An Artificial Intelligence Approach to Predict the Thermophysical Properties of MWCNT Nanofluids

An Artificial Intelligence Approach to Predict the Thermophysical Properties of MWCNT Nanofluids

Experimental data of thermal conductivity, thermal stability, specific heat capacity, viscosity, UV–vis (light transmittance) and FTIR (light absorption) of Multiwalled Carbon Nanotubes (MWCNTs) dispersed in glycols, alcohols and water with the addition of sodium dodecylbenzene sulfonate (SDBS) surf...

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Bibliographic Details
Main Authors: Balaji Bakthavatchalam, Nagoor Basha Shaik, Patthi Bin Hussain
Format: Article
Language:English
Published: MDPI AG 2020-06-01
Series:Processes
Subjects:
thermophysical properties
Artificial Neural Networks
experimental data
nanofluids
prediction
Online Access:https://www.mdpi.com/2227-9717/8/6/693

Internet

https://www.mdpi.com/2227-9717/8/6/693

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