Mathematical model of the QUENCH-06 experiment with sensitivity and uncertainty analysis in hydrogen generation

During the cooling of the reactor core, as a result of a severe accident, a strongly exothermic oxidation reaction of the zirconium cladding occurs and leads to hydrogen production, this has been observed in Fukushima, Chernobyl and Three Mile Island accidents. Several experiments have been carried out for the understanding of the phenomena that are involved in a severe accident and of the adequate mathematical modeling of the behavior of these scenarios. The objective of this work is to develop a reduced model of low computational cost that simulates the cooling phenomenon considering the heat transfer for the fuel rods, the thermohydraulic phenomena in the coolant, and the hydrogen generation focus on the QUENCH-06 experiment, where the purpose of this experiment is to investigate the cooling process of fuel rods in a severe accident scenario in a light-water nuclear reactor. The reduced model is solved numerically. It is implemented in a C++ compiler and it is validated with the data of the experiment, obtaining a deviation in the integral hydrogen generation of -4.7%. Subsequently, a sensitivity and uncertainty analysis is carried out to determine the parameters involved with greater relevance in the integral hydrogen generation. The results show that the variables with the greatest impact on hydrogen generation are: the variation of the steam flow, the convective heat transfer coefficient, and the inlet temperature of steam and argon, the latter with the largest value of the Pearson's correlation coefficient. (C) 2022 Elsevier Ltd. All rights reserved.

Automated summary

This study investigates the cooling process during a severe accident in a nuclear reactor core. A reduced model with low computational cost is developed and numerically solved. The model considers heat transfer in fuel rods, thermohydraulic phenomena in the coolant, and hydrogen generation. The model is validated using experimental data and sensitivity analysis is performed to determine the parameters with the greatest impact on hydrogen generation.