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Application of the Dynamic Cone Penetrometer (DCP) for determination of
the engineering parameters of sandy soils
Article in Engineering Geology · October 2008
DOI: 10.1016/j.enggeo.2008.05.006
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Engineering Geology 101 (2008) 195–203
Contents lists available at ScienceDirect
Engineering Geology
j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / e n g g e o
Application of the Dynamic Cone Penetrometer (DCP) for determination of the
engineering parameters of sandy soils
S.D. Mohammadi a,⁎, M.R. Nikoudel a, H. Rahimi b, M. Khamehchiyan a
a
b
Department of Engineering Geology, Tarbiat Modares University, Tehran, Iran
Department of Irrigation Engineering, Tehran University, Tehran, Iran
A R T I C L E
I N F O
Article history:
Received 20 November 2007
Received in revised form 26 April 2008
Accepted 22 May 2008
Available online 4 June 2008
Keywords:
Dynamic Cone Penetrometer (DCP)
Poorly graded sandy soil (SP)
Dynamic Penetration Index (DPI)
Index Parameters
Coefficient of variations (Cv)
A B S T R A C T
Determination of the in situ engineering properties of foundation materials has always been a challenge for
geotechnical engineers and, thus, several methods have been developed so far. Dynamic Cone Penetration
(DCP) test is one of the most versatile amongst them. In the present research, a light weight simple DCP
device was developed and used for evaluation of the engineering properties of sandy soils in laboratory
conditions. The device consisted of an 8-kg hammer that drops over a height of 575 mm, and drives a 60°
cone tip with 20 mm base diameter into the ground. To control the validation of the results, laboratory direct
shear and plate load tests were used as reference tests. The soil sample was a poorly graded sandy soil (SP)
taken from alluvial deposits of the Tehran plain. All DCP tests and PLTs were undertaken on compacted soil in
a mould with 700 mm diameter and 700 mm height. Based on the results of the experiments, the
relationships between Dynamic Penetration Index (DPI), relative density (Dr), modulus of elasticity (E), shear
modulus (G), modulus of subgrade reaction (KS), and the friction angle of the soil were obtained with a high
coefficient of determination (N 90%). The repeatability of the test results was also evaluated by calculating the
coefficient of variations (Cv), which was less than 30% for all tests.
© 2008 Elsevier B.V. All rights reserved.
1. Introduction
A truly undisturbed sample is defined as completely intact soil
which its in place structure has not been changed in any way. Such
samples are desirable for those laboratory tests which are dependent
on the structure of soil, such as shear strength. Unfortunately, several
issues make it almost impossible to obtain a truly undisturbed sample,
specially in non-cohesive soils. Regarding to these issues, variety of
techniques have been developed to perform in situ tests such as
dynamic probing. Dynamic probing is a continuous soil investigation
technique and is assumed as one of the simplest soil penetration tests.
It basically consists of repeatedly driving a metal tipped probe into the
ground using a drop weight of fixed mass and travel. Testing is carried
out continuously from the ground level to the final penetration depth.
The continuous sounding profiles enable easy recognition of dissimilar layers and even thin strata by the observed variation in
penetration resistance. The Dynamic Cone Penetrometer (DCP) is a
lightweight dynamic penetrometer which is considerably faster and
cheaper tool than boring, particularly when the depth of exploration is
low and the soils being investigated are not coarse gravel (Sawangsuriya and Edil, 2005).
Scala (1959) originally developed the DCP in Australia. Since then,
it has been used for site characterization of pavement layers and
⁎ Corresponding author.
E-mail address: s_d_mohammadi@yahoo.com (S.D. Mohammadi).
0013-7952/$ – see front matter © 2008 Elsevier B.V. All rights reserved.
doi:10.1016/j.enggeo.2008.05.006
subgrades in South Africa, the United Kingdom, Australia, New
Zealand, and several states in the United States, such as California,
Florida, Illinois, Minnesota, Kansas, Mississippi, and Texas (AbuFarsakh et al., 2004). Some relationships have been developed
between DCP results and CBR (Abu-Farsakh et al., 2004; Chen et al.,
2001; Karunaprema and Edirisinghe, 2002; Rahim and George, 2004;
Nazzal, 2002) and elastic modulus (E) (Mohammadi et al., 2007;
Webster et al., 1992).
