Experimental Benchmark of Computational Fluid Dynamics Models to Predict Used Nuclear Fuel Cladding Temperatures during Vacuum Drying Conditions

Abstract

Vacuum drying of a used nuclear fuel (UNF) canister, in which helium pressure is considerably reduced, is an important process the UNF undergo after it is removed from water and the canister is filled with helium. During this process, the temperature of the fuel claddings may considerably increase because it is the first time the fuel is transferred from a water cooled environment to a lower thermal conductivity helium environment while its heat generation is still relatively high. The low pressures associated with vacuum drying also contribute to the increase of temperature due to rarefaction effect. It is essential to keep the temperature of the fuel claddings below certain limits (roughly 400°C) to avoid temperature-dependent phenomena, such as corrosion and radial hydride formation, which has the potential to decrease the ductility of the claddings and make them unsafe for transportation and long-term storage.This dissertation aims to develop a computational fluid dynamics (CFD) model that can be used to predict the temperature of UNF canisters during vacuum drying process by including the effect of gas rarefaction. The CFD model is first compared to two kinetic models that solve the Boltzmann equation (Direct simulation Monte Carlo, DSMC, and Shakhov S-model) in simple geometries. The model is then validated against measurements from an experimental setup that consists of a 7×7 array of heater rods enclosed in a stainless steel square cross section pressure vessel and maintained between two spacer plates. The CFD model was able to predict the temperature of the heater rods in all rarefaction regimes.