Reducing Uncertainties via Predictive Modeling: FLICA4 Calibration Using BFBT Benchmarks

This work applies the predictive modeling procedure formulated by Cacuci and Ionescu-Bujor [Nucl. Sci. Eng., Vol. 165, p. 18 (2010)] to assimilate experimental data from the international Organisation for Economic Co-operation and Development/U.S. Nuclear Regulatory Commission boiling water reactor full-size fine-mesh bundle test (BFBT) benchmarks to calibrate and reduce systematically and significantly the uncertainties in the predictions of the light water reactor thermal-hydraulic code FLICA4. The BFBT benchmarks were designed by the Nuclear Power Engineering Corporation of Japan for enabling systematic validation of thermal-hydraulic codes by using full-scale experimental data. This work specifically uses BFBT experimental data for the “pump trip for a high-burnup assembly” in the predictive modeling formalism to calibrate parameters and time-dependent boundary conditions (power, mass flow rates, and outlet pressure distributions) in FLICA4, yielding best-estimate predictions of axial void fraction distributions. The resulting uncertainties for the best-estimate time-dependent model parameters and void fraction response distributions are shown to be smaller than the a priori experimental and computed uncertainties, thus demonstrating the successful use of predictive modeling for the large-scale reactor analysis code FLICA4 using BFBT benchmark-grade experiments.