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Article
Assessment of Nucleation Boiling Models and Improvement by the Chen Correlation for Two-Fluid Model CFD
International Journal of Heat and Mass Transfer
  • Yu Chen Lin
  • Yang Zhao
  • Mamoru Ishii
  • Joshua P. Schlegel, Missouri University of Science and Technology
  • Kevin J. Hogan
  • John R. Buchanan
Abstract

Accurate prediction of vapor generation due to wall nucleation boiling is important in boiling heat transfer systems such as nuclear reactors. In current studies, simulations were performed using the commercial three-dimensional (3-D) Computational Fluid Dynamics (CFD) code ANSYS CFX to compare the predictive capabilities of different bubble departure diameter models and departure frequency models for subcooled boiling flow. Six diameter models and seven frequency models, a total of 42 model combinations, were compared with data from four experimental conditions. The simulation results showed a large variation between different model combinations. There was no specific frequency model or diameter model which could consistently perform the best. Also, most of the results showed smaller void fraction than the experimental data near the heated wall as well as the bulk region. To improve, the Chen correlation was used in place of the bubble departure frequency model. The results showed void fraction predictions closer to experimental data.

Department(s)
Nuclear Engineering and Radiation Science
Research Center/Lab(s)
Center for High Performance Computing Research
Keywords and Phrases
  • Bubbly Flow,
  • Chen Correlation,
  • Condensation,
  • Nucleation Boiling,
  • Subcooled Boiling,
  • Two-Fluid Model
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2021 Elsevier, All rights reserved.
Publication Date
8-1-2021
Publication Date
01 Aug 2021
Disciplines
Citation Information
Yu Chen Lin, Yang Zhao, Mamoru Ishii, Joshua P. Schlegel, et al.. "Assessment of Nucleation Boiling Models and Improvement by the Chen Correlation for Two-Fluid Model CFD" International Journal of Heat and Mass Transfer Vol. 175 (2021) ISSN: 0017-9310
Available at: http://works.bepress.com/joshua-schlegel/91/