Computationally efficient Complete-Sampling-based fault tree analyses for seismic probabilistic safety assessment of nuclear facilities

The seismic risk of nuclear power plants (NPPs) can be assessed through seismic probabilistic safety assessment (PSA) based on fault tree analyses (FT). The conventional FT-based approach has limitations for handling the correlated relation of basic events and utilizing the sampling-based FT analysis for addressing such issues demands considerable computational cost. In particular, accurate consideration of the partial dependences between the failure probabilities of NPP components in seismic hazard events can further increase the computational cost of risk quantification. Therefore, this paper presents an improved complete-sampling-based seismic PSA risk quantification method. The novelty of this method is that it increases the efficiency of the risk quantification by introducing sequential sampling and truncation to the conventional fault tree analysis. In addition, as sub-concepts, we eliminate unrequired sampling extraction steps via integrated multivariate response distribution-based sampling for components and continual evaluation of the convergence of system failure probabilities. On three considered examples, including an actual NPP, the proposed method requires 91%–96% fewer samples than the conventional method, without sacrificing accuracy. These results indicate the efficiency of the proposed method, which is expected to become a useful tool in the future.