
implementation effort of the new Mechanistic-Empirical Pavement Design Guide (ME-PDG)
will generally depend upon a deflection based backcalculated moduli database available for
customized calibration. While no national standard for deflection testing exists, many states and
other governmental agencies are closely tied to the methodology established by the US SHRP-
LTPP program. However, many states, including Arizona, utilize a different set of conditions,
equipment and procedures to maintain network system deflection data in their existing state PMS
systems.
The SHRP–LTPP pavement performance data was widely used in the development of the
recently released ME-PDG, particularly in the performance calibration of the distress models.
The comparability of not only non-destructive testing data but also any distress data reflecting
the performance of the pavement is fundamental as an initial step aiming at a regional
implementation of the ME-PDG. Extensive studies of comparability of pavement performance
data between SHRP LTPP and the Department of Transportation has been conducted in the State
of Arizona (1). Results from studies like this one will allow DOTs to evaluate the feasibility of
using their own PMS database over the SHRP LTPP data used in the national calibration of the
ME-PDG. If differences between SHRP LTPP sections and PMS sections data input are
significant; then, the DOT must make the important decision to solely rely on their PMS data or
include both SHRP LTPP and PMS sections in the same calibration dataset.
This study presents a comprehensive comparative analysis of backcalculated moduli
results performed to quantify what difference, if any, exists between the historic Arizona
TRB 2009 Annual Meeting CD-ROM Paper revised from original submittal.
Cary and Zapata 3
Department of Transportation – Pavement Management System (ADOT-PMS) database and the
Strategic Highway Research Program-Long Term Pavement Performance (SHRP-LTPP)
programs. Pavement sections, containing both types of deflection data, were selected from
numerous LTPP sites in Arizona, having deflection data available at the same location and
general time frame of their corresponding ADOT-PMS test locations. .
Many factors may lead to differences between the backcalculation of layer moduli from
deflection basin backcalculation approaches. Different FWD devices used for measurements,
environmental factors, different backcalculation programs, and the pavement cross section data
used for the backcalculation procedure are among the key factors to be accounted for when
comparing results obtained from different sources. Non-reproducibility of results when using
different types of FWDs has been documented in the literature (2, 3). Furthermore, FWD sensors
can easily be located at positions that are different from those reported, which can lead to
inaccuracies in backcalculated moduli (4). Discontinuities in pavement structure, air temperature
and pavement damage reflected in distresses at the time of testing have been also considered
among the most significant variables contributing to variability when measuring deflections (5).
In addition, factors such as the specific backcalculation program and methodology used must
obviously influence the results.
STUDY OBJECTIVES
The specific objectives of this study were three fold:
• To evaluate the relative similarity of backcalculated layer moduli obtained from two
different sources: the SHRP–LTPP database and the ADOT-PMS database.
• To evaluate the relative similarity of backcalculated layer moduli obtained from two
different computational programs: MODULUS v 6.0 and MODCOMP v 4.2.
• To evaluate the similarity of backcalculated subgrade moduli obtained from full
backcalculation procedures (MODCOMP and MODULUS), relative to results obtained from the
simple, closed form equation presented in the 1993 AASHTO Design Guide, using the outer
geophone.
FWD DEFLECTION DATA AVAILABLE
The FWD data used for this study was obtained from two different sources: ADOT-PMS
database provided by ADOT and the SHRP-LTPP Standard Database-Releases (SDR) 20 and 22
provided by LTPP products.
ADOT-PMS Data
ADOT measures deflections from one drop for 7 sensors at 5 load levels: 5, 8, 9, 12 and 16 kip.
As a result, 5 lines of deflections per each test location are obtained. All 5 load drops are
normalized by ADOT to a 9 kip load and only one line of deflections per test location was used
by Arizona State University (ASU) in this study. The normalized deflection data is also available
in the ADOT PMS file for each of 2 lanes in every highway
The FWD used by ADOT is a truck-mounted unit, model JILS-20T. The loading plate is
a 12-in diameter rigid steel disk with 5/6 in neoprene pad for uniform loading distribution. The 7
geophones are located at radial distances of 0, 12, 24, 36, 48, 60, and 72 inches from the center
loading. The interval of FWD tests used in the ADOT-PMS program is either every 0.20 or 0.33
miles depending on the road. ADOT deflections are measured on the outer wheel path in both
Lane 1 (L1) and Lane 2 (L2) of the same direction.
