Natural convection and entropy generation of Fe3O4-H2O nanofluids in square cavities with cylindrical grooves under magnetic field

Liu, Yibo; Tian, Zhen; Qi, Cong; Li, Runjuan

doi:10.1016/j.colsurfa.2023.132564

Cited by 3 publications

(1 citation statement)

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“…These techniques involve mixing nanoparticles (NPs) with conventional base fluids, the use of fins and obstacles, and the application of magnetic fields. Liu et al [1] explored the impacts of NP concentration, MF intensity and direction, and cylindrical grooves on nanofluid convective flow 2D cavities. The results show that stepped grooves and specific magnetic configurations considerably improve heat transfer.…”

Section: Introductionmentioning

confidence: 99%

Control of Three-Dimensional Natural Convection of Graphene–Water Nanofluids Using Symmetrical Tree-Shaped Obstacle and External Magnetic Field

Aich,

Hilali-Jaghdam,

Alshahrani

et al. 2024

Symmetry

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This numerical investigation explores the enhanced control of the 3D natural convection (NC) within a cubic cavity filled with graphene–water nanofluids, utilizing a bottom-center-located tree-shaped obstacle and a horizontal magnetic field (MF). The analysis includes the effects of the Rayleigh number (Ra), the solid volume fraction of graphene (φ), the Hartmann number (Ha), and the fins’ length (W). The results show complex flow patterns and thermal behavior within the cavity, indicating the interactive effects of nanofluid properties, the tree-shaped obstacle, and magnetic field effects. The MHD effects reduce the convection, while the addition of graphene improves the thermal conductivity of the fluid, which enhances the heat transfer observed with increasing Rayleigh numbers. The increase in the fins’ length on the heat transfer efficiency is found to be slightly negative, which is attributed to the complex interplay between the enhanced heat transfer surface area and fluid flow disruption. This study presents an original combination of non-destructive methods (magnetic field) and a destructive method (tree-shaped obstacle) for the control of the fluid flow and heat transfer characteristics in a 3D cavity filled with graphene–water nanofluids. In addition, it provides valuable information for optimizing heat transfer control strategies, with applications in electronic cooling, renewable energy systems, and advanced thermal management solutions. The application of a magnetic field was found to reduce the maximum velocity and total entropy generation by about 82% and 76%, respectively. The addition of graphene nanoparticles was found to reduce the maximum velocity by about 5.5% without the magnetic field and to increase it by 1.12% for Ha = 100. Varying the obstacles’ length from W = 0.2 to W = 0.8 led to a reduction in velocity by about 23.6%.

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Section: Introductionmentioning

confidence: 99%