Modeling of Magnetic Refrigeration Device by Using Artificial Neural Networks Approach

Younes Chiba, Yacine Marif, Noureddine Henini and Abdelhalim Tlemcani
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Younes Chiba: Medea University, Algeria
Yacine Marif: Université de Ouargla, Algeria
Noureddine Henini: Medea University, Algeria
Abdelhalim Tlemcani: Medea University, Algeria

International Journal of Energy Optimization and Engineering (IJEOE), 2021, vol. 10, issue 4, 68-76

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.

Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:igg:jeoe00:v:10:y:2021:i:4:p:68-76

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