Development of CFD based model for sodium flow boiling in narrow channel akin to SFR fuel subchannel towards high void fraction regimes

Abstract

The Sodium cooled fast reactor (SFR) is one of the Gen IV reactor type meant for the highest nuclear safety standards. Understanding of flow boiling heat transfer characteristics of liquid sodium is essential under certain postulated events of SFR. This study is intended towards the development of computational fluid dynamics (CFD) based multiphase flow model for the sodium boiling in SFR subchannel using the finite volume method. The numerical simulations have been performed for the basic two-dimensional domain that has a resemblance with the flow subchannel of SFR fuel subassembly. The sodium boiling inception, the nucleate flow boiling regime, and further the forced convective vaporization regime characteristics are numerically predicted by the Eulerian-Eulerian model (two-fluid model) developed using flow regime based modeling within the Algebraic Interfacial Area Density (AIAD) framework for the interfacial closure correlations. The improved non-equilibrium wall boiling model is implemented for wall heat flux partitioning. The liquid turbulence is modeled using a Realizable k-ε model with standard wall function. The CFD simulations are performed for the reference experimental cases of liquid sodium flow boiling in narrow annuli and a tubular channel till high void fraction regimes using the model developed. The predictions of void growth behavior along the axial and in the radial direction depict the dominance of annular flow boiling pattern as observed in sodium flow boiling experiments based on the literature. The numerical predictions for the sodium two-phase flow pressure drop are compared with the experimental results and also with the existing empirical correlations. The mechanistic model-based predictions for boiling heat transfer coefficient are obtained from the wall heat balance model and compared with the available empirical correlations. Also based on the flow parameters predicted the possible flow patterns are identified using the available flow regime maps.