TRB 2009 Annual Meeting CD-ROM Paper revised from original submittal.
Cary and Zapata 4
SHRP-LTPP Data
The latest version of LTPP Standard Data-Release 22 was used to obtain deflection
measurements for this study. Deflections for 4 drops per each one of the 4-drop heights specified
in the testing protocol were measured. All deflections obtained with a drop height corresponding
to a 9 kip load were used in the backcalculation, reducing the number of deflection data sets from
16 to 4 per test location. The frequency of FWD tests for the 500 ft long LTPP sections is either
every 25 ft or 50 ft depending on the test plan.
The deflections are measured in the middle of the lane, 6 ft away from the outer
pavement edge. The FWD type used in the LTPP program was the Dynatest 8002. The loading
plate is a 12-in diameter three layer solid plate: the topmost of which is steel, the middle is PVC,
and the bottommost is a ribbed rubber sheet. According to LTPP test protocol, the deflection
sensors, for the 9-sensor unit, are located at radial distances of: 0, 8, 12, 18, 24, 36, 48, 60 and 72
inches. However, other FWDs collecting data for the LTPP database had only 7 deflection
sensors: 0, 8, 12, 18, 24, 36 and 60 inches.
The modulus of materials in the LTPP database was obtained by using MODCOMP v 4.2
as the backcalculation program. It should be mentioned that this program allows the input of only
7 sensor deflections. Therefore, even when data for 9 sensors was available, the deflections used
are those corresponding to the 7-sensor FWD setup.
DEFLECTION DATA UTILIZED
A total of 14 SHRP-LTPP sections from the state of Arizona were selected for the
analysis. In order to perform a consistent study, each LTPP section was selected so that the
information regarding the test date and the pavement structure, as well as the test location at the
time of the FWD testing was as close as possible to that available from their corresponding 14
ADOT-PMS selected test locations. Two out of the 14 ADOT-PMS test locations did not fall
within their corresponding SHRP-LTPP sections. However, these two points were located very
close to the beginning of their corresponding SHRP LTPP section as to assume that they were
obtained from the same location.
It is worth mentioning that even when the test date was close between both data sources,
differences in temperature did exist. Therefore, it must be recognized that this difference in test
dates induces a probable uncertainty when comparing results due to environmental factors
(surface temperature). It would be expected that this impact is greatest for the comparison of the
asphalt layers.
Another factor responsible for differences was that the pavement structure was not
necessarily identical for both databases. Thus, this parameter became one of the contributing
factors accounting for any observed differences. These differences were minimal in some
sections but important in others.
In summary, 14 paired sets of backcalculated moduli were compared. An average of
moduli, obtained at every test location within the SHRP LTPP sections, was paired to a single
modulus obtained from ADOT-PMS data. The single values corresponded to test location that
falls within their paired LTPP-SHRP sections. Detailed information for every section is available
in the report “Evaluating the Utility of Existing PMS State FWD Deflection Data for Use in
Implementing the ME-PDG for the Arizona DOT” (6).
TRB 2009 Annual Meeting CD-ROM Paper revised from original submittal.
Cary and Zapata 5
GENERAL BASIS OF COMPARISON
The general process used to qualitatively characterize the relative correspondence between layer
moduli was the analysis of three statistical criterion applied to each analysis.
The first criterion was based upon the similarity between the trend line obtained from a
linear regression and the line of equality. A good correspondence between log moduli could be
suggested when the slope of the regression approached a value equal to 1.0. The second criterion
used the coefficient of Determination (R2). Obviously, the higher the value of this coefficient, the
more precise the relationship between moduli was.
