Case Study on the Performance of Bayesian and Frequentist Statistical Approaches for Criticality Safety Evaluations with Used Nuclear Fuel

In this study, a comparison is presented between two distinct approaches for interpreting validation results for light water reactor (LWR) fuel criticality safety assessments: one based on frequentist tolerance limits and the other on a Bayesian framework. In general, both the frequentist statistical methods and Bayesian models have inherent advantages and disadvantages, making it valuable to compare the results of the criticality safety evaluations (CSEs) obtained using both approaches. Of particular interest in this context is the application of CSE in conjunction with the burnup credit concept for LWR used nuclear fuel (UNF), whose composition differs significantly from that of fresh fuel, which is primarily used in validation studies worldwide.