View
216
Download
0
Category
Preview:
Citation preview
8/11/2019 A Study of Correlation Between California Bearing Ratio
1/4
International Journal of Emerging Technology and Advanced Engineering
Website: www.ijetae.com (ISSN 2250-2459,ISO 9001:2008 Certified Journal,Volume 4, Issue 1, January 2014)
559
A Study of Correlation Between California Bearing Ratio(CBR) Value With Other Properties of Soil
Dr. Dilip Kumar Talukdar1
1Lecturer, Civil Engineering Department, Nowgong Polytechnic, Nagaon, Assam. India. 782001.
Abstract-- California Bearing Ratio (CBR) value is an
important soil parameter for design of flexible pavements
and runway of air fields. It can also be used for
determination of sub grade reaction of soil by using
correlation. It is one of the most important engineering
properties of soil for design of sub grade of rural roads.
CBR value of soil may depends on many factors like
maximum dry density (MDD), optimum moisture content(OMC), liquid limit (LL), plastic limit (PL), plasticity index
(PI), type of soil, permeability of soil etc. Besides, soaked or
unsoaked condition of soil also affects the value.
Determination of CBR is a very lengthy and time
consuming process. An attempt has been made here to
correlate soaked CBR value with MDD, OMC, LL, PL and
PI of some soil sample collected from different locations of
Nogaon District of Assam, India. These tests can easily be
performed in the laboratory. Soaked CBR is considered as
Assam is a flood prone state and some rural roads remain
under water for two or three days. Correlation coefficient
(r) of each of these properties with CBR is determined and
their significance is tested by using statistical t- test. Finally
a linear multiple regression model was developed by usinglinex statistics of Microsoft Excel (version 13.0) for
determination of CBR value involving the above mentioned
soil parameters.
Keywords-- California Bearing Ratio, Coefficient of
correlation, t-test, soaked, significant.
I. INTRODUCTION
Most of the Indian highways system consists of
flexible pavement. There are different methods of design
of flexible pavement. The California Bearing Ratio
(CBR) test is an empirical method of design of flexiblepavement. It is a load test applied to the surface and used
in soil investigations as an aid to the design of
pavements. The CBR value obtained in this test forms an
integral part of several flexible pavement design methods
(ASTM, 2007). For applications where the effect of
compaction water content on CBR is small, such as
cohesionless, coarse-grained materials, or where an
allowance is made for the effect of differing compaction
water contents in the design procedure, the CBR may be
determined at the optimum water content of a specified
compaction effort. The dry unit weight specified isnormally the minimum percent compaction allowed by
the using agencys field compaction specification.
For applications where the effect of compaction water
content on CBR is unknown or where it is desired to
account for its effect, the CBR is determined for a rangeof water contents, usually the range of water content
permitted for field compaction by using agencys field
compaction specification. The design for new
construction should be based on the strength of thesamples prepared at optimum moisture content (OMC)
corresponding to the Proctor Compaction and soaked in
water for a period of four days before testing. In case of
existing road requiring strengthening, the soil should be
moulded at the field moisture contentand soaked for four
days before testing. But, Bindra (1991) reported that,
soaking for four days may be very severe and may be
discarded in some cases. This test method is used toevaluate the potential strength of subgrade, subbase, and
base course material, including recycled materials for use
in road and airfield pavements. Bindra (1991) reported
that design curves (based on the curve evolved by Road
Research Laboratory, U.K) are adopted by Indian RoadCongress (IRC: 37-1970). As per IRC, CBR test should
be performed on remoulded soil in the laboratory. In-situ
tests are not recommended for design purpose (Bindra,
1991). Most of the rural roads in Assam, constructed
under Pradhan Mantri Gram Sadak Yojana (PMGSY) are
designed on the basis of CBR value. For a given soil, the
CBR value, and consequently the design, will depend
largely on the density and the moisture content of the
soil. It is also depends on type of soil. CBR is more for
sandy soil than clayey soil. But, CBR test is laborious
and time consuming; Furthermore, the results sometimes
are not accurate due to poor quality of skill of the
technicians testing the soil samples in the laboratory(Roy, Chattopadhyay and Roy, 2010). To overcome these
difficulties, an attempt has been made in this study to
correlate CBR value statistically with the liquid limit
(LL). Plastic limit (PL), plasticity index (PI), maximum
dry density (MDD) and optimum moisture content(OMC) of soil, because these tests are simple and can be
completed with less period of time.
II. EXPERIMENTAL WORKS
Collection of soil sample
Sixteen numbers of disturbed soil samples were
collected from different sites of Nagaon district ofAssam, India.
8/11/2019 A Study of Correlation Between California Bearing Ratio
2/4
International Journal of Emerging Technology and Advanced Engineering
Website: www.ijetae.com (ISSN 2250-2459,ISO 9001:2008 Certified Journal,Volume 4, Issue 1, January 2014)
560
Determination of particle size
The percentages of various sizes of particles in all the
soil samples were obtained by wet sieve analysis and the
percentages of different fractions are presented in
Table 1.
Determination of Consistency limit
The consistency is largely related with the amount of
water content of soil and mostly used for fine grained
soils. Liquid limit was determined by using cone
penetrometer and plastic limit was obtained by threadrolling method. Shrinkage limit was not determined here.
The test results are shown in Table 2.
Table 1Test results of sieve analysis
Sample
No.
