Thermodynamics-Informed Neural Networks for the Design of Solar Collectors: An Application on Water Heating in the Highland Areas of the Andes

This study addresses the challenge of optimizing flat-plate solar collector design, traditionally reliant on trial-and-error and simplified engineering design methods. We propose using physics-informed neural networks (PINNs) to predict optimal design conditions in a range of data that not only char...

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Bibliographic Details
Main Authors: Mauricio Cáceres, Carlos Avila, Edgar Rivera
Format: Article
Language:English
Published: MDPI AG 2024-10-01
Series:Energies
Subjects:
Online Access:https://www.mdpi.com/1996-1073/17/19/4978
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