基于ISM和信息熵的铁路隧道塌方风险分析

doi:10.16265/j.cnki.issn1003-3033.2018.S1.012

中国安全科学学报 ›› 2018, Vol. 28 ›› Issue (S1): 64-70.doi: 10.16265/j.cnki.issn1003-3033.2018.S1.012

基于ISM和信息熵的铁路隧道塌方风险分析

孟超¹ 高级工程师, 李晓萌², 孙玉岭³ 高级工程师, 王景春² 教授, 刘向东¹ 教授级高级工程师

1 国家铁路局工程质量监督中心,北京 100891
2 石家庄铁道大学土木工程学院,河北石家庄 050043
3 北京铁建工程监理有限公司, 北京 100055

收稿日期:2018-02-07 修回日期:2018-05-10 出版日期:2018-06-30 发布日期:2020-11-20
作者简介:孟超 (1968—),男,山东滕州人,本科,高级工程师,主要从事铁路工程质量安全监督工作。E-mail:shmengchao@126.com。

Risk analysis of railway tunnel collapse based on ISM and entropy-weighted method

MENG Chao¹, LI Xiaomeng², SUN Yuling³, WANG Jingchun², LIU Xiangdong¹

1 Center of Engineering Quality Supervision, National Railway Administration, Beijing 100891, China
2 College of Civil Engineering, Shijiazhuang Tiedao University, Shijiazhuang Hebei 050043, China
3 Beijing Railway Construction Engineering Supervision Co. Ltd., Beijing 100055, China

Received:2018-02-07 Revised:2018-05-10 Online:2018-06-30 Published:2020-11-20

摘要/Abstract

摘要： 为深入了解铁路隧道塌方风险,以铁路隧道塌方事故为研究对象,运用解释结构模型(ISM)化技术对从事故中总结的18个风险因素进行层次化分析,找出风险因素间的关系,建立铁路隧道塌方风险因素ISM;通过直接风险因素和中间风险因素求出底层风险因素的加权归一化信息熵。研究得出导致塌方事故的8个底层风险因素为安全管理不到位、地质勘测不力、选择的开挖方式不当、喷混凝土质量达不到要求、闭合成环周期过长、偏压严重、处于不良地质、地下水渗流;其中,地下水渗流、处于特殊不良地质、开挖方式的选择对隧道塌方影响较大。

关键词: 铁路隧道, 塌方, 解释结构模型(ISM), 信息熵, 风险分析

Abstract: Taking the railway tunnel collapse accident as the research object, the 18 risk factors summarized from the accident were analyzed hierarchically using the ISM technology, the relationship between the risk factors was found out, and the structural model of the risk factors of the collapse of the railway tunnel was established. Eight underlying risk factors leading to landslide accidents were identified: inadequate safety management, poor geological survey, improper excavation method selected, insufficient sneeze quality, long closing cycle, severe bias, poor geological conditions Groundwater seepage. The weighted normalized information entropy of the underlying risk factors was obtained through direct risk factors and intermediate risk factors. It is concluded that the selection of groundwater seepage, special adverse geology, and excavation methods has a greater impact on tunnel collapse and provides ideas for reducing tunnel collapse accidents.

Key words: railway tunnel, landslide, interpretative structural modeling(ISM), information entropy, risk analysis

中图分类号:

X913.4

孟超, 李晓萌, 孙玉岭, 王景春, 刘向东. 基于ISM和信息熵的铁路隧道塌方风险分析[J]. 中国安全科学学报, 2018, 28(S1): 64-70.

MENG Chao, LI Xiaomeng, SUN Yuling, WANG Jingchun, LIU Xiangdong. Risk analysis of railway tunnel collapse based on ISM and entropy-weighted method[J]. China Safety Science Journal, 2018, 28(S1): 64-70.

