EVALUATING THE UTILITY OF EXISTING PAVEMENT …docs.trb.org/prp/09-3199.pdf · EVALUATING THE...

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


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.


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).


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


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.


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


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 .


(b) Base Layer Modulus


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

.


(c) Subgrade Material Modulus

FIGURE 1 Comparison of backcalculated modulus: SHRP vs. ADOT when using

different pavement cross section data.


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


(-) 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




(-) 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.


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)


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


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


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.


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


(-) 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




(-) 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




(-) 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



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


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.


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.


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


(-) 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


(-) 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


(-) 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.


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

Transportation Research Board, No. 1905, Transportation Research Board of the National

Academies, Washington, D.C., 2005, pp. 90-96.

3. Van Gurp, C. Consistency and Reproducibility of Falling Weight Deflectometer. Proc., Road

and Airport Pavement Response Monitoring Systems Conference, U.S. Army Cold Regions

Research & Engineering Laboratory, Sept. 1991, pp. 291-305.

4. Stubstad, R. N., L. H. Irwin, E. O. Lukanen, and, M. L. Clevenson. It’s 10 o’clock Do You

Know Where Your Sensors Are? In Transportation Research Record: Journal of the

Transportation Research Board, No. 1716, Transportation Research Board of the National

Academies, Washington, D.C., 2000, pp. 10-19.

5. Rauhut, J. B., and P. R. Jordhal. Variability in Measured Deflections and Backcalculated

Moduli for the Strategic Highway Research Program Region. In Transportation Research

Record: Journal of the Transportation Research Board, No. 1377, Transportation Research

Board of the National Academies, Washington, D.C., 1992, pp. 45-56.

6. Cary, C. E., and C. E. Zapata. Evaluating the Utility of Existing PMS State FWD Deflection

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,

Washington, D.C., 1993.


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