Prediction Model of Dilatancy Stress Based on Brittle Rock: A Case Study of Sandstone

Abstract

In this paper, the dilatancy stress and mechanical characterization of sandstone were evaluated under uniaxial loading at different elastic modulus and porosity conditions. The prediction model of dilatancy stress was established using a regression equation and an artificial neural network based on a multilayer perceptron (ANN–MLP). The results indicate that: (1) The rock crack initiation stress, dilatancy stress and its elastic modulus are a power function relationship, while porosity is linearly negatively correlated. (2) σci/σmax hardly changes with the change of elastic modulus (E) and porosity (n); its value is about 0.443. σcd/σmax increase with the increase in the elastic modulus, but decrease with the increase in the porosity. (3) Most of the rock samples are observed as a tensile failure when the porosity is low, while they are a shear failure at medium porosity and tensile shear composite failure at high porosity. (4) The optimum value from the ANN–MLP model for dilatancy stress with architecture 6-5-1 having coefficient correlation (R2, 0.96%) was obtained at mean absolute error (MAE, 0.18981) and root mean square error (RMSE, 0.17016). It is worth mentioning that the research results will help and provide a reference for the related to rock mechanics test, rock engineering deformation and failure mechanism, and will also give specific guidelines significance for the efficient design of excavation and support in deep rock engineering.