Failure evolution and disaster prediction of rock under uniaxial compression based on non-extensive statistical analysis of electric potential

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外文摘要：Rock failure can cause serious geological disasters,and the non-extensive statistical features of electric potential(EP)are expected to provide valuable information for disaster prediction.In this paper,the uni-axial compression experiments with EP monitoring were carried out on fine sandstone,marble and gran-ite samples under four displacement rates.The Tsallis entropy q value of EPs is used to analyze the self-organization evolution of rock failure.Then the influence of displacement rate and rock type on q value are explored by mineral structure and fracture modes.A self-organized critical prediction method with q value is proposed.The results show that the probability density function(PDF)of EPs follows the q-Gaussian distribution.The displacement rate is positively correlated with q value.With the displacement rate increasing,the fracture mode changes,the damage degree intensifies,and the microcrack network becomes denser.The influence of rock type on q value is related to the burst intensity of energy release and the crack fracture mode.The q value of EPs can be used as an effective prediction index for rock fail-ure like b value of acoustic emission(AE).The results provide useful reference and method for the mon-itoring and early warning of geological disasters.

外文关键词：

Electric potentialNon-extensive statistical featureDisplacement rateq-Gaussian distributionPrecursor predictionRock materials

作者：

Tiancheng Shan、Zhonghui Li、Haishan Jia、Enyuan Wang、Xiaoran Wang、Yue Niu、Xin Zhang、Dong Chen、Shan Yin、Quancong Zhang

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作者单位：

State Key Laboratory of Coal Mine Disaster Prevention and Control,China University of Mining and Technology,Xuzhou 221116,China

National Engineering Research Center for Coal Gas Control,China University of Mining and Technology,Xuzhou 221116,China

School of Safety Engineering,China University of Mining and Technology,Xuzhou 221116,China

State Key Laboratory for Fine Exploration and Intelligent Development of Coal Resources,China University of Mining and Technology,Xuzhou 221116,China

State Key Laboratory for Geomechanics and Deep Underground Engineering,China University of Mining and Technology,Xuzhou 221116,China

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基金：

National Key R&D Program of ChinaNational Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaPostgraduate Research & Practice Innovation Program of Jiangsu ProvinceGraduate Innovation Program of China University of Mining and Technology

项目编号：

2022YFC3004705520742805222790152204249KYCX24_29132024WLKXJ139

出版年：

2024

DOI：

10.1016/j.ijmst.2024.07.008

矿业科学技术学报(英文版)

中国矿业大学

矿业科学技术学报(英文版)

CSTPCDEI

影响因子：1.222

ISSN：2095-2686

年,卷(期)：2024.34(7)