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IJESRT
INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH
TECHNOLOGY
EFFECT OF FIELD MOISTURE CONTENT ON PENETRATION INDEX VALUE
OF DYNAMIC CONE PENETROMETER IN ALLUVIAL SOIL SUBGRADES
Daljeet Singh1, *, J.N.Jha2, K.S.Gill3
Research Scholar, IK Gujral Punjab Technical University, Jalandhar, Punjab, India.
2
Principal, Government of Bihar, Muzaffarabad Institute of Technology, Muzaffarabad Bihar, India.
3
Head, Department of (Civil), Guru Nanak Dev Engineering College, Ludhiana, Punjab, India.
1
DOI: 10.5281/zenodo.827508
ABSTRACT
Dynamic Cone Penetrometer is an ideal instrument for testing subgrade and embankment compaction and it insitu California Bearing Ratio (CBR). The Dynamic Cone Penetration Index (DCPI) value has valid correlation
with CBR. The relation has higher value of coefficient of determination, denoted as R2, for non-cohesive soils dry
soils. The fine grained alluvial soils having some Plasticity Index (PI) value shows the lower R2 value. The Various
alluvial soil samples having PI value from 0 to 10 were tested for finding the moisture correction factor so that
DCPI values can be correlated with In-situ CBR at different field moisture conditions.
Keywords: DCP, CBR, DCPI, PI, Field Moisture Content and Correction Factor.
I.
INTRODUCTION
Performance of flexible pavement greatly depends upon the accurate evaluation of subgrade strength. To ensure
the subgrade and embankment has achieved the design CBR, one has to cut the core and soak it for 4 to 7 days
in still water and test it in laboratory for its CBR or remold the sample in cylindrical mould with inside dia 150
mm and height 175 mm, provided with a detachable extension collar 50 mm height and a detachable perforated
base plate 10 mm thick. 2. Spacer disc 148 mm in dia and 47.7 mm in height along with handles. The samples
are then tested as per IS 2720 Part 16 [1] As per revised Indian Road Congress (IRC: 37) [2] subgrade soil should
be non-expensive in nature having CBR more than 8%. but most of the roads constructed prior to this code of
practice do not conform to this further more due lack of awareness on the part of field engineers it is considered
that some plasticity is considered helpful in compaction and easy to maintain profile leads to long term
complications. The procedure to ensure in-situ CBR as described above is very complicated and time consuming,
more over repeat-ability and reproduce-ability of the test procedure is very low. Keeping the importance of insitu CBR in view the various government agencies and individual researchers tried to find the in-situ CBR
through alternative testing procedures the most prominent are direct in-situ CBR as per IS 2720 Part-31 [3],
Light Weight Falling Deflectometer ASTM [4] and Dynamic Cone Penetrometer IRC [5]. All these methods
have their own implications as DCP Test is not suitable for soils have large particle size, ideal non-cohesive finegrained soils are rarely available in actual field conditions for that most of researchers have developed
correlations. The DCPI results are moisture sensitive To make the use of DCP for wider range of soils, the effect
of moisture on DCPI is studied and efforts are made to find the possible correlation with other properties such
as Plasticity index, field moisture content and DCPI and CBR. For this purpose, a 16 KM stretch of Ludhiana to
Malerkotla State Highway No 11 passing through state of Punjab (India) as shown in Figure-1, is tested for
various in-situ and laboratory tests.
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Figure-1 Key Plan Showing the Location of Testing Location on Ludhiana Malerkotla Section of Punjab SH -11
II.
REVIEW OF LITERATURE
Performance of soil subgrade of a flexible pavement is influenced by several factors. Kolisoja [6] have
demonstrated that in addition to grain size distribution and degree of compaction, water content with mineralogy
had effects on the deformation properties. Ekblad [7] have shown that the resilient modulus is inversely
proportional to the content of fines (grain size < 0.075 mm). He proved that the rise of water content decreases
more the stiffness of the materials with high contents of fines. If the content of fines is small then the bigger grains
can contact each other and distribute the load, while the fines fill the empty voids between grains. As the content
of fines increases, the bigger grains do not necessarily contact each other to distribute the load Kolisoja [8]. As a
result, there is a decrease in the deformation modulus. Besides water content and grain size distribution, one of
the most important factors of permanent deformation is the degree of compaction of the material. Lekarp has
demonstrated that the degree of compaction has an even stronger effect on the permanent deformations than on
the resilient deformations Lekarp et al. [9]. van Niekirk [10] has addressed the fact that the degree of compaction
has a more important effect on the permanent deformation than the grain size distribution. Uthus [11] demonstrates
that the dry density, the degree of saturation and the stress level seem to be key parameters for determining the
permanent deformation behaviour, but mineralogy, fines content and grain size distribution are also of importance.
