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Neural Computing and Applications
Erschienen in: Neural Computing and Applications 4/2018

03.12.2016 | Original Article

Magnetic source impact on nanofluid heat transfer using CVFEM

verfasst von: M. Sheikholeslami

Erschienen in: Neural Computing and Applications | Ausgabe 4/2018

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Abstract

Influence of variable magnetic field on Fe3O4–H2O heat transfer in a cavity with circular hot cylinder is investigated. Innovative numerical method is chosen, namely CVFEM. The effects of radiation parameter, Rayleigh and Hartmann numbers on hydrothermal characteristics are presented. Results indicated that Lorentz forces cause the nanofluid motion to decrease and augment the thermal boundary layer thickness. Temperature gradient augments with augmentation of radiation parameter, Rayleigh number, but it reduces with augmentation of Lorentz forces.
Vorheriger Artikel Cubic-RBF-ARX modeling and model-based optimal setting control in head and tail stages of cut tobacco drying process
Nächster Artikel Chaotic metaheuristic algorithms for learning and reproduction of robot motion trajectories

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Metadaten
Titel
Magnetic source impact on nanofluid heat transfer using CVFEM
verfasst von
M. Sheikholeslami
Publikationsdatum
03.12.2016
Verlag
Springer London
Erschienen in
Neural Computing and Applications / Ausgabe 4/2018
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-016-2740-7

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