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New Evolutionary Method for Studying Physical Properties of Magneto Caloric Materials
- Source :
- CEC, International Conference on the IEEE Congress on Evolutionary, International Conference on the IEEE Congress on Evolutionary, Jun 2021, En ligne, France
- Publication Year :
- 2021
- Publisher :
- HAL CCSD, 2021.
-
Abstract
- Magnetic refrigeration (MR) is an alternative technology to conventional vapour compression with a high potential to reduce energy consumption and greenhouse gases. The working principle of MR is based on the property of magneto caloric materials (MCMs) to respond to applied external magnetic field by a variation in their temperature. To find the inexpensive MCMs with needed physical properties is still an issue. This paper describes a new method, whose objective is to automate the characterization process of MCM physical properties. This method is based on a multi-objective evolutionary optimization to define the combination of Hamiltonian model free parameters, which corresponds to needed physical properties of MCM. The advantage of this method is that it doesn’t need first-principles calculations or huge databases. The description is followed by a thorough validation of the proposed method for two alloys. The obtained results are in good agreement with the experimental measurements.
- Subjects :
- [INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI]
Property (programming)
Computer science
Mechanical engineering
02 engineering and technology
Energy consumption
7. Clean energy
Evolutionary computation
[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
Characterization (materials science)
Magnetic field
13. Climate action
0202 electrical engineering, electronic engineering, information engineering
Magnetic refrigeration
020201 artificial intelligence & image processing
Magneto
Free parameter
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Journal :
- CEC, International Conference on the IEEE Congress on Evolutionary, International Conference on the IEEE Congress on Evolutionary, Jun 2021, En ligne, France
- Accession number :
- edsair.doi.dedup.....5be279bbdd31502a99c8ab01247e1ff9