| Issue |
EPJ Nuclear Sci. Technol.
Volume 12, 2026
|
|
|---|---|---|
| Article Number | 8 | |
| Number of page(s) | 16 | |
| DOI | https://doi.org/10.1051/epjn/2025079 | |
| Published online | 04 March 2026 | |
https://doi.org/10.1051/epjn/2025079
Regular Article
Extension of the turbulent heat flux modelling in OpenFOAM for improved simulation of liquid metal flows
Gesellschaft für Anlagen- und Reaktorsicherheit (GRS) gGmbH, Boltzmannstr. 14, 85748 Garching, Germany
* e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
Received:
5
August
2025
Received in final form:
5
December
2025
Accepted:
9
December
2025
Published online: 4 March 2026
Abstract
Turbulent heat transfer is a fundamentally complex physical process that has challenged turbulence modellers for many years. A full differential second-moment closure model provides a solid foundation for the derivation of the simpler Algebraic Heat Flux Model (AHFM), which retains the primary production terms that represent the underlying physical mechanisms driving the turbulent heat flux. This allows for accurate modelling of natural and mixed convection flows, which becomes particularly evident in advanced nuclear reactor applications with low Prandtl number coolants. In the present work, an AHFM model was implemented in the open-source code OpenFOAM, and was first verified using a simple channel test case. In the next step, the implementation was validated against Direct Numerical Simulation (DNS) data of a Rayleigh–Bénard convection case. The latter was based on simple geometry with natural convection of a low-Prandtl-number fluid, being of particular importance for Generation IV reactors using liquid metal coolants. The comparison of the generated numerical results with DNS data demonstrated the improvements in the prediction of turbulent heat flux in low-Prandtl number fluids with the new model.
© H. Mistry et al., Published by EDP Sciences, 2026
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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