Broad Multi-Parameter Dimensioning of Magnetocaloric Systems Using Statistical Learning Classifiers

Broad Multi-Parameter Dimensioning of Magnetocaloric Systems Using Statistical Learning Classifiers

Prototyping innovative energy devices is a complex multivariable dimensioning problem. For the case of magnetocaloric systems, one aims to obtain an optimized balance between energy conversion performance, useful power generated, and power consumed. In these devices, modeling is entering a mature ph...

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Bibliographic Details
Main Authors: Daniel J. Silva, João S. Amaral, Vitor S. Amaral
Format: Article
Language:English
Published: Frontiers Media S.A. 2020-06-01
Series:Frontiers in Energy Research
Subjects:
magnetocaloric
machine learning
statistical method
caloric materials
dimensioning algorithm
Online Access:https://www.frontiersin.org/article/10.3389/fenrg.2020.00121/full

Internet

https://www.frontiersin.org/article/10.3389/fenrg.2020.00121/full

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