期刊
NANOMATERIALS
卷 11, 期 11, 页码 -出版社
MDPI
DOI: 10.3390/nano11113084
关键词
hybrid nanostructures; thermophysical features; dynamic viscosity; thermal conductivity
类别
资金
- King Saud University [RGP-080]
The thermal performance of energy conversion systems is crucial for efficiency improvement and depends heavily on the thermophysical features of the applied fluids. Increasing the volume fraction of solids can enhance thermal conductivity and dynamic viscosity, while the variation trend of specific heat depends on the base fluid. Higher temperature leads to increased thermal conductivity but decreased dynamic viscosity.
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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