A novel approach for reliability assessment of residual heat removal system for HPR1000 based on failure mode and effect analysis, fault tree analysis, and fuzzy Bayesian network methods

Abstract Residual heat removal system (RHRS) is one of the important and complicated safety systems for Hualong Pressurized Reactor 1000 (HPR1000). Therefore, it is essential to carry out the reliability assessment of the RHRS for HPR1000. In order to fill the gap of how to assess the reliability of the RHRS with uncertainty, the failure mode and effect analysis (FMEA), fault tree (FT) analysis (FTA), and fuzzy Bayesian network (BN) (FBN) methods were applied to establish a novel approach for assessing its reliability. The proposed approach included: (1) identifying the events containing failure modes, failure causes, and resulted failures for the RHRS by FMEA; (2) analyzing the deterministic logical relationship among events, and establishing the FT for the RHRS by FTA; and (3) establishing the FBN model for reliability assessment of the RHRS by FBN according to the transformation process from FT to FBN model, and modifying the conditional probability tables (CPTs) so as to express the event polymorphism and non-deterministic logical relationship between events. The applicability of the approach was validated in East China.