Обзорная статья

Thermophysical Properties of Hybrid Nanofluids and the Proposed Models: An Updated Comprehensive Study

Mohammad Mehdi RashidiInstitute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu 610054, ChinaMohammad Alhuyi NazariInstitute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu 610054, ChinaIbrahim MahariqCollege of Engineering and Technology, American University of the Middle East, KuwaitMamdouh El Haj AssadSustainable and Renewable Energy Engineering Department, University of Sharjah, Sharjah P.O. Box 27272, United Arab EmiratesMohamed AliMechanical Engineering Department, College of Engineering, King Saud University, P.O. Box 800, Riyadh 11421, Saudi ArabiaRedhwan AlmuzaiqerMechanical Engineering Department, College of Engineering, King Saud University, P.O. Box 800, Riyadh 11421, Saudi ArabiaAbdullah NuhaitMechanical Engineering Department, College of Engineering, King Saud University, P.O. Box 800, Riyadh 11421, Saudi ArabiaNimer MurshidCollege of Engineering and Technology, American University of the Middle East, Kuwait

2021en

ABI

Аннотация

Thermal performance of energy conversion systems is one of the most important goals to improve the system's efficiency. Such thermal performance is strongly dependent on the thermophysical features of the applied fluids used in energy conversion systems. Thermal conductivity, specific heat in addition to dynamic viscosity are the properties that dramatically affect heat transfer characteristics. These features of hybrid nanofluids, as promising heat transfer fluids, are influenced by different constituents, including volume fraction, size of solid parts and temperature. In this article, the mentioned features of the nanofluids with hybrid nanostructures and the proposed models for these properties are reviewed. It is concluded that the increase in the volume fraction of solids causes improvement in thermal conductivity and dynamic viscosity, while the trend of variations in the specific heat depends on the base fluid. In addition, the increase in temperature increases the thermal conductivity while it decreases the dynamic viscosity. Moreover, as stated by the reviewed works, different approaches have applicability for modeling these properties with high accuracy, while intelligent algorithms, including artificial neural networks, are able to reach a higher precision compared with the correlations. In addition to the used method, some other factors, such as the model architecture, influence the reliability and exactness of the proposed models.

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Идентификаторы

DOI: 10.3390/nano11113084

Цитирования и источники

Цитирований: 3Использованных источников: 0

Показатели — AkademScholar