Application of the automated statistical treatment of uncertainty method (ASTRUM) for the assessment of large break LOCA margins of AP1000 design

This presentation summarizes results from the application of a realistic (Best-Estimate) LOCA analysis performed with the Westinghouse Automated Statistical Treatment of Uncertainty Method (ASTRUM) which was recently licensed by the USNRC. The methodology relies on the order statistics for the determination of 95th percentile of Peak Clad Temperature (PCT), Local Maximum Oxidation (LMO) and Core-Wide Oxidation at a 95% confidence level. The methodology was used to assess the LOCA margins of the AP1000 design. The AP1000 is a Westinghouse advanced passive plant which recently obtained the FDA by the NRC. The original safety analysis was based generally on more conservative assumptions where the aim was to demonstrate that the AP1000 Passive Core Cooling System satisfy the 10 CFR 50.46 criteria (PCT < 2200 F degree, LMO < 17% and CWO < 1%). The application of the ASTRUM methodology provides a better quantification of the margins, relying on more realistic input assumptions. The ASTRUM methodology requires the execution of a large number of simulation (124 in this case) where the uncertainty attributes are simultaneously ranged similarly to a direct Monte Carlo Simulation. The execution of this calculation relies on an automated process which significantly streamlines the process required to assess the effect of the propagation of the several uncertainty parameters of a LOCA analysis. The work was performed in a relatively short time as part of a summer practicum at the Westinghouse Energy Center in Pittsburgh which resulted from collaboration among China National Nuclear Corporation, Westinghouse and the University of Michigan (UM). The UM is one of the most highly regarded university in US and its nuclear engineering department is consistently ranked as one of the top two or three programs by U.S. News and World Report. (author)