Exploring wave propagation behaviors in rock: A grain-based perspective on mineral structures

Rock, composed of diverse minerals, exhibits macroscopic mechanical properties largely determined by its grain-scale structure, making microscale studies crucial for understanding rock dynamic behavior. This study employs a grain-based model (GBM) within the discrete element method framework, calibrated using Lac du Bonnet granite test results, to investigate wave propagation and attenuation in rock at the grain scale. Using GBM, we analyzed the effects of grain distribution, mineral mechanical properties, and grain size on wave propagation, focusing on peak particle velocity (PPV) attenuation during stress wave propagation. Our results reveal that while the geometric distribution of mineral grains has a limited effect on stress wave propagation, changes in the elastic modulus of minerals significantly impact wave propagation, with higher elastic modulus correlating with lower stress wave attenuation rates. Based on these findings, we propose a PPV attenuation prediction model that effectively captures PPV attenuation behaviors. This study is the first to consider the influence of grains in the study of stress wave propagation, which not only provides novel insights into rock grain-scale wave propagation and validates the GBM method's applicability in wave propagation research but also proposes an effective PPV attenuation prediction model. The results offer valuable references for practical engineering applications and lay a foundation for future investigations in this field. © 2025 The Author(s). Deep Underground Science and Engineering published by John Wiley & Sons Australia, Ltd on behalf of China University of Mining and Technology.