A feed-forward artificial neural network with several training methods and various geometries for predicting the rheological behavior of Al2O3/ethylene glycol-water hybrid nanofluid

A feed-forward artificial neural network with several training methods and various geometries for predicting the rheological behavior of Al2O3/ethylene glycol-water hybrid nanofluid

In this study, the effect of volume fraction of nanoparticles (φ), temperature (Tem.), and shear rates (SR) on the viscosity (μnf) of Al2O3/Ethylene Glycol-Water hybrid nanofluid is investigated using an artificial neural network (ANN). To this end, the μnf is computed for all 180 different combinat...

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Bibliographic Details
Main Authors: S. Ali Eftekhari, Maboud Hekmatifar, Davood Toghraie, Mohammad Hemmat Esfe
Format: Article
Language:English
Published: Elsevier 2023-11-01
Series:Ain Shams Engineering Journal
Subjects:
Training method
Hybrid nanofluid
Rheological behavior
Feed-forward ANN
Online Access:http://www.sciencedirect.com/science/article/pii/S2090447923004446

Internet

http://www.sciencedirect.com/science/article/pii/S2090447923004446

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