Parametric MELCOR 2.2 sensitivity and uncertainty study with a focus on aerosols based on Phébus test FPT1

The Phébus test FPT-1 was carried out to investigate the fission product release, transportation, and distribution in the reactor coolant system and the simulated containment during a severe accident. The test was divided into three phases: the core degradation, aerosol transport, and containment phenomena. In this work, a parametric sensitivity and uncertainty analysis of the two first phases, i.e., core degradation and aerosol transport, is conducted with the focus on aerosol parameters. The study was done in a frame of WP4 of the European MUSA project whose main objective is to develop a methodology for severe accident uncertainty analysis. Due to the wide scope of the MUSA project, this study focuses not only on the UQ analysis but also on the parametric dependency and data interpretation. The main subject was investigating the uncertainty of the MELCOR 2.2 aerosol models and the relation between the chosen parameters as well as evaluating the usability of essential analytical tools available for such analyses. The calculations were carried out using the integral severe accident code MELCOR2.2 and the generic input deck of the FPT-1 experiment. The uncertainty quantification tool DAKOTA was used as a statistical tool. It was coupled with MELCOR within the SNAP environment. Fifteen uncertain parameters related with the aerosol release and transport were investigated. Two figures of merit were chosen to be the amount of deposition of Cs in the reactor coolant circuit, and the mass of air-borne aerosol in the containment. Preliminary analysis showed a significant correlation between the aerosol dynamic and agglomeration shape factors, density and minimum aerosol diameter with both FOMs. In addition to the standard uncertainty analysis, five MELCOR/DAKOTA UQ sensitivity calculations with modified parameters were performed and analyzed. Additionally, the impact of the parameters was investigated by excluding the most correlated ones from the analysis. The results confirm the strong correlation of shape factors and the importance of their ranges for overall UQ results. The authors show that by coupling the chosen analytical tools together, it is possible to carry out uncertainty quantification of severe accident analysis. Based on the study performed, the authors underline the need for further investigation of parameter distributions, the effect of the chosen number of samples on the results, and a global time-dependent UQ analysis.