Association between CBR and Soil Index Properties: Empirical Analysis from Chitwan and Makwanpur District Soil Samples

Dipak Koirala, K. D. Awasthi, Niraj Bohara
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Abstract

The California Bearing Ratio (CBR) value is a crucial soil parameter in road construction and design. Obtaining representative CBR values is challenging, requiring time-consuming and expensive testing procedures. To address this issue, regression equations were developed to establish correlations between CBR and soil index properties. Laboratory tests were conducted to determine the soaked CBR, Liquid Limit (LL), Plastic Limit (PL), Plasticity Index (PI), Maximum Dry Density (MDD), and Optimum Moisture Content (OMC) of soil samples. Regression models were then created between CBR and different sets of soil index properties using Microsoft Excel 2007. Strong correlations were observed between soaked CBR, PL, PI, OMC, and MDD (R2 = 0.744); CBR, LL, PL, OMC, and MDD (R2 = 0.702); CBR, PI, OMC, and MDD (R2 = 0.643); CBR, LL, OMC, and MDD (R2 = 0.621); and CBR, OMC, and MDD (R2 = 0.602). Among all equations, the relation CBR = 0.72 PL – 1.22 PI + 2.34 OMC + 106.97 MDD – 222.46 exhibited the strongest correlation with a P-value of 0.005 and R2 of 0.744.
CBR与土壤指数性质的关系——来自Chitwan和Makwanpur地区土壤样品的实证分析
加州承载比(CBR)值是道路施工和设计中至关重要的土壤参数。获得具有代表性的CBR值具有挑战性,需要耗时且昂贵的测试过程。为了解决这一问题,建立了回归方程来建立CBR与土壤指数特性之间的相关性。通过室内试验确定了土壤样品的浸渍CBR、液限(LL)、塑限(PL)、塑性指数(PI)、最大干密度(MDD)和最佳含水率(OMC)。然后使用Microsoft Excel 2007建立CBR与不同土壤指标属性集之间的回归模型。浸泡后的CBR、PL、PI、OMC和MDD呈强相关(R2 = 0.744);CBR、LL、PL、OMC和MDD (R2 = 0.702);CBR、PI、OMC、MDD (R2 = 0.643);CBR、LL、OMC和MDD (R2 = 0.621);CBR、OMC和MDD (R2 = 0.602)。其中CBR = 0.72 PL - 1.22 PI + 2.34 OMC + 106.97 MDD - 222.46相关性最强,p值为0.005,R2为0.744。
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