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• It is important to mention that the state DOTs do not may result in different moduli, because strains experi-
use the same backcalculation program for interpreting enced in the subgrades are different for different stress
the resilient moduli properties. Currently, several soft- conditions.
ware programs are available with different algorithms • The majority of the new nondestructive devices show
to backcalculate moduli. According to the Pavement a considerable potential to be used for quality assess-
Design group survey , the most used programs are ments of compacted subgrades and unbound bases. A
EVERCALC and MODULUS. recent research study also correlated the moduli from
• GeoGauge, another nondestructive device used for LWDs with the parameters measured in the intelli-
stiffness measurements, provides stiffness values of gent compaction devices. Though certain issues such
the subsoils based on the analysis of deformations as moisture and temperature effects on the moduli
measured by applying a harmonic load. Stiffness properties of field sections still need to be addressed,
properties measured are related to a shallow depth the overall potential of these devices as alternatives to
of soil layer and are valid for medium levels of shear nuclear gauge devices for compaction quality assess-
strains. A few studies showed a good match between ments are commendable. Further research is expected
GeoGauge moduli and FWD moduli. Correlations in these areas.
between GeoGauge moduli and resilient moduli still
need to be developed.
• Another device known as the PSPA was recently intro- Intrusive Methods
duced, and its potential use in providing reliable moduli
properties of base and subgrades was recently investi- Intrusive or in situ penetration methods have been used for
gated. An extension of this device, the DSPA, was also years to determine moduli properties of various pavement
recently evaluated. Though this device holds consider- layers. Intrusive methods can be used for new pavement con-
able initial promise, it still requires more research to struction projects and also in pavement rehabilitation proj-
fully evaluate the potential of this device for determin- ects wherein the structural support of the pavement systems
ing the moduli of subsoils. can be measured (Newcomb and Birgisson 1999). Various
• Several LWDs were addressed in many DOT-funded intrusive methods are briefly reviewed here and then a sum-
research studies. These devices including PRIMA mary is provided of the findings from various state-funded
100, LOADMAN PFWD, ZFG 2000, and Dynatest/ research projects.
KEROS were evaluated in several studies funded by
Minnesota, Wisconsin, and Louisiana DOTs. Moduli Dynamic Cone Penetrometer
interpreted by most of these devices showed good cor-
relations with FWD moduli, though not always match- The DCP is a widely used in situ method for determining the
ing with the FWD moduli. Nevertheless, the moduli compaction density, strength, or stiffness of in situ soils. The
trends with respect to soil type and soil compaction DCP is a simple testing device, wherein a slender shaft is
are similar, and hence it is possible that these devices driven into the compacted subgrades and bases using a slid-
could be used to predict resilient moduli of compacted ing hammer weight and the rate of penetration are measured.
subgrades and unbound bases. ASTM has recently Penetration is carried out as the hammer drops to reach the
approved a standard test procedure for performing desired depth. The rod is then extracted using a specially
LWD tests in the field. The intent is to standardize a adapted jack. Data from the DCP test are then processed to
test procedure using LWDs with load cells to measure produce a penetration index, which is simply the distance the
the deflection and modulus of compacted subgrades cone penetrates at each drop of the sliding hammer. In brief,
in the field. Another standard for LWDs without load the DCP is a miniature version of the Standard Penetration
cells is currently under development (J. Siekmeier, Test method with a conical tip.
personal communication, Aug. 21, 2007; K.C. Kessler,
personal communication, Aug. 21, 2007). Figure 66 presents a schematic of DCP used for field inves-
• Irwin (1995) summarized various problems noted tigations. The hammer weight and height of drop configura-
by a discussion group and then outlined methods to tions of DCPs vary from one state to another. Hence, these
overcome a few of these problems. Interpretations of details should be included when discussing the results of the
moduli from nondestructive devices yield moduli of QA studies utilizing this equipment. An ASTM standard on
subgrades at considerable depths, and hence it is impor- the DCP method was introduced in 2003 (ASTM D6951-03).
