Using radial basis function network to model the heat transfer and pressure drop of water based nanofluids containing MgO nanoparticles

Using radial basis function network to model the heat transfer and pressure drop of water based nanofluids containing MgO nanoparticles

Present study is focused on feasibility of predicting the thermal and fluid properties of MgO/water nanofluid using radial based function (RBF) type artificial neural networks (ANNs). To design the ANN, Reynolds number and volume fraction of nanoparticles (ϕ) were considered as ANN inputs and in pri...

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Bibliographic Details
Main Authors: Mohammad Hemmat Esfe, Mohammad Hassan Kamyab, Ali Alirezaie, Davood Toghraie
Format: Article
Language:English
Published: Elsevier 2021-12-01
Series:Case Studies in Thermal Engineering
Subjects:
RBF-ANN
Nanofluids
Heat transfer coefficient
Pressure drop
MgO nanoparticles
Online Access:http://www.sciencedirect.com/science/article/pii/S2214157X21006389

Internet

http://www.sciencedirect.com/science/article/pii/S2214157X21006389

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