4.7 Article

A phase-field method for boiling heat transfer

期刊

JOURNAL OF COMPUTATIONAL PHYSICS
卷 435, 期 -, 页码 -

出版社

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.jcp.2021.110239

关键词

Boiling heat transfer; Phase field method; Velocity correction scheme; Entropy viscosity method

资金

  1. ESRDC ONR project
  2. Department of Energy PhILMs project [DESC001954]

向作者/读者索取更多资源

A phase field method for heat transfer in two-phase flow with boiling is proposed, modeling the vapor/liquid interface evolution and using velocity correction schemes. The method predicts the growth of vapor bubbles in different scenarios with good agreement with experimental measurements and available simulation results, showing comparable mesh resolution to other methods like VoF and level-set.
We present a phase field method for heat transfer in two-phase flow with boiling. The vapor/liquid interface evolution is modeled by the Cahn-Hilliard equation. The phase change rate is determined by accounting for the heat conduction balance on either vapor or liquid side of the interfacial area, depending on which side the temperature is assumed to be maintained at the saturation temperature during boiling. The velocity correction scheme proposed by Dong & Shen [27] is extended to solve the Navier-Stokes equations for a non solenoidal velocity field, and the entropy viscosity method is employed for stabilization. The phase change model is verified by two-dimensional simulations of a vapor bubble growing in super-heated liquid and in film boiling. In both cases, mesh independence of the results is systematically performed. Subsequently, the method is applied to predict the growth of three-dimensional vapor bubble in a rectangular microchannel with boiling flow, achieving good agreement with experimental measurements and available simulation results using the level-set method. The numerical experiments demonstrate that the required mesh resolution for the phase field method is comparable with that of volume of fluid (VoF) and level-set methods. (C) 2021 Elsevier Inc. All rights reserved.

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