Abstract

The Standard Penetration Test (SPT) is widely used to provide estimates of shear strength parameters for design. The test is commonly used for cohesionless soils as the correlations between the SPT value and internal friction angle are only subjected to clean sand. Uncertainty in the internal friction angle tends to occur in SPT correlations for fine sand mixed with fine-grained soils located in Louisiana as the soil becomes more cohesive. In this study, several small and large direct shear tests were conducted at normal stresses of 10, 16, and 22 psi for soils located in Louisiana with different mixtures of fines content. Each mixture was conducted at different relative densities and water contents. The laboratory data were used to perform a non-linear regression analysis to modify current SPT correlations by observing the effect of the fine content, relative density, water content, and particle shape on the internal friction angle. A scanning electron microscope was conducted to observe the particle shape of the soil selected for the experimental work. Artificial Neural Network (ANN) models were also developed to provide better predictions for the shear strength parameters. In addition, the study included an overview to explain the parameters that govern the threshold percent of fines content beyond which the sand soils mixed with fines will behave as cohesive soils rather than cohesionless soils.

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