Passive system reliability assessment based on an adaptive surrogate model
Passive design is adopted by many advanced reactors to enhance safety,and reliability assessment is im-portant for its wide application.A passive safety system is more susceptible to uncertainties because its work de-pends on physical laws such as natural circulation.Thermal hydraulics process failure is the main contribution to passive system failure;however,traditional methods such as fault tree analysis are unavailable for analyzing this type of failure possibility.In this study,a surrogate model is trained with thermal-hydraulic simulation results.Fur-thermore,the adaptive sampling strategy is applied to effectively reduce the call times of the thermal hydraulics pro-gram.The algorithm is validated using a highly nonlinear test function and then applied to a passive residual heat removal system of an integral-type pressurized water reactor.The calculation results indicate that the adaptive Krig-ing model has higher computational efficiency than traditional Monte Carlo and Kriging model methods.
passive safety systemreliabilitysurrogate modelprobabilistic safety analysisintegral pressurized water reactorRELAP5adaptive sampling