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Mathematical Model for Estimation of Shear Parameters of Alluvial Soils of Kamrup Metro District (Assam, India) from Index Properties
Projects related to Geotechnical Engineering require thorough ground study to know the soil behaviour thus making it necessary to determine the strength and stability parameters of soil. The soils of Assam are primarily of four types viz., Alluvial (old and new), Piedmont, Hill and Lateritic soils with the alluvium abundantly available in the state. The most important soil parameters are the shear strength parameters, namely, cohesion (c) and angle of internal friction (Φ) which can be obtained using triaxial tests with different drainage conditions. But one triaxial test may take weeks to complete and are very expensive. Moreover, for large projects it is practically preposterous to conduct large number of triaxial tests. Hence, an alternate way is to develop a relation between different parameters which enable us to determine others. The main objective of this study is establishing prediction models that allow the shear parameters to be predicted from soil index properties. For this, three prediction models are developed by combining various soil parameters viz., Liquid Limit (LL), Plastic Limit (PL), Specific Gravity (G) and Optimum Moisture Content (OMC) using Multivariate Regression Analysis (MRA) and Artificial Neural Network (ANN). The results show better performance for ANN than MRA.
Mathematical Model for Estimation of Shear Parameters of Alluvial Soils of Kamrup Metro District (Assam, India) from Index Properties
Projects related to Geotechnical Engineering require thorough ground study to know the soil behaviour thus making it necessary to determine the strength and stability parameters of soil. The soils of Assam are primarily of four types viz., Alluvial (old and new), Piedmont, Hill and Lateritic soils with the alluvium abundantly available in the state. The most important soil parameters are the shear strength parameters, namely, cohesion (c) and angle of internal friction (Φ) which can be obtained using triaxial tests with different drainage conditions. But one triaxial test may take weeks to complete and are very expensive. Moreover, for large projects it is practically preposterous to conduct large number of triaxial tests. Hence, an alternate way is to develop a relation between different parameters which enable us to determine others. The main objective of this study is establishing prediction models that allow the shear parameters to be predicted from soil index properties. For this, three prediction models are developed by combining various soil parameters viz., Liquid Limit (LL), Plastic Limit (PL), Specific Gravity (G) and Optimum Moisture Content (OMC) using Multivariate Regression Analysis (MRA) and Artificial Neural Network (ANN). The results show better performance for ANN than MRA.
Mathematical Model for Estimation of Shear Parameters of Alluvial Soils of Kamrup Metro District (Assam, India) from Index Properties
Chakraborty, Arunav (author) / Goswami, Anasuya (author)
Australian Journal of Civil Engineering ; 22 ; 179-190
2024-07-02
12 pages
Article (Journal)
Electronic Resource
English
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