An uncertainty analysis for the plant-specfic reliability data application

In spite of the current general trends of reliability data analysis using Bayesian techniques, which have been applied in most Korean PSAs, it is also necessary to apply the plant-specific data alone in risk-informed applications, because it can give more plant-specific insights. Considering the application of effective plant-specific data evidence, we developed the simulation methods for uncertainty propagation. With the separation of two uncertainty categories of both lack of knowledge and stochastic features, we can propagate the parameter uncertainty using Monte Carlo simulation technique. From the example application for the consideration on the arbitrary plant-specific input parameters, it shows that more broad uncertainty bounds can be developed than the case of generic input parameters