Caloric devices: A review on numerical modeling and optimization strategies

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.

Automated summary

The research focuses on modeling of heat effect device systems, optimizing key geometrical parameters, and utilizing a range of optimization strategies, including sensitivity analysis, brute force methods, statistical learning, and genetic algorithms. These models are crucial in designing the most efficient, cheap, and robust setups with reliable performances.