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Communication Dans Un Congrès Année : 2022

A hybrid optimization tool for active magnetic regenerator

Résumé

Active Magnetic Regenerator (AMR) refrigeration is an innovate technology, which can reduce energy consumption and the depletion of the ozone layer. However, to develop a commercially applicable design of the AMR model is still an issue, because of the difficulty to find a configuration of the AMR parameters, which are suitable for various applications needs. In this work, we focus on the optimization method for finding a common parameters of the AMR model in two application modes: a magnetic refrigeration system and a thermo-magnetic generator. This paper proposes a robust optimisation tool, which ensures the scalability with respect to the number of objectives and allows to easily set up different optimisation experiments. A tool validation is presented. It is expected that this tool can help to make a qualitative jump in the development of AMR refrigeration. CCS CONCEPTS • Computing methodologies → Artificial intelligence; Modeling and simulation.
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Dates et versions

hal-03902551 , version 1 (16-12-2022)

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Anna Ouskova Leonteva, Michel Risser, Radia Hamane, Anne Jeannin-Girardon, Pierre Parrend, et al.. A hybrid optimization tool for active magnetic regenerator. GECCO '22: Genetic and Evolutionary Computation Conference, Jul 2022, Boston Massachusetts, United States. pp.739-742, ⟨10.1145/3520304.3529055⟩. ⟨hal-03902551⟩
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