Predictive modeling of liquid-sodium thermal-hydraulics experiments and computations

This work applies the predictive modeling procedure formulated by Cacuci and Ionescu-Bujor (2010) to assimilate data from liquid-sodium thermal-hydraulics experiments in order to reduce systematically the uncertainties in the predictions of computational fluid dynamics (CFD) simulations. The predicted CFD-results for the best-estimate model parameters and results describing sodium-flow velocities and temperature distributions are shown to be significantly more precise than the original computations and experiments, in that the predicted uncertainties for the best-estimate results and model parameters are significantly smaller than both the originally computed and the experimental uncertainties.