参考文献

[1] 赵勇, 田四明. 中国铁路隧道数据统计[J]. 隧道建设, 2017, 37(5): 641-642.
ZHAO Yong, TIAN Siming. Statistics of Chinese railway tunnels[J]. Tunnel Construction, 2017, 37(5): 641-642.
[2] 张胜, 陈修, 汪波, 等. 明堂山隧道塌方风险评估及控制措施建议[J]. 地下空间与工程学报, 2012, 8(增1): 1 567-1 570, 1 620.
ZHANG Sheng, CHEN Xiu, WANG Bo, et al. Risk assessment and control measures of mingtangshan tunnel collapse[J]. Chinese Journal of Underground Space and Engineering, 2012, 8(S1): 1 567-1 570, 1 620.
[3] 姚志刚, 郭建宁, 方勇, 等. 强透水砂卵石地层泥水盾构掌子面塌方处理措施研究[J]. 施工技术, 2017, 46(13): 119-122.
YAO Zhigang, GUO Jianning, FANG Yong, et al. Study on the treatment of collapse of slurry shield in the strong permeable sand pebble formation[J]. Construction Technology, 2017, 46(13): 119-122.
[4] 李风云. 隧道塌方风险预测与控制研究[D]. 长沙: 中南大学, 2011.
LI Fengyun. Research on prediction and control of tunnel collapse risk[D]. Changsha: Central South University, 2011.
[5] 时惠黎, 马淑芝, 贾洪彪. 基于可拓综合评价模型的隧道塌方概率计算方法[J]. 安全与环境工程, 2015, 22(2): 154-158.
SHI Huili, MA Shuzhi, JIA Hongbiao. Calculation of tunnel collapse probability based on extension comprehensive evaluation model[J]. Safety and Environmental Engineering, 2015, 22(2): 154-158.
[6] FRALDI M, GUARRACINO F. Evaluation of impending collapse in circular tunnels by analytical and numerical approaches[J]. Tunnelling & Underground Space Technology, 2011, 26(4): 507-516.
[7] WANG Benshuo, LI Shucai, ZHANG Qianqing, et al. Risk assessment of a tunnel collapse in a mountain tunnel based on the attribute synthetic evaluation system[C].Geo-China International Conference, 2016: 198-209.
[8] HUANG Fu, ZHAO Lianheng, LING Tonghua, et al. Rock mass collapse mechanism of concealed karst cave beneath deep tunnel[J]. International Journal of Rock Mechanics & Mining Sciences, 2017, 91: 133-138.
[9] HOU Yanjuan, ZHANG Dingli, LI Ao. Analysis and control of collapse events during tunnel construction[J]. Modern Tunnelling Technology, 2018, 55(1): 45-52.
[10] 周波, 谭芳敏. 安全管理[M]. 北京: 国防工业出版社, 2015: 65-77.
[11] 杨新安, 姚永勤, 喻渝. 铁路隧道[M]. 北京: 中国铁道出版社, 2011: 149-202.
[12] 陈洁金, 周峰, 阳军生, 等. 山岭隧道塌方风险模糊层次分析[J]. 岩土力学, 2009, 30(8): 2 365-2 370.
CHEN Jiejin, ZHOU Feng, YANG Junsheng, et al. Analytic hierarchy process for the risk of collapse in mountain tunnels[J]. Rock and Soil Mechanics, 2009, 30(8): 2 365-2 370.
[13] TB 10003—2016, 铁路隧道设计规范[S].
TB 10003-2016, Railway tunnel design specification[S].
[14] 顾伟红, 王胜国. 基于ISM和模糊故障树的铁路黄土隧道塌方风险分析[J]. 安全与环境学报, 2016, 16(5): 31-36.
GU Weihong, WANG Shengguo. Analysis of the collapse risk of railway loess tunnel based on ISM and fuzzy fault tree[J]. Journal of Safety and Environment, 2016, 16(5): 31-36.
[15] 岳诚东. 隧道工程施工塌方风险评估研究[D]. 兰州: 兰州大学, 2016.
YUE Chengdong. Risk assessment of tunnel collapse in tunnel construction[D]. Lanzhou: Lanzhou University, 2016.
[16] 汪应洛. 系统工程[M]. 北京: 机械工业出版社, 2015: 39-51.
[17] 董伟, 张晓明, 陈绍杰, 等. 可拓论与信息熵在煤层注水效果优化中的应用研究[J]. 中国安全科学学报, 2016, 26(10): 121-126.
DONG Wei, ZHANG Xiaoming, CHEN Shaojie, et al. The application of extension theory and information entropy in optimization of coal seam water injection effect[J]. China Safety Science Journal, 2016, 26(10): 121-126.
[18] 王新民, 柯愈贤, 鄢德波, 等. 基于熵权法和物元分析的采空区危险性评价研究[J]. 中国安全科学学报, 2012, 22(6): 71-78.
WANG Xinmin, KE Yuxian, YAN Debo, et al. Study on risk assessment of goaf based on entropy method and matter element analysis[J]. China Safety Science Journal, 2012, 22(6): 71-78.

基于ISM和信息熵的铁路隧道塌方风险分析

Risk analysis of railway tunnel collapse based on ISM and entropy-weighted method

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