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Curve-fitting on experimental thermal conductivity of motor oil under influence of hybrid nano additives containing multi-walled carbon nanotubes and zinc oxide

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  • Wu, Huawei
  • Al-Rashed, Abdullah A.A.A.
  • Barzinjy, Azeez A.
  • Shahsavar, Amin
  • Karimi, Ali
  • Talebizadehsardari, Pouyan

Abstract

Hybrid nanofluids has been attracted lots of attention due to simultaneous take advantage of the properties of two or more kinds of nanoparticles in the base fluid. Carbon Nanotubes (CNTs) are utilized widely attached to metal oxide nanoparticles due to significant thermal characteristics. This study aims to assess experimentally the thermal conductivity of the hybrid nanofluid of Zinc Oxide (ZnO) and Multi-Wall CNT (MWCNT) in Engine oil (SAE 10W40). The influences of nanoparticles concentration as well as fluid’s temperature are evaluated. The experiments performed at the temperature between 25 oC and 50 oC and nanoparticles volume fraction from 0.05 to 0.8 %. The experimental results showed that a higher ratio of nano-lubricant thermal conductivity is achieved for a higher volume fraction and temperature of nanoparticles. According to the absence of an exact relationship to determine the thermal conductivity of ZnO-MWCNT/Engine oil, a correlation is developed based on the test measurements presented in terms of volume fraction and temperature using a curve-fitting method. A deviation analysis is also performed on the ratio of thermal conductivity achieved from the developed correlation and experimental data showing a reasonable agreement

Suggested Citation

  • Wu, Huawei & Al-Rashed, Abdullah A.A.A. & Barzinjy, Azeez A. & Shahsavar, Amin & Karimi, Ali & Talebizadehsardari, Pouyan, 2019. "Curve-fitting on experimental thermal conductivity of motor oil under influence of hybrid nano additives containing multi-walled carbon nanotubes and zinc oxide," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
    • Handle: RePEc:eee:phsmap:v:535:y:2019:i:c:s0378437119312373
    DOI: 10.1016/j.physa.2019.122128
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    References listed on IDEAS

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    1. Ghasemi, Ali & Hassani, Mohsen & Goodarzi, Marjan & Afrand, Masoud & Manafi, Sahebali, 2019. "Appraising influence of COOH-MWCNTs on thermal conductivity of antifreeze using curve fitting and neural network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 36-45.
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    4. Al-Rashed, Abdullah A.A.A., 2019. "Optimization of heat transfer and pressure drop of nano-antifreeze using statistical method of response surface methodology," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 521(C), pages 531-542.
    5. Al-Rashed, Abdullah A.A.A. & Ranjbarzadeh, Ramin & Aghakhani, Saeed & Soltanimehr, Mehdi & Afrand, Masoud & Nguyen, Truong Khang, 2019. "Entropy generation of boehmite alumina nanofluid flow through a minichannel heat exchanger considering nanoparticle shape effect," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 521(C), pages 724-736.
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    2. Karol Sztekler & Wojciech Kalawa & Łukasz Mika & Agata Mlonka-Medrala & Marcin Sowa & Wojciech Nowak, 2021. "Effect of Additives on the Sorption Kinetics of a Silica Gel Bed in Adsorption Chiller," Energies, MDPI, vol. 14(4), pages 1-13, February.
    3. Anna Kulakowska & Anna Pajdak & Jaroslaw Krzywanski & Karolina Grabowska & Anna Zylka & Marcin Sosnowski & Marta Wesolowska & Karol Sztekler & Wojciech Nowak, 2020. "Effect of Metal and Carbon Nanotube Additives on the Thermal Diffusivity of a Silica Gel-Based Adsorption Bed," Energies, MDPI, vol. 13(6), pages 1-15, March.

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