Predictive uncertainty reduction in coupled neutron-kinetics/thermal hydraulics modeling of the BWR-TT2 benchmark

By applying a comprehensive predictive modeling methodology, this work demonstrates a substantial (up to 50%) reduction of uncertainties in the predicted total transient power in the BWR Turbine Trip 2 (BWR-TT2) benchmark while calibrating the numerical simulation of this benchmark, comprising 6090 macroscopic cross sections, and 570 thermal-hydraulics parameters involved in modeling the phase-slip correlation, transient outlet pressure, and total mass flow. The BWR-TT2 benchmark is based on an experiment that was carried out in 1977 in the NPP Peach Bottom 2, involving the closure of the turbine stop valve which caused a pressure wave that propagated with attenuation into the reactor core. The condensation of the steam in the reactor core caused by the pressure increase led to a positive reactivity insertion. The subsequent rise of power was limited by the feedback and the insertion of the control rods. The BWR-TT2 benchmark was modeled with the three-dimensional reactor physics code system DYN3D, by coupling neutron kinetics with two-phase thermal-hydraulics. All 6660 DYN3D model parameters were calibrated by applying a predictive modeling methodology that combines experimental and computational information to produce optimally predicted best-estimate results with reduced predicted uncertainties. Simultaneously, the predictive modeling methodology yields optimally predicted values for the BWR total transient power while reducing significantly the accompanying predicted standard deviations.