Railway dangerous goods transportation system risk analysis: An Interpretive Structural Modeling and Bayesian Network combining approach

Frequent collapse accidents in tunnels are associated with many construction risk factors, and the interrelationship among these risk factors is complex and ambiguous. This study’s aim is to clarify the relationship among risk factors to reduce the tunnel collapse risk. A multicriteria decision-making method is proposed by combining interpretive structural modeling (ISM) and fuzzy Bayesian network (FBN). ISM is used to determine the hierarchical relationships among risk factors. FBN quantitatively analyzes the strength of the interaction among risk factors and conducts risk analysis. The ISM-FBN method contains three steps: (1) drawing the ISM-directed graph; (2) obtaining the probability of the FBN nodes; and (3) using GeNle to implement risk analysis. The proposed method is also used to assess the collapse risk and detect the critical factors in the Canglongxia Tunnel, China. This method’s tunnel collapse risk model can provide managers with clear risk information and better realize project management.

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Railway dangerous goods transportation system risk identification: Comparisons among SVM, PSO-SVM, GA-SVM and GS-SVM

Applied Soft Computing ◽

10.1016/j.asoc.2021.107541 ◽

2021 ◽

pp. 107541

Author(s):

Wencheng Huang ◽

Hongyi Liu ◽

Yue Zhang ◽

Mirong Wei ◽

Chuangui Tong ◽

...

Keyword(s):

Transportation System ◽

Risk Identification ◽

Dangerous Goods ◽

System Risk

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A Bayesian network approach for predicting seismic liquefaction based on interpretive structural modeling

Georisk Assessment and Management of Risk for Engineered Systems and Geohazards ◽

10.1080/17499518.2015.1076570 ◽

2015 ◽

Vol 9 (3) ◽

pp. 200-217 ◽

Cited By ~ 6

Author(s):

Ji-Lei Hu ◽

Xiao-Wei Tang ◽

Jiang-Nan Qiu

Keyword(s):

Bayesian Network ◽

Structural Modeling ◽

Network Approach ◽

Interpretive Structural Modeling ◽

Seismic Liquefaction

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Using an expanded Safety Failure Event Network to analyze railway dangerous goods transportation system risk-accident

Journal of Loss Prevention in the Process Industries ◽

10.1016/j.jlp.2020.104122 ◽

2020 ◽

Vol 65 ◽

pp. 104122

Author(s):

Wencheng Huang ◽

Yue Zhang ◽

Borui Zuo ◽

Yaocheng Yu ◽

Gatesi Jean De Dieu ◽

...

Keyword(s):

Transportation System ◽

Dangerous Goods ◽

Failure Event ◽

System Risk

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Risk Analysis of Tunnel Water and Mud Inrush Using Interpretive Structural Modeling and Fault Tree

10.21203/rs.3.rs-1212772/v1 ◽

2022 ◽

Author(s):

Min Han ◽

Teng Xia ◽

Maoxin Su ◽

Yiguo Xue

Keyword(s):

Risk Factors ◽

Risk Analysis ◽

Fault Tree ◽

Fault Tree Analysis ◽

Structural Modeling ◽

Geological Structure ◽

Geological Hazard ◽

Analysis Model ◽

Interpretive Structural Modeling ◽

Water And Mud Inrush

Abstract Water and mud inrush is a common geological hazard in tunnel construction. Risk analysis of tunnel water and mud inrush has always been an important subject. In order to avoid the geological hazard, this paper presents a risk analysis model of tunnel water and mud inrush. The model combines the interpretive structural modeling method (ISM) and fault tree analysis (FTA). Relying on the Qinyu tunnel in the Weiwu expressway project, water and mud inrush risk factors are obtained by using ISM. Fundamental risk factors include formation lithology, attitude of stratum, strata combination, topography and geomorphology, geological structure and weather. ISM core risk factors are used as FTA basic events. Fuzzy importance of FTA basic events is obtained by using fuzzy interval calculation. The results show that geological structure is the primary risk factor causing Qinyu tunnel water and mud inrush. The model achieves qualitative and quantitative analysis of tunnel water and mud inrush. It accurately determines the main factors affecting the tunnel water and mud inrush, which is conducive to accident prevention.

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