A Study on Quantitative Assessment of Design Specification of Reactor Protection System Software Using Bayesian Belief Networks

This report propose a method that can produce quantitative reliability of safety-critical software for PSA by making use of Bayesian Belief Networks (BBN). BBN has generally been used to model the uncertain system in many research fields. The proposed method was constructed by utilizing BBN that can combine the qualitative and the quantitative evidence relevant to the reliability of safety-critical software, and then can infer a conclusion in a formal and a quantitative way. A case study was also carried out with the proposed method to assess the quality of software design specification of safety-critical software that will be embedded in reactor protection system. The V and V results of the software were used as inputs for the BBN model. The calculation results of the BBN model showed that its conclusion is mostly equivalent to those of the V and V expert for a given input data set. The method and the results of the case study will be utilized in PSA of NPP. The method also can support the V and V expert's decision making process in controlling further V and V activities