Physics-guided Covered Mapping: a new approach for quantifying experimental coverage and bias scaling

This summary deals with a fundamental question in any reactor model validation practice: given a body of available experiments, and an envisaged domain of reactor operating conditions (referred to as reactor application), can one develop a quantitative measure that measures the portion of the prior uncertainties of the reactor application that is covered by the available experiments? Coverage here means that the uncertainties of the reactor application are originating from and behaving in exactly the same way as those observed at the experimental conditions. This approach is valuable as it provides a scientifically defendable criterion by which experimentally measured biases can be credibly extrapolated (i.e., mapped or scaled) to biases for the reactor applications. Our proposed approach is referred to as physics-guided coverage mapping (PCM), and in this introductory summary, we will demonstrate its application to fission reactors criticality safety applications. Potential advantages of PCM over the methods of similarity (representativity), data adjustments (also known as data assimilation or model calibration) commonly employed in the nuclear community will be briefly discussed.