Artificial neural network algorithm for hybrid nanofluid in Jeffery-Hamel flow under Thompson and Troian velocity slip effects: Comparison of Xue and Yamada-Ota models

•Artificial Neural Network Algorithm for hybrid nanofluid in Jeffery-Hamel flow.•Thomson and Troian Velocity Slip Effects.•Comparison of Xue and Yamada-Ota models.•The governing equations solved using the Explicit Runge-Kutta Method (ERKM).•Advanced thermal management optimization with hybrid nanofl...

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Vydáno v:	Chemical engineering science Ročník 321; s. 122785
Hlavní autoři:	Nacereddine, Mohamed Kherief, Usman, Rashid, Farhan Lafta, Shah, Nehad Ali, Ali Yousif, Badria Almaz, Mahariq, Ibrahim, Kezzar, Mohamed, Sari, Mohamed Rafik
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Elsevier Ltd 01.02.2026
Témata:	Artificial neural network algorithm Explicit Runge-Kutta method Hybrid nanofluid Thomson-Troian slip Xue and Yamada-Ota models Explicit Runge-Kutta method Artificial neural network algorithm Thomson-Troian slip Hybrid nanofluid Xue and Yamada-Ota models
ISSN:	0009-2509
On-line přístup:	Získat plný text
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