Caloric devices: A review on numerical modeling and optimization strategies

Abstract

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.

Thermal Response of Magnetic Refrigerants: Combined Effect of Temperature Dependent Specific Heat and Thermal Conductivity

“…Even in cases where a single cooling process presents slight differences in thermal response, these changes can impact significantly the complete AMR model's accuracy, as it depends on the solid refrigerant's ability to execute many heat transfer cycles with the smallest thermal response error propagation. Nevertheless, in the literature the temperature dependent thermal properties (especially the thermal conductivity k) are still ignored by most numerical reference models [18,20,38].…”

“…Silva et al (2021) compiled several published MC numerical models, classifying them by the degree to which the underlying physical phenomena are solved and implemented [20]. Each physical property used in MC models depends on parameters like temperature T and magnetic field H. In MCM numerical modelling, the use of these two dependencies in the literature presents itself considerably divergent.…”

Ferrofluidic thermal switch in a magnetocaloric device

“…To improve the particular components or whole caloric devices with respect to the temperature span, cooling power, costs, and coefficient of performance(COP), different optimization strategies were used ( Silva et al., 2021a ; 2021b ). However, most of these concern caloric devices based on active caloric regeneration and not thermal switches.…”

“…However, most of these concern caloric devices based on active caloric regeneration and not thermal switches. For thermal switches, Silva et al., (2021a ; 2021b ) investigated the effect of the thermal-conductivity variation inside a thermal switch on the performance of the caloric device.…”

Modelado del estrés termo-mecánico en películas finas de La(Fe,Co,Si)13 depositadas en estructuras porosas

“…La refrigeración juega un papel crucial en una gran parte de sectores industriales e incluso residenciales, siendo el consumo relacionado a sistemas de gestión térmica alrededor del 30% de la electricidad total producida a nivel mundial [1] [2]. Además de los impactos ambientales asociados con este importante consumo de energía primaria, los sistemas actuales de refrigeración por vapor-compresión contribuyen al calentamiento global significativamente debido a la liberación de gases contaminantes a la atmósfera, tales como fluorocarburos o dióxidos de carbono utilizados como refrigerantes, demostrando también una pobre eficiencia en el ciclo de Carnot (alrededor del 10%) [3].…”