Extension of the CIRCE methodology to improve the Inverse Uncertainty Quantification of several combined thermal-hydraulic models

Abstract

The Inverse Uncertainty Quantification (IUQ) of physical correlations used in thermal-hydraulic system codes is a crucial issue in the BEPU (Best Estimate Plus Uncertainty) framework for the licensing and safety analyses of nuclear reactors. The CIRCE methodology is one of the most widely applied IUQ methods. It estimates the (log-)normal probability distribution of a multiplicative factor applied to the reference closure model used in thermal-hydraulic computer codes. CIRCE can jointly estimate the uncertainty of several physical models. However, in some particular cases, a problem of identifiability may occur resulting in less accuracy and precision of the estimated uncertainties.For this reason, in this work, the methodology is improved under the name of CIRCE 2-Steps. This new approach aims at improving the quantification of the model uncertainties when experiments with more than one physical phenomena interacting simultaneously on the output of interest has to be used. In a first step, the uncertainties of the least influential models are evaluated with classic CIRCE methodology using experiments for which only one physical phenomenon is dominant. Then, these uncertainties are properly taken into account when quantifying the remaining uncertainties on the experimental database. This approach is proven to provide more accurate and precise results on several analytical test cases where the uncertainties of two models has to be jointly estimated. The study of the impact of the relative importance of the two models shows that the biggest gain in precision is obtained when the hierarchy of models is such that one model is significantly more influential than the other.Finally, the newly developed methodology is applied to estimate the uncertainties of two condensation heat transfer correlations in the cold leg of a pressurised nuclear reactor.