Evaluating Code Uncertainty–II: An Optimal Statistical Estimator Method to Evaluate the Uncertainties of Calculated Time Trends

Abstract

When best-estimate calculations are performed, uncertainty needs to be quantified. An optimal statistical estimator (OSE) algorithm is adapted, extended, and used for response surface generation to demonstrate the algorithm’s applicability to evaluating uncertainties in single-value or time-dependent parameters. A small-break loss-of-coolant accident with the break in the cold leg of a two-loop pressurized water reactor is selected for analysis. The code scaling, applicability, and uncertainty (CSAU) method was used for uncertainty quantification. The uncertainty was quantified for the RELAP5/MOD3.2 thermal-hydraulic computer code.The study shows that an OSE can be efficiently used instead of regression analysis for response surface generation. With the OSE, optimal information obtained from the code calculation is used for response surface generation. This finding indicates that by increasing the number of code calculations, one increases the confidence level of the uncertainty bounds. Increasing the number of calculations also results in convergence of the peak cladding temperature. As uncertainty can be evaluated for time-dependent parameters, the OSE tool makes the CSAU method universal for evaluating uncertainties of transients other than those of a loss-of-coolant accident.