Hydrothermal Characteristics of Spinel Manganese Ferrite Nanofluid in a Metal Foam Tube: Modeling of Experimental Results using Artificial Neural Network

Abstract

ABSTRACTIn this research, an experimental evaluation is conducted on the hydrothermal behavior of water-based manganese ferrite nanofluid flowing in a metal foam tube. For this purpose, manganese ferrite nanoparticles are synthesized, and X-ray diffraction and scanning electron microscopy are implemented to specify the samples for determination of phase and size of nanoparticles. The effects of Reynolds number, Prandtl number, and presence of MnFe2O4 nanoparticles inside the water on the Nusselt number and friction factor have been studied. The experimental analysis shows that the increment of Reynolds number, Prandtl number, and nanoparticles concentration improve the heat transfer performance. The maximum of 19.1% and 10.5% increase in Nusselt number and friction factor have been achieved respectively by dispersion of 2 wt% manganese ferrite nanoparticles inside the deionized water at Reynolds number of 1,000. A hydrothermal index is proposed to consider the thermal and hydrodynamic characteristics of the nanofluid, and it is attained that the convection heat transfer improvement dominates the pressure drop in this work. According to the experimental results, the Nusselt number and friction factor of the nanofluid is modeled as a function of Reynolds number, Prandtl number, and nanoparticles concentration using artificial neural network with an acceptable precision.