Journal
JOURNAL OF LOSS PREVENTION IN THE PROCESS INDUSTRIES
Volume 62, Issue -, Pages -Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.jlp.2019.103964
Keywords
Fire accident; Emergency safety; Causal factors; Interpretative structural modeling; Modified Bayesian network
Categories
Funding
- National Natural Science Foundation of China [51404052, 71571025, 71774019]
- Youth Foundation of Humanities and Social Science Research of Ministry of Education of China [17YJAZH115]
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The paper focuses on emergency process safety and presents a novel analysis method for the causal factors in emergency processes of fire accidents for oil-gas storage and transportation based on the interpretative structural modeling (ISM) and modified Bayesian network (MBN) model. Twenty-one causal factors are summarized according to the statistical analysis of actual accident cases. Based on three classes of hazard theory, a classification system of causal factors leading to secondary accidents in emergency processes, which includes twenty-one influencing factors from four aspects of the human-material-environment-management, is established. Using the ISM method, the relationships among causal factors are analyzed, and an 8-layer hierarchical ISM model of the causal factors in emergency processes is established. Moreover, the direct factors, indirect factors and root factors leading to secondary accidents are obtained. The fault tree model of secondary accidents is constructed, and the probability importance of each cause factor is calculated using the fault tree analysis method. However, to more accurately assess the quantitative influence of each cause factor on secondary accidents, the fault tree model is transformed into a Bayesian network (BN) model. Furthermore, the conditional probability tables in the BN are modified using the expert scoring method, and the MBN model is established. The more accurate posterior probability of each causal factor is calculated based on the MBN model, and the sensitivity and influence are analyzed by GeNIe software. The six most probable paths leading to secondary accidents are identified. Finally, the proposed method is applied to analyze the causal factors in the emergency processes of two actual accident cases. The research results have important scientific significance and application value for grasping the evolution law of secondary accidents in emergency processes and preventing secondary accidents in oil-gas storage and transportation systems.
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