Issue |
EPJ Web Conf.
Volume 302, 2024
Joint International Conference on Supercomputing in Nuclear Applications + Monte Carlo (SNA + MC 2024)
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|
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Article Number | 05005 | |
Number of page(s) | 10 | |
Section | Multi-Physics Simulations | |
DOI | https://doi.org/10.1051/epjconf/202430205005 | |
Published online | 15 October 2024 |
https://doi.org/10.1051/epjconf/202430205005
salome_cfd: An HPC framework for thermalhydraulics and multiphysics powered by the open-source Computational Fluid Dynamics Toolbox code_saturne
EDF R&D, Fluid Mechanics, Energy and Environment Dept., 6 quai Watier, Chatou, 78400, France
* e-mail: chai.koren@edf.fr
Published online: 15 October 2024
EDF R&D lab Chatou, Fluid Mechanics Energy and Environment department (MFEE), has been developping an HPC oriented Computational Fluid Dynamics toolbox since the late 1990s. This toolbox is based on the open-source Computational Fluid Dynamics (CFD) and multiphysics solver code_saturne. It has a proprietary extension, neptune_cfd, which is a Computational Multiphase Fluid Dynamics solver dealing with multi-phase flows. After a brief overview of code_saturne and neptune_cfd architecture and HPC capabilites, the present paper will focus on the effort made at EDF R&D to harness HPC clusters for thermalhydraulics at an industrial scale. This is made available by codes built from the start with massively-parallel architectures in mind, thus leading to highly scalable solvers which are able to handle tens of billions of cells. User-friendly access and interoperability are pivotal for engineers to take advantage of these HPC capabilities. Among common applications requiring HPC resources, a focus is first made on frontier scale simulations, then on parametric studies and uncertainty quantifications experiments, where a twolevel parallelism is needed : a parallel Design of Experiment evaluation drives computations themselves (massively) parallel.
© The Authors, published by EDP Sciences, 2024
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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