Finally, the third criterion that was employed was the statistical comparison of the
backcalculated values by analyzing the differences between the corresponding modulus from the
two populations. If there were no statistical difference between backcalculated values, then the
mean of the differences (for a paired data set) would be equal to zero. This analysis is called “the
two sample paired t-test”. The variable used is the difference of modulus logarithms (∆log) and
is defined in equation 1:
yixini EE logloglog )1:( −=∆→
........................................................................................................ (1)
where,
log Ex = logarithm of modulus from population x, and
log Ey = logarithm of modulus from population y.
The following parameters based on ∆log were computed and included in the statistical
comparison:
• D: ∆log mean
• SD: ∆log deviation
• SD2: ∆log variance
• n: sample size
• cv: ∆log coefficient of variation
• Se: standard error of predicted values
In order to decide whether the mean of the differences between moduli values (∆log) is
statistically zero, hypothesis-testing using the equality of two sample means (paired differences)
was performed. The following hypotheses were tested for all comparisons conducted in this
study: H0: D = 0 and H1: D ≠ 0. The use of this hypothesis test is equivalent to checking if there
is any bias in the relationship. The appropriate test statistic for the hypothesis is expressed by the
t-distribution (t0) in equation 2:
nS
Dt
D ⋅
=0 .................................................................................................................................. (2)
The two sample t-test was compared with three different significance levels (α) for every
comparison: 1, 5 and 10%. This was done as an aid to assess the relative sensitivity of the
significance level to the final decision reached in the hypothesis test. The results of the t-paired
test in conjunction with the statistical parameters obtained from linear regressions were used to
decide on the equality or difference of the samples evaluated for every comparison study.
Afterwards, extreme outlier pairs were identified by looking at the scatter plots and removed for
TRB 2009 Annual Meeting CD-ROM Paper revised from original submittal.
Cary and Zapata 6
the second round of statistical analysis. Therefore, every comparison in this study was performed
without including outlier points.
COMPARISON OF BACKCALCULATED MODULI: ADOT VERSUS. SHRP-LTPP
The first objective of the study was to evaluate the relative similarity of FWD data obtained from
two different sources: the SHRP-LTPP program database and the ADOT-PMS sections. This
was accomplished by selecting deflection measurements suitable for comparison from both
sources and obtaining resilient modulus by using the MODULUS v6.0 backcalculation software.
The three layered system mode of MODULUS v6.0 was employed in this part of the study. In
this mode, the program estimates the depth to a rigid layer. Since no data regarding depth to a
rigid layer was provided by ADOT-PMS, the program was run in this mode for both, ADOT-
PMS and SHRP-LTPP databases for the sake of consistency. Thus, any differences found were
attributed to the FWD type, testing methodology used by SHRP and ADOT, pavement structure,
and environmental conditions (test date).
Ideally, 28 pairs of data should compound the sample for the statistical comparison of all
the three pavement layers if values obtained for the two lanes at each one of the 14 ADOT-PMS
test locations were considered. However, some backcalculated results were considered outliers
and removed from the sample. In addition, some pavement structures are full depth. Therefore,
the value of “n” in Table 1 should not be expected to be always the same. Similar criterion was
applied to the analyses shown in this paper (2).
Figure 1 (a, b and c) shows the comparison between moduli backcalculated from the
ADOT–PMS and the SHRP-LTPP databases using MODULUS v6.0. Figure 1(a) shows little, if
any, correspondence for the surface modulus comparison. However, it is important to recall that
a portion of this scatter is undoubtedly due to slight temperature differences between database
observations. Even though the hypothesis of equality of means is accepted at 1 and 5%, and
rejected for a 10% of significance level as shown in Table 1; the high scatter reflected by a
coefficient of determination of 0.06 and a low slope value of 0.24 are proof of a very poor
correspondence between moduli. For the granular base, the hypothesis is accepted at all levels.
However, Figure 1(b) shows a coefficient of determination of 0.04 and a slope of 0.24 which is
indicative of a poor comparison.
For the subgrade modulus, the hypothesis test is always accepted. However, Figure 1(c)
shows a low coefficient of determination of 0.20 suggesting high dispersion in the data points.
