Development of a general purpose subgrid wall boiling model from improved physical understanding for use in computational fluid dynamics

Abstract

Advanced modeling capabilities were developed for application to subcooled flow boiling through this work. The target was to introduce, and demonstrate, all necessary mechanisms required to accurately predict the temperature and heat flux for subcooled flow boiling in CFD simulations. The model was developed using an experimentally based mechanistic approach, where the goal was to accurately capture all physical phenomena that affect heat transfer and occur at the heated surface to correctly predict surface temperatures. The proposed model adopts a similar approach to the classical heat partitioning method, but captures additional boiling physical phenomena. It introduces a new evaporation term, to truly capture the evaporation occurring on the surface while also tracking the bubble crowding effect on the boiling surface. This includes evaporation from the initial bubble inception and evaporation through the bubble microlayer. The convection term is modified to account for increased surface roughness caused by the presence of the bubbles on the heated surface. The quenching term accounts for bringing the bubble dry spot back to the wall superheat prior to bubble inception. In addition to the changes to these three classic components, a sliding conduction term is added to capture the increased heat transfer due to bubble sliding on the heated surface prior to lift-off. The sliding conduction component includes all heat removal associated with transient conduction caused by disruption of the thermal boundary layer. The new method extends the generality and applicability of boiling models in CFD through a fully mechanistic representation. The new model also tracks the dry surface area during boiling for possible application in DNB predictions. A statistical tracking method for bubble location on the heated surface provides information on the bubble merging probability and prevents the active nucleation site density from reaching un-physical values. The model was implemented in the CFD software STAR-CCM+, and the wall temperature predictions were recorded and compared against the standard model's predictions and experimental data for a range of mass fluxes, heat fluxes, inlet subcoolings, and pressures. In general, the new model predicts wall temperatures closer to experimental data for both low and high pressures when compared against the standard model. The new model also converges at higher heat fluxes and greater subcoolings than the standard model.