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Adaptive Mesh Refinement of the Domain Decomposition+L2-Jumps Method applied to the Neutron Diffusion Equation on 3D Structured Meshes

  • Université Paris-Saclay

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Résumé

A deterministic solver for neutron calculation is classically based on the two step calculation scheme: the 2D lattice step to find the homogenized cross sections and the 3D core step usually based on the neutron diffusion equation for the whole core domain. In general, this equation can be recast in a mixed variational form, and then discretized by using the Raviart-Thomas-Nédélec Finite Element. More importantly, the neutron diffusion equation usually admits low regularity solution due to heterogeneous coefficients. This requires Adaptive Mesh Refinement (AMR) to improve the accuracy of the solution. In order to have independent local refinement on each subdomain, the AMR strategy is combined with the domain decomposition+L2 jumps as illustrated in [1] with two subdomains on 2D numerical test cases. The goal of this work is to extend the above strategy to 3D structured meshes with multiple subdomains which leads to a more optimal refinement for the full 3D core calculation.

langue originaleAnglais
titreProceedings of the International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering, M and C 2025
EditeurAmerican Nuclear Society
Pages460-469
Nombre de pages10
ISBN (Electronique)9780894482229
Les DOIs
étatPublié - 1 janv. 2025
Evénement2025 International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering, M and C 2025 - Denver, États-Unis
Durée: 27 avr. 202530 avr. 2025

Série de publications

NomProceedings of the International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering, M and C 2025

Une conférence

Une conférence2025 International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering, M and C 2025
Pays/TerritoireÉtats-Unis
La villeDenver
période27/04/2530/04/25

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