Analysis of pool fire scenarios in a process industry using a fuzzy Bayesian network approach

Pool fires in tanks are one of the most common types of fire accidents in chemical process industries. Therefore, identifying the intermediate and basic events of these fires is crucial for risk planning and management. In this study, the identification of intermediate and basic events of a pool fire scenario in storage tanks was initially carried out using the FTA method. Subsequently, a fault tree for pool fires was designed and illustrated. This fault tree was then mapped into Bayesian networks, and using fuzzy logic, the probabilities of basic events were determined. The most significant factors influencing the pool fire scenario were identified. The results of the study showed that the most critical basic event leading to ignition sources in atmospheric tanks is maintenance and repair activities, while the most significant basic event affecting leaks is the improper and untimely operation of the tank level metre. Pool fires in tanks can pose significant hazards and lead to domino effects in process industries. Therefore, training operational and safety personnel in hazard identification for leaks in tanks, preventing sparks, and planning for emergency response and crisis management in the event of fire escalation in these industries is crucial.