The establishment of spatial correlation among scattering acoustic emission (AE) signals has great potential applied into a deep analysis of triaxial compression behaviors by the AE monitoring technology. Taking the randomly distributed AE signal could as the cube cluster by an introduction of covering strategy from the percolation theory, the quantitative evaluation of spatial correlation instead of spatial distribution is effectively made. It presents a cluster-based perspective to investigate the triaxial compression behaviors, especially including the dilatancy based on the volumetric strain correlated to the cube cluster evolution. Besides, considering a damage definition by the AE energy count, the cube cluster damage model is successfully established. Then, by implanting the cube cluster termed AE percolation cluster (APC) into the numerical software FLAC 3D , the consistency between numerical and experimental results of four descriptors of strength, axial, hoop and volumetric strains excellently proves the reliability of the cluster damage model. In addition, the damaged cluster shows a potential application for quantitative analysis of the shear failure. Furthermore, a percolation analysis of the granite deformation under triaxial compression is made based on the cluster damage model. The effect of pressure-induced percolation transition (PIPT) is verified for the granite and the volume fraction shows a strong linear dependence on the covering length. Moreover, a series of discussion is made to analyze the influence of mechanical parameters on the sensibility of the cluster damage model. Finally, the influence of damage distribution of sub-clusters on the triaxial compression behaviors is quantitatively determined by the comparison between the linear and exponential distributions. The results verify the effectiveness and sensitivity of the cluster damage model in describing triaxial compression behaviors, which provides a new modeling method to extract more valuable information from the correlated AE signals.

中文翻译：

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一种模拟花岗岩三轴压缩行为的基于声发射的簇损伤模型

散射声发射（AE）信号之间空间相关性的建立对于AE监测技术在三轴压缩行为的深入分析中具有很大的潜力。通过引入渗流理论中的覆盖策略，将随机分布的AE信号作为立方体簇，有效地对空间相关性而非空间分布进行定量评价。它提出了一个基于集群的视角来研究三轴压缩行为，特别是包括基于与立方体集群演化相关的体积应变的剪胀。此外，考虑到AE能量计数的损伤定义，成功地建立了立方体簇损伤模型。然后，通过将称为AE渗流簇（APC）的立方体簇植入数值软件FLAC 3D中，强度、轴向、环向和体积应变四个描述符的数值和实验结果的一致性很好地证明了簇损伤模型的可靠性。此外，损坏的簇显示了对剪切破坏进行定量分析的潜在应用。此外，基于簇损伤模型对三轴压缩下花岗岩变形进行了渗流分析。验证了花岗岩的压力诱导渗透转变 (PIPT) 的影响，并且体积分数显示出对覆盖长度的强烈线性依赖性。此外，还进行了一系列讨论，以分析力学参数对簇损伤模型敏感性的影响。最后，通过线性分布和指数分布的比较，定量确定子簇损伤分布对三轴压缩行为的影响。结果验证了簇损伤模型在描述三轴压缩行为方面的有效性和敏感性，为从相关AE信号中提取更有价值的信息提供了一种新的建模方法。