Evaluation of the Rock Burst Intensity of a Cloud Model Based on the CRITIC Method and the Order Relation Analysis Method

被引:6
|
作者
Zhang, Qianjun [1 ]
Liu, Chuanju [1 ,2 ]
Guo, Sha [1 ]
Wang, Wentong [1 ]
Luo, Haoming [1 ]
Jiang, Yongheng [3 ]
机构
[1] Southwest Univ Sci & Technol, Sch Environm & Resource, Mianyang 621010, Peoples R China
[2] Southwest Univ Sci & Technol, Shock & Vibrat Engn Mat & Struct Key Lab Sichuan P, Mianyang 621010, Peoples R China
[3] Changchun Gold Res Inst Co Ltd, Changchun 130012, Peoples R China
基金
中国国家自然科学基金;
关键词
Cloud model; Rock burst; Grade evaluation; Combination weighting; Sensitivity; PREDICTION; HAZARD;
D O I
10.1007/s42461-023-00838-7
中图分类号
TF [冶金工业];
学科分类号
0806 ;
摘要
Rock burst has always been a major problem in deep underground engineering with high stress, and rock burst strength evaluation has become an important research topic. To effectively predict the rock burst hazard in underground rock mass engineering, a cloud model (CM) rock burst intensity evaluation method based on the CRITIC method and order relation analysis method (G1) was proposed in this paper. First, a rock's uniaxial compressive strength & sigma;c, tangential stress & sigma;& theta;, uniaxial tensile strength & sigma;t, ratio of uniaxial compressive strength to tensile strength & sigma;c/& sigma;t (brittleness coefficient), ratio of tangential stress to uniaxial compressive strength & sigma;& theta;/& sigma;c (stress coefficient), elastic deformation energy index Wet, and depth of cover H were selected as evaluation indices of rock burst intensity. Ninety-five groups of rock burst measured data at home and abroad were selected, and the objective weight and subjective weight of each index were calculated by using the CRITIC method and G1 method, respectively. The comprehensive weight was determined according to the combined weighting method of game theory, and the sensitivity of each evaluation index was analyzed. By utilizing a forward cloud generator, the membership degrees of different rock burst grades were calculated, and then the rock burst intensity grades of the samples were evaluated and compared with the evaluation results of the CRITIC-CM method and G1-CM method and the actual grades. Finally, the rock burst classification ability of the model was analyzed. To better verify the accuracy and reliability of this model, the rock burst case of the W39 line in the Chengchao Iron Mine was analyzed by using this model. The research results show that the rock burst evaluation results based on CRITIC-G1-CM are basically consistent with the actual rock burst grade, and the rock burst intensity grade evaluation model has good practicability and reliability.
引用
收藏
页码:1849 / 1863
页数:15
相关论文
共 50 条
  • [31] A new method for rock brittleness evaluation based on statistical damage constitutive relation
    Hu Q.
    Liang H.
    Yang T.
    Cheng X.
    Chen H.
    Zhang L.
    Harbin Gongye Daxue Xuebao/Journal of Harbin Institute of Technology, 2020, 52 (11): : 147 - 156
  • [32] An Improved Comprehensive Index Method for the Evaluation of Rock Burst Risk in Mining
    Zhang, Zhizhen
    Gao, Feng
    Shang, Xiaoji
    ADVANCED MEASUREMENT AND TEST, PTS 1-3, 2011, 301-303 : 1389 - +
  • [33] Optimization and Application of Composite Index Method for Evaluation of Rock Burst Rating
    Zhang Jiayong
    Luo Xinrong
    Guo Liwen
    Gong Xuemin
    MANUFACTURING SCIENCE AND TECHNOLOGY, PTS 1-8, 2012, 383-390 : 7708 - +
  • [34] Rock burst prediction based on coefficient of variation and sequence analysis-multidimensional normal cloud model
    Li M.
    Li K.
    Liu Y.
    Wu S.
    Qin Q.
    Wang H.
    Yanshilixue Yu Gongcheng Xuebao/Chinese Journal of Rock Mechanics and Engineering, 2020, 39 : 3395 - 3402
  • [35] Evaluation model of regional water supply capacity based on AHP-CRITIC method
    Zhou, Lingjie
    PROCEEDINGS OF THE 2016 INTERNATIONAL CONFERENCE ON ECONOMICS, SOCIAL SCIENCE, ARTS, EDUCATION AND MANAGEMENT ENGINEERING (ESSAEME), 2016, 71 : 299 - 302
  • [36] Evaluation of rock burst intensity based on annular grey target decision-making model with variable weight
    Xinlong Zhou
    Guang Zhang
    Yinghua Song
    Shaohua Hu
    Mingze Liu
    Junzhe Li
    Arabian Journal of Geosciences, 2019, 12
  • [37] Evaluation of rock burst intensity based on annular grey target decision-making model with variable weight
    Zhou, Xinlong
    Zhang, Guang
    Song, Yinghua
    Hu, Shaohua
    Liu, Mingze
    Li, Junzhe
    ARABIAN JOURNAL OF GEOSCIENCES, 2019, 12 (02)
  • [38] Rock burst intensity grading prediction model based on automatic machine learning
    He, Long-ping
    Yao, Nan
    Wang, Qi-hu
    Ye, Yi-cheng
    Ling, Ji-suo
    ROCK AND SOIL MECHANICS, 2024, 45 (09) : 2839 - 2848
  • [39] The Eutrophication Degree Evaluation Method Based on Multidimensional Normal Cloud Model
    Zeng, Debiao
    Wang, Dong
    Ding, Hao
    Zhang, Liyuan
    INFORMATION TECHNOLOGY FOR RISK ANALYSIS AND CRISIS RESPONSE, 2014, 102 : 720 - 724
  • [40] Evaluation Method of Public Transportation System Based on Fuzzy Cloud Model
    Tu, Min
    Xu, Shiyang
    Xu, Jianfeng
    INTERNATIONAL JOURNAL OF DIGITAL CRIME AND FORENSICS, 2018, 10 (04) : 36 - 51