Selection of representative accident scenarios for major industrial accidents

Abstract This paper analyzes the problems with selecting representative accident scenarios, which are understood as the maximum credible accidents for major industrial accidents. The selection process is based on the risk ranking scheme, which is applicable to all potential accident scenarios identified during the process hazard analysis (PHA) for a major hazard plant. Unfortunately, the process implies a substantial level of uncertainty due to incomplete and vague information concerning the assessment of the frequency and severity of the categories required for the risk ranking matrix as well as the lack of data reflecting the impact of the layer of protection on those categories. In most cases, the uncertainty is caused by insufficient knowledge and experience of the PHA team. This uncertainty usually affects the credibility of the accident scenario identification process and, by the same token, results in underestimation or overestimation of the process risk level. To address all knowledge-based uncertainties, a new approach for the identification of representative accident scenarios is proposed. This approach consists of the inclusion of a semi-quantitative assessment of the safety performance of protection layers combined with a fuzzy logic approach to risk ranking assessment. The proposed methodology may be successfully used for any major hazard industry; a case study for the fictional model of LNG storage facilities is presented here. Preliminary tests confirmed that the final results of the risk index were determined in a more precise and realistic manner.