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Article
Effect of Two-Group Void Fraction Covariance Correlations on Interfacial Drag Predictions for Two-Fluid Model Calculations in Large Diameter Pipes
Experimental and Computational Multiphase Flow
  • Alexander Swearingen
  • Sean Drewry
  • Joshua P. Schlegel, Missouri University of Science and Technology
  • Takashi Hibiki
Abstract

Void fraction covariance has been introduced into the interfacial drag calculation used to close the one-dimensional two-fluid model. A model for void fraction covariance has been developed for large diameter pipes. The newly developed model has been compared with two previously developed models in terms of void fraction prediction accuracy. The effects of these additions on the void fraction prediction uncertainty have been evaluated utilizing a computational tool developed in MATLAB. The results indicate that there are small differences in the void fraction prediction between the models evaluated and the two-fluid model without void fraction covariance. Higher void fractions above 0.7 show the most significant changes. However, the differences in the uncertainty are not significant when compared to the uncertainty in the data used for the comparison. The results highlight a need for additional data for higher void fractions, collected with steam-water systems in large diameter pipes.

Department(s)
Nuclear Engineering and Radiation Science
Keywords and Phrases
  • Interfacial Area Transport,
  • Large Diameter Pipe,
  • Numerical Solution,
  • Two-Fluid Model,
  • Void Fraction Covariance
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2023 Springer, All rights reserved.
Publication Date
6-1-2023
Publication Date
01 Jun 2023
Disciplines
Citation Information
Alexander Swearingen, Sean Drewry, Joshua P. Schlegel and Takashi Hibiki. "Effect of Two-Group Void Fraction Covariance Correlations on Interfacial Drag Predictions for Two-Fluid Model Calculations in Large Diameter Pipes" Experimental and Computational Multiphase Flow Vol. 5 Iss. 2 (2023) p. 221 - 231 ISSN: 2661-8877; 2661-8869
Available at: http://works.bepress.com/joshua-schlegel/99/