A novel dynamic risk assessment method for the petrochemical industry using bow-tie analysis and Bayesian network analysis method based on the methodological framework of ARAMIS project

•A novel dynamic risk assessment method based on bow-tie analysis and Bayesian network analysis was proposed.•The mapping algorithm from bow-tie to Bayesian network was proposed to characterize system dynamics and uncertainty.•The most likely development paths of events were generated by implementin...

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Veröffentlicht in:Reliability engineering & system safety 2023-09, Vol.237, p.109397, Article 109397
Hauptverfasser: Wu, Xingguang, Huang, Huirong, Xie, Jianyu, Lu, Meixing, Wang, Shaobo, Li, Wang, Huang, Yixuan, Yu, Weichao, Sun, Xiaobo
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Sprache:eng
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Zusammenfassung:•A novel dynamic risk assessment method based on bow-tie analysis and Bayesian network analysis was proposed.•The mapping algorithm from bow-tie to Bayesian network was proposed to characterize system dynamics and uncertainty.•The most likely development paths of events were generated by implementing strength of influence analysis.•Which events can be prevented and controlled and to what extent the consequences are mitigated were clarified by implementing the dynamic risk assessment.•The actual risk level on site can be evaluated by comprehensively considering the prevention, control and mitigation effects of safety barriers on events and their availability. In order to obtain the actual risk level and assess the performance of the safety barriers, bow-tie (BT) approach proposed by ARAMIS project is applied to accident scenarios identification and risk analysis, but this approach has limitations in dynamic risk assessment due to its static nature. This study takes the floating roof tank as the research object, and further proposes a dynamic risk assessment method based on the methodology proposed by the ARAMIS project. The BT model of the major leak of external floating roof tank was established by comprehensive consideration of the barrier functions and the logical relationship between causes and events. Furthermore, The BT to Bayesian network (BN) mapping algorithm was proposed to characterize system dynamics and uncertainty. The analysis results show that not only the dynamic assessment of the risk level for safety barriers in different states can be implemented, but also whether the current overall safety protection capability of the system is sufficient can be judged. The proposed method and findings can help managers identify safety barriers that play a key role in various accident risks, and provide effective support for risk management decision-making and implementation of preventive strategies.
ISSN:0951-8320
1879-0836
DOI:10.1016/j.ress.2023.109397