标题:An optimal classification method for risk assessment of water inrush in karst tunnels based on grey system theory
作者:Zhou, Z. Q.;Li, S. C.;Li, L. P.;Shi, S. S.;Xu, Z. H.
作者机构:[Zhou, Z.Q] Geotechnical and Structural Engineering Research Center, Shandong University, Shandong, 50061, China;[ Li, S.C] Geotechnical and Structura 更多
通讯作者:Zhou, ZQ
通讯作者地址:[Zhou, ZQ]Shandong Univ, Geotech & Struct Engn Res Ctr, Jinan 250061, Shandong, Peoples R China.
来源:Geomechanics and engineering
出版年:2015
卷:8
期:5
页码:631-647
DOI:10.12989/gae.2015.8.5.631
关键词:optimal classification method;GST;risk assessment;water inrush;engineering application
摘要:Engineers may encounter unpredictable cavities, sinkholes and karst conduits while tunneling in karst area, and water inrush disaster frequently occurs and endanger the construction safety, resulting in huge casualties and economic loss. Therefore, an optimal classification method based on grey system theory (GST) is established and applied to accurately predict the occurrence probability of water inrush. Considering the weights of evaluation indices, an improved formula is applied to calculate the grey relational grade. Two evaluation indices systems are proposed for risk assessment of water inrush in design stage and construction stage, respectively, and the evaluation indices are quantitatively graded according to four risk grades. To verify the accuracy and feasibility of optimal classification method, comparisons of the evaluation results derived from the aforementioned method and attribute synthetic evaluation system are made. Furthermore, evaluation of engineering practice is carried through with the Xiakou Tunnel as a case study, and the evaluation result is generally in good agreement with the field-observed result. This risk assessment methodology provides a powerful tool with which engineers can systematically evaluate the risk of water inrush in karst tunnels.
收录类别:EI;SCOPUS;SCIE
WOS核心被引频次:9
Scopus被引频次:11
资源类型:期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-84930917517&doi=10.12989%2fgae.2015.8.5.631&partnerID=40&md5=5747dd4c666e46b162bd616224042f90
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