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

被引:9
|
作者
Wang Sheng [1 ,2 ]
Li Li-ping [1 ]
Cheng Shuai [1 ]
Hu Hui-jiang [1 ]
Zhang Ming-guang [3 ]
Wen Tao [2 ]
机构
[1] Shandong Univ, Geotech & Struct Engn Res Ctr, Jinan 250061, Peoples R China
[2] Yangtze Normal Univ, Sch Civil Engn, Chongqing 408100, Peoples R China
[3] Shandong Univ Sci & Technol, Coll Safety & Environm Engn, Qingdao 266590, Peoples R China
基金
中国国家自然科学基金;
关键词
water inrush; risk assessment; attribute interval recognition model; TFN-AHP; KARST TUNNELS; MUD INRUSH; MODEL;
D O I
10.1007/s11771-020-4313-2
中图分类号
TF [冶金工业];
学科分类号
0806 ;
摘要
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.
引用
收藏
页码:517 / 530
页数:14
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