• 中国出版政府奖提名奖

    中国百强科技报刊

    湖北出版政府奖

    中国高校百佳科技期刊

    中国最美期刊

    Volume 47 Issue 6
    Jun.  2022
    Turn off MathJax
    Article Contents
    Zhou Hang, Liao Xin, Chen Shikuo, Feng Tao, Wang Zhimin, 2022. Rockburst Risk Assessment of Deep Lying Tunnels Based on Combination Weight and Unascertained Measure Theory: A Case Study of Sangzhuling Tunnel on Sichuan-Tibet Traffic Corridor. Earth Science, 47(6): 2130-2148. doi: 10.3799/dqkx.2021.170
    Citation: Zhou Hang, Liao Xin, Chen Shikuo, Feng Tao, Wang Zhimin, 2022. Rockburst Risk Assessment of Deep Lying Tunnels Based on Combination Weight and Unascertained Measure Theory: A Case Study of Sangzhuling Tunnel on Sichuan-Tibet Traffic Corridor. Earth Science, 47(6): 2130-2148. doi: 10.3799/dqkx.2021.170

    Rockburst Risk Assessment of Deep Lying Tunnels Based on Combination Weight and Unascertained Measure Theory: A Case Study of Sangzhuling Tunnel on Sichuan-Tibet Traffic Corridor

    doi: 10.3799/dqkx.2021.170
    • Received Date: 2021-07-22
    • Publish Date: 2022-06-25
    • Aming at the uncertain factors in the rockburst risk assessment of deep lying tunnels in complex mountainous areas, the unascertained measurement theory was used to establish a tunnel rockburst risk evaluation model. By summarizing and analyzing the rockburst failure characteristics and key influencing factors of deep lying tunnels under typical high geostress conditions, 5 evaluation indexes were determined from three levels that objectively reflect the high geostress environment, rock mechanical properties and surrounding rock properties. In order to fully consider the subjective and objective factors of rockburst risk assessment, by introducing a distance function, using the combination of entropy weight method and analytic hierarchy process to construct a combination weighting method, and comprehensively determined the weight coefficient of each index. Based on the unascertained measurement theory and calculation rules, it constructed a linear single-index measurement function according to the rockburst risk classification standard. By calculating the single-index measurement evaluation matrix and the multi-index measurement vector, the rockburst risk assessment was carried out according to the confidence criterion. The unascertained measurement model of rockburst risk assessment was applied to the Sangzhuling tunnel of the Sichuan-Tibet traffic corridor. The evaluation accuracy was compared with that obtained from single index criteria such as strength-stress ratio method, Russenes criterion, rock brittleness coefficient, rock mass integrity coefficient, rock elastic energy index and the actual rockburst results. The research results show that the accuracy rate of the evaluation result of the model is 94.4%, which is 16.7%-66.7% higher than that of the single-index rockburst criterion.

       

