An advanced probability safety margin analysis approach combined deterministic and probabilistic safety assessment

Abstract The conventional deterministic safety margin lacks the capability for real safety margin estimation in nuclear power plants (NPPs). To improve the accuracy of safety margin analysis, the risk-informed safety margin characterization (RISMC) approach has been proposed to capture the real safety margin in NPPs. However, existing literature lacks detailed application of the RISMC approach to improving the efficiency of safety margin analysis. To solve this problem, an advanced probability safety margin (APSM) analysis approach is proposed to improve safety margin analysis efficiency. The proposed APSM combines, the best estimate plus uncertainty (BEPU) analysis approach and the probability safety assessment (PSA) approach to screen key sequences. To reduce the number of calculation samples of Monte Carlo approach, the small sample estimation method is used to obtain the conditional exceedance probability (CEP). The proposed approach is subsequently used to estimate the reactor core damage frequency (CDF) of a 900 MW pressurized water reactor (PWR) under a small break lack of coolant accident, and for two reactor power levels. Evaluation results show that the proposed APSM analysis approach efficiently and accurately quantifies the core damage frequency under different reactor statuses. Moreover, the total number of calculation sequences is reduced from 64 to 8 and the total number of iterations is reduced from 8,320 to 520. In addition, the proposed APSM approach is compared with the PSA-only approach under 105% power condition. The comparison result shows that, the CDF obtained by APSM is 41% lower than that of the PSA. Moreover, for the APSM, the core damage frequency increased by 152.98% with core power uprates at 5%.