Modeling thermal conductivity of ethylene glycol-based nanofluids using multivariate adaptive regression splines and group method of data handling artificial neural network

Modeling thermal conductivity of ethylene glycol-based nanofluids using multivariate adaptive regression splines and group method of data handling artificial neural network

Augmenting the thermal conductivity (TC) of fluids makes them more favorable for thermal applications. In this regard, nanofluids are suggested for achieving improved heat transfer owing to their modified TC. The TC of the base fluid, the volume fraction and mean diameter of particles, and the tempe...

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Bibliographic Details
Main Authors: Sorour Alotaibi, Mohammad Ali Amooie, Mohammad Hossein Ahmadi, Narjes Nabipour, Kwok-wing Chau
Format: Article
Language:English
Published: Taylor & Francis Group 2020-01-01
Series:Engineering Applications of Computational Fluid Mechanics
Subjects:
nanofluid
gmdh
mars
thermal conductivity
artificial neural network
Online Access:http://dx.doi.org/10.1080/19942060.2020.1715843

Internet

http://dx.doi.org/10.1080/19942060.2020.1715843

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