Performance Characteristics of a Magnetic Ericsson Refrigeration Cycle Using La(Fe0.88Si0.12)13H1 or Gd as the Working Substance

2013 ◽  
Vol 631-632 ◽  
pp. 322-325 ◽  
Author(s):  
Jun Yi Wang ◽  
Gildas Diguet ◽  
Guo Xing Lin ◽  
Jin Can Chen
Keyword(s):  
Numerical Calculation ◽  
Room Temperature ◽  
Magnetic Refrigeration ◽  
Performance Characteristics ◽  
Coefficient Of Performance ◽  
Refrigeration Cycle ◽  
Regenerative Heat ◽  
Heat Quantity ◽  
Room Temperature Magnetic Refrigeration

Based on the experimental characteristics of iso-field entropy varying with temperature for the room-temperature magnetic refrigeration material La(Fe0.88Si0.12)13H1 or Gd, the regenerative Ericsson refrigeration cycle using La(Fe0.88Si0.12)13H1 or Gd as the working substance is established and their thermodynamic performances are evaluated and analyzed. By means of numerical calculation, the influence of non-perfect regeneration on the main thermodynamic performances of the cycle is revealed and discussed. Furthermore, the coefficient of performance (COP), non-perfect regenerative heat quantity, and net cooling quantity of the Ericsson refrigeration cycle using La(Fe0.88Si0.12)13H1 or Gd as the working substance are compared. The results obtained show that it is beneficial to the cooling quantity of the cycles using La(Fe0.88Si0.12)13H1 or Gd as the working substance to operate in the region of Tcold >T0 and, at the condition of a same temperature span, the cooling quantity for La(Fe0.88Si0.12)13H1 is larger than that for Gd.

Modeling of Magnetic Refrigeration Device by Using Artificial Neural Networks Approach

2021 ◽  
Vol 10 (4) ◽  
pp. 68-76
Author(s):  
Younes Chiba ◽  
Yacine Marif ◽  
Noureddine Henini ◽  
Abdelhalim Tlemcani
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Room Temperature ◽  
Magnetic Refrigeration ◽  
Coefficient Of Performance ◽  
Refrigeration Cycle ◽  
Multiple Linear Regressions ◽  
Artificial Neural ◽  
Experimental Data Collection ◽  
Linear Regressions

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.

Thermodynamic Performance Characteristics of a Regenerative Brayton Refrigeration Cycle Using Gd0.45Tb0.55 and Gd as the Working Substance

2013 ◽  
Vol 750-752 ◽  
pp. 1016-1019 ◽  
Author(s):  
Shan He Su ◽  
Zhi Chao Xu ◽  
Guo Xing Lin ◽  
Gildas Diguet ◽  
Jin Can Chen
Keyword(s):  
Heat Capacity ◽  
Numerical Calculation ◽  
Room Temperature ◽  
Magnetic Entropy Change ◽  
Entropy Change ◽  
Performance Characteristics ◽  
Refrigeration Cycle ◽  
Magnetic Entropy ◽  
Thermodynamic Performance ◽  
Brayton Refrigeration Cycle

Based on experimental characteristics of the iso-field heat capacity of the working substances Gd0.45Tb0.55and Gd, the magnetic entropy change with temperature is calculated. The regenerative Brayton refrigeration cycles employing these materials as the working substances are established. By means of thermodynamic analysis and numerical calculation, the effects of the non-perfect regeneration on the performance characteristics of the refrigeration cycles are revealed. Furthermore, the cyclic performances employing Gd0.45Tb0.55and Gd as the working substances are evaluated and compared. The results obtained may provide some useful information for the optimal design of the room temperature magnetic refrigerators.

scholarly journals Progress of room temperature magnetic refrigeration technology

2017 ◽  
Vol 66 (11) ◽  
pp. 110701
Author(s):  
Li Zhen-Xing ◽  
Li Ke ◽  
Shen Jun ◽  
Dai Wei ◽  
Gao Xin-Qiang ◽  
...  
Keyword(s):  
Room Temperature ◽  
Magnetic Refrigeration ◽  
Room Temperature Magnetic Refrigeration
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