International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395 -0056
Volume: 04 Issue: 03 | Mar -2017
p-ISSN: 2395-0072
www.irjet.net
Correlation Of CBR Value With Properties Of Red Soil Ammu John1, Anju Joson2, Jesu Venia3, Krishna Chandran B 4, Prof Anniamma Chacko5 under – Graduate Students, 5 -Professor 1, 2, 3, 4, 5 Mar Athanasius College of Engineering, Kothamangalam, Kerala, India 1, 2, 3, 4
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Abstract – California Bearing Ratio (CBR) is a commonly
used indirect method to assess the stiffness modulus and shear strength of sub grade in pavement design. CBR value of soil depends on many factors like maximum dry density (MDD), optimum moisture content (OMC), liquid limit (LL), plastic limit (PL), type of soil and permeability of soil. In this paper an attempt has been made to establish relationship between CBR value and index properties of red earth, a type of locally available soil in Kerala. Keywords— Coefficient of correlation (R) 2, MLRA, Regression, Soaked CBR value, SLRA
1. INTRODUCTION
A pavement is a relatively stable crust constructed over natural soil for supporting and distributing wheel loads and providing durable wearing surface. Pavement is usually built in several layers, and these are usually termed sub-grade, sub-base, base and surfacing. The design and the behaviour of flexible pavement depend mainly on the strength of subgrade soil, and hence it is necessary to assess its strength. CBR test is now an empirical test widely applied in design of flexible pavements over the world. The CBR test is essentially a penetration test, which can be carried out either in the laboratory or in the field.CBR value can be measured directly in the laboratory test in accordance with IS 2720 part XVI on soil sample acquired from site. Laboratory test takes at least four days to measure the CBR value for each soil sample. Civil engineers always encounter difficulties in obtaining representative CBR value for design of pavement. In addition, CBR test in laboratory requires a huge soil sample and is laborious as well as time consuming. This would result in serious delay in the progress of the project, since in most situations the materials for earth work construction come from highly variable sources. Any delay in construction inevitably leads to rise of project cost. To overcome this situation, it is better to predict CBR value of sub-grade soil with easily determinable parameters. This paper aims to establish relationship. © 2017, IRJET
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Impact Factor value: 5.181
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Magdi M. E. and Zumrawi (2012), have established a reliable strong correlation between CBR values and plasticity index. The primary objective of the paper was to predict the CBR values (soaked and unsoaked) of clayey soils using soil index properties such as water content, dry density, void ratio and plasticity index. Dilip Kumar Talukdar (2014) conducted a test to establish correlation between CBR value with other index properties like maximum dry density, optimum moisture content, liquid limit, plastic limit and plasticity index of soil. About sixteen number of disturbed soil samples were collected from different sites of Nagaon district of Assam. CBR test was conducted and their correlation was tested using Multiple Linear Regression Analysis (MLRA) with index properties. Mukesh A Patel and H S Patel (2013), developed correlations between various properties like maximum dry density(MDD), optimum moisture content(OMC), unconfined compression strength, direct cone penetration value and CBR of soil in soaked condition. The paper presents the empirical correlations developed from multiple variable regression analysis from test results obtained from experimental investigation of soil sample taken from different locations of Gujarat region.
2. METHODOLOGY Soil samples were collected from three different locations in Kothamangalam, Kerala. Field density was calculated using core cutter method. The various steps involved in the correlation includes determination of index properties of the soil like specific gravity, field density, liquid limit, plastic limit (PL), plasticity index (PI), optimum moisture content, determination of CBR value of the sample followed by correlation of the index properties of the sample using Simple Linear Regression Analysis (SLRA) and Multiple Linear Regression Analysis (MLRA) by using Excel software. The geotechnical properties of the soil samples were tested as per IS 2720 and the results are presented in Table1.
3. RESULTS AND DISCUSSIONS The various test results were initially correlated with the observed CBR value to determine the degree of correlation existing between the values and then arrived at five simple regression models and 21 multiple regression models. ISO 9001:2008 Certified Journal
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