Modeling of Magnetic Refrigeration Device by Using Artificial Neural Networks Approach

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 pred...

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Bibliographic Details
Published inInternational journal of energy optimization and engineering Vol. 10; no. 4; pp. 68 - 76
Main Authors Chiba, Younes, Marif, Yacine, Henini, Noureddine, Tlemcani, Abdelhalim
Format Journal Article
LanguageEnglish
Published IGI Global 01.10.2021
Subjects
Chlorofluorocarbons
Magnetic fields
Neural networks
Algeria
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Summary: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.
ISSN:2160-9500
2160-9543
DOI:10.4018/IJEOE.2021100105