tant to address the effects of confining and deviatoric Typically, in this test, the measured soil parameter from the
stresses on the moduli values, which in turn should be test is the number of blows for a given depth of penetration.
properly accounted for in the triaxial tests. Otherwise, Several parameters from DCP tests are typically determined
comparisons will not be meaningful. Also, the stresses and these are termed as dynamic cone resistance (qd) or DCP
imposed by the loading mechanisms of certain LWDs index (DCPI) in millimeters per blow or inches per blow or
are quite small when compared with FWDs, and this blows per 300 mm penetration. These parameters are used
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Yoon (2003) provided a summary of these available rela-
tionships in the literature. Chai and Roslie (1998) developed
the following relationship between DCP parameters and soil
subgrade modulus backcalculated from the FWD studies:
E in MPa = 2224 × DCP-0.99 (6)
where DCP is measured in blows per 300 mm penetra-
tion. Overall this correlation indicates that the FWD moduli
are inversely proportional to the DCP parameter measured
in the field.
Hassan (1996) developed a correlation of MR with the
DCPI parameter (Equation 7). This correlation is valid for
the materials tested in the original investigations. The com-
paction moisture contents varied between optimum and wet
of optimum:
MR in psi = 7013.0 – 2040.8 ln (DCPI) (7)
where the DCPI is in inches per blow.
George and Uddin (2000) correlated MR of subgrades as a
function of DCPI, moisture content, liquid limit, and density
of subgrades. In this research, both manual and automated
DCPs were used. Figure 67 presents a typical comparison
of both DCP results, which indicate no differences between
both operations on the DCP measurements.
FIGURE 66 Schematic of dynamic cone penetrometer
(ASTM D6951-03).
to evaluate the compaction density, strength, or stiffness of
in situ soils.
One major limitation reported in the research studies is
the lack of standardization of the testing devices. Differ- FIGURE 67 Comparisons between ADCP and MDCP results
ent size cones, hammer weights, and heights of drop have (George and Uddin 2000).
been used in these studies, which result in different ener-
gies applied by each device. As a result, the parameters mea- The DCPI was then determined for each layer by taking
sured from a particular study and the correlations developed the slope of the plots. The change in slope defines the varia-
from that study could not be applied elsewhere if a different tions in layers in the test. Once DCPI values of subgrades
type of DCP was used. Practitioners and researchers should were determined, they were used in the correlation analysis
always record the potential energy applied with the DCP with the resilient moduli data from the laboratory tests con-
device when used in the field conditions. ducted on the cores collected from different depths.
Stiffness Predictions by Dynamic Cone Penetrometer From the laboratory results, data for a confining pres-
sure of 14 kPa and a deviatoric stress of 37 kPa were used
Several researchers have developed design charts showing as moduli parameters for the analysis. Figure 68 presents a
correlations between resilient modulus (MR) or stiffness of correlation between resilient moduli and DCPI in millime-
subgrades and bases and the penetration parameters mea- ters per blow of the corresponding subgrade layer for fine-
sured from the DCP test. Amini (2003) and Salgado and grained soils.
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blow, yielded a nonlinear regression model presented in
Equation 10:
ln MFWD = 2.35 + [5.21 /ln PR] (10)
The R2 value for this correlation is 0.91, indicating a good
correlation. Figure 70 presents comparisons between the
developed correlation predictions along with the raw test
data as well as other available models in the literature.
Edil and Benson (2005) reported several correlations
FIGURE 68 Correlation between resilient modulus and DCPI composed of DCP parameters and GeoGauge SSG param-
for fine-grained soils (George and Uddin 2000). eters (see Figure 71). No direct relationships were developed
between DCP parameters and the resilient moduli; however,
For simple use, George and Uddin (2000) also pro- moduli can be approximated based on GeoGauge stiffness
vided direct one-to-one relationships for both coarse- and parameters.
fine-grained soils for the same parameters. The following
relationships were developed from their field studies (Equa- Edil and Benson (2005) determined correlation coeffi-
tion 8 for coarse-grained and Equation 9 for fine-grained cients in their regression analysis. This study also showed
soils): the potential use of DCP to address compaction quality of
the subgrades. The normalized DCP parameter with respect
MR in MPa = 235.3 × DCPI-0.48 (8) to compaction moisture contents was correlated with the rel-
ative compaction of the subgrades (see results in Figure 72).
