An integrated EDIB model for probabilistic risk analysis of natural gas pipeline leakage accidents

An integrated EDIB model for probabilistic risk analysis of natural gas pipeline leakage accidents

Chen, Xing lin (Fuzhou University)
Lin, Wei dong (Fujian Provincial Institute of Architectural Design and Research)
Liu, Chun xiang (Fuzhou University)
Yang, Fu qiang (Fuzhou University)
Guo, Yong (Fuzhou University)
Li, Xin (Fuzhou University)
Yuan, S. (TU Delft Safety and Security Science)
Reniers, G.L.L.M.E. (TU Delft Safety and Security Science; Universiteit Antwerpen; Katholieke Universiteit Leuven)

2023

Natural gas pipeline construction is developing rapidly worldwide to meet the needs of international and domestic energy transportation. Meanwhile, leakage accidents occur to natural gas pipelines frequently due to mechanical failure, personal operation errors, etc., and induce huge economic property loss, environmental damages, and even casualties. However, few models have been developed to describe the evolution process of natural gas pipeline leakage accidents (NGPLA) and assess their corresponding consequences and influencing factors quantitatively. Therefore, this study aims to propose a comprehensive risk analysis model, named EDIB (ET-DEMATEL-ISM-BN) model, which can be employed to analyze the accident evolution process of NGPLA and conduct probabilistic risk assessments of NGPLA with the consideration of multiple influencing factors. In the proposed integrated model, event tree analysis (ET) is employed to analyze the evolution process of NGPLA before the influencing factors of accident evolution can be identified with the help of accident reports. Then, the combination of DEMATEL (Decision-making Trial and Evaluation Laboratory) and ISM (Interpretative Structural Modeling) is used to determine the relationship among accident evolution events of NGPLA and obtain a hierarchical network, which can be employed to support the construction of a Bayesian network (BN) model. The prior conditional probabilities of the BN model were determined based on the data analysis of 773 accident reports or expert judgment with the help of the Dempster-Shafer evidence theory. Finally, the developed BN model was used to conduct accident evolution scenario analysis and influencing factor sensitivity analysis with respect to secondary accidents (fire, vapor cloud explosion, and asphyxia or poisoning). The results show that ignition is the most critical influencing factor leading to secondary accidents. The occurrence time and occurrence location of NGPLA mainly affect the efficiency of emergency response and further influence the accident consequence. Meanwhile, the weight ranking of economic loss, environmental influence, and casualties on social influence is determined with respect to NGPLAs.

Accident evolution analysis
Bayesian network
Gas leakage
Natural gas pipeline
Probabilistic risk analysis

http://resolver.tudelft.nl/uuid:086009aa-e22d-495f-912e-bea55dcee975

https://doi.org/10.1016/j.jlp.2023.105027

0950-4230

Journal of Loss Prevention in the Process Industries: the international journal of chemical and process plant safety, 83

Institutional Repository

journal article

© 2023 Xing lin Chen, Wei dong Lin, Chun xiang Liu, Fu qiang Yang, Yong Guo, Xin Li, S. Yuan, G.L.L.M.E. Reniers