Statistical Analysis on Shear Strength Parameter from Index Properties of Fine-grained Soils

Bakala, Tariku Tafari and Quezon, Emer Tucay and Yasin, Mohammed (2021) Statistical Analysis on Shear Strength Parameter from Index Properties of Fine-grained Soils. Journal of Engineering Research and Reports, 20 (4). pp. 15-28. ISSN 2582-2926

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Abstract

Shear strength is the essential engineering property of soil required to analyze and design foundations, retaining walls, bridges, embankment, and related infrastructure. The laboratory equipment and field instruments are not sufficient in developing countries to obtain soil engineering properties, especially strength properties. Thus, Geotechnical engineers usually endeavor to develop statistical models that best fit a particular area and soil type, especially for analysis and design purposes. In this research, a Statistical Analysis on the Shear Strength parameter from the Index Properties of Fine-Grained Soils was studied. For predicting the undrained shear strength parameter, single linear regression (SLR) and multiple linear regressions (MLR) analyses were developed. To develop the intended statistical models for a study, SAS JMP Pro 13, SPSS v22, and Microsoft Excel-2013 software were introduced. The results of a study indicated that undrained shear strength(Cu) was significantly correlated with liquid limit(LL), plastic limit(PL), bulk density (ρbulk), dry density(ρdry), natural moisture content(NMC), and plasticity index(PI). While it was not significantly correlated with a specific gravity (Gs) and liquidity index (LI) of study area soil. Finally, a strong Model of Cu with a coefficient of determination (R2 = 0.806), good significance level, and less Std. error was obtained from multiple linear regression (MLR) analysis. The developed model can figure undrained shear strength parameter and wide application in the construction industry to minimize the cost, effort, and time for laboratory tests of shear strength parameter of a study area.

Item Type: Article
Subjects: e-Archives > Engineering
Depositing User: Managing Editor
Date Deposited: 08 Mar 2023 11:32
Last Modified: 31 May 2024 09:55
URI: http://ebooks.abclibraries.com/id/eprint/825

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