Combinatory Finite Element and Artificial Neural Network Model for Predicting Performance of Thermoelectric Generator
Thermoelectric generators (TEGs) are rapidly becoming the mainstream technology for converting thermal energy into electrical energy. The rise in the continuous deployment of TEGs is related to advancements in materials, figure of merit, and methods for module manufacturing. However, rapid optimizat...
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| Principais autores: | , , |
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| Format: | Artigo |
| Sprog: | Inglês |
| Udgivet: |
MDPI AG
2018-08-01
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| Serier: | Energies |
| Fag: | |
| Online adgang: | http://www.mdpi.com/1996-1073/11/9/2216 |
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