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Entropy Generation Optimization for Rarified Nanofluid Flows in a Square Cavity with Two Fins at the Hot Wall
Computational Fluid Dynamics (CFD) is utilized to study entropy generation for the rarefied steady state laminar 2-D flow of air-Al(2)O(3) nanofluid in a square cavity equipped with two solid fins at the hot wall. Such flows are of great importance in industrial applications, such as the cooling of...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7514587/ https://www.ncbi.nlm.nih.gov/pubmed/33266819 http://dx.doi.org/10.3390/e21020103 |
Sumario: | Computational Fluid Dynamics (CFD) is utilized to study entropy generation for the rarefied steady state laminar 2-D flow of air-Al(2)O(3) nanofluid in a square cavity equipped with two solid fins at the hot wall. Such flows are of great importance in industrial applications, such as the cooling of electronic equipment and nuclear reactors. In this current study, effects of the Knudsen number (Kn), Rayleigh number (Ra) and the nano solid particle’s volume fraction ([Formula: see text]) on entropy generation were investigated. The values of the parameters considered in this work were as follows: [Formula: see text] , [Formula: see text]. The length of the fins (L(F)) was considered to be fixed and equal to 0.5 m, whereas the location of the fins with respect to the lower wall (H(F)) was set to 0.25 and 0.75 m. Simulations demonstrated that there was an inverse direct effect of Kn on the entropy generation. Moreover, it was found that when Ra was less than 10(4), the entropy generation, due to the flow, increased as [Formula: see text] increases. In addition, the entropy generation due to the flow will decrease at Ra greater than 10(4) as [Formula: see text] increases. Moreover, the entropy generation due to heat will increase as both the [Formula: see text] and Ra increase. In addition, a correlation model of the total entropy generation as a function of all of the investigated parameters in this study was proposed. Finally, an optimization technique was adapted to find out the conditions at which the total entropy generation was minimized. |
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