Correlations with DCPI and CBR
Webster et al. [12] have reported the development of a relationship between the CBR and the penetration rate
(DCPI) expressed in mm per Equation (1) by the U.S. Army Corps of Engineers for a wide range of granular
and cohesive materials. they also found that that the effects of soil moisture content and dry density influence
both CBR and DCP test values in similar ways hence not considered for the correlation where moisture and
density is kept constant.
Log CBR = 2.465 – 1.12 Log (DCPI)
(1)
This correlation was adopted by many researchers for their work with different soils and reported similar results,
prominent and relevant to the present problem is (2) given by Livneh et al. [14] with granular and cohesive soil.
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Log(CBR) = 2.45-1.12 log(DCPI)
(2)
Webster et al. [13] developed a much similar correlation relation (3) after conducting tests on various soils.
Log(CBR) = 2.46-1.12 log(DCPI)
(3)
Ese, et al. [14] carried out a detailed field and laboratory testing with DCPT, for evaluating low volume roads
having gravel base course and established (4).
Log CBR(lab) = 2.438-1.065*log (DCPI)field
(4)
Daljeet Singh et al. [15] studied fifteen different soil in road subgrades using DCPT, grain size and Atterberg’s
limits in laboratory and actual field conditions at optimum moisture content and developed a CBR prediction
model (5)
CBR =43.73-1.043N-0.717LL-0.149PL+5.39D60
(5)
With R2 =0.995 and a standard error of 0.407
The model is very useful for verification of CBR during construction only as the field moisture conditions at
OMC can only be at the time of construction or at any specific period of time after rainy season. The field
moisture conditions remain changing rapidly.
As the review of previous works indicates
i)
DCPI and Index Properties Grain Size and Plasticity Index have definite correlation with CBR of
soil.
ii)
The model developed by Daljeet Singh et al [15] is useful for verification of CBR during construction
only as the field moisture conditions at OMC can only be at the time of construction. Verification of
sub grade CBR for rehabilitation, upgradation or post construction evaluation purposes is not
possible as the CBR and DCPI are moisture sensitive Amini, F [16].
iii)
The previous researchers have primarily investigated relation of a particular parameter with CBR.
The effect of other parameters if studied is only at a particular moisture content un-soaked or
soaked conditions. To investigate in-situ CBR it is essential to study the effect of moisture on DCPI
and CBR.
hence, it is felt performance of soil subgrade under flexible pavement layers can be anticipated with the help of
DCPT apparatus by applying suitable moisture correction factor to the available prediction model (5).
III.
MATERIALS AND METHODS
To investigate the effect of field moisture content on the DCPI a 16 KM long widened and strengthened from two
lane to four lane dual carriage of SH 11 from Ludhiana to Malerkotla is investigated. The selected stretch has the
advantage of having different alluvial soils subgrade with variable field moisture content. The research
methodology is based upon the assessment of in-situ subgrade strength at optimum moisture content and worst
moisture conditions. The in-situ soil strength can be measured directly from the response of the soil to applied
loads or correlated to several equipment’s penetration resistance. The various available techniques that can be
used to measure the direct response of the soil when subjected to loads are static plate test, LWD, Benkelman
Beam, Geo Gauge, time domain reflectometry and other means. In this study Standard Dynamic Cone
Penetrometer (DCPT) apparatus is used. Other soil properties such as dry density, grain size, liquid limit and
plastic limit and effect of moisture content is used. The Dynamic Cone Penetrometer (DCP) consists of a guiding
rod fitted with a cone at the tip and is operated by dropping an 8 kg mass from a specified height. The DCP test
is conducted as per standard procedure IRC-Special Publication [5] and ASTM [4] The penetration index given
by DCP can be correlated to the CBR and density of a particular soil at a particular moisture content. The other
soil parameters are also used to fine tune the results and enhance the usability to a wider range of soil type. This
tests are conducted upto significant depth of influence of wheel load. Many researchers and agencies have
developed the relationships between in-situ tests with Dynamic Cone Penetration Index (DCPI) versus CBR. To
find the effect of moisture content on DCPI and mould CBR, samples are tested at different moisture content to
develop correlations. The soils are grouped based upon their Plasticity Index (PI) value into three groups.
IV.
RESULTS AND DISCUSSION
The CBR of soil is determined at selected location using the standard CBR test procedure and verified using DCPT
apparatus using predication model (5). Since this equation gives the CBR of soil at OMC hence correction factor
for moisture are developed for three different categories of soil based upon their Plasticity Index. Group A for
non-plastic soils PI Value 0, Group B for PI value 1 to 4 and Group C for PI value 5 to 7. The graphs are plotted
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to find the correlation equations and and coefficient of determination as given below.
