Feasibility of least-square support vector machine in predicting the effects of shear rate on the rheological properties and pumping power of MWCNT–MgO/oil hybrid nanofluid based on experimental data-Reference-Cited by-同舟云学术

Feasibility of least-square support vector machine in predicting the effects of shear rate on the rheological properties and pumping power of MWCNT–MgO/oil hybrid nanofluid based on experimental data

Published:2020-01-24 Issue:2 Volume:143 Page:1439-1454
ISSN:1388-6150
Container-title:Journal of Thermal Analysis and Calorimetry
language:en
Short-container-title:J Therm Anal Calorim

Author:

Asadi Amin^ORCID,Alarifi Ibrahim M.,Nguyen Hoang M.,Moayedi Hossein

Funder

Majmaah University

Publisher

Springer Science and Business Media LLC

Link

http://link.springer.com/content/pdf/10.1007/s10973-020-09279-6.pdf

Reference81 articles.

1. Choi JA, Eastman SUS. Enhancing thermal conductivity of fluids with nanoparticles, ASME FED, 231: 99–103, International Mechanical Engineering Congress and Exhibition, San Francisco, CA (United States); 1995.

2. Minakov AV, Rudyak VY, Pryazhnikov MI. Rheological behavior of water and ethylene glycol based nanofluids containing oxide nanoparticles. Colloids Surf A. 2018;554:279–85. https://doi.org/10.1016/j.colsurfa.2018.06.051.

3. Bhattacharyya A, Seth GS, Kumar R, Chamkha AJ. Simulation of Cattaneo–Christov heat flux on the flow of single and multi-walled carbon nanotubes between two stretchable coaxial rotating disks. J Therm Anal Calorim. 2019. https://doi.org/10.1007/s10973-019-08644-4.

4. Seth GS, Bhattacharyya A, Kumar R, Chamkha AJ. Entropy generation in hydromagnetic nanofluid flow over a non-linear stretching sheet with Navier’s velocity slip and convective heat transfer. Phys Fluids. 2018. https://doi.org/10.1063/1.5054099.

5. Yıldız Ç, Arıcı M, Karabay H. Comparison of a theoretical and experimental thermal conductivity model on the heat transfer performance of Al2O3–SiO2/water hybrid-nanofluid. Int J Heat Mass Transf. 2019;140:598–605. https://doi.org/10.1016/j.ijheatmasstransfer.2019.06.028.

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