期刊
RELIABILITY ENGINEERING & SYSTEM SAFETY
卷 204, 期 -, 页码 -出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.ress.2020.107220
关键词
Railway dangerous goods transportation system; Risk analysis; Interpretive Structural Modeling; Bayesian Network
资金
- Traffic and Transportation Engineering Experiment and Comprehensive Innovation Center, School of Transportation and Logistics, Southwest Jiaotong University, Chengdu Sichuan
- National Natural Science Foundation of China [71173177]
- Southwest Jiaotong University 2015 Graduate Innovative Experimental Practice Program [YC201507103]
- Southwest Jiaotong University 2018 Postgraduate Academic Literacy Improvement Plan [2018KXK04]
In this paper, an Interpretive Structural Modeling (ISM) and Bayesian Network (BN) combining approach is applied to analyze the relationships and interaction strengths among the risk factors or accident causes of railway dangerous goods transportation system (RDGTS), quantitatively. According to the statistical data, 17 sub-indicators are concluded and applied as the nodes in BN. Based on the 17 sub-indicators and with the help of experts, the combined ISM and BN approach is used to analyze the system risk with seven steps: establish the relation matrix, calculate the reachability matrix, divide the reachability matrix into different levels, form the directed graph, form the Bayesian Network, establish the prior marginal and conditional probabilities of the subindicators in the BN, causal reasoning for the BN and obtain the final probabilities of occurrence for all subindicators. The conditional probability tables (CPTs) are used to express the relationships and interaction strengths among the nodes and the parent node variables. The final analysis results show that the sub-indicator, staffs are lack of technical and knowledge during transportation processes, has the highest impact to the RDGTS with probability 0.74, and the sudden natural disaster has the weakest impact to the RDGTS with probability 0.05.
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