4.6 Article

Investigating the convection heat transfer of Fe3O4 nanofluid in a porous metal foam tube under constant magnetic field

Journal

EXPERIMENTAL THERMAL AND FLUID SCIENCE
Volume 82, Issue -, Pages 439-449

Publisher

ELSEVIER SCIENCE INC
DOI: 10.1016/j.expthermflusci.2016.12.003

Keywords

Fe3O4 nanofluid; Magnetic field; Metal foam; Forced convection

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An experimental study is conducted to investigate the convection heat transfer of Fe3O4/water nanofluid through a porous metal foam tube with uniform heat flux under the influence of constant magnetic field. This magnetic field is generated by four identical electromagnets. The electromagnets sequence is one of the most important parameters that has considerable effect on the convection heat transfer in this subject. Therefore, four different configurations of electromagnets are considered and the efficient arrangement is obtained by a numerical simulation using single-phase method in order to reach the higher heat transfer rate. Furthermore, the effects of Reynolds number, nanofluid weight fraction and magnetic field intensity on the forced convection heat transfer in the porous metal foam tube are examined under presence and absence of constant magnetic field. The experimental results show that the application of Fe3O4/water nanofluid enhances the convection heat transfer compared to DI-water. Additionally, implement of constant magnetic field leads to improve the convection heat transfer of nanofluid through the porous metal foam tube. This heat transfer improvement is more intensified in the lower fluid velocities as well as higher nanoparticle weight fractions. The maximum of 23.4% heat transfer enhancement is obtained by dispersion of 2% weight fraction of nanofluid inside the DI-water at Re = 200 under applied magnetic field of 200 G (0.02 T) intensity. A new correlation has been proposed for the Nusselt number of Fe3O4/water nanofluid in terms of Reynolds number, Prandtl number, nanoparticle weight fraction and magnetic field intensity which predicts the experimental data accurately. (C) 2016 Elsevier Inc. All rights reserved.

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