Overcoming the uncertainty in a research reactor LOCA in level-1 PSA; Fuzzy based fault-tree/event-tree analysis

Abstract

Probabilistic safety assessment (PSA) which plays a crucial role in risk evaluation is a quantitative approach intended to demonstrate how a nuclear reactor meets the safety margins as part of the licensing process. Despite PSA merits, some shortcomings associated with the final results exist. Conventional PSA uses crisp values to represent the failure probabilities of basic events. This causes a high level of uncertainty due to the inherent imprecision and vagueness of failure input data. In this paper, to tackle this imperfection, a fuzzy approach is employed with fault tree analysis and event tree analysis. Thus, instead of using the crisp values, a set of fuzzy numbers is applied as failure probabilities of basic events. Hence, in the fault tree and event tree analysis, the top events and the end-states frequencies are treated as fuzzy numbers. By introducing some fuzzy importance measures the critical components which contribute maximum to the system failure and total uncertainty are identified. As a practical example, under redesign Iranian heavy water research reactor loss of coolant accident is studied. The results show that the reactor protection system has the largest index in sequences lead to a core meltdown. In addition, the emergency core cooling system has a main role in preventing abnormal conditions.