A Mutual Information–Based Experimental Design Framework to Use High-Fidelity Nuclear Reactor Codes to Calibrate Low-Fidelity Codes

AbstractSimulation-based nuclear reactor design requires highly efficient codes that quantify the requisite physics while having the efficiency required for optimization-based design and uncertainty quantification. To achieve the required accuracy and predictive capabilities, phenomenological parameters, often employed in closure relations or to quantify unmodeled or unresolved physics, must be calibrated for considered reactor conditions and designs. When available, experimental data with quantified observation errors are ideally employed for calibration. However, for many thermal-hydraulic, fuel, and Chalk River Unidentified Deposits modeling regimes, experimental data are prohibitively expensive or impossible to collect. For such cases, we demonstrate the use of a mutual information–based experimental design framework to employ validated high-fidelity codes to calibrate parameters in low-fidelity design codes. We demonstrate the use of the high-fidelity computational fluid dynamics package STAR-CCM+ to...