Fuzzy logic approach for identifying representative accident scenarios

Selecting representative accident scenarios (RAS) is one of the most discussed and important aspects of the HAZOP process, which is the main part of risk analysis. During that process, several uncertainties can occur, which may lead to critical oversights with further consequences for life and property. These mainly concern the semi-quantitative process of risk ranking, especially the evaluation of the frequency and severity of the categories of potential accident scenarios. According to our experience, other sources of uncertainty, which are hardly taken into account at this stage of the analysis, are connected with the effects of the type and performance of the safety barriers and protection measures as well as the impact of the quality of HAZOP analysis on the risk ranking process. The latter aspect depends on many continuously changing factors that are generally related to the safety culture that exists in a specific organization. These aspects are always the focal area for discussion by analysts, and these were hardly taken into account in our previous research. In this study, both aspects, the effects of the protection layers and the quality of hazard identification analysis on the selection of RASs, are considered. The major idea is connected with the extension of the classical HAZOP study by the application of a modified risk ranking method to identify potential accident scenarios. For that process, we propose applying appropriate correction indexes concerning both aspects. The impacts of the safety layers were assessed by the efficacy index (EI), which evaluates the effectiveness of the safety barriers, and the effects of the quality of HAZOP analysis were assessed by the quality index (QI). Both indexes were used to develop the risk correction index (RCI) that was used to modify the final risk, which was the basis for selecting the RASs. The analysis was performed in two ways: 1. traditional and 2. with fuzzy logic support. Both approaches were applied to the case study concerning the storage of liquefied natural gas (LNG). The results illustrated the sensitivity of the risk ranking matrix to the risk correction index and proved the advantages of the fuzzy risk ranking methodology in relation to the traditional approach. The proposed RAS selection process supports the credibility of the risk analysis by taking into account its further application in the subsequent stages of risk analysis and then in emergency planning.