Bayesian update of fragility curves for equipment failure probability in seismic probabilistic safety assessment in nuclear power plant

Abstract

The assessment of equipment failure probability during seismic probabilistic safety assessment (PSA) is a crucial and fundamental component in nuclear power plant seismic PSA. A Monte Carlo program must be formulated to compute the equipment failure probability and uncertainty analysis in seismic PSA. A numerical calculation method is employed for the integration calculation to obtain the conditional failure probability and the uncertainty distribution for each equipment. The fragility parameters of the equipment and the hazard data of the plant site serve as the input parameters for the failure probability of equipment in seismic PSA. In this study, the probability of occurrence of the minimal cut set in equipment failure under earthquake conditions is calculated using the Monte Carlo sampling method, and the uncertainty distribution for each peak ground acceleration interval is presented. Furthermore, we have updated the fragility parameters of the equipment through the utilization of the Bayesian approach. Based on the updated fragility curves, we have recalculated the failure probability of the equipment and compared it with the results before the update.