    • loading
    • Cai, M. F., 2016. Prediction and Prevention of Rockburst in Metal Mines: A Case Study of Sanshandao Gold Mine. Journal of Rock Mechanics and Geotechnical Engineering, 8(2): 204-211. https://doi.org/10.1016/j.jrmge.2015.11.002
      Chen, H. J., Li, N. H., Nie, D. X., et al., 2002. A Model for Prediction of Rockburst by Artificial Neural Network. Chinese Journal of Geotechnical Engineering, 24(2): 229-232(in Chinese with English abstract).
      Chen, S. K., Li, H. R., Zhou, H., et al., 2021. Route Selection of Deep-Lying and Hard Rock Tunnel in the Sichuan-Tibet Railway Based on Rock Burst Risk Assessment. Hydrogeology and Engineering Geology, 48(5): 81-90(in Chinese with English abstract).
      Cheng, Q. S., 1997. Attribute Recognition Theoretical Model with Application. Acta Scicentiarum Naturalum Universitis Pekinesis, 33(1): 12-20(in Chinese with English abstract).
      Dong, L. J., Li, X. B., Peng, G. K., 2013. Prediction of Rockburst Classification Using Random Forest. Transactions of Nonferrous Metals Society of China, 23(2): 472-477. https://doi.org/10.1016/s1003-6326(13)62487-5
      Dong, L. J., Peng, G. J., Fu, Y. H., et al., 2008. Unascertained Measurement Classifying Model of Goaf Collapse Prediction. Journal of Coal Science and Engineering (China), 14(2): 221-224. https://doi.org/10.1007/s12404-008-0046-9
      Feng, X. T., Xiao, Y. X., Feng, G. L., et al., 2019. Study on the Development Process of Rockbursts. Chinese Journal of Rock Mechanics and Engineering, 38(4): 649-673(in Chinese with English abstract).
      Gong, F. Q., Li, X. B., 2007. A Distance Discriminant Analysis Method for Prediction of Possibility and Classification of Rockburst and Its Application. Chinese Journal of Rock Mechanics and Engineering, 26(5): 1012-1018(in Chinese with English abstract).
      Guo, J. L., Zhang, H. F., Xu, W. C., et al., 2019. The Bulk Crustal Composition of the Southeastern Lhasa Terrane and Its Origin. Earth Science, 44(6): 1809-1821(in Chinese with English abstract).
      He, Y. F., Li, T. B., Cao, H. Y., 2020. Attribute Recognition Model of Fatalness Assessment of Rockburst in Tunnel Construction and Its Application. Hydrogeology & Engineering Geology, 47(2): 102-111(in Chinese with English abstract).
      Jia, Q. J., Wu, L., Li, B., 2019. The Comprehensive Prediction Model of Rockburst Tendency in Tunnel Based on Optimized Unascertained Measure Theory. Geotechnical and Geology Engineering, 37: 3399-3411. https://doi.org/10.1007/s10706-019-00854-9
      Jia, Y. P., Lü, Q., Shang, Y. Q., et al., 2014. Rockburst Prediction Based on Rough Set and Ideal Point Method. Journal of Zhejiang University (Engineering Science), 48(3): 498-503(in Chinese with English abstract).
      Kidybiński, A., 1981. Bursting Liability Indices of Coal. International Journal of Rock Mechanics and Mining Sciences, 18(4): 295-304. https://doi.org/10.1016/0148-9062(81)91194-3
      Li, P. X., Chen, B. R., Zhou, Y. Y., et al., 2019. Research Progress of Rockburst Prediction and Early Warning in Hard Rock Underground Engineering. Journal of China Coal Society, 44(Suppl. 2): 447-465(in Chinese with English abstract).
