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Modeling of Magnetic Refrigeration Device by Using Artificial Neural Networks Approach

Author

Listed:
  • Younes Chiba

    (Medea University, Algeria)

  • Yacine Marif

    (Université de Ouargla, Algeria)

  • Noureddine Henini

    (Medea University, Algeria)

  • Abdelhalim Tlemcani

    (Medea University, Algeria)

Abstract

The aim of this work is to use multi-layered perceptron artificial neural networks and multiple linear regressions models to predict the efficiency of the magnetic refrigeration cycle device operating near room temperature. For this purpose, the experimental data collection was used in order to predict coefficient of performance and temperature span for active magnetic refrigeration device. In addition, the operating parameters of active magnetic refrigerator cycle are used for solid magnetocaloric material under application 1.5 T magnetic fields. The obtained results including temperature span and coefficient of performance are presented and discussed.

Suggested Citation

  • Younes Chiba & Yacine Marif & Noureddine Henini & Abdelhalim Tlemcani, 2021. "Modeling of Magnetic Refrigeration Device by Using Artificial Neural Networks Approach," International Journal of Energy Optimization and Engineering (IJEOE), IGI Global, vol. 10(4), pages 68-76, October.
    • Handle: RePEc:igg:jeoe00:v:10:y:2021:i:4:p:68-76
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