The main objectives of this paper are to describe the capability of
the DCP to study the inplace engineering properties of sandy soils.
2. Materials and methods
In order to achieve the appropriate correlations between the DCP
test results and engineering parameters of sandy soils, it was
necessary to select suitable sample. The appropriate sampling area
was selected based on previous experiences and sampling was
performed according to standard methods. Then, the selected samples
were shipped to the laboratory and was prepared for the tests as
explained in the later sections.
2.1. Geology of the sampling area
The sampling area contains four types of lithology belonging to
Late Eocene and Quaternary deposits (Fig. 1). The Late Eocene rock
covers almost 5% of the land surface and it comprises one type of
196
S.D. Mohammadi et al. / Engineering Geology 101 (2008) 195–203
Fig. 1. Geological map of sampling location, modified from Geological Survey of Iran (1998).
lithology which is categorised as Trachyte to Trachyandesite. The
Quaternary deposits cover almost 95% of the land surface and it
comprises three types of lithology which are categorised as conglomerates, old terrace deposits and young terrace deposits. In the present
research, the sampling was performed on the young terrace deposits.
Geologically, the young deposits comprise subrounded sand grains
containing 5% gravel (Fig. 2). The X-ray analysis has shown that the
sandy samples are made of quartz, feldspar, pyroxene and calcite.
2.2. Sample preparation
The data used in this paper were obtained from laboratory tests
undertaken by the authors at the Geotechnical Engineering Laboratory of Tarbiat Modares University, Tehran, Iran.
To prepare the soil samples for testing, alluvial deposits were oven
dried and passed through sieve No. 4. Fig. 3 shows the gradiation
curves of the original soil and the sample after passing sieve No. 4
Fig. 2. Grains of the used soil in prepared thin section (under PPL, 6× magnification).
which is classified as poorly graded sand (SP) according to the Unified
Soil Classification System. The index properties of the soil are shown
on Table 1. To achieve a uniform compaction, the sample in the testing
mould was compacted in seven 100 mm thick lifts. The soil was dried
and compaction effort was applied using a 300 mm vibrating plate in a
way that the required density to be achieved. The in place density for
each case was controlled using the sand cone method. Details of the
tests on samples having different densities are indicated in Table 2.
To prepare the soil sample for direct shear test, a circular shear box,
having 60 mm internal diameter and 25 mm height was used. To
achieve a uniform compaction in the circular shear mould of the direct
shear machine, tamping by a small circular steel plate with 60 mm
diameter was used. To eliminate the effects of pore pressure, all direct
shear tests were carried out in dry condition.
Fig. 3. Gradiation curves of alluvial deposited and used soil.
S.D. Mohammadi et al. / Engineering Geology 101 (2008) 195–203
Table 1
The index properties of used soil
Parameter
Value
emax (−)
emin (−)
Gs (−)
γd(max)(KN/m3)
γd(min)(KN/m3)
Cu (−)
Cc (−)
value of clay (%)
value of silt (%)
USCS soil classification
0.97
0.46
2.66
17.85
13.24
1.16
1
0
2
SP
197
steel rod to which the cone is attached has a smaller diameter than the
cone (16 mm) to minimize the effect of skin friction. Depth of
investigation of DCP is 1 m to 2 m. The number of blows during
operation is recorded with depth of penetration. The slope of the
curve defining the relationship between number of blows and depth
of penetration (in millimeters per blow) at a given linear depth
segment is recorded as the DCP penetration index (DPI). DPI for each
depth can also be calculated by Eq. (1) (Embacher, 2005):
DPI ¼
Piþ1 −Pi
Biþ1 −Bi
ð1Þ
Where:
Table 2
Testing program for laboratory investigations and different densities for tested soil
Dr(%)⁎
Mean of
water content
(%)
Dry unit
weight
(gr/cm3)
DCP
(number
of test)
PLT⁎⁎
(number of test)
Direct shear
(number of test)
25
35
50
60
75
0.4
0.4
0.4
0.4
0.4
1.44
1.48
1.55
1.60
1.67
3
3
3
3
3
3
3
3
3
3
7
7
7
7
7
⁎ Relative density
⁎⁎ Plate Load Test
DPI
P
B
DCP Penetration Index (mm/blow)
Penetration at i or i + 1 hammer drops (mm); and
blow count at i or i + 1 hammer drops
Analysis of the DCP data must be interpreted, following a standard
