Rashidi Mohammad M, Nazari Mohammad Alhuyi, Mahariq Ibrahim, Assad Mamdouh El Haj, Ali Mohamed E, Almuzaiqer Redhwan, Nuhait Abdullah, Murshid Nimer
Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu 610054, China.
College of Engineering and Technology, American University of the Middle East, Kuwait.
Nanomaterials (Basel). 2021 Nov 16;11(11):3084. doi: 10.3390/nano11113084.
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.
能量转换系统的热性能是提高系统效率的最重要目标之一。这种热性能强烈依赖于能量转换系统中所使用的工作流体的热物理特性。热导率、比热容以及动力粘度是显著影响传热特性的属性。作为很有前景的传热流体，混合纳米流体的这些特性受不同因素影响，包括体积分数、固体颗粒尺寸和温度。在本文中，对具有混合纳米结构的纳米流体的上述特性以及针对这些特性所提出的模型进行了综述。得出的结论是，固体体积分数的增加会导致热导率和动力粘度提高，而比热容的变化趋势取决于基础流体。此外，温度升高会提高热导率，同时降低动力粘度。而且，正如综述文献所述，不同方法在高精度建模这些特性方面具有适用性，而包括人工神经网络在内的智能算法与关联式相比能够达到更高的精度。除了所使用的方法外，一些其他因素，如模型架构，也会影响所提出模型的可靠性和准确性。
