Predicting the Timing of Catastrophic Failure During Triaxial Compression: Insights from Discrete Element Method Simulations

Abstract

Examining the deformation of rocks during triaxial compression may provide insights into the precursory phase that leads to large earthquakes by revealing the components of the deformation field that evolve with predictable, systematic behavior preceding catastrophic failure. Here, we build three-dimensional discrete element method simulations of the triaxial compression of rock cores that include a variety of fault geometries in order to identify the components of the deformation field, including the velocity and strain components, that enable machine learning models to predict the timing of macroscopic failure. The results suggest that the velocity field provides more valuable information about the timing of macroscopic failure than the strain field, and in particular, the velocity component parallel to the maximum compression direction. The models also strongly depend on the second invariant of the strain deviator tensor, {J}_{2}, indicative of the shear strain. The importance of {J}_{2} on the model predictions increases with confining stress, consistent with laboratory observations that show a transition from tensile- to shear-dominated deformation with increasing confining stress. In contrast to expectations from previous machine learning analyses, none of the models strongly depend on components of the strain tensor indicative of dilation, such as the first invariant of the strain tensor. This difference may arise because the simulations host less dilative strain than the experimental rocks.