procedure, to generate a representative value of penetration per blow
for the material being tested. This representative value can be
obtained by averaging the DPI across the entire penetration depth at
each test location. For calculating the representative DPI value for a
given penetration depth, two methods are available: (i) arithmetic
average; and (ii) weighted average. The arithmetic average can be
obtained from Eq. (2) (Edil and Benson, 2005):
2.3. Testing procedures
Several tests including Dynamic Cone Penetration (DCP), Plate
Load (PLT) and direct shear tests were undertaken on the compacted
materials as described in the following sections:
2.3.1. Dynamic Cone Penetration tests
The Dynamic Cone Penetrometer (DCP) has been described by
ASTM 6951-03 (2003). The typical DCP consists of an 8-kg hammer
that drops over a height of 575 mm, which yields a theoretical driving
energy of 45 J or 14.3 J/cm2, and drives a 60o cone tip with 20 mm base
diameter vertically into the pavement or subgrade layer (Fig. 4). The
DPIavg ¼
∑Ni ðDPIÞ
N
ð2Þ
where N is the total number of DPI recorded in a given penetration
depth of interest. In the weighted average technique, Eq. (3) can be
used (Edil and Benson, 2005):
DPIwt:avg ¼
1 N
∑ ½ðDPIÞi ð Z Þi H i
ð3Þ
Where Z is the penetration distance per blow set and H is the
overall penetration depth of interest.
Fig. 4. Dynamic Cone Penetrometer (DCP) (Edil and Benson, 2005).
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S.D. Mohammadi et al. / Engineering Geology 101 (2008) 195–203
Fig. 7. Correlation between DPI and mould diameter.
Fig. 5. A schematic diagram of DCP test in testing mould (a) side view (b) plan view.
The main advantages of the DCP include:
•
•
•
•
•
speed of operation;
applicability in difficult terrains where access is poor;
minimal equipment and personnel;
low cost of the equipment;
simplicity of the operation and data recording/analysis.
As previously mentioned, the DCP tests were carried out in a
mould with a diameter and height of 700 mm, respectively (Fig. 5). To
have more uniform results, readings were taken around the center of
the test mould. The results of DCP tests on samples of different relative
densities are presented in Fig. 6.
To overcome the effects of the mould side walls, the minimum
distance between cone and edge of the testing mould was taken as
225 mm (Abu-Farsakh et al., 2004). To investigate the effects of the
mould size on the results, several DCP tests were conducted on the
Fig. 6. Average of DPI versus depth for studied soil at test mould.
moulds of different diameters of 300 mm, 500 mm and 700 mm.
Variation of the average DPI values versus different mould diameters
are presented in Fig. 7. The results show that with increase of relative
density (Dr), the effect of the side wall is more pronounced. This effect
is fully negligible for moulds with a diameter grater than 500 mm. On
the other hand, a distance of 250 mm between the cone and the edge
of the test mould can fully eliminate the mould size effects. Thus, in
the present research, all DCP tests were carried out in a mould with a
diameter of 700 mm.
The repeatability of the DCP test results is an important
consideration. To evaluate the repeatability, several tests were carried
out. Each testing series included three DCP tests. Fig. 8 shows the
results of the three series of tests undertaken for different relative
densities (Dr). In this figure, DPI values are converted to NDCP , where
NDCP is the number of blow for 100 mm penetration.
In order to study the repeatability of the results, it was important
to choose a suitable parameter that represents the repeatability. For
this purpose, percent of the coefficient of variation (Cv) was employed
as an indicator for repeatability.
Table 3 shows some soil properties, determined by various standard
tests, along with their coefficients of variation reported by various
researchers (Lee et al., 1983). The sources of variability in soil properties
differ, and accordingly the coefficients of variation differ for different
properties (Fakher et al., 2006). The coefficient of variation, Cv, for the
results of Standard Penetration Test (N), which is basically a super heavy
dynamic probe test, is reported to be between 27% and 85% with a
Fig. 8. Example of the results of tests repeated at mould test (a) for Dr = 25% (b) for
Dr = 50% (c) for Dr = 75%.
