Research on fuel-coolant interaction by using a multi-phase multi-component Code

Cao, X.

Fuel Coolant Interactions (FCls) are the important phenomena during the Core Disruptive Accidents (CDAs) in Liquid Metal Cooled Fast Breader Reactors (LMFBRs) or Core Melt Accidents (CMAs) in Light Water Reactors (LWRs) and have been numerically investigated in recent years. The development and verification of models for the fundamental processes in FCIs are required for the application of a multi-phase, multi-component, fluid-dynamics computer code. In this study the drag coefficient model and the thermal fragmentation models for melt droplets are developed and verified through the application of SIMMER-III code, which is being developed at JNC, to the experiments, QUEOS, MIXA and KROTOS. The FCI phenomena are characterized by a configuration that hot particles/droplets surrounded with vapor film moves in coolant liquid. The correlation of drag coefficient has not been developed for such a configuration. In this study, based on the basic conservative equations and the mixture viscosity concept, the drag coefficients between melt droplets with vapor film and the surrounding coolant liquid under laminar and turbulent flow conditions are developed, which are expressed as functions of Reynolds number, vapor/liquid viscosity and density ratios and the other two dimensionless numbers newly introduced in this study. The proposed correlations are coupled into the SIMMER-III code and applied to simulate the QUEOS experiment. The results show that the proposed correlations reasonably improve the agreement of the calculated results with the experimental data. Thermal fragmentation mechanisms have been studied for many years, but the fragmentation models, triggered by boiling effect and surface solidificatjon effect, are not available for numerical simulation tools. In this study, based on the Taylor instability, the fragmentation models, triggered by surface solidification and vapor film collapse are developed and simplified non-dimensional correlations are ...