Moment Tensor-Based Approach for Acoustic Emission Simulation in Brittle Rocks Using Combined Finite-Discrete Element Method (FDEM)

Acoustic emission (AE), a phenomenon of elastic waves released by localized fracture generation, has been extensively utilized as an effective tool for monitoring rock failure processes in many rock mechanics related fields. Within the framework of the combined finite-discrete element method (FDEM), we develop a new AE simulation technique based on moment tensor theory considering the clustering effect of microcracks. The technique first integrates forces around the AE source to obtain the moment tensor, and then estimates the AE magnitude associated with the acquired moment tensor. In addition to quantifying the seismic source mechanisms of the modeled AE events, the technique can also distinguish fracture types based on moment tensor decomposition approaches when an AE event contains multiple microcracks. The effectiveness of the newly developed approach for capturing the distribution of AE event magnitude is firstly verified by establishing a heterogeneous rock model under uniaxial compressive load. Then, we perform four typical tests to validate the effectiveness of the proposed approach for distinguishing the source mechanism of microcracks, and further revise the traditional criterion to better accommodate the discrimination of the full spectrum of AE source types. Furthermore, the fractures generated in the heterogeneous model demonstrate the capability of the moment tensor decomposition approach in distinguishing macro-fracture types on laboratory scales. As an exemplar application, we also establish a numerical model to analyze the failure mechanism in a bridge region of two pre-existing flaws in a rock specimen through laboratory-scale uniaxial compression tests. The work may provide a new means to analyze fracturing and failure in rocks and the associated seismic behaviors. Highlights Moment tensor-based AE simulation approach is realized in FDEM for the first time. A clustering algorithm to integrate spatially and temporally connected microcracks is implemented. The effectiveness of the proposed approach for capturing AE event magnitude is verified. The proposed approach’s capability to distinguish macroscopic fracture types is validated. The traditional criterion is modified to better discriminate full-spectrum AE source types.