Estimation of reactor protection system software failure probability considering undetected faults

Abstract

Over the years, the probabilistic safety assessment (PSA) of digital reactor protection systems (RPSs) has been a field of research because of the ambiguity over the mechanism of the software failure and quantification of the failure probability. Currently, the software failure probability in the PSA of a nuclear power plant (NPP) is determined mostly based on expert elicitation. Although a number of software reliability assessment methods are available, none of them appears to be compatible to assess the failure probability of safety grade software in an NPP. Quantification of the software reliability becomes challenging, especially when the software reveals no test failures. This paper proposes an integrated approach for an estimation of the probability of failure on demand of safety critical software considering its undetected residual faults. In the proposed approach, the software reliability can be quantified by incorporating the BBN modeling approach, test results, and operational experiences. A case study is also presented by employing the proposed method. The proposed approach is expected to be helpful for a probabilistic safety analysis of a digital I&C system.