E3S Web Conf.
Volume 321, 2021XIII International Conference on Computational Heat, Mass and Momentum Transfer (ICCHMT 2021)
|Number of page(s)||8|
|Published online||11 November 2021|
Numerical Prediction of Two-Phase Flow in Tube Bundles with a CFD Porous Media Approach Based on Mixture Model and a Void Fraction Correlation
Naval Group Nantes-Indret, Rue du Bac, 44620 La Montagne, France
2 LaSIE, UMR-7356-CNRS, La Rochelle Université, Avenue Michel Crépeau, 17042 La Rochelle, France
* Corresponding author: email@example.com
Being able to predict the void fraction is essential for a numerical prediction of the thermohydraulic behaviour in steam generators. Indeed, it determines two-phase mixture density and affects two-phase mixture velocity which enable to evaluate the pressure drop of heat exchanger, the mass transfer and heat transfer coefficients. In this study, the flow is modelled by coupling Ansys Fluent with an in-house code library where a CFD porous media approach is implemented. In this code, the two-phase flow has been modelled so far using the Eulerian model. However, this two-phase model requires interaction laws between phases which are not known and/or reliable for a flow within a tube bundle. The aim of this paper is to use the mixture model, for which it is easier to implement suitable correlations for tube bundles. By expressing the relative velocity, as a function of slip, the void fraction model of Feenstra et al. developed for upward cross-flow through horizontal tube bundles is introduced. With this method, physical phenomena that occur in tube bundles are taken into consideration in the mixture model. The developed approach is validated based on the experimental results obtained by Dowlati et al.
Key words: Steam generator / Void fraction / Mixture Model / Porous media approach
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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