Nonetheless, it should be noticed that the slope of 0.66 indicates that the subgrade modulus is the
material with the highest degree of reliability among all layers in the pavement structure.
In order to evaluate the error caused by the difference in pavement structures between the
two data sources, deflections from the ADOT-PMS and SHRP-LTPP were backcalculated using
MODULUS v6.0 but this time considering the same LTPP pavement structure for both
deflection data sets. For brevity, the detailed figures and tables have not been shown. However,
it was concluded that while the general comparative criterion did improve somewhat; differences
in pavement cross section utilized by each agency, had little impact upon the backcalculated
modulus. Because the results indicate that the pavement cross section had little influence upon
the backcalculated modulus; it appears other factors, like temperature variation, differences in
FWD equipment or FWD backcalculation methodology used are the significant factors causing
the discrepancy between the ADOT and SHRP databases.
TRB 2009 Annual Meeting CD-ROM Paper revised from original submittal.
Cary and Zapata 7
log MR ADOT = 0.24 log MR SHRP + 4.35
R2 = 0.059
1.E+05
1.E+06
1.E+07
1.E+05 1.E+06 1.E+07
Modulus (psi) - SHRP
Mo
du
lus
(psi
) -
AD
OT
.
SHRP vs. ADOT-L1 SHRP vs. ADOT-L2
(a) Surface Layer Modulus
log MR ADOT = 0.24 log MR SHRP + 3.51
R2 = 0.036
1.E+03
1.E+04
1.E+05
1.E+06
1.E+07
1.E+03 1.E+04 1.E+05 1.E+06 1.E+07
Modulus (psi)-SHRP
Mo
du
lus
(psi
)-A
DO
T .
SHRP vs. ADOT-L1 SHRP vs. ADOT-L2
(b) Base Layer Modulus
log MR ADOT = 0.66 log MR SHRP + 1.44
R2 = 0.196
1.E+04
1.E+05
1.E+06
1.E+04 1.E+05 1.E+06
Modulus (psi)-SHRP
Mod
ulu
s (p
si)-
AD
OT
.
SHRP vs. ADOT-L1 SHRP vs. ADOT-L2
(c) Subgrade Material Modulus
FIGURE 1 Comparison of backcalculated modulus: SHRP vs. ADOT when using
different pavement cross section data.
TRB 2009 Annual Meeting CD-ROM Paper revised from original submittal.
Cary and Zapata 8
TABLE 1 Statistical Comparison of Backcalculated Moduli: SHRP vs. ADOT - Use of
Different Pavement Cross Section Data
Subgrade Modulus - ∆ Log Base Modulus - ∆ Log Surface Modulus - ∆ Log
D 0.07039 D -0.24264 D 0.09836
sD 0.21247 sD 0.73984 sD 0.25627
n 26 n 20 n 26
cv 3.02 cv 3.05 cv 2.61
Se 0.210 Se 0.651 Se 0.205
Significance Level: αααα = 0.01
(-) t.005,25 -2.787 (-) t.005,19 -2.861 (-) t.005,25 -2.787
(+) t.005,25 2.787 (+) t.005,19 2.861 (+) t.005,25 2.787
t0 1.69 t0 -1.47 t0 1.96
H0: D=0 accepted H0: D=0 accepted H0: D=0 accepted
H1: D≠0 rejected H1: D≠0 rejected H1: D≠0 rejected
Significance Level: αααα = 0.05
(-) t.025,25 -2.06 (-) t.025,19 -2.093 (-) t.025,25 -2.06
(+) t.025,25 2.06 (+) t.025,19 2.093 (+) t.025,25 2.06
t0 1.69 t0 -1.47 t0 1.96
H0: D=0 accepted H0: D=0 accepted H0: D=0 accepted
H1: D≠0 rejected H1: D≠0 rejected H1: D≠0 rejected
Significance Level: αααα = 0.10
(-) t.050,25 -1.708 (-) t.050,19 -1.729 (-) t.050,25 -1.708
(+) t.050,25 1.708 (+) t.050,19 1.729 (+) t.050,25 1.708
t0 1.69 t0 -1.47 t0 1.96
H0: D=0 accepted H0: D=0 accepted H0: D=0 rejected
H1: D≠0 rejected H1: D≠0 rejected H1: D≠0 accepted
COMPARISON OF SUBGRADE BACKCALCULATED MODULI: MODULUS V6.0 /
MODCOMP V4.2 VS. OUTER GEOPHONE EQUATION
This part of the study evaluated the similarity of subgrade modulus results by analyzing
deflections obtained from several predictive schemes. The first set of moduli comparisons were
obtained from backcalculation runs performed with MODCOMP v4.2 and reported by SHRP-
LTPP in their SDR 20.
