Best-practice severe accident uncertainty and sensitivity analysis for a short-term SBO sequence of a reference PWR using MAAP5

The integrated severe accident codes like MELCOR and MAAP5 include numerous uncertain models and parameters representing a wide range of physico-chemical phenomena for a comprehensive plant simulation, consequently making relevant uncertainty analysis a non-trivial task. In this paper, best-practice uncertainty and sensitivity analysis was performed to statistically quantify uncertainties associated with the analysis results of interest and identify potentially important uncertain parameters, based on the key modeling parameters employed in MAAP5. Three reference scenarios related to a short-term station blackout (STSBO) accident of a reference pressurized water reactor (PWR: OPR1000), were considered for the purpose: one base scenario and two mitigation scenarios to investigate the impact of dedicated severe accident mitigation (SAM) actions on the results of interest. A series of uncertainty and sensitivity analyses were carried out for these model parameters. Uncertainties for the results of interest were quantified through a random set of the Monte Carlo samples per case scenario, with values statistically sampled from the probability distributions of the individual model parameters. In addition, the relative importance of these model parameters to each relevant analysis result was then quantitatively evaluated through the sensitivity and importance analysis. Analysis results and relevant insights are summarized in terms of particular points of interest.

Automated summary

This study quantifies uncertainties and identifies key parameters in integrated severe accident codes using best-practice uncertainty and sensitivity analysis. It investigates the impact of severe accident mitigation actions on the analysis results through scenario analysis. The results provide insights into the importance of model parameters and the effectiveness of mitigation measures.