Solving coupled problems of lumped parameter models in a platform for severe accidents in nuclear reactors

Louis Viot 1, * Laurent Saas 2 Florian de Vuyst 3
* Corresponding author
1 CMLA - Centre de Mathématiques et de Leurs Applications
2 SMTA - Service Mesures et modélisation des Transferts et des Accidents graves
3 LMAC - Laboratoire de Mathématiques Appliquées de Compiègne
Abstract : This paper focuses on solving coupled problems of lumped parameter models. Such problems are of interest for the simulation of severe accidents in nuclear reactors: these coarse-grained models allow for fast calculations for statistical analysis used for risk assessment and solutions of large problems when considering the whole severe accident scenario. However, this modeling approach has several numerical flaws. Besides, in this industrial context, computational efficiency is of great importance leading to various numerical constraints. The objective of this research is to analyze the applicability of explicit coupling strategies to solve such coupled problems and to design implicit coupling schemes allowing stable and accurate computations. The proposed schemes are theoretically analyzed and tested within CEA's procor platform on a problem of heat conduction solved with coupled lumped parameter models and coupled 1D models. Numerical results are discussed and allow us to emphasize the benefits of using the designed coupling schemes instead of the usual explicit coupling schemes.
Keywords : Severe Accidents Multiphysics Coupling Scheme Partitioned Approach Stability Analysis Lumped Parameter Model Complex System Computing Efficiency Acronyms LP lumped parameter ECS explicit coupling scheme ICS implicit coupling scheme
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https://hal.utc.fr/hal-01958872
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Submitted on : Thursday, May 16, 2019 - 4:10:42 PM
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CEA | LMAC | UNIV-PARIS-SACLAY | TDS-MACS | ENS-CACHAN | UNIV-COMPIEGNE | CNRS | DEN | CEA-CAD | DEN-CAD

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Louis Viot, Laurent Saas, Florian de Vuyst. Solving coupled problems of lumped parameter models in a platform for severe accidents in nuclear reactors. International Journal for Multiscale Computational Engineering, Begell House, 2018, 16, pp.6. ⟨10.1615/IntJMultCompEng.2018025643⟩. ⟨hal-01958872⟩

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