S.D. Mohammadi et al. / Engineering Geology 101 (2008) 195–203
199
Table 3
Coefficient variation for soil engineering tests (Lee et al., 1983)
Test
Reported Cv (%)
Recommended standard
Angle of friction (sands)
CBR
Undrained cohesion (clays)
Standard penetration test (SPT)
Unconfined compressive strength (clays)
5–15
17–58
20–50
27–85
6–100
10
25
30
30
40
recommended value of 30%, (Lee et al., 1983). The repeatability of SPT
test results could be used as a measure of the repeatability of DCP results
by comparing Cv values of the two methods. In the present research, the
values of Cv have been determined for each depth in each series of the
tests. The average value of Cv is 5.6% and its standard deviation is 9.51. In
more than 68.7% of the tests, the value of Cv is 0% and in 12.5% of the
tests, this value is 20.28%. In the tests undertaken, the values of Cv varied
between 0 and 28.3% and for all cases it was less than 30%. Therefore, the
results of DCP tests for the three relative densities (Dr) can be considered
as repeatable when compared with the values presented in Table 3.
2.3.2. Plate Load Test (PLT)
The Plate Load Test (PLT) is a useful site investigation tool and has
been used for proof testing of pavement layers in many European
countries for many years. Currently, it is used for evaluation of both
rigid and flexible pavements (Abu-Farsakh et al., 2004). The PLT in full
or small scale, is sometimes considered as the best means of
determining deformation characteristics of the soils, but is only used
in exceptional cases due to the costs involved (Bowles, 1997). In the
present research, a round plate with 230 mm diameter was used for
conducting plate load tests. The PLT was used as a reference test to
obtain the strength parameters of the soil under investigation. A
loading frame was designed to fit the mould and its support. To
perform the test, the bearing plate and hydraulic jack were carefully
Fig. 10. Definition of modulus from PLT (Abu-Farsakh et al., 2004).
placed at the center of the sample under the loading frame (Fig. 9). The
hydraulic jack and the supporting frame were able to apply a 60 tons
load. For measurement of deformations, dial gauges that are capable
of recording a maximum deformation of 25.4 mm (1 in) with an
accuracy of 0.001 in., were employed. The ASTM-D 1195-93 (1998)
standard method was followed to perform the test.
Elasticity modulus is always considered as a more important
deformability parameter for geomaterials. As in the case for other
stress–strain tests, different elasticity moduli can be obtained from the
PLT. Soil elasticity moduli can be defined as: (1) the initial tangent
modulus; (2) the tangent modulus at a given stress level; (3) reloading
and unloading modulus; and (4) the secant modulus at a given stress
level (Abu-Farsakh et al., 2004). In this study, since the stress–strain
Fig. 9. A schematic diagram of Plate Load Test (PLT) set up (a) side view (b) plan view.
200
S.D. Mohammadi et al. / Engineering Geology 101 (2008) 195–203
Table 4
The proposed classification for estimating of Dr by DPI
DPI (mm/blow)
Dr(%)
Description
N42
42–23
23–12
12–5
b5
b25
25–35
35–50
50–75
N75
Very loose
Loose
Medium
Dense
Very dense
3.1. DPI versus Dr(%)
The relative density is a useful parameter to describe the
consistency of sands (Coduto, 2001). Kulhawy and Mayne (1990)
suggested an empirical correlation between SPT results and Dr as
follows (Eq. (6)).
Dr ðkÞ ¼
Fig. 11. Correlation between DPI and Dr(%).
curves had a clear peak point, the initial tangent modulus was
determined for all plate load test results. To determine the initial
modulus (EPLT(i)), a line was drawn tangent to the initial segment of the
stress–strain curve, then an arbitrary point was chosen on the line and
the stress and deflection corresponding to this point were determined
for calculation of the initial modulus. Fig. 10 describes the deformations
and stresses used for determining EPLT(i). A reloading stiffness modulus
called EPLT(R2), was also determined for each stress–strain curve.
