Thermal Conductivity of Multiwalled Carbon Nanotubes-Kapok Seed Oil-Based Nanofluid
The synthesis of a nanofluid from multiwalled carbon nanotubes (MWCNTs) and Kapok seed oil by a one-step method is reported. The nanofluid showed excellent stability of nanoparticle dispersion in the base fluid. Furthermore, this study deals with the prediction of the thermal conductivity of the MWC...
| Main Authors: | Ul Islam, B., Mukhtar, A., Saqib, S., Mahmood, A., Rafiq, S., Hameed, A., Khan, M.S., Hamid, K., Ullah, S., Al-Sehemi, A.G., Ibrahim, M. |
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| Format: | Article |
| Institution: | Universiti Teknologi Petronas |
| Record Id / ISBN-0: | utp-eprints.30078 / |
| Published: |
Wiley-VCH Verlag
2020
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| Online Access: |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85086270438&doi=10.1002%2fceat.201900600&partnerID=40&md5=3137beb4c29fbf00c9296b64e65023d0 http://eprints.utp.edu.my/30078/ |
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| Summary: |
The synthesis of a nanofluid from multiwalled carbon nanotubes (MWCNTs) and Kapok seed oil by a one-step method is reported. The nanofluid showed excellent stability of nanoparticle dispersion in the base fluid. Furthermore, this study deals with the prediction of the thermal conductivity of the MWCNTs-kapok seed oil nanofluid. To improve the prediction of the thermal conductivity of the nanofluid, the artificial neural network (ANN) computing approach was used with different algorithms including the back-propagation, Levenberg-Marquardt, and genetic algorithm (GA). Finally, the ANN-GA model is recommended for the prediction of thermal conductivity with higher accuracy. © 2020 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim |
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