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Erschienen in: Neural Computing and Applications 10/2018

28.02.2017 | Original Article

Analysis of natural convective heat transport in homocentric annuli containing nanofluids with an oriented magnetic field using nonhomogeneous dynamic model

verfasst von: M. J. Uddin, M. M. Rahman, M. S. Alam

Erschienen in: Neural Computing and Applications | Ausgabe 10/2018

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Abstract

In this paper, the time-dependent natural convective heat transport in homocentric annuli containing nanofluids accompanying an oriented magnetic field using a nonhomogeneous dynamic mathematical model is numerically investigated. The analysis is carried out for four different shapes of inner walls such as triangular, square, elliptical and cylindrical. The outermost cylindrical boundary of the annulus is regarded at an unvarying low temperature and undifferentiated thermal condition on the inner surface of the annulus is considered. A finite element method is implemented for finding the solutions to the nanofluid equations of the problem. The magnetite iron oxide–kerosene nanofluid has been taken to gain insight into the thermal fields and concentration levels in terms of isotherms and isoconcentrations, respectively. The local Nusselt number distributions along the interior and exterior boundaries have been displayed for various flow parameters of the problem. To find the best performer, the average Nusselt number enhancements are demonstrated varying four different shapes of inner wall for ten sorts of nanofluids compared to that of base fluids. Results show that the dispersion of local Nusselt number decreases with the increase in the nanoparticle diameter and Hartmann number, whereas it enhances with the increase in the measure of nanoparticle by volume, magnetic field inclination angle and Rayleigh number. It is also found that the inner shape of the annulus significantly affects the thermal flow as well as the Nusselt number.

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Metadaten
Titel
Analysis of natural convective heat transport in homocentric annuli containing nanofluids with an oriented magnetic field using nonhomogeneous dynamic model
verfasst von
M. J. Uddin
M. M. Rahman
M. S. Alam
Publikationsdatum
28.02.2017
Verlag
Springer London
Erschienen in
Neural Computing and Applications / Ausgabe 10/2018
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-017-2905-z

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