Spatial correlation-based characterization of acoustic emission signal-cloud in a granite sample by a cube clustering approach

To extract more in-depth information of acoustic emission (AE) signal-cloud in rock failure under triaxial compression, the spatial correlation of scattering AE events in a granite sample is effectively described by the cube-cluster model. First, the complete connection of the fracture network is regarded as a critical state. Then, according to the Hoshen-Kopelman (HK) algorithm, the real-time estimation of fracture connection is effectively made and a dichotomy between cube size and pore fraction is suggested to solve such a challenge of the one-to-one match between complete connection and cluster size. After, the 3D cube clusters are decomposed into orthogonal layer clusters, which are then transformed into the ellipsoid models. Correspondingly, the anisotropy evolution of fracture network could be visualized by three orthogonal ellipsoids and quantitatively described by aspect ratio. Besides, the other three quantities of centroid axis length, porosity, and fracture angle are analyzed to evaluate the evolution of cube cluster. The result shows the sample dilatancy is strongly correlated to four quantities of aspect ratio, centroid axis length, and porosity as well as fracture angle. Besides, the cube cluster model shows a potential possibility to predict the evolution of fracture angle. So, the cube cluster model provides an in-depth view of spatial correlation to describe the AE signal-cloud. (C) 2021 Published by Elsevier B.V. on behalf of China University of Mining & Technology.

Automated summary

The cube-cluster model effectively describes the spatial correlation of scattering AE events in a granite sample under triaxial compression, allowing for the analysis of fracture network and quantitative evaluation of fracture angle evolution. Additionally, it provides a potential possibility to predict the evolution of fracture angle.