The second parameter which can be calculated from PLT results, is
shear modulus (G). Shear modulus is defined as the ratio of shear
stress to shear strain (Bowles, 1997) and is calculated from Eq. (4)
(Timoshenko and Goodier, 1970):
GPLT ¼
qD π
ð1−vÞ
ρ 8
ð4Þ
where:
q=
D=
ρ=
υ=
bearing pressure
diameter of the loading plate
settlement
Poisson's ratio
Since the non-rigid methods consider the effect of local mat
deformations on distribution of bearing pressure, it is needed to
define the relationship between settlement and bearing pressure. This
is usually done using the coefficient of subgrade reaction (Ks). Eq. (5) is
used to determine Ks from PLT results (Coudoto, 2004):
KS ¼ ΔP=ΔS
ð5Þ
sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
ðN1 Þ60
100
Cp CA COCR
ð6Þ
Where (N1)60 is SPT's N value corrected for field procedure and
overburden stress, and Cp, CA and COCR are grain size, aging correction
and overconsolidation factors, respectively.
In this study, the correlation between average DPI and Dr was
investigated. Eq. (7) and Fig.11 suggest a good correlation between these
two parameters. The determination coefficient (R2) of Eq. (7) is 0.98.
Table 4 shows the proposed classification for estimating of Dr(%) by DPI.
Dr ðkÞ ¼ 189:93=ðDPIÞ0:53
R2 ¼ 0:98
3.2. DPI versus modulus of elasticity (E)
For the data obtained in this study, the best correlations between
average DPI, EPLT(i) and EPLT(R2) are presented in Figs. 12 and 13 (Eqs. (8)
and (9)). However, there is a better correlation (Eq. (9)) between the
average DCP penetration rate and PLT reloading modulus (EPLT(R2))
compared to the correlation with EPLT(i).
EPLTðiÞ ðMPaÞ ¼ 55:033=ðDPIÞ0:54 R2 ¼ 0:83
ð8Þ
EPLTðR2 Þ ðMPaÞ ¼ 53:73=ðDPIÞ0:74 R2 ¼ 0:94
ð9Þ
Fig. 14 and Eq. (10) show the correlation between EPLT(i) and EPLT(R2)
which has a power trend.
1:49 2
ðR ¼ 0:94Þ
EPLTðR2 Þ ðMPaÞ ¼ 0:16 EPLTðiÞ
modulus of subgrade reaction
applied pressure
measured settlement
2.3.3. Direct shear test
In order to determine the soil friction angle ( ϕ), 35 direct shear tests
(Table 2) were undertaken in a circular shear mould as described earlier.
Due to the nature of the soil samples (non-cohesive), cohesion parameter
(C) was equal to zero and thus, friction angles were calculated. The ASTMD 308-90 (2000) standard method was followed to perform the test.
3. Results and discussions
In the following sections, the results of the tests and their
correlations with important engineering parameters of the studied
soil samples are discussed.
ð10Þ
Fig. 15 shows the proposed correlations found in the present study
and some correlations between average DPI versus elastic modulus
where:
Ks =
ΔP =
ΔS =
ð7Þ
Fig. 12. Correlation between DPI and EPLT(i).
S.D. Mohammadi et al. / Engineering Geology 101 (2008) 195–203
201
suggested by other authors (e.g. Pen, 1990; DeBeer, 1990; Konard and
Lanchance, 2000). Due to the smaller grain size, the values of elasticity
moduli from correlations suggested in this study are smaller than
those presented by others.
3.3. DPI versus shear modulus (G)
Several methods are available to evaluate the shear modulus of
coarse-grained and fine grained soils, such as geophysical methods,
Plate Load Test (PLT) etc., which are all costly. In the present research,
Fig. 16. Correlation between DPI and GPLT.
Fig. 13. Correlation between DPI and EPLT(R2).
Fig. 17. Correlation between DPI and KS.
Fig. 14. Correlation between EPLT(i) and EPLT(R2).
Fig. 18. Correlation between Dr and friction angle.
several correlations between average DPI versus PLT shear moduli
(GPLT) were investigated. The best correlation between the average DPI
and (GPLT) is presented in Fig. 16 and Eq. (11). The results show that the
Table 5
The proposed classification for estimating of (ϕ′) by DPI
Fig. 15. Correlations between DPI and E from other authors.
