Cluster modeling of the short-range correlation of acoustically emitted scattering signals

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Abstract

As a widely used measurement technique in rock mechanics, spatial correlation modeling of acoustic emission (AE) scattering signals is attracting increasing focus for describing mechanical behavior quantitatively. Unlike the statistical description of the spatial distribution of randomly generated AE signals, spatial correlation modeling is based mainly on short-range correlation considering the interrelationship of adjacent signals. As a new idea from percolation models, the covering strategy is used to build the most representative cube cluster, which corresponds to the critical scale at peak stress. Its modeling process of critical cube cluster depends strongly on the full connection of the main fracture network, and the corresponding cube for coverage is termed the critical cube. The criticality pertains to not only the transition of local-to-whole connection of the fracture network but also the increasing-to-decreasing transition of the deviatoric stress with an obvious stress drop in the brittle failure of granite. Determining a reasonable critical cube guarantees the best observation scale for investigating the failure process. Besides, the topological connection induces the geometric criticality of three descriptors, namely anisotropy, pore fraction, and specific surface area, which are evaluated separately and effectively. The results show that cluster modeling based on the critical cube is effective and has criticality in both topology and geometry, as well as the triaxial behavior. Furthermore, the critical cube length presents a high confidence probability of being correlated to the mineral particle size. Besides, its pore fraction of cube cluster is influenced strongly by the critical cube length and confining pressure.

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Xue, D., Lu, L., Zhou, J., Lu, L., & Liu, Y. (2021). Cluster modeling of the short-range correlation of acoustically emitted scattering signals. International Journal of Coal Science and Technology, 8(4), 575–589. https://doi.org/10.1007/s40789-020-00357-6

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