期刊
INTERNATIONAL JOURNAL OF ENERGY RESEARCH
卷 45, 期 13, 页码 18498-18539出版社
WILEY-HINDAWI
DOI: 10.1002/er.7023
关键词
caloric materials; heat pump; modeling; multiobjective optimization; refrigeration
资金
- Fundacao para a Ciencia e a Tecnologia [NORTE-01-0145-FEDER-022096, PTDC/EME-TED/3099/2020]
- Fundação para a Ciência e a Tecnologia [PTDC/EME-TED/3099/2020] Funding Source: FCT
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.
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.
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