Comparison of Results from Different Backcalculation Programs
Eleven sections were used to compare the results obtained from using MODULUS v6.0 to those
obtained from using MODCOMP v4.2, as the backcalculated moduli for three of the 14 original
sections were not reported within the LTPP SDR 20. The MODULUS v6.0 is the software
provisionally selected to backcalculate modulus from deflection data sets available for building
the database in the ADOT-ASU project towards the implementation of the ME-PDG. Therefore,
the main objective of this preliminary phase in the second part of this study was to determine
whether the software to be used provided results consistent with those obtained and reported by
SHRP-LTPP using MODCOMP v4.2.
TRB 2009 Annual Meeting CD-ROM Paper revised from original submittal.
Cary and Zapata 9
In this study, the pavement cross section data as well as the Poisson’s ratio for each layer were
used to run both, the MODULUS v6.0 and MODCOMP v4.2 programs. Also, the depth to a rigid
layer was used as an input in the multilayer analysis mode of MODULUS v6.0. The input data
used for MODULUS v6.0 was the same as that reported by SHRP LTTP when runs with
MODCOMP v4.2 were performed.
Figure 2 (a, b and c) shows the comparison of results. Acceptable values for the slope of
the regression trend lines for the three pavement materials (0.9 – 1.3) were obtained. High
coefficients of determination for the surface, base and subgrade layers noted in Figure 2 (a, b and
c) plus the acceptance of the hypothesis test for every significance level in Table 2, suggest a
good to very good correspondence in the results obtained for backcalculation of surface, base
and subgrade modulus by using different programs. Based upon the results of this preliminary
work, it was concluded that no significant difference was encountered between backcalculated
modulus obtained with MODULUS v6.0 and MODCOMP v4.2.
Suitability of Outer Geophone Equation for Prediction of Subgrade Moduli
From the previous section; it was concluded that regardless of which data source was being used
to estimate the subgrade modulus, the agreement between methods and programs was good
enough to consider this value for the implementation of the ME-PDG for ADOT. This final part
of the study evaluated if the predictions of the subgrade modulus, obtained with backcalculation
programs, could be achieved by using Equation 3, proposed in the “1993 AASHTO Guide for
Design of Pavement Structures” (7) for backcalculation of design subgrade modulus. For
purposes of this report, this equation is referred to as the “outer Geophone” equation.
rd
PM
r
R⋅
⋅=
24.0............................................................................................................................... (3)
where,
MR = backcalculated subgrade resilient modulus in psi,
P = applied load in pounds,
dr = measured deflection at radial distance r in inches, and
r = radial distance at which the deflection is measured, in inches.
The equation is based on linear elasticity and therefore, it can be deduced that at a point
sufficiently distant from the center of loading, the measured surface deflection is entirely due to
deformation in the subgrade and is independent of the load radius. If nonlinearity exists in the
subgrade, the surface deflection used for backcalculation should be measured far enough away to
provide a good estimate of subgrade modulus, independently of the effect of any layers above,
but also close enough to avoid any misleading result due to any stress dependent response.
The minimum distance for considering a deflection measurement capable of reflecting
only the subgrade resilience properties is determined by using the following relationship:
ear ⋅≥ 7.0 ..................................................................................................................................... (4)
TRB 2009 Annual Meeting CD-ROM Paper revised from original submittal.