The normalized parameters were close to 0 for the major-
MR in MPa = 532.1 × DCPI-0.49 (9) ity of the compacted subgrade and varied between −200 and
150 for uncompacted subgrades. These results show that the
DCP can be utilized for compaction quality assessments of
Abu-Farsakh et al. (2004) studies also focused on the subgrades. Other studies by Amini (2003) and Zhang et al.
DCP device for determining moduli properties of Louisiana (2004) reported similar DCP applications.
subsoils. Experimental and field investigations are already
explained in the previous sections. Figure 69 shows two As part of the research performed for the Kansas DOT,
DCP tests conducted on the identical subgrade material Chen et al. (1999) conducted DCP and FWD tests on six
specimen in laboratory conditions, and these results show pavements. EVERCALC was used for backcalculating the
that the DCP provides repeatable results.
The regression analysis, which was conducted to find
the best correlation between the MFWD in MPa and the
DCP parameter, penetration ratio (PR) in millimeters per
FIGURE 69 DCP tests on compacted material (Abu-Farsakh FIGURE 70 Comparisons between backcalculated moduli
et al. 2004). from DCP correlation (Abu-Farsakh et al. 2004).
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stiffness of subgrades. The following correlation was devel-
oped between backcalculated moduli or stiffness of subgrade
and the DCP parameter, DCPI in millimeters:
MR (ksi) = 338 × DCPI-0.39 (11)
where DCPI is expressed in millimeters per blow. The R2
of 0.42 is obtained for this correlation.
Chen et al. (2001) used CBR DCP parameter-based indi-
rect correlations to estimate the moduli from DCP results of
field sections used for TxDOT accelerated loading-related
tests. The predicted moduli are comparable with those cal-
culated from maximum dry density measurements under
FWD tests. This study reported that the laboratory-deter-
mined subgrade soil moduli were slightly higher than the
estimated moduli from the DCP-based indirect correlations.
The factor of 0.33 currently recommended by the 1993
AASHTO design guide to convert backcalculated modulus
to laboratory resilient modulus is not applicable to the data
measured by Chen et al. (2001).
Chen et al. (2007) developed new equations based on
their test data for both base and subgrade soils. The equation
is of the following form:
MR (ksi) = 78.05 × DPI-0.67 (12)
where DPI is measured in millimeters per blow.
Nazarian et al. (1996) used DCP on aggregate bases to
measure the DCPI values. Figure 73 presents the DCP results
at different elevations of the base layer. This research has not
FIGURE 71 Correlations between DCP parameters and SSG addressed the use of DCP to determine the modulus as the
stiffness properties of compacted subgrades (Edil and Benson equations used are empirical in nature. The results in the
2005).
figure show the transitions from layer to layer.
The MnDOT supported several new studies addressing
the use of DCP to assess compaction quality to determine
the moduli of pavement layers. Dai and Kremer (2006) and
Petersen and Petersen (2006) assessed the newly developed
FIGURE 72 Correlations between normalized DCP parameter
with relative compaction (RC) of the subgrades (Edil and
Benson 2005). FIGURE 73 DCP results on a base layer (Nazarian et al. 1996).
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DCP-based specifications for addressing the construction of tional resistance ( fs). Another independent parameter is the
compacted subgrades and bases as well as the potential use total pore pressures (ut) at one or more locations, which are
of the DCP in place of sand cones to evaluate the relative measured when the cone penetrometer is fitted with piezome-
densities of the granular fills. The overall feedback from the ters. Figure 75 shows a piezocone device. All these measured
field inspectors was positive.
