Risk modelling of a hydrogen gasholder using Fuzzy Bayesian Network (FBN). (1st January 2020) - Mirzaei Aliabadi, Mostafa; Pourhasan, Afshin; Mohammadfam, Iraj
Abstract: Gasholder is one of the principal types of storage for gaseous hydrogen. It plays an important role in the hydrogen production. Nonetheless, hydrogen leakage in gasholders may lead to great hazard and dire consequences such as fire and explosion. Therefore, safety analysis is vital for preventing such potential accidents. Root causes of hydrogen leakage and possible consequences were obtained using Bow-Tie analysis (BT). Then, to relax the limitation of BT in modelling uncertainties and conditional dependency, a Bayesian Network (BN) model for gasholder leakage was established by converting BT to BN (BTBN). In the meantime, in order to cope with the uncertainty of the failure data, the fuzzy logic based on expert judgment was applied. Unlike the traditional FTA, the proposed approach can be used for backward inference (i.e. accident tracing) of systems, which is particularly important to find the most critical causes of accident scenarios Based on the results of the study, the main influencing factors to the hydrogen gasholder leakage were human factor, that is, operation error, inspection not specified, inspection not performed and delay of inspection. The events missle (due to domino), lightning, vehicle collision, downstream compressor failure were the second level critical events in the failure of gasholder. Highlights: A novel procedure is proposed for risk modelling of hydrogen gasholders. A fuzzy expert elicitation is used to obtain basic events failure data. The most likely causes of gasholders leakage are determined by converting Bow Tie (BT) to Bayesian Network (BTBN). Bow tie (BT) is employed to analyze hydrogen leakage from gasholders.