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Risk assessment of water inrush in tunnels based on attribute interval recognition theory

基于改进属性区间辨识模型的隧道突涌水灾害风险评价方法

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Abstract

Water inrush is one of the most serious geological hazards in underground engineering construction. In order to effectively prevent and control the occurrence of water inrush, a new attribute interval recognition theory and method is proposed to systematically evaluate the risk of water inrush in karst tunnels. Its innovation mainly includes that the value of evaluation index is an interval rather than a certain value; the single-index attribute evaluation model is improved non-linearly based on the idea of normal distribution; the synthetic attribute interval analysis method based on improved intuitionistic fuzzy theory is proposed. The TFN-AHP method is proposed to analyze the weight of evaluation index. By analyzing geological factors and engineering factors in tunnel zone, a multi-grade hierarchical index system for tunnel water inrush risk assessment is established. The proposed method is applied to ventilation incline of Xiakou tunnel, and its rationality and practicability is verified by comparison with field situation and evaluation results of other methods. In addition, the results evaluated by this method, which considers that water inrush is a complex non-linear system and the geological conditions have spatial variability, are more accurate and reliable. And it has good applicability in solving the problem of certain and uncertain problem.

摘要

突涌水灾害是地下工程建设过程中最严重的地质灾害之一。为了实现突涌水灾害的有效主动防 控,提出了一种新的属性区间辨识模型来系统地评价岩溶隧道突涌水风险。其创新主要在于评价指标 的取值是一个区间,而不是一个确定值;引入正态分布理念对传统属性综合评价模型进行非线性改进, 提出基于改进直觉模糊理论的综合属性区间测度分析方法;并采用TFN-AHP 法进行突涌水评价指标 权重分析。同时,通过分析岩溶隧道突涌水灾害的地质影响因素和工程影响因素,建立了一个多层次 突涌水风险评价指标体系。将建立的评价方法应用于峡口隧道斜井某段的突涌水风险分析,通过与现 场情况和其他方法的评估结果对比,验证了该方法的合理性与实用性。此外,本方法考虑了突涌水这 一复杂非线性系统与围岩的空间变异性,评价结果更准确、可靠;且在解决确定与不确定问题方面具 有较好的适用性。

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Authors and Affiliations

  1. Geotechnical and Structural Engineering Research Center, Shandong University, Ji’nan, 250061, China

    Sheng Wang  (王升), Li-ping Li  (李利平), Shuai Cheng  (成帅) & Hui-jiang Hu  (胡慧江)

  2. School of Civil Engineering, Yangtze Normal University, Chongqing, 408100, China

    Sheng Wang  (王升) & Tao Wen  (文桃)

  3. College of Safety and Environmental Engineering, Shandong University of Science and Technology, Qingdao, 266590, China

    Ming-guang Zhang  (张明光)

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  1. Sheng Wang  (王升)
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  2. Li-ping Li  (李利平)
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  3. Shuai Cheng  (成帅)
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  4. Hui-jiang Hu  (胡慧江)
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Correspondence to Li-ping Li  (李利平).

Additional information

Foundation item: Project(51722904) supported by the National Science Fund for Excellent Young Scholars, China; Project(51679131) supported by the National Natural Science Foundation of China; Project(2019JZZY010601) supported by the Shandong Provincial Key Research and Development Program (Major Scientific and Technological Innovation Project), China; Project(KJ1712304) supported by the Science and Technology Research Program of Chongqing Municipal Education Commission, China; Project(2016XJQN13) supported by the Yangtze Normal University Research Project, China

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Wang, S., Li, Lp., Cheng, S. et al. Risk assessment of water inrush in tunnels based on attribute interval recognition theory. J. Cent. South Univ. 27, 517–530 (2020). https://doi.org/10.1007/s11771-020-4313-2

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  • DOI: https://doi.org/10.1007/s11771-020-4313-2

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