FIGURE 74 presents the moduli interpreted from DCP
and other devices for a site subjected to intelligent compac-
tion. The DCP correlation used to determine the modulus
(EDCP, which is similar to backcalculated FWD or LWD
stiffness values) follows:
Log (EDCP) = 3.05 – 1.06 × log (DCP) (13)
where DCP is measured in millimeters per blow.
In summary, the DCP device has been used by different
agencies for years to estimate the moduli of compacted sub-
grades and granular soils. Other applications of this device
include compaction QC/QA tests and determination of lay-
ering by studying the slope variations in the DCP profiles.
The majority of the correlations developed for resilient mod-
ulus are site specific and empirical in nature and hence their
use for soils other than those used in the studies requires a
careful examination and engineering judgment.
Quasi-Static Cone Penetrometer
Cone penetration tests (CPTs) provide two independently
measured parameters, cone tip resistance (qc) and cone fric- FIGURE 75 Piezocone penetrometer.
FIGURE 74 Moduli interpreted by DCP and comparisons with other moduli (Petersen and Peterson 2006).
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parameters, upon various corrections and modifications, can that are representative of the stress conditions under a traffic
be used to classify soil strata and interpret various properties single-wheel loading of 20 kN. ELSYM5 was used for the
of the stratified soils. Several classification and interpreta- stress analysis. Based on statistical analyses, two correla-
tion charts are already available in the literature (a summary tion models were proposed to estimate the resilient modulus
can be found in Meigh 1987). from the CPT data and basic soil properties. The first one
is valid for in situ subgrade conditions and the second one
Resilient Moduli Interpretations by Cone Penetration is valid for overburden and traffic conditions. Equation 14
Tests is derived for overburden conditions and Equation 15 is for
overburden and traffic conditions:
Mohammad et al. (2000, 2002, 2007; Gudishala 2004) pres-
ent the results of a research investigation in which CPT
soundings were used to predict the resilient modulus of sub- (14)
grade soils. Field and laboratory testing programs were car-
ried out on two types of cohesive soils. CPT soundings were
performed using two types of cones: large and miniature
CPT devices with cross-sectional areas of 15 cm 2 and 2 cm2. (15)
Figure 76 presents CPT results obtained on sites containing
heavy clay material. Resilient modulus tests were also con-
ducted on both clays, and these results along with the CPT where MR is the resilient modulus (MPa), qc is the cone
results were statistically analyzed. resistance (MPa), fs is the sleeve friction (MPa), σc or σ3
is the confining stress (kPa), σv is the vertical stress (kPa),
Resilient modulus results of clays at various stress condi- w is the water content in decimal number format, γ is the
d
tions in the laboratory are used to determine realistic moduli dry unit weight (kN/m3), and γ is the unit weight of water
w
FIGURE 76 CPT results on heavy clay (Mohammad et al. 2000).
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(kN/m3). The coefficients of determination values for both for coarse soils was separately developed for coarse-grained
equations are reported as 0.99. materials for both overburden and combined overburden and
traffic conditions (Mohammad et al. 2000).
Figure 77 shows the predictions of the above model and
the resilient moduli measurements for various site sub- Pressuremeter
grades. The authors reported that a good agreement between
predicted and measured moduli of cohesive subgrades was The following section provides detailed descriptions and
obtained (Mohammad et al. 2000). These correlations are operation details of pressuremeters (PMTs) used for resilient
developed for silty clay and heavy clayey soils, and hence moduli predictions. Figure 78 presents a typical schematic of
they are valid for such soils only. Another set of correlations a TEXAM PMT device.
Typically, this test is performed either in stress-controlled
or strain-controlled environments. In stress-controlled con-
ditions, applied pressure is increased on the membrane and
the corresponding displacements are monitored. In strain-
controlled tests, the rate of expansion of the membrane is
controlled by the use of volumetric increments through liq-
uid-filled PMTs. In these tests, the corresponding pressures
resulting from constant volume increments are monitored.
The measured pressure–strain profiles from these tests can
be used to determine in situ strength and compressibility
characteristics, including stiffness properties. Figure 79
presents the procedure adopted by Cosentino and Chen
(1991) for determining the resilient modulus of subgrades.
