Fire and explosion risk analysis, using bow-tie method and fuzzy-bayesian network in the process industries

Abstract

Background and aims: Process industries are categorized as complex systems due to the hazardous materials, large number of employees and the complexity of the processes. For this reason, it is necessary to design an appropriate risk assessment system to control and manage the risks associated with such places. Therefore, the purpose of this study is to provide a comprehensive and quantitative risk analysis of the explosion, using the integration of modern approaches of Bayesian networks and fuzzy theory in a process industry. Methods: In this study, compressor gas leakage was selected as the scenario to evaluate the probabilistic risks of explosion. For the cause-consequence analysis of the selected scenario and reducing the uncertainty of the occurrence of basic events probability, Bow-Tie method and fuzzy logic approach was used, respectively. Results: By using the Bow-Tie method, the compressor gas leak analysis have detected 24 basic events and 11 intermediate events. With regard to performance of the safety barriers, i.e. success and failure of these safety barriers, led to the determination of 9 consequences that included a flash fire, jet fire, and the vapor cloud explosion that results in the release of materials. Conclusion: The results of this study showed that, based on the fuzzy Bayesian network analysis, the filtering failure was identified as the most important event in the occurrence of gas compressor leakage. Therefore, in designing the preventive and control strategies for the accident risk management, attentions should be paid to these root events.