A comprehensive two-dimensional numerical study on unsteady conjugate heat transfer in magnetic refrigerator with Gd plates

Summary The discovery of giant caloric effects and further investigation on device systems that can compete with current heat management technologies in terms of efficiency have led to a major increase in modeling investigations. These models have been crucial in designing the most efficient, cheap, and robust setups with reliable performances. One example is the modeling of magnetic refrigerators and heat pumps that has been used in the optimization of critical geometrical parameters of magnetocaloric regenerators. In this paper, we review the model components of caloric heat pump and refrigerator systems, including field generation, heat transfer, caloric effects, fluid dynamics, and loss mechanisms. We also review the optimization strategies used so far, which are based on sensitive analysis, brute force approaches, statistical learning, and genetic algorithms. The analysis is applied to magnetocaloric, electrocaloric, elastocaloric, and barocaloric systems.

show abstract

“…While the energetic continuity at interfaces has been modeled at 1D using the heat transfer coefficient

h

, which must be symmetric for the two interface objects, 131 the energetic continuity has been modeled at 2D by the following equality 32,158 :

k_{f} \frac{\partial T_{f}}{\partial \overset{n}{true}} = k_{s} \frac{\partial T_{s}}{\partial \overset{n}{true}},

where

\overset{n}{true}

is the normal vector at the interface.…”

Section: Thermodynamic Modelingmentioning

confidence: 99%

Caloric devices: A review on numerical modeling and optimization strategies

2021

View full text Add to dashboard Cite

show abstract

“…In addition to developing new MCMs [ 4 , 5 ], scholars and scientists have made great efforts to improve magnetic refrigerator performance from various aspects, such as efficient magnets [ 6 , 7 , 8 ], advanced refrigeration cycles [ 9 , 10 ], heat transfer enhancement [ 11 , 12 , 13 , 14 , 15 ], smart mechanical design [ 16 , 17 , 18 , 19 , 20 ], and optimal control [ 21 , 22 ]. On the other hand, in addition to building prototypes for experiments [ 23 , 24 ], various 1D and 2D numerical models, based on solving the energy conservation equations of fluid and solid MCMs, have been developed for the research of magnetic refrigeration [ 2 , 10 , 11 , 12 , 13 , 14 , 15 , 25 , 26 ], and Nielsen et al have made a review on the AMR modeling [ 27 ]. In these models the magnetic refrigeration fundamental was studied [ 10 , 12 ] and the effects of structural and operational parameters on performance aspects, such as temperature span, refrigeration capacity, and Coefficient of Performance (COP), were studied for optimization [ 28 , 29 , 30 ].…”

Section: Introductionmentioning

confidence: 99%

“…On the other hand, in addition to building prototypes for experiments [ 23 , 24 ], various 1D and 2D numerical models, based on solving the energy conservation equations of fluid and solid MCMs, have been developed for the research of magnetic refrigeration [ 2 , 10 , 11 , 12 , 13 , 14 , 15 , 25 , 26 ], and Nielsen et al have made a review on the AMR modeling [ 27 ]. In these models the magnetic refrigeration fundamental was studied [ 10 , 12 ] and the effects of structural and operational parameters on performance aspects, such as temperature span, refrigeration capacity, and Coefficient of Performance (COP), were studied for optimization [ 28 , 29 , 30 ]. With the assumption of local thermal equilibrium between the fluid and solid phases, Teyber et al developed a semi-analytic AMR model with two-layer MCMs [ 31 ], which could be extended for the optimization of AMRs with multi-layer MCMs.…”

Section: Introductionmentioning

confidence: 99%

Refrigeration Performance and Entropy Generation Analysis for Reciprocating Magnetic Refrigerator with Gd Plates

You

Yang

et al. 2018

Entropy

Self Cite

View full text Add to dashboard Cite

In the current work, a novel 2D numerical model of stationary grids was developed for reciprocating magnetic refrigerators, with Gd plates, in which the magneto-caloric properties, derived from the Weiss molecular field theory, were adopted for the built-in energy source of the magneto-caloric effect. The numerical simulation was conducted under the conditions of different structural and operational parameters, and the effects of the relative fluid displacement (φ) on the specific refrigeration capacity (qref) and the Coefficient of Performance (COP) were obtained. Besides the variations of entropy, the generation rate and number were studied and the contours of the local entropy generation rate are presented for discussion. From the current work, it is found that with an increase in φ, both the qref and COP followed the convex variation trend, while the entropy generation number (Ns) varied concavely. As for the current cases, the maximal qref and COP were equal to 151.2 kW/m 3 and 9.11, respectively, while the lowest Ns was the value of 2.4 × 10 −4 K −1 . However, the optimal φ for the largest qref and COP, and for the lowest Ns, were inconsistent, thus, some compromises need be made in the optimization of magnetic refrigerators.

show abstract

Magnetocaloric Refrigeration

Siroux

2023

Refrigerators, Heat Pumps and Reverse Cycle Engines

View full text Add to dashboard Cite

A comprehensive two-dimensional numerical study on unsteady conjugate heat transfer in magnetic refrigerator with Gd plates

Cited by 14 publications

References 30 publications

Caloric devices: A review on numerical modeling and optimization strategies

Caloric devices: A review on numerical modeling and optimization strategies

Refrigeration Performance and Entropy Generation Analysis for Reciprocating Magnetic Refrigerator with Gd Plates

Magnetocaloric Refrigeration

Contact Info

Product

Resources

About