Experimental and ANN Analysis of Shearing Rate Effects on Coarse Sand Crushing

Abstract

The present study analyzes laboratory experiments on how shearing rate affects the shear strength and crushability of natural coarse sand, employing artificial neural network (ANN) analysis. This study tested three different coarse sands obtained from the crushing of natural rocks: Black Virgin Tuff, weathered Zeolitic Tuff, and calcareous limestone. The behavior of crushed sand specimens with consistent grading, which passed through sieve #4 and were retained on sieve #8, was analyzed using a direct shear box. The specimens were subjected to varied normal loads and shearing speeds to examine their behavior at different relative densities. The test results were analyzed using ANN to investigate the significance of shearing rates on shearing strength parameters, specifically internal mobilized peak friction, the constant volume (residual) internal friction angle, and the consequence of shearing rate on the particle's breakage index. The selected normal (Gaussian) rate significantly affected both the shear strength parameters and breakage. The loading rate increased both shear strength parameters and particle breakage. Therefore, it's highly recommended to maintain secure sets of shear strength values and comprehensive test data for assessing parameters at typical strain rates, prioritizing using slower rates whenever possible. Doi: 10.28991/CEJ-2024-010-03-011 Full Text: PDF