Abstract
In this study, a comprehensive approach based on the Fuzzy Bayesian Network (FBN) was presented to reduce completeness, modeling, and parameter uncertainties and to analyze the risk of hazardous material release in floating roof storage tanks accurately. In this method, managerial, organizational, human and process factors, were investigated using human and process HAZOP technique before the occurrence of accident scenarios. These factors were examined after the intended scenario in a sequential modeling approach based on SHIPP methodology as a barrier model. Moreover, according to the initial probabilities and interference of barriers, the relevant conditional probability tables (CPTs) were modified by utilizing l-NOR gates, and the accident scenario model was developed using the Bow-tie (BT) model. Triangular fuzzy numbers and expert opinion incorporated into the Bayesian network to deal with the uncertainty in the occurrence probability of basic events and safety barriers. The methanol storage tank was selected to present the applicability potential of the proposed model. The results showed that the validation of the position and conditional probabilities (CPs) of barriers in the BT structure will reduce the uncertainties, and the combination of FBN and lNOR gate is an appropriate way to evaluate the risk of tanks accurately.
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