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Risk assessment of water inrush in karst tunnels based on attribute synthetic evaluation system
Highlights An attribute synthetic evaluation system is presented to systematically evaluate the risk of water inrush in karst tunnels. The methodology consists of two attribute recognition models which are different in attribute evaluation indices. The evaluation indices are quantitatively graded, and the weights of evaluation indices are rationally distributed. The evaluation results obtained from the proposed method are generally in a good agreement with the field-observed results.
Abstract A veracious and feasible method is presented to systematically evaluate the risk of water inrush in karst tunnels. The methodology consists of two attribute recognition models: one is used in design stage, and the other one is applied in construction stage. Based on the principles of scientificity, rationality, operability and representative, several influence factors are selected as evaluation indices. In order to meet the requirement of the data format of attribute mathematical theory, a couple of evaluation indices are modified and quantitatively graded according to four risk grades through expert evaluation method. The weights of evaluation indices are rationally distributed by comprehensive assignment method, and the attribute measure functions are constructed to compute single index attribute measure and synthetic attribute measure. A confidence criterion is adopted to discern the risk grade of water inrush. Comparisons of the results derived from the present method and a case study are made. The results of the comparisons indicate that the evaluation results obtained from the proposed method are generally in a good agreement with the field-observed results. This risk assessment methodology provides a powerful tool for systematically assessing the risk of water inrush in karst tunnels.
Risk assessment of water inrush in karst tunnels based on attribute synthetic evaluation system
Highlights An attribute synthetic evaluation system is presented to systematically evaluate the risk of water inrush in karst tunnels. The methodology consists of two attribute recognition models which are different in attribute evaluation indices. The evaluation indices are quantitatively graded, and the weights of evaluation indices are rationally distributed. The evaluation results obtained from the proposed method are generally in a good agreement with the field-observed results.
Abstract A veracious and feasible method is presented to systematically evaluate the risk of water inrush in karst tunnels. The methodology consists of two attribute recognition models: one is used in design stage, and the other one is applied in construction stage. Based on the principles of scientificity, rationality, operability and representative, several influence factors are selected as evaluation indices. In order to meet the requirement of the data format of attribute mathematical theory, a couple of evaluation indices are modified and quantitatively graded according to four risk grades through expert evaluation method. The weights of evaluation indices are rationally distributed by comprehensive assignment method, and the attribute measure functions are constructed to compute single index attribute measure and synthetic attribute measure. A confidence criterion is adopted to discern the risk grade of water inrush. Comparisons of the results derived from the present method and a case study are made. The results of the comparisons indicate that the evaluation results obtained from the proposed method are generally in a good agreement with the field-observed results. This risk assessment methodology provides a powerful tool for systematically assessing the risk of water inrush in karst tunnels.
Risk assessment of water inrush in karst tunnels based on attribute synthetic evaluation system
Li, Shu-cai (author) / Zhou, Zong-qing (author) / Li, Li-ping (author) / Xu, Zhen-hao (author) / Zhang, Qian-qing (author) / Shi, Shao-shuai (author)
Tunnelling and Underground Space Technology ; 38 ; 50-58
2013-05-06
9 pages
Article (Journal)
Electronic Resource
English
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