Predictive capability and maturity assessment with Bayesian network

The past few decades have witnessed a rapid growth in computer power and increasing emphasis on the development of high-fidelity modeling and simulation (M&S) tools. In nuclear engineering, M&S tools, also known as evaluation model, are widely applied to the accident and transient analysis. Validation methodologies, that are able to measure the credibility of a computer model, are in high demand by both regulatory and industrial departments. Predictive Capability Maturity Quantification (PCMQ) is a new methodology that aims to formalize the validation as an argument, which is further quantified as a decision-making process. In addition, PCMQ is combined with the theory of value of information. By calculating the expected value of sample information (EVSI), suggestions are made for the design of new validation experiments or models. This study aims to demonstrate the application of PCMQ in validating the evaluation model. The credibility of selected models, including landscape overflow and core flow pressure loss model, is assessed with PCMQ methodology. Based on the concept of validation data plan, suggestions are also made for the design of new landscape overflow model and the design of new core-flow-pressure-loss experiment.