DCPT CBR ~Moisture Correction Factor for Soils (PI =0)
1.6
CF = 1.9801 x (MC)-0.345
R² = 0.8545
1.4
Correction Factor (CF)
1.2
1
0.8
0.6
0.4
0.2
0
0
5
10
15
20
25
Moisture Content (MC) (% age)
Figure- 3: DCPT CBR Moisture Correction Factor Relationship for Non-Plastic Soils (PI=0)
Correction Factor (CF)
DCPT CBR ~ Moisture Correction Factor for PI 1 to 4
2
1.8
1.6
1.4
1.2
1
0.8
0.6
0.4
0.2
0
CF= 5.4283 x (MC)-0.771
R² = 0.9161
0
5
10
15
20
25
Moisture Content (MC) (% age)
Figure- 4: DCPT CBR Moisture Correction Factor Relationship for Plastic Soils (PI value 1 to 4)
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DCPT CBR ~ Moisture Correction Factor for PI 5 to 7
3
Correction Factor (CF)
2.5
CF = 17.799x (MC)-1.274
R² = 0.8936
2
1.5
1
0.5
0
0
5
10
15
20
25
30
Moisture Content (MC) (% age)
Figure- 5: DCPT CBR Moisture Correction Factor Relationship for Plastic Soils (PI value 5 to 7)
The correction factor (CF) for non-plastic soils can derived from the equation
CF = 1.9801 x (MC)-0.345
(13)
having R² = 0.8545
Similarly, for PI value 1 to 4 and 5 to 7 the following equations can be used respectively.
CF= 5.4283 x (MC)-0.771
(14)
having R² = 0.9161
And
CF = 17.799x (MC)-1.274
(15)
with R² = 0.8936
The results obtained from the above equations are in accordance with correction factors used for Benkelman
Beam deflection procedure defined in IRC [17].
V.
FIELD VERIFICATION OF RESULTS
To verify the applicability of established relationships to moisture correction in field application 15 samples from
different locations were taken and tested for their properties as detailed in Table-1. The grain size of the samples
varies from D60 From 0.925 mm to 0.045, Plasticity Index from Non Plastic to PI upto 7 and moisture content
from 3.5% to 22% since the sample are taken from the subgrade of road constructed under the strict supervision
of international engineering consultant firm and reputed construction agency the in-situ compaction is nearly 97
to 98 percent of maximum dry density (modified).
Table: 1 Properties of different subgrade soils along with percentage error in Estimated and
Laboratory CBR in saturated condition.
Sample
Ref.
D60
mm
LL
PL
PI
Γd
insitu
kN/m3
N
mm/
blow
MC
%
C.F.
(Divis
ible)
Esti.
Sat.
CBR
CB
RLab
Error
%
(Satur
ated)
S1
0.925
15
15
NP
18.6
6.33
3.5
1.29
22.6
23.4
3.42
S2
0.515
16
16
NP
18.24
10
7.5
0.99
22.4
21.7
-3.23
S3
0.35
17
17
NP
18.57
20
22
0.68
14.8
15.2
2.63
S4
0.209
18
18
NP
17.52
16.67
8.5
0.95
12.5
12.6
0.79
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S5
0.172
18
18
NP
17.16
10
4.5
1.18
15.8
16.6
4.82
S6
0.176
19
18
1
16.47
13.67
9
1
14.1
13.9
-1.44
S7
0.166
20
18
2
18.42
13.67
9.5
0.96
13.9
13.6
-2.21
S8
0.126
21
18
3
18.93
21
21
0.52
9.2
9.6
4.17
S9
0.101
22
18
4
18.42
20
22
0.5
9.9
10.4
4.81
S10
0.206
23
19
4
16.83
12.66
9.5
0.96
12.8
12.3
-4.07
S11
0.084
23
18
5
18.24
12
11.5
0.79
15.8
15.2
-3.95
S12
0.058
24
18
6
17.37
14.33
12
0.75
12.3
11.8
-4.24
S13
0.058
24
18
6
17.37
3
6
1.82
11.6
11.9
2.52
S14
0.416
24
18
6
20.04
4
4.75
2.45
8.9
9.3
4.3
S15
0.045
25
18
7
16.8
11.66
13
0.68
16.5
15.8
-4.43
The results shown in the table indicates that percentage error in estimation of CBR are within the ± 5% range,
hence can be very useful for rapid quality assurance in field applications.
VI.
CONCLUSION
From the present study, the followings conclusions are drawn:
1. The DCPI values are influenced by the field moisture content in general.
2. The moisture cotenant have significant effect in case of fine grained plastic soils.
3. DCPI can be very useful to evaluate the in-situ CBR of subgrade and embankment layers of alluvial soils
if sufficient data such as grain size, Atterberg and field moisture etc. with reasonable accuracy is available.
