Computational fluid dynamics and machine learning integration for evaluating solar thermal collector efficiency -Based parameter analysis

Computational fluid dynamics and machine learning integration for evaluating solar thermal collector efficiency -Based parameter analysis

Abstract The present paper provides a novel hybrid computational framework that integrates Computational Fluid Dynamics (CFD) with advanced machine learning techniques to optimize solar thermal collectors employing micro-heat pipe arrays (MHPA) for food dehydration applications. The methodology addr...

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Bibliographic Details
Main Authors: Xiaoyu Hu, Lanting Guo, Jiyuan Wang, Yang Liu
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
Subjects:
CFD-ML hybrid model
Entropy optimization
Solar thermal collector
Online Access:https://doi.org/10.1038/s41598-025-10212-w
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https://doi.org/10.1038/s41598-025-10212-w

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