A Study of Correlation Between California Bearing Ratio

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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)

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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.


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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.


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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%


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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

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A Study of Correlation Between California Bearing Ratio