4. DCPI have very good repeatability and reproducibility subject to the conditions that other parameters
affecting it are taken into consideration.
5. Moisture correction factors once established for particular range of soil can be very useful for speedy
testing of subgrade and embankment layers for desired strength parameters such as CBR.
VII.
ACKNOWLEDGEMENTS
Authors are very thankful for the cooperation of staff and faculty of Guru Nanak Dev Engineering College
Ludhiana, Punjab, Engineers of Public Works department Punjab, Field Engineers of Execution Agencies for
their cooperation and sharing valuable information without which this work was not possible.
VIII.
REFERENCES
[1] Bureau of Indian Standards (BIS) IS: 2720 ( Part 16) – (1987). Indian Standard. Methods of Test for Soil.
Part 16 Laboratory. Determination. of CBR. (Second Revision).
[2] Indian Road Congress, Code of practice, Guidelines for the design of flexible pavements IRC 37: (2012).
The Indian Road Congress New Delhi, India.
[3] Bureau of Indian Standards (BIS) IS 2720-3(part 31)- (1990). Methods of test for soils, Part 31: Field
determination of California Bearing Ratio.
[4] American Society for Testing Materials, ASTM D6951- (2009). Standard Test Method for Use of the
Dynamic Cone Penetrometer in Shallow Pavement Applications. ASTM standard
[5] Indian Road Congress, IRC SP-72- (2007), Guidelines for the Design of Flexible Pavements for Low
Volume Rural Roads.
[6] Kolisoja, P. (1993). Sitomattomien kerrosten kiviainesten muodonmuutos-ominaisuudet –
Kirjallisuusselvitys. Tielaitoksen selvityksiä 39/1993, TIEL 3200163, Helsinki. 147 pp. (In Finnish)
[7] Ekblad, J. (2004). Influence of water on resilient properties of coarse granular materials. Licentiate Thesis,
Kungliga Tekniska Högskolan (KTH), Stockholm, 2004. TRITA-VT FR 03:03. ISSN 1650-867X. 192 p.
[8] Kolisoja, P. (1997). Resilient deformation characteristics of granular materials, Thesis for the degree of
Doctor of Technology. Tampere University of Technology, Publication 223, Tampere. 216 p.
[9] Lekarp, F., Isacsson, U. and Dawson, A. (2000b). State of art. II: Permanent Strain Response of Unbound
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Aggregates. Journal of Transportation Engineering January/February 2000, pp. 76–83.
[10] Van Niekirk, A.A. (2002). Mechanical Behaviour and Performance of Granular Bases and Sub-Bases in
Pavements. PhD thesis, Delft University of Technology. 516 p.
[11] Uthus, L. (2007). Deformation Properties of Unbound Granular Aggregates, Doctoral thesis. Norwegian
University of Science and Technology, Faculty of Engineering Science and Technology, Department of
Civil and Transport Engineering. 52 p.
[12] Webster, S. L., Grau, R. H., and Williams, T. P. (1992). Description and application of Dual Mass Dynamic
Cone Penetrometer. Final Report, Department of Army, Waterways Experiment Station, Vicksberg, MS
[13] Webster, S.L.; Brown, R.W.; and Porter, J.R. (1994). Force Projection Site Evaluation Using the Electric
Cone Penetrometer (ECP) and the Dynamic Cone Penetrometer (DCP). Technical Report, GL - 94- 17,
U.S Army Engineers Waterways Experiment Station. Vicksburg, USA.
[14] Ese, D., Myre, J., Noss, P., and Vxrnes, E.(1994) “The Use of Dynamic Cone Penetrometer (DCP) for
Road Strengthening Design in Norway. Proceedings of the 4th International Conference on the Bearing
Capacity of Roads and Airfields, pp.343-357.
[15] Daljeet Singh , J. N. Jha , K. S. Gill (2016). Strength Evaluation of Soil Subgrade Using In-situ Tests. Civil
Engineering and Architecture, 4 , 201 - 212. doi: 10.13189/cea.2016.040601
[16] Amini, F.,Potential (2003) Applications of Dynamic and Static Cone Penetrometers in MDOT Pavement
Design and Construction, Final Report for Mississippi Department of Transportation, Jackson State
University, Jackson.
[17] Indian Road Congress IRC:81-(1987), Guidelines· for Strengthening of Flexible Road Pavements Using
Benkelman Beam Deflection Technique.
CITE AN ARTICLE
Singh, Daljeet , J. N. Jha, and K. S. Gill. "EFFECT OF FIELD MOISTURE CONTENT ON
PENETRATION INDEX VALUE OF DYNAMIC CONE PENETROMETER IN ALLUVIAL
SOIL SUBGRADES." INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES &
RESEARCH TECHNOLOGY 6.7 (2017): 327-33. Web. 15 July 2017.
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