Cary and Zapata 10
log MR MODCOMP = 0.89 log MR MODULUS + 0.66
R2 = 0.913
1.E+05
1.E+06
1.E+07
1.E+05 1.E+06 1.E+07
Modulus (psi)-MODULUS v6.0
Mod
ulu
s (p
si)-
MO
DC
OM
P v
4.2
rt
(a) Surface Layer Modulus
log MR MODCOMP = 1.31 log MR MODULUS +1.33
R2 = 0.970
1.E+04
1.E+05
1.E+06
1.E+04 1.E+05 1.E+06
Modulus (psi)-MODULUS v6.0
Mod
ulu
s (p
si)-
MO
DC
OM
P v
4.2
rt
(b) Base Layer Modulus
log MR MODCOMP = 0.9019 log MR MODULUS + 0.4521
R2 = 0.855
1.E+04
1.E+05
1.E+06
1.E+04 1.E+05 1.E+06
Modulus (psi)-MODULUS v6.0
Mod
ulu
s (p
si)-
MO
DC
OM
P v
4.2
rt
(c) Subgrade Material Modulus
FIGURE 2 Comparison of backcalculated modulus for LTPP sections: MODULUS
v6.0 vs. MODCOMP v4.2.
TRB 2009 Annual Meeting CD-ROM Paper revised from original submittal.
Cary and Zapata 11
TABLE 2 Statistical Comparison of Backcalculated Moduli: MODCOMP v4.2 vs.
MODULUS v6.0
Subgrade Modulus - ∆ Log Base Modulus - ∆ Log Surface Modulus - ∆ Log
D -0.00401 D -0.08489 D 0.00854
sD 0.10489 sD 0.17195 sD 0.10888
n 12 n 8 n 11
cv 26.15 cv 2.03 cv 12.75
Se 0.102 Se 0.111 Se 0.106
Significance Level: αααα = 0.01
(-) t.005,11 -3.106 (-) t.005,7 -3.499 (-) t.005,10 -3.169
(+) t.005,11 3.106 (+) t.005,7 3.499 (+) t.005,10 3.169
t0 -0.13 t0 -1.40 t0 0.26
H0: D=0 accepted H0: D=0 accepted H0: D=0 accepted
H1: D≠0 rejected H1: D≠0 rejected H1: D≠0 rejected
Significance Level: αααα = 0.05
(-) t.025,11 -2.201 (-) t.025,7 -2.365 (-) t.025,10 -2.228
(+) t.025,11 2.201 (+) t.025,7 2.365 (+) t.025,10 2.228
t0 -0.13 t0 -1.40 t0 0.26
H0: D=0 accepted H0: D=0 accepted H0: D=0 accepted
H1: D≠0 rejected H1: D≠0 rejected H1: D≠0 rejected
Significance Level: αααα = 0.10
(-) t.050,11 -1.796 (-) t.050,8 -1.895 (-) t.050,10 -1.812
(+) t.050,11 1.796 (+) t.050,8 1.895 (+) t.050,10 1.812
t0 -0.13 t0 -1.40 t0 0.26
H0: D=0 accepted H0: D=0 accepted H0: D=0 accepted
H1: D≠0 rejected H1: D≠0 rejected H1: D≠0 rejected
where,
ae = radius of the stress bulb at the subgrade-pavement interface in inches, as follows:
⋅+=
2
32
R
p
eM
EDaa ......................................................................................................... (5)
where,
a = non-destructive test (NDT) load plate radius in inches,
D = total thickness of pavement layers above the subgrade in inches, and
Ep = effective modulus of all pavement layers above the subgrade in psi.
To obtain the effective modulus of the pavement, the subgrade modulus and total
thickness of all layers above the subgrade should be known or assumed. The deflection measured
at the center of the load plate is used to determine the effective modulus of the entire pavement
TRB 2009 Annual Meeting CD-ROM Paper revised from original submittal.
Cary and Zapata 12
structure. The specific equations to use to determine the Ep value of a pavement system can be
found in reference (7).
