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New horizons in magnetic refrigeration using artificial intelligence

Author

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  • Chdil, O.
  • Bikerouin, M.
  • Balli, M.
  • Mounkachi, O.

Abstract

A number of magnetic refrigeration prototypes have been developed in recent years. Nevertheless, their optimization remains a challenging process. This paper presents an efficient approach based on artificial intelligence for optimizing the cooling performance of multi-layer active magnetic regenerators. To this end, a validated numerical model was used to predict the temperature difference between the hot and cold sources of a four-layer active magnetic regenerator. By using a nanofluid as a heat transfer fluid, the maximum temperature span of the device can be increased by approximately 20%. More importantly, by simultaneously optimizing a set of 10 key parameters, including the geometric parameters and the working conditions, the thermodynamic performance of the four-layer active magnetic regenerator prototype can be markedly enhanced by almost 40%. The newly established approach will be of considerable practical importance to both scientists and engineers since it will enable them to avoid costly experimental trials by optimizing a wide number of parameters.

Suggested Citation

  • Chdil, O. & Bikerouin, M. & Balli, M. & Mounkachi, O., 2023. "New horizons in magnetic refrigeration using artificial intelligence," Applied Energy, Elsevier, vol. 335(C).
    • Handle: RePEc:eee:appene:v:335:y:2023:i:c:s030626192300137x
    DOI: 10.1016/j.apenergy.2023.120773
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    References listed on IDEAS

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