Modeling of Magnetic Refrigeration Device by Using Artificial Neural Networks Approach

Pub Date : 2021-10-01 DOI:10.4018/ijeoe.2021100105
Y. Chiba, Y. Marif, N. Henini, A. Tlemçani
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引用次数: 1

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.
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基于人工神经网络的磁制冷装置建模
本工作的目的是使用多层感知器人工神经网络和多元线性回归模型来预测磁制冷循环装置在室温附近运行的效率。为此,利用实验数据收集来预测主动磁制冷装置的性能系数和温度跨度。此外,还将主动磁制冷循环的运行参数用于固体磁热材料在1.5T磁场下的应用。给出并讨论了所获得的结果,包括温度跨度和性能系数。
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