DPI (mm/blow)
ϕ′
Description
N45
45–25
25–15
15–5
b5
b30
30–34
34–36
36–42
N42
Very loose
Loose
Medium
Dense
Very dense
202
S.D. Mohammadi et al. / Engineering Geology 101 (2008) 195–203
shear modulus decreases with increasing values of DPI. This correlation is exponential with a determination coefficient of 0.93.
Table 6
Summary of developed e-questions in this paper
GPLT ðMPaÞ ¼ 75:74=ðDPIÞ0:99 R2 ¼ 0:93
Parameters
Equations
Type
correlation
Determination
coefficient (R2)
Dr–DPI
EPLT(i)–DPI
EPLT(R2)–DPI
EPLT(i)–EPLT(R2)
GPLT–DPI
Ks–DPI
ϕ′–Dr
ϕ′–DPI
Dr(%) = 189.93/(DPI)0.53
EPLT(i) = (MPa) = 55.033/(DPI)0.54
EPLT(R2) = (MPa) = 53.73/(DPI)0.74
EPLT(R2)(MPa) = 0.16(EPLT(i))1.49
GPLT(MPa) = 75.74/(DPI)0.99
KS(MN/m3) = 898.36/(DPI)0.9
ϕ′ = 26.31 + 0.21(Dr)
ϕ′ = (Deg) = 52.16/(DPI)0.13
Expotential
Expotential
Expotential
Power
Expotential
Expotential
Linear
Expotential
0.98
0.83
0.94
0.94
0.93
0.95
0.90
0.90
ð11Þ
3.4. DPI versus modulus of subgrade reaction (KS)
The best correlation between average DPI and KS is presented in
Fig. 17 and Eq. (12).
KS MN=m3 ¼ 898:36=ðDPIÞ0:9 R2 ¼ 0:95
ð12Þ
3.5. DPI versus shear strength
Several correlations between relative density (Dr) and friction
angle (ϕ) have been suggested by different authors including
Meyerhof (1959). He has suggested Eq. (13) for a normally consolidated sand.
/ ¼ 28 þ 0:15ðDr Þ
ð13Þ
For the results obtained in the present research, the correlation
between average effective friction angle (ϕ′) and relative density Dr(%)
is presented in Fig. 18 and Eq. (14),
/ V¼ 26:31 þ 0:21ðDr Þ
R2 ¼ 0:90
ð14Þ
which is similar to Meyerhof's equation (Fig. 18).
Several correlations between Standard Penetration Test (SPT)
results and the effective friction angle of uncemented sand (ϕ′) have
been suggested (e.g. DeMello, 1971). Table 5 presents the proposed
classification for estimating of (ϕ′) from DPI, using the results obtained
in the present research. The correlation between average DPI and
effective friction angle (ϕ′) is presented in Fig. 19 and Eq. (15).
/ VðDegÞ ¼ 52:16=ðDPIÞ0:13 R2 ¼ 0:90
ð15Þ
4. Summary and conclusions
The DCP is a lightweight device, which can be conveniently used
for soil investigation up to a depth of 2 m. Therefore, it can easily be
used in difficult terrains with poor access. The results of DCP testing
can be used rapidly to assess variability of soil conditions, allowing
different layers to be identified. Based on the results of the present
research, correlations can be established between DPI and engineering parameters of sandy soils. Statistical approach has been applied to
find the best correlations of the results with a high coefficient of
determination (R2). For the results obtained, the determination
Fig. 19. Correlation between DPI and friction angle.
coefficients (R2) between DPI and engineering parameters were
mostly greater than 0.90. Table 6 shows summary of the equations
obtained in this study. To control the repeatability of the results of DCP
tests, values of coefficient of variation (Cv) were calculated. This
coefficient varied between 0 and 28.3%. Therefore, it can be concluded
that the results of DCP tests for three relative densities (Dr) can be
considered as repeatable when compared with the values presented
by Lee et al. (1983).
Acknowledgments
The authors wish to express their deepest gratitude to the
authorities of Tarbiat Modares University for their financial support
of the research and to Mr. M. Zarrabi Rad for his close cooperation in
performing the experimental part of the work.
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