2017
DOI: 10.1016/j.ijrefrig.2016.12.018
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Numerical analysis of a near-room-temperature magnetic cooling system

Abstract: In this study, for a near-room-temperature magnetic cooling system, a decoupled multiphysics numerical approach (Magnetism, Fluid Flow, and Heat Transfer) is developed using a commercial CFD solver, ANSYS-FLUENT, as a design tool. User defined functions are incorporated into the software in order to take into account the magnetocaloric effect. Magnetic flux density is assumed to be linear during the magnetization and demagnetization processes. Furthermore, the minimum and maximum magnetic flux densities (Bmin … Show more

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Cited by 16 publications
(8 citation statements)
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“…In order to validate, the results obtained from the current numerical analysis are compared with the experimental work of Bahl et al 21 and the numerical work of Ezan et al. 25 Here, the Gd sample is magnetized from 0.3 to 1.3 T for a duration of 0.1 s. Figure 4(a) reports the variation in temperature span with the magnetic field intensity. When the current numerical results are compared with the experimental results, a constant deviation of 13.7% is observed, though a similar trend is followed.…”
Section: Mathematical Modelingmentioning
confidence: 91%
“…In order to validate, the results obtained from the current numerical analysis are compared with the experimental work of Bahl et al 21 and the numerical work of Ezan et al. 25 Here, the Gd sample is magnetized from 0.3 to 1.3 T for a duration of 0.1 s. Figure 4(a) reports the variation in temperature span with the magnetic field intensity. When the current numerical results are compared with the experimental results, a constant deviation of 13.7% is observed, though a similar trend is followed.…”
Section: Mathematical Modelingmentioning
confidence: 91%
“…Another used boundary condition is to impose a fluid velocity profile at the boundaries (eg, a harmonic fluid velocity profile at the fluid entrance, zero velocity at the cavity walls, and zero pressure at the outlet). All modeling works have used water for the fluid, with a considerable amount of investigations using additionally monoethylenglycol, propylenglycol, 100 ethanol, 111 and glycol, 106 so that the final fluid results in antifreezing mixtures.…”
Section: Thermodynamic Modelingmentioning
confidence: 99%
“…One of the implementation using Python has resulted in a package dedicated to caloric systems 118 . Nevertheless, most of the research used software packages already available, such as COMSOL Multiphysics, 32 Ansys Fluent, 90,111 Ansys Maxwell, 82 Openfoam, 168 modelica, 169 Flux2D and Flux3D, 78 GMESH and GETDP, 85 and FEMM 83 …”
Section: Numerical Implementationmentioning
confidence: 99%
“…[54], Lozano et al [55], Velazquez et al [51] and Ezan et al [56] are plotted in Figure 3 to examine the 13 variation of no-load temperature span with respect to utilization. In the operating range of utilization of Richard et al [47] given in Figure 3, which is much below 0.1, the temperature span sharply increases with the utilization.…”
Section: Utilizationmentioning
confidence: 99%
“…In the operating range of utilization of Richard et al [47] given in Figure 3, which is much below 0.1, the temperature span sharply increases with the utilization. Both, Tagliafico [53] and Ezan et al [56] observed the variation of no-load temperature span with utilization for different cycle frequencies but the operating range of cycle frequencies and the obtained no-load temperature spans presented by Tagliafico [53] are relatively much higher. Engelbrecht [39] performed an experimental investigation to determine the variation of no-load temperature spans with utilization using a parallel plate regenerator with different spacing between them.…”
Section: Utilizationmentioning
confidence: 99%