Assessment of wall heat flux partitioning model for two-phase CFD

Abstract

The Eulerian-Eulerian two-phase flow (EETF) model coupled with the Wall Heat Flux Partitioning (WHFP) model is slowly becoming an effective tool for two-phase hydrothermal analysis in nuclear applications, with prediction accuracy highly dependent on sub-models for three bubble parameters, namely nucleation site density (N), bubble departure diameter (Dw) and bubble departure frequency (f). In this study, the preformance of different sub-models combinations is evaluated under a wide range of conditions, especially focusing on the prediction of void fraction. The four most commonly used or investigator-recommended combinations are identified by a literature review. A large database of flow boiling experiments covering 52 sets of experiments is developed for the assessment, rather than the popular case-by-case adjustment for a limited number of experiments. One of the combinations is distinguished to be the optimal combination, with an overall 44.2% mean absolute error (MAE). A nearly fixed relationship between void fraction and steam quality is predicted by this combination. It suggests that there is an ‘optimal’ range of operating conditions for which the combination can accurately predict the results. Based on the current assessment, for water, this range is between 17 and 97 K for subcooling and a mass flux larger than 770 kg/(m2s). However, the prediction of bubble diameter and gas velocity are not accurate, since the Kurul and Podowski model simply assumes the bubble diameter as the function of liquid temperature. Models considering bubble coalescence and breakup are desired to predict the bubble diameter and gas velocity more accurately. It is also shown that the performance of combinations, which are genreally considered to be applicable to a broader range, is not satisfactory. Experimental measurements of bubble departure diameter and nucleation site density under a wider range of conditions are desired to evaluate those sub-models.