The AASHTO Outer Geophone equation was used to compute the subgrade modulus of
the same sections considered in the previous part of the study. An analysis of the minimum radial
distance was computed for each of the 11 sections studied. These values ranged from 16.4 in to
50.9 in. As a result, deflections from the outer two sensors: 6th
and 7th
at 36 in and 60 in of
distance from the center of loading, respectively, were used, depending upon the pavement
structure. The predicted subgrade moduli using the outer geophone equation was then compared
with the subgrade backcalculated modulus from both software packages: MODCOMP v4.2 and
MODULUS v6.0.
It is important to note that two outlier points were identified in the first round of the
statistical analysis and removed from the samples. Even though Table 3 shows rejection of the
hypothesis at the 5 and 10% levels of significance, when comparing results from the outer
geophone equation with results from MODULUS v6.0, the hypothesis becomes accepted at the
1% level of significance. Furthermore, the scatter plot in Figure 3 (a) shows an acceptable
coefficient of determination of 0.8 indicating little to moderate dispersion; and a slope of 0.77
suggesting that results of the comparison are acceptable. Therefore, it was concluded that there is
a fair to good correspondence between subgrade modulus obtained from MODULUS v6.0 and
the outer geophone equation. A coefficient of determination of 0.77 and a slope of 0.82 observed
in Figure 3 (b) accompanied by the acceptance in the hypothesis test at all levels of significance
in Table 3 suggests a good to very good correspondence between predicted subgrade moduli
from MODCOMP v4.2 and those from the outer geophone equation.
In summary, this part of the study revealed a fairly strong correspondence between
backcalculated subgrade moduli obtained by using the simple outer geophone equation and those
obtained by using MODULUS v6.0 and MODCOMP v4.2.
CONCLUSIONS AND RECOMENDATIONS
For all layer materials, there appears to be a poor correspondence of backcalculated modulus
obtained by using deflection data from SHRP–LTPP and ADOT–PMS databases. Even when
assuming that the pavement structure for both data sources is the same one, results of the
comparison are not improved significantly. Different factors contribute to the uncertainty in the
correspondence of results from both data sources: different FWD type used for field testing,
different test dates (variation in pavement AC layer temperature), different backcalculation
methodologies, and different pavement structures. Surface and base modulus generally show a
weak correspondence and are not considered reliable.
Results show that the subgrade modulus seems to be the most reliable value among the
materials analyzed in the pavement structure. In general, regardless of the deflection data source
employed for the backcalculation, the comparison results obtained for subgrade modulus always
showed to be the best.
It has been observed that by using two of the best known backcalculation programs in
this study, reasonably comparable results may be obtained. This observation can be extended to
backcalculation methodologies other than elaborate backcalculation programs like the outer
geophone equation. The modulus obtained by using the outer geophone equation appears to be a
highly accurate estimation of subgrade moduli predicted from any complex multilayer
backcalculated FWD deflection basin program, currently in use today.
TRB 2009 Annual Meeting CD-ROM Paper revised from original submittal.
Cary and Zapata 13
log MR Outer Geo. Eq. = 0.77 log MR MODULUS + 1.07
R2 = 0.809
1.E+04
1.E+05
1.E+04 1.E+05
Modulus from MODULUS v6.0 (psi)
Mod
ulu
s fr
om
Ou
ter
Geo
. E
q. (p
si)
rg
(a) Comparison with MODULUS
log MR Outer Geo. Eq. = 0.82 log MR MODCOMP + 0.78
R2 = 0.774
1.E+04
1.E+05
1.E+04 1.E+05
Modulus from MODCOMP v4.2 (psi)
Mod
ulu
s fr
om
Ou
ter
Geo
. E
q. (p
si)
rg
(b) Comparison with MODCOMP
FIGURE 3 Comparison of subgrade modulus: Backcalculation programs vs. outer
geophone equation.
TRB 2009 Annual Meeting CD-ROM Paper revised from original submittal.
