Predicting the performance of magnetocaloric systems using machine learning regressors
Since refrigeration, air-conditioning and heat pump systems account to 25–30% of all energy consumed in the world, there is a considerable potential to mitigate the Global Warming by increasing the efficiency of the related appliances. Magnetocaloric systems, i.e. refrigerators and heat pumps, are p...
Main Authors: | D.J. Silva, J. Ventura, J.P. Araújo |
---|---|
Format: | Article |
Language: | English |
Published: |
Elsevier
2020-11-01
|
Series: | Energy and AI |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S2666546820300306 |
Similar Items
-
Prediction of the magnetocaloric behaviors of the Kekulene structure for the magnetic refrigeration
by: M. Arejdal
Published: (2020-09-01) -
Effect of Dy substitution in the giant magnetocaloric properties of HoB2
by: Pedro Baptista de Castro, et al.
Published: (2020-01-01) -
EXPLORATION OF NEW MAGNETOCALORIC AND MULTIFUNCTIONAL MAGNETIC MATERIALS
by: Quetz, Abdiel
Published: (2017) -
The Magnetocaloric Effect & Performance of Magnetocaloric Materials in a 1D Active Magnetic Regenerator Simulation
by: Bayer, Daniel Nicholas
Published: (2019) -
Design and Analysis of a Nested Halbach Permanent Magnet Magnetic Refrigerator
by: Tura, Armando
Published: (2013)