Based on the method of installation, PMTs can be clas-
sified into prebored PMTs, self-bored PMTs, and push-in
a) Correlation for overburden stress conditions
b) Correlation for overburden and traffic loading conditions
FIGURE 77 Resilient moduli predictions by CPT models and
measurements by repeated load triaxial tests (Mohammad et
al. 2000). FIGURE 78 TEXAM pressuremeter (Cosentino et al. 2006).
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Major advantages of PMTs are that
they are performed in situ and hence no
soil sampling is needed. One reason for
an insufficient number of research stud-
ies performed on PMTs is the need for
trained individuals to perform the PMT
testing. However, advances in instrumen-
tation and the development of new PMT
probes make these devices more attrac-
tive for performing in situ studies in the
field in a quick and efficient manner. New
PMTs including Pencel PMTs (PPMTs)
can be used in shallow subgrades either
by pushing or by driving. Sophisticated
instrumentation in the PPMTs makes
them more attractive for pavement mod-
uli evaluation studies.
Plate Load Test
Plate load tests (PLTs) were used for
resilient moduli interpretations and a few
states, including Florida and Louisiana,
FIGURE 79 Resilient moduli measurements from radial stress—strain profile have attempted to use them for correlating
(Cosentino and Chen 1991). with the resilient modulus of subgrades
(Abu-Farskh et al. 2003). The PLT opera-
PMTs. Prebored PMTs are lowered into a soil pocket that tions involve loading a circular plate that is in contact with
is bored especially for the test. Self-bored PMTs, such as the layer to be tested and measuring the deflections under
the Cambridge Self-boring Pressuremeter, create their own load increments. Circular plates usually 30 cm (12 in.) in
pockets for tests. Push-in or displacement PMTs, such as diameter are generally used and the loading is transmitted to
cone pressuremeters, are either pushed or driven into vari- the plates by a hydraulic jack.
ous elevations for testing.
During the test, a load-deformation curve will be
The special PMT test called the resilient modulus PMT recorded and these data will be used to estimate the moduli
test was developed to enable six resilient moduli to be of the load—deformation or stress—strain plot, which is
determined from six unload–reload cycles conducted for referred to as EPLT. If the field test is performed in cyclic
various load durations along the linear portion of the in situ mode, then the slope of the stress–strain curve provides the
stress–strain response. The various cycle lengths enabled the moduli. The moduli measured from this test are regarded
resilient moduli to be determined as a function of the load as a composite moduli as the depth of influence is con-
durations typically encountered during the traffic loading of sidered to extend more than one layer (Abu-Farskh et al.
a pavement. The cycle lengths used were 10, 20, 30, 60, 120, 2003). Nelson et al. (2004) also reported the use of PLTs to
and 240 s. The duration of the whole test after the preboring estimate the moduli of compacted retaining wall backfill
operation is 17 minutes. material. Though the PLT method is primarily used for rigid
pavements, several researchers have attempted to correlate
To increase the usefulness of the PMT in the area of pave- the moduli with the elastic moduli of the subgrades. More
ment design and evaluation, resilient moduli (determined research is still needed to better understand the applicabil-
from a special PMT test) were correlated to CBR test results ity of this method in evaluating the resilient properties of
(Cosentino and Chen 1991). The PMT resilient moduli-CBR subgrades and bases.
correlations developed based on 30, 60, and 120 s cycle
lengths compared well with the existing resilient moduli– Dilatometer
CBR correlations measured from 0.1 s cycles. Another study
conducted by Nelson et al. (2004) reported the use of PMT Another in situ intrusive device known as a dilatometer
for estimating the moduli of backfill material. The intent of (DMT) has been used to de termine the resilient moduli
this study was to address the compaction quality of a backfill properties of subgrade soils. Borden et al. (1986) noted
material of a retaining wall. Based on 15 PMTs, the moduli the unique relationship between the resilient modulus and
of subgrades is 26 MPa with a standard deviation of 7 MPa. dilatometer modulus, a parameter measured from field
