Numerical investigation of heat transfer in a power-law non-Newtonian fluid in a C-Shaped cavity with magnetic field effect using finite difference lattice Boltzmann method

Purpose The purpose of this paper is to investigate the compact finite-difference lattice Boltzmann method is used to simulate the free convection within a cavity. Design/methodology/approach The finite-difference discretization method enables the numerical simulations to be run when there are non-uniform and curvilinear grids with a finer near-wall grid resolution. Furthermore, the high-order method is applied in the numerical approach, which makes it possible to go with relatively coarse mesh in respect to simulations, which used classical lattice Boltzmann method. The configuration of the cavity is set to sine-walled square. In addition, the cavity is filled with Al2O3-water nanofluid, and the Koo–Kleinstreuer–Li model is used to estimate the properties of nanofluid. Findings The nanoparticle (Al2O3) concentration in the base fluid (water) is considered in a range of 0-0.04. The nanofluid flow and heat transfer are investigated in laminar regime with Rayleigh number in the range of 103-106. The second law analysis is used to study the effects of different governing parameters on the local and volumetric entropy generation. The Rayleigh number, configuration of the cavity and nanoparticle concentration are considered as the governing parameters. The results are mainly focused on the flow structure, temperature field, local and volumetric entropy generation and heat transfer performance. Originality/value The originality of this study is using of a modern numerical method supported by an accurate prediction for nanofluid properties to simulate the flow and heat transfer during natural convection in a cavity.

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Magnetic field effects on natural convection and entropy generation of non-Newtonian fluids using multiple-relaxation-time lattice Boltzmann method

International Journal of Modern Physics C ◽

10.1142/s0129183121500157 ◽

2020 ◽

pp. 2150015

Author(s):

Aimon Rahman ◽

Preetom Nag ◽

Md. Mamun Molla ◽

Sheikh Hassan

Keyword(s):

Magnetic Field ◽

Heat Transfer ◽

Entropy Generation ◽

Lattice Boltzmann ◽

Hartmann Number ◽

Magnetic Field Effect ◽

Multiple Relaxation Time ◽

Number Formula ◽

Boltzmann Method ◽

The Magnetic Field

The magnetic field effect on natural convection flow of power-law (PL) non-Newtonian fluid has been studied numerically using the multiple-relaxation-time (MRT) lattice Boltzmann method (LBM). A two-dimensional rectangular enclosure with differentially heated at two vertical sides has been considered for the computational domain. Numerical simulations have been conducted for different pertinent parameters such as Hartmann number, [Formula: see text], Rayleigh number, [Formula: see text], PL indices, [Formula: see text]–1.4, Prandtl number, [Formula: see text], to study the flow physics and heat transfer phenomena inside the rectangular enclosure of aspect-ratio [Formula: see text]. Numerical results show that the heat transfer rate, quantified by the average Nusselt number, is attenuated with increasing the magnetic field, i.e. the Hartmann number (Ha). However, the average Nusselt number is increased by increasing the Rayleigh number, [Formula: see text] and decreasing the PL index, [Formula: see text]. Besides, the generation of entropy for non-Newtonian fluid flow under the magnetic field effect has been investigated in this study. Results show that in the absence of a magnetic field, [Formula: see text], fluid friction and heat transfer irreversibilities, the total entropy generation decreases and increases with increasing [Formula: see text] and [Formula: see text], respectively. In the presence of the magnetic field, [Formula: see text], the fluid friction irreversibility tends to decrease with increasing both the shear-thinning and shear thickening effect. It is noteworthy that strengthening the magnetic field leