3-D computational investigation and experimental validation of effect of shear-lift on two-phase flow and heat transfer characteristics of highly subcooled flow boiling in vertical upflow

• Published in: International journal of heat and mass transfer 2020-04, Vol.150, p.119291, Article 119291
• Main Authors: Lee, Jeongmin, O'Neill, Lucas E., Mudawar, Issam
• Format: Article
• Language: English
• Subjects: Boiling; CFD; Heat transfer; Heat transfer coefficients; Multiphase flow; Shear-lift force; Subcooled flow boiling; Temperature profiles; Two phase flow; Wall temperature
• ISSN: 0017-9310; 1879-2189
• DOI: 10.1016/j.ijheatmasstransfer.2019.119291

•A 3-D computational model is constructed to predict interfacial behavior in subcooled flow boiling.•The model incorporates the important influence of shear-lift force on bubbles.•The model is used to predict detailed interfacial behavior as well as key flow and heat transfer parameters.•Good accuracy is achieved against data for FC-72 at four operating conditions. The present study is focused on development of a 3-D computational approach to predict highly subcooled nucleate flow boiling in vertical upflow. Investigation of existing computational methodology based on Volume of Fluid (VOF) approach revealed fundamental weaknesses in modeling multiphase flows, which stems mostly from inadequate representation of shear-lift force on bubbles. A user defined function is adopted which provides detailed information relating to this important effect, and computed results are validated through comparison with experimental results and analytic predictions of single bubble trajectory. The computational method is then used to model the entire flow field for subcooled flow boiling in a rectangular channel heated on two opposite walls, and predictions are validated against FC-72 experimental data for four different mass velocities. Overall, computationally predicted interfacial behavior, flow pattern, and heat transfer parameters (wall temperature and heat transfer coefficient) show good agreement with experimental data. The model is also shown highly effective at predicting local phenomena (velocity and temperature profiles) not easily determined through experiments.