A failure probability evaluation method for collapse of drill-and-blast tunnels based on multistate fuzzy Bayesian network

doi:10.1016/j.enggeo.2020.105752

	A failure probability evaluation method for collapse of drill-and-blast tunnels based on multistate fuzzy Bayesian network
	Zhang, Guo-Hua 3; Chen, Wu 1,3; Jiao, Yu-Yong 2; Wang, Hao 3; Wang, Cheng-Tang 1,3
刊名	ENGINEERING GEOLOGY
	2020-10-01
卷号	276 页码:16
关键词	Tunnel Drill-and-blast method Collapse Failure probability evaluation Multistate fuzzy Bayesian networks
ISSN号	0013-7952
DOI	10.1016/j.enggeo.2020.105752
英文摘要	Collapse is one of the main hazards during tunnel construction by the drill-and-blast method. In order to evaluate the collapse risk and provide a basis for risk control, a failure probability evaluation method for collapse of drill-and-blast tunnels based on the multistate fuzzy Bayesian network is proposed in this paper. First, the typical tunnel collapse cases are analyzed statistically based on the risk breakdown structure method, a fault tree model is built for drill-and-blast tunnel collapses and the causal relationships between the tunnel collapse and the influential factors, such as natural conditions, engineering geology and construction etc., are revealed. Secondly, the multiple fault states of nodes, including rock mass grade and groundwater, are described by the fuzzy numbers. The fuzzy subsets are utilized to describe the failure probability of nodes and the uncertain logic relationship between nodes described by the multistate fuzzy conditional probability table is established. In order to ensure the reliability of the survey data when evaluating the possibility intervals of the multistate fuzzy conditional probability tables and the fuzzy failure probability of root nodes, as well as taking the expert judgment ability level and subjective reliability level into consideration, an expert investigation method based on the confidence indicator is proposed. Finally, in order to fully exploit expert knowledge and empirical data, the alpha-weighted valuation method is adopted for defuzzification so as to obtain precise parameters for the conditional probability tables. The 3 sigma criterion is employed to calculate the characteristic values of triangular fuzzy numbers so as to determine the prior fuzzy failure probability of root nodes. By means of the fuzzy Bayesian inference, the proposed method is capable of calculating the probability distribution of tunnel collapse and identifying the critical risk factors under both prior knowledge and given evidence circumstances. Taking the collapse failure probability evaluation for the Xiucun Tunnel passing through the fault F18 as an example, the application results demonstrated the feasibility and efficiency of the proposed method and it can be utilized as a decision-making tool for safety risk management during tunnel construction.
资助项目	National Key R&D Program of China[2017YFC1501304] ; China National Natural Science Foundation[51579235] ; China National Natural Science Foundation[41202227] ; China National Natural Science Foundation[41920104007]
WOS研究方向	Engineering ; Geology
语种	英语
出版者	ELSEVIER
WOS记录号	WOS:000576189100004
内容类型	期刊论文
源URL	[http://119.78.100.198/handle/2S6PX9GI/24893]
专题	中科院武汉岩土力学所
通讯作者	Chen, Wu; Jiao, Yu-Yong
作者单位	1.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 2.China Univ Geosci, Fac Engn, Wuhan 430074, Hubei, Peoples R China 3.Chinese Acad Sci, Inst Rock & Soil Mech, State Key Lab Geomech & Geotech Engn, Wuhan 430071, Hubei, Peoples R China
推荐引用方式 GB/T 7714	Zhang, Guo-Hua,Chen, Wu,Jiao, Yu-Yong,et al. A failure probability evaluation method for collapse of drill-and-blast tunnels based on multistate fuzzy Bayesian network[J]. ENGINEERING GEOLOGY,2020,276:16.
APA	Zhang, Guo-Hua,Chen, Wu,Jiao, Yu-Yong,Wang, Hao,&Wang, Cheng-Tang.(2020).A failure probability evaluation method for collapse of drill-and-blast tunnels based on multistate fuzzy Bayesian network.ENGINEERING GEOLOGY,276,16.
MLA	Zhang, Guo-Hua,et al."A failure probability evaluation method for collapse of drill-and-blast tunnels based on multistate fuzzy Bayesian network".ENGINEERING GEOLOGY 276(2020):16.