An Approach for the Dynamic Reliability Assessment of the Digital Power Control System for Nuclear Reactor

Abstract

The digital power control system for nuclear reactor (DPCSNR) for a nuclear power plant has dynamic characteristics including dynamic interaction, time dependence, and causal relationship uncertainty, and it is of great significance to assess its dynamic reliability. This study aimed to propose an approach for the dynamic reliability assessment of the DPCSNR with dynamic characteristics. First, the dynamic fault tree analysis (DFTA) method was used to establish a DFT characterizing the dynamic interaction for the DPCSNR. Then, the dynamic Bayesian network (DBN) method was used to transform the DFT into the initial DBN (IDBN) model characterizing the dynamic interaction and time dependence for the DPCSNR. Furthermore, the fuzzy mathematics (FM) method was used to modify the conditional probability table (CPT) characterizing the causal relationship uncertainty in the IDBN model and to establish the DBN model characterizing the dynamic interaction, time dependence, and causal relationship uncertainty for the DPCSNR. Finally, DBN reasoning was applied to assess the dynamic reliability of the DPCSNR. The results showed that the system reliability under conditions of periodic tests and predictable maintenance was 99.959%, and the computer system was the most critical event of the DPCSNR failure.