Cary and Zapata 14
TABLE 3 Statistical Comparison of Subgrade Backcalculated Moduli:
MODULUS/MODCOMP vs. Outer Geophone Equation
Comparison with
MODULUS - ∆ Log
Comparison with
MODCOMP - ∆ Log
D -0.04256 D 0.033231
sD 0.08710 sD 0.087140
n 20 n 20
cv 2.05 cv 2.62
Se 0.076 Se 0.083
Significance Level: αααα = 0.01
(-) t.005,19 -2.861 (-) t.005,19 -2.861
(+) t.005,19 2.861 (+) t.005,19 2.861
t0 -2.19 t0 1.71
H0: D=0 accepted H0: D=0 accepted
H1: D≠0 rejected H1: D≠0 rejected
Significance Level: αααα = 0.05
(-) t.025,19 -2.093 (-) t.025,19 -2.093
(+) t.025,19 2.093 (+) t.025,19 2.093
t0 -2.19 t0 1.71
H0: D=0 rejected H0: D=0 accepted
H1: D≠0 accepted H1: D≠0 rejected
Significance Level: αααα = 0.10
(-) t.050,19 -1.729 (-) t.050,19 -1.729
(+) t.050,19 1.729 (+) t.050,19 1.729
t0 -2.19 t0 1.71
H0: D=0 rejected H0: D=0 accepted
H1: D≠0 accepted H1: D≠0 rejected
Based on the previously stated conclusions, the following recommendations are
suggested regarding the implementation of the ME-PDG for ADOT:
• Regardless of any backcalculation methodology used to estimate layer modulus, the
characterization of the asphalt concrete and granular bases based on backcalculation results may
not be the most optimal approach for implementation of the ME-PDG for ADOT.
• The use of E* Dynamic Modulus testing results or predictive models are suggested
for characterization of the asphalt concrete as proposed in the hierarchical levels of analysis in
the ME-PDG. Even when further studies should be pursued to analyze the accuracy of these
methods, the characterization of resilience properties for granular bases can be achieved by using
direct correlations of resilient modulus with California Bearing Ratio (CBR) values or indirect
correlations of resilient modulus with R values and index properties as proposed in the 2nd
hierarchical level of analysis in the ME-PDG.
• Either MODULUS or MODCOMP can be used to characterize the resilient properties
of the subgrade for the implementation of the ME-PDG for ADOT.
• Since surface and base backcalculated modulus may be highly dependent on the
specific deflection procedure used; the outer geophone approach presented in the “1993
AASHTO Guide for Design of Pavement Structures” for backcalculation of subgrade resilient
modulus is recommended for its simplicity and reliability.
TRB 2009 Annual Meeting CD-ROM Paper revised from original submittal.
Cary and Zapata 15
ACKNOWLEDGEMENTS
The authors would like to thank the Arizona Department of Transportation for financially
supporting this research under project “SPR 606-Development and Implementation of the
Mechanistic Empirical (M-E) Pavement Design Guide for Arizona”. Dr. Matthew Witczak
serves as the Principal Investigator for this project and his general overview guidance and
valuable input and corrections to the manuscript are acknowledged.
REFERENCES
1. Witczak, M. W., M. S. Mamlouk, C. E. Zapata, and, K. E. Kaloush. SPR 606-Development
and Implementation of the Mechanistic Empirical (M-E) Pavement Design Guide for
Arizona, 2007.
2. Zaghloul, S., Z. Ahmed, D. J. Swan, A. A. Jumikis, and, N. Vitillo. Falling Weight
Deflectometer Correlation. In Transportation Research Record: Journal of the
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3. Van Gurp, C. Consistency and Reproducibility of Falling Weight Deflectometer. Proc., Road
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Data for Use in Implementing the ME-PDG for the Arizona DOT. SPR 606-Development
and Implementation of the Mechanistic Empirical (M-E) Pavement Design Guide for
Arizona, Inter Team Technical Report, August 2008.
7. AASHTO Guide for Design of Pavement Structures, Washington, D.C. AASHTO,
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TRB 2009 Annual Meeting CD-ROM Paper revised from original submittal.