摘要:
深部岩体在受扰动时产生的损伤是引发岩爆等冲击性灾害的主要诱因。本研究对花岗岩进行了三轴加载试验和声发射试验，分析了花岗岩破坏过程中声发射的响应特征。为更好地表征岩石裂纹扩展所产生的累积损伤效应，提出了“声发射空间累计能量释放系数（AE SAERC）”的概念。采用三维克里金插值算法，实现了岩石损伤程度的三维可视化及量化表征。结果表明：基于球状模型的普通克里金三维插值算法（OK）在三轴加载下花岗岩损伤三维可视化方面表现出最佳效果，有效展示了花岗岩在渐进破坏过程中不同程度损伤区域的演化特征。轻度损伤区、中度损伤区和高度损伤区在破坏过程中逐层递进，与岩石内部断裂带有较好的一致性，并通过CT扫描技术进一步验证了三维可视化算法的合理性。此外，本文通过对无损伤区、轻度损伤区、中度损伤区和高度损伤区的体积占比进行分析，结合“层次分析法-熵值法”组合赋权法定义了岩石三维损伤因子。这一过程实现了对岩石在不同损伤阶段的定量表征。本研究不仅丰富了岩石损伤理论体系，而且为地下工程中岩体稳定性监测和灾害预警提供了新思路。
关键词:
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真三轴
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花岗岩
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声发射
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损伤
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三维可视化
Abstract:
Damage caused by disturbances in deep rockmass is a key factor triggering seismic hazards such as rockbursts. In this study, triaxial loading and acoustic emission (AE) tests were conducted on granite, and the response characteristics of AE during the granite failure process were analyzed. To better characterize the cumulative damage effects of rock crack expansion, the concept of the AE spatial-accumulated energy release coefficient (AE SAERC) was introduced. A 3D Kriging interpolation method was employed to visualize and quantify the extent of rock damage. The results showed that the ordinary Kriging 3D interpolation algorithm, based on a spherical model, provided optimal performance in visualizing rock damage. It effectively demonstrated the evolution of various damage zones in granite during progressive failure. Low, moderate, and high damage zones progressed in stages throughout the failure process, in an irreversible manner. The distribution of high damage areas closely aligned with the internal fracture zones of the rock, further validating the accuracy of the 3D visualization algorithm. Additionally, this study analyzed the volume proportions of undamaged, mildly damaged, moderately damaged, and highly damaged zones. A combination weighting method, integrating the Analytic Hierarchy Process and the Entropy Weight Method, was used to define the 3D rock damage factor. This process enabled quantitative characterization of rock at various stages of damage. This study not only enhances the theoretical framework of rock damage but also offers new insights for monitoring rock mass stability and disaster early warning in underground engineering.
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