Prediction of the thermophysical properties of Ag-reduced graphene oxide-water/ethylene-glycol hybrid nanofluids using different machine learning methods

Background: Because of their enhanced thermophysical characteristics, namely greater thermal conductivity, viscosity control, and long-term stability than traditional nanofluids, hybrid nanofluids drew interest. Such properties make them suitable candidates for many industrial applications such as s...

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Autori principali:	Huaguang Li, Ali B.M. Ali, Rasha Abed Hussein, Narinderjit Singh Sawaran Singh, Barno Abdullaeva, Zubair Ahmad, Soheil Salahshour, Mohammadreza Baghoolizadeh, Mostafa Pirmoradian
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	Elsevier 2025-05-01
Serie:	Case Studies in Thermal Engineering
Soggetti:	Thermophysical properties Hybrid nanofluids Machine learning methods
Accesso online:	http://www.sciencedirect.com/science/article/pii/S2214157X25002989
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