Gravel
(%)
Sand
(%)
Silts &
clay (%)
Type of soil
1 0.00 27.15 72.85 Fine grained
2 2.35 28.94 68.71 Fine grained
3 1.31 28.94 68.71 Fine grained
4 0.64 30.14 69.22 Fine grained
5 4.71 36.52 58.77 Fine grained
6 2.39 35.23 62.38 Fine grained
7 1.44 35.01 63.55 Fine grained
8 0.35 29.44 70.21 Fine grained
9 2.35 28.94 68.71 Fine grained
10 1.87 26.92 71.21 Fine grained
11 0.00 25.94 74.06 Fine grained
12 2.65 18.12 79.23 Fine grained
13 1.25 27.64 71.11 Fine grained
14 3.81 26.92 69.27 Fine grained
15 3.35 13.44 83.21 Fine grained
16 2.38 28.21 69.41 Fine grained
Table 2
Results of consistency tests and classification of soil.
Sample
No.
LL
(%)
PL
(%)
PI
(%)
Type of
soil
1 28.46 20.24 8.22 ML2 34.62 26.65 7.97 ML
3 34.92 27.4 7.52 ML
4 35.2 27.51 7.69 MI
5 34.42 27.47 6.95 ML
6 29.35 23.23 6.12 ML
7 30.34 23.78 6.56 ML
8 36.78 28.32 8.46 MI
9 32.21 25.69 6.52 ML
10 34.25 27.53 6.72 ML
11 35.69 28.54 7.15 MI
12 36.29 28.18 8.11 MI
13 35.23 27.88 7.35 MI14 36.23 28.98 7.25 MI
15 34.56 26.44 8.12 ML
16 35.36 28.34 7.02 MI
Determination of Compaction Property and CBR value
Compaction properties are determined by standard
Proctor test as per IS:2720 (PartVII).The test was
performed in a cylindrical mould of 1000 ml capacity
using a rammer of weight 2.6 kg with 310 mm height of
free fall. Soaked CBR values of soil sample were
determined as per procedure laid down in IS: 2720 (Part
XVI) - 1979. The values are shown in Table 3.
Classification of Soil
Considering the soil properties from Table 1 and 2 the
soils are then classified according to grain size and as per
IS (IS: 1498-1970). All the soil samples were found to be
of silts of low compressibility (ML) and of silts of
intermediate compressibility (MI).
Table 3
Compaction properties and CBR values
Sample
No.
MDD
(gm/cc)
OMC
(%)
CBR
(%)
1 1.65 14.56 5.56
2 1.7 15.11 5.62
3 1.71 15.2 5.77
4 1.69 15.35 5.69
5 1.72 15.62 5.81
6 1.77 14.39 6.12
7 1.76 14.92 6.1
8 1.64 15.82 5.72
9 1.75 14.42 6.2
10 1.74 14.16 6.05
11 1.73 15.62 5.95
12 1.62 15.76 5.67
13 1.66 15.52 5.92
14 1.68 15.62 5.88
15 1.71 15.4 5.98
16 1.74 14.65 6.02
Graphical Analysis of Soil Properties
The relation of CBR value with respect to different
soil properties are presented in Fig.1 through Fig.3. FromFig.1, 2 and 3, it has been observed that CBR value
decreases with increase in the value of plasticity index
and optimum moisture content of soil. On the other hand,
it is increases with increase in the value of maximum dry
density.
Statistical Analysis of Soil Properties
The variations shown by tables and graphs do not
provide quantitative information regarding prediction,
judgement or decision making. Basic trends of property
required for design and construction purpose of a projectwork generally lie hidden in the data generated.
8/11/2019 A Study of Correlation Between California Bearing Ratio
3/4
International Journal of Emerging Technology and Advanced Engineering
Website: www.ijetae.com (ISSN 2250-2459,ISO 9001:2008 Certified Journal,Volume 4, Issue 1, January 2014)
561
A mathematical description of the sets of variables is
the best way of scientific explanation, because in agraphical presentation, prior to this, there is always an
element of biasness or misleading presentation (Barua
and Patgiri, 1996). To know the association of CBR
value with other properties of soil, correlation coefficient
(r) between the CBR value and LL, PL, PL, PI, MDD and
OMC are determined. Goon, Gupta and Dasgupta (1993)
reported that it is customary in common statistical work;
the level of significance to be tested. The significance of
the correlation ratio has been tested by t- test (Saxena,
1962). The value of correlation coefficients is shown in
Table 4.
Table 4Value of r between CBR and other properties.
Soil
Property
LL
(%)
PL
(%)
PI
(%)
MDD
(gm/cc)
OMC
(%)
Value of r -0.084 0.07 -0.613 0.695 -0.317
Level of
signify-
cance
>50% >50%
8/11/2019 A Study of Correlation Between California Bearing Ratio
4/4
International Journal of Emerging Technology and Advanced Engineering
Website: www.ijetae.com (ISSN 2250-2459,ISO 9001:2008 Certified Journal,Volume 4, Issue 1, January 2014)
562
Table 5
Comparison of CBR values
5.5
5.6
5.7
5.8
5.9
6
6.1
6.2
6.3
0 5 10 15 20
Sample No.
CBR(%)
Laboratory CBR Computed CBR
Fig. 4 Comparison of Laboratory and computed CBR value.
Comparison of CBR value (Table 5) shows that in
some soil samples, the laboratory and computed value of
CBR have no difference. The maximum difference is
3.67% but in most cases the differences are
Recommended