      Li, S. C., Zhou, Z. Q., Li, L. P., et al., 2013. Risk Evaluation Theory and Method of Water Inrush in Karst Tunnels and Its Applications. Chinese Journal of Rock Mechanics and Engineering, 32(9): 1858-1867(in Chinese with English abstract).
      Li, T. B., Ma, C. C., Zhu, M. L., et al., 2017. Geomechanical Types and Mechanical Analyses of Rockbursts. Engineering Geology, 222: 72-83. https://doi.org/10.1016/j.enggeo.2017.03.011
      Li, T. B., Meng, L. B, Wang, L. S., et al., 2016. High Stress Tunnel Stability and Large Deformation Disaster Prevention. Science Press, Beijing, 361-391(in Chinese).
      Ministry of Housing and Urban-Rural Development of the People's Republic of China, General Administration of Quality Supervision, Inspection and Quarantine of the People's Republic of China, 2014. GB50218-2014. Standard for Engineering Classification of Rock Mass. China Planning Press, Beijing(in Chinese).
      National Railway Administration, 2016. TB10003-2016. Code for Design of Railway Tunnel. China Railway Publishing House, Beijing(in Chinese).
      Pan, G. T., Ren, F., Yin, F. G., et al., 2020. Key Zones of Oceanic Plate Geology and Sichuan-Tibet Railway Project. Earth Science, 45(7): 2293-2304(in Chinese with English abstract).
      Russenes, B. F., 1974. Analysis of Rock Spalling for Tunnels in Steep Vally Site. Norwegian Institute of Technology, Depatment of Geology, Norway.
      Saaty, T. L., 1997. Applications of Analytical Hierarchies. Mathematics and Computers in Simulation, 21(1): 1-20. https://doi.org/10.1016/0378-4754(79)90101-0
      Shirani Faradonbeh, R., Taheri, A., 2019. Long-Term Prediction of Rockburst Hazard in Deep Underground Openings Using Three Robust Data Mining Techniques. Engineering with Computers, 35(2): 659-675. https://doi.org/10.1007/s00366-018-0624-4
      Song, B. W., Zhang, K. X., Xu, Y. D., et al., 2020. Paleogene Tectonic-Stratigraphic Realms and Sedimentary Sequence in China. Earth Science, 45(12): 4352-4369(in Chinese with English abstract).
      Wang, D., Li, T., B., Jiang, L. W., et al. 2017. Analysis of the Stress Characteristics and Rock Burst of Ultra Deep Buried Tunnel in Sichuan-Tibet Railway. Journal of Railway Engineering Society, 34(4): 46-50(in Chinese with English abstract).
      Wang, G. Y., 1990. Uncertainty Information and Its Mathematical Treatment. Journal of Harbin Architecture and Engineering Institute, 23(4): 1-9(in Chinese with English abstract).
      Wang, M. W., Li, L., Jin, J. L., 2008. An Improved Set Pair Analysis Model for the Prediction of Rockburst. Rock and Soil Mechanics, 29(Suppl. 1): 511-518(in Chinese with English abstract).
      Wang, Q. W., Ju, N. P., Du, L. L., et al., 2018. Three Dimensional Inverse Analysis of Geostress Field in the Sangri-Jiacha Section of Lasa-Linzhi Railway. Rock and Soil Mechanics, 39(4): 1450-1462(in Chinese with English abstract).
      Wang, Y. C., Jing, H. W., Ji, X. W., et al., 2014. Model for Classification and Prediction of Rock Burst Intensity in a Deep Underground Engineering with Rough Set and Efficacy Coefficient Method. Journal of Central South University (Science and Technology), 45(6): 1992-1997(in Chinese with English abstract).
      Wang, Y. H, Li W. D., Li, Q. G., et al., 1998. Method of Fuzzy Comprehensive Evaluations for Rockburst Prediction. Chinese Journal of Rock Mechanics and Engineering, 17(5): 493-501(in Chinese with English abstract).
      Wu, F. Y., He, C., Wang, B., et al., 2021. Rock Burst Intensity Classification of Lhasa-Linzhi Railway Based on Stress Criterion. Journal of Southwest Jiaotong University, 56(4): 792-800(in Chinese with English abstract).
      Xu, C., Liu, X. L., Wang, E. Z., et al., 2018. Rockburst Prediction and Classification Based on the Ideal-Point Method of Information Theory. Tunnelling and Underground Space Technology, 81: 382-390. https://doi.org/10.1016/j.tust.2018.07.014
      Xue, Y. G., Li, Z. Q., Li, S. C., et al., 2019. Prediction of Rock Burst in Underground Caverns Based on Rough Set and Extensible Comprehensive Evaluation. Bulletin of Engineering Geology and the Environment, 78(1): 417-429. https://doi.org/10.1007/s10064-017-1117-1
      Yan, J., He, C., Wang, B., et al., 2019. Inoculation and Characters of Rockbursts in Extra-Long and Deep-Lying Tunnels Located on Yarlung Zangbo Suture. Chinese Journal of Rock Mechanics and Engineering, 38(4): 769-781(in Chinese with English abstract).
      Zhang, C., Wang, Q., Chen, J. P., et al., 2011. Evaluation of Debris Flow Risk in Jinsha River Based on Combined Weight Process. Rock and Soil Mechanics, 32(3): 831-836(in Chinese with English abstract).
      Zhang, J. J., Fu, B. J., 2008. Rockburst and Its Criteria and Control. Chinese Journal of Rock Mechanics and Engineering, 27(10): 2034-2042(in Chinese with English abstract).
      Zhou, H., Chen, S. K., Li, H. R., et al., 2021. Rockburst Prediction for Hard Rock and Deep-Lying Long Tunnels Based on the Entropy Weight Ideal Point Method and Geostress Field Inversion: A Case Study of the Sangzhuling Tunnel. Bulletin of Engineering Geology and the Environment, 80(5): 3885-3902. https://doi.org/10.1007/s10064-021-02175-9
      Zhou, H., Chen, S. K., Zhang, G. Z., et al., 2020. Efficiency Coefficient Method and Ground Stress Field Inversion for Rockburst Predicition in Deep and Long Tunnel. Journal of Engineering Geology, 28(6): 1386-1396(in Chinese with English abstract).
      Zhou, J., Li, X. B., Mitri, H. S., 2018. Evaluation Method of Rockburst: State-of-the-Art Literature Review. Tunnelling and Underground Space Technology, 81: 632-659. https://doi.org/10.1016/j.tust.2018.08.029
      Zhu, L., Yang, J. Z., Wang, K., et al., 2009. Analysis of Heterogeneous Soil Water Using Information Entropy and Multifractal Theory. Earth Science, 34(6): 1037-1042(in Chinese with English abstract).
      陈海军, 郦能惠, 聂德新, 等, 2002. 岩爆预测的人工神经网络模型. 岩土工程学报, 24(2): 229-232. doi: 10.3321/j.issn:1000-4548.2002.02.023
      陈仕阔, 李涵睿, 周航, 等, 2021. 基于岩爆危险性评价的川藏交通廊道某深埋硬岩隧道线路方案比选研究. 水文地质工程地质, 48(5): 81-90.
      程乾生, 1997. 属性识别理论模型及其应用. 北京大学学报(自然科学版), 33(1): 12-20. doi: 10.3321/j.issn:0479-8023.1997.01.002
      冯夏庭, 肖亚勋, 丰光亮, 等, 2019. 岩爆孕育过程研究. 岩石力学与工程学报, 38(4): 649-673. https://www.cnki.com.cn/Article/CJFDTOTAL-YSLX201904002.htm
      宫凤强, 李夕兵, 2007. 岩爆发生和烈度分级预测的距离判别方法及应用. 岩石力学与工程学报, 26(5): 1012-1018. doi: 10.3321/j.issn:1000-6915.2007.05.021
      郭京梁, 张宏飞, 徐旺春, 等, 2019. 拉萨地体东南部整体地壳成分及其成因分析. 地球科学, 44(6): 1809-1821. doi: 10.3799/dqkx.2019.050
      国家铁路局, 2016. TB 10003-2016. 铁路隧道设计规范. 北京: 中国铁道出版社.
      何怡帆, 李天斌, 曹海洋, 2020. 隧道施工期岩爆危险性评价的属性识别模型及工程应用. 水文地质工程地质, 47(2): 102-111. https://www.cnki.com.cn/Article/CJFDTOTAL-SWDG202002014.htm
      贾义鹏, 吕庆, 尚岳全, 等, 2014. 基于粗糙集-理想点法的岩爆预测. 浙江大学学报(工学版), 48(3): 498-503. https://www.cnki.com.cn/Article/CJFDTOTAL-ZDZC201403019.htm
      李鹏翔, 陈炳瑞, 周扬一, 等, 2019. 硬岩岩爆预测预警研究进展. 煤炭学报, 44(增刊2): 447-465. https://www.cnki.com.cn/Article/CJFDTOTAL-MTXB2019S2006.htm
      李术才, 周宗青, 李利平, 等, 2013. 岩溶隧道突水风险评价理论与方法及工程应用. 岩石力学与工程学报, 32(9): 1858-1867. doi: 10.3969/j.issn.1000-6915.2013.09.018
      李天斌, 孟陆波, 王兰生, 等, 2016. 高地应力隧道稳定性及岩爆、大变形灾害防治. 北京: 科学出版社, 361-391.
      潘桂棠, 任飞, 尹福光, 等, 2020. 洋板块地质与川藏交通廊道工程地质关键区带. 地球科学, 45(7): 2293-2304. doi: 10.3799/dqkx.2020.070
      宋博文, 张克信, 徐亚东, 等, 2020. 中国古近纪构造-地层区划及地层格架. 地球科学, 45(12): 4352-4369. doi: 10.3799/dqkx.2020.122
      王栋, 李天斌, 蒋良文, 等, 2017. 川藏交通廊道某超深埋隧道地应力特征及岩爆分析. 铁道工程学报, 34(4): 46-50. doi: 10.3969/j.issn.1006-2106.2017.04.010
      王光远, 1990. 未确知信息及其数学处理. 哈尔滨建筑工程学院学报, 23(4): 1-9. https://www.cnki.com.cn/Article/CJFDTOTAL-HEBJ199004000.htm
      汪明武, 李丽, 金菊良, 2008. 岩爆预测的改进集对分析模型. 岩土力学, 28(增刊1): 511-518. https://www.cnki.com.cn/Article/CJFDTOTAL-YTLX2008S1102.htm
      王庆武, 巨能攀, 杜玲丽, 等, 2018. 拉林铁路桑日至加查段三维地应力场反演分析. 岩土力学, 39(4): 1450-1462. https://www.cnki.com.cn/Article/CJFDTOTAL-YTLX201804038.htm
      王迎超, 靖洪文, 吉咸伟, 等, 2014. 深埋地下工程岩爆烈度分级预测的RS-功效系数模型. 中南大学学报(自然科学版), 45(6): 1992-1997. https://www.cnki.com.cn/Article/CJFDTOTAL-ZNGD201406033.htm
      王元汉, 李卧东, 李启光, 等, 1998. 岩爆预测的模糊数学综合评判方法. 岩石力学与工程学报, 17(5): 493-501. doi: 10.3321/j.issn:1000-6915.1998.05.003
      吴枋胤, 何川, 汪波, 等, 2021. 基于应力判据法的拉林铁路岩爆烈度分级. 西南交通大学学报, 56(4): 792-800. https://www.cnki.com.cn/Article/CJFDTOTAL-XNJT202104015.htm
      严健, 何川, 汪波, 等, 2019. 雅鲁藏布江缝合带深埋长大隧道群岩爆孕育及特征. 岩石力学与工程学报, 38(4): 769-781. https://www.cnki.com.cn/Article/CJFDTOTAL-YSLX201904011.htm
      张晨, 王清, 陈剑平, 等, 2011. 金沙江流域泥石流的组合赋权法危险度评价. 岩土力学, 32(3): 831-836. doi: 10.3969/j.issn.1000-7598.2011.03.032
      张镜剑, 傅冰骏, 2008. 岩爆及其判据和防治. 岩石力学与工程学报, 27(10): 2034-2042. doi: 10.3321/j.issn:1000-6915.2008.10.010
      中华人民共和国住房和城乡建设部, 中华人民共和国国家质量监督检验检疫总局, 2014. GB50218-2014. 工程岩体分级标准. 北京: 中国计划出版社.
      周航, 陈仕阔, 张广泽, 等, 2020. 基于功效系数法和地应力场反演的深埋长大隧道岩爆预测研究. 工程地质学报, 28(6): 1386-1396. https://www.cnki.com.cn/Article/CJFDTOTAL-GCDZ202006025.htm
      朱磊, 杨金忠, 王康, 等, 2009. 基于信息熵与多重分形理论的非均匀流动分析. 地球科学, 34(6): 1037-1042. doi: 10.3321/j.issn:1000-2383.2009.06.020
    • 加载中

    Catalog

      通讯作者: 陈斌, bchen63@163.com
      • 1. 

        沈阳化工大学材料科学与工程学院 沈阳 110142

      1. 本站搜索
      2. 百度学术搜索
      3. 万方数据库搜索
      4. CNKI搜索

      Figures(12)  / Tables(9)

      Article views (1161) PDF downloads(66) Cited by()
      Proportional views

      /

      DownLoad:  Full-Size Img  PowerPoint
      Return
      Return