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AI-driven and machine learning-based prediction of angled funnel fin geometry and penta-hybrid nanofluid performance in TTHX-LHTESS: a multi-technique approach for enhanced solidification

This study presents a numerical investigation to enhance the solidification performance of latent heat thermal energy storage systems (LHTESS) by integrating a novel Angled Funnel-shaped Fin geometry with hybrid and penta-hybrid nanofluids in a triplex-tube heat exchanger (TTHX). The combined use of...

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Bibliografiske detaljer
Principais autores: Mehdi Mahboobtosi, Hesam Ehsani, Fateme Nadalinia Chari, Davood Domiri Ganji
Format: Artigo
Sprog:Inglês
Udgivet: Elsevier 2026-05-01
Serier:Energy Conversion and Management: X
Fag:
Online adgang:http://www.sciencedirect.com/science/article/pii/S2590174526001844
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