Common cause failure model updating (both qualitatively and quantitatively) is a key factor in risk monitoring for nuclear power plants when configuration changes (e.g. components become unavailable) occur among a redundant configuration. This research focuses on the common cause failure updating based on the alpha factor model method, which is commonly used in the living probabilistic safety assessment models for nuclear power plant risk monitoring. This article first discusses the common cause failure model updating in an ideal condition, which evaluates the common cause failure model parameters for the configurationally changed system in different ways, based on the causes of the detected failures. Then, two alternative updating processes are proposed considering the difficulty to identify failure causes immediately during plant operation: one is to update the common cause failure models with the assumption that the failures detected are independent failures and the other is to update the common cause failure models with the parameters as expectations of the values for all possible failure causes. Finally, a case study is given to illustrate the common cause failure updating process and to compare these two alternative processes. The results show that (1) common cause failures can be reevaluated automatically by the methods proposed in this article and (2) the second process is more conservative and reasonable but with more data requirements compared with the first approach. Considering limitations in accessibility of the data, the first strategy is suggested currently. More future work on data acquisition is demanded for better assessment of common cause failures during nuclear power plant risk monitoring.
Feasibility Study of Developing Alternative Common-Cause Failure Model for Event Assessment
