Validation and uncertainty quantification for FEBA, FLECHT–SEASET, and PERICLES tests incorporating multi-scaling effects

Abstract This paper presents model parameter estimation conducted by data assimilation and associated uncertainty quantification for predictive engineering with specific application to reflood phenomena in PWR rod bundles. The uncertainties in the prediction of engineering systems are known to be originated from various non-input parameters, e.g., numerics, scaling effects, etc., as well as modeling parameters such as initial and boundary conditions, and physical models. Since the physical models are usually developed by small scale experiments and the experiments used for validation and uncertainty evaluation may not cover the real plant scale, the up-scaling capabilities of a best-estimate safety analysis code must be evaluated. The objective of this work is thus first of all, to refine the model parameters based on the Bayes’ theorem and subsequently estimate the uncertainties on parameters/responses during reflood phase. To illustrate this, reflood experiment data were collected and utilized to complete model calibration for the thermal–hydraulic parameters. The second goal of this study is to suggest optimum parameter distributions for the simulation of the multiple reflood tests performed at different facilities with different scales and dimensions. Since existing experimental data and physical models/correlations were produced from several tests performed at the small scale with limited initial and boundary conditions, scaling considerations must be addressed when simulating larger scale tests for the uncertainty analysis. Blind calculations were carried out to observe whether the a posteriori parameter samples obtained via the model calibration against a basis test, i.e., a small scale test, which was performed by compensating the scaling distortions properly simulate scaled up tests. Simulations were performed using Safety and Performance Analysis Code (SPACE) developed by multiple research institutes in Republic of Korea to predict the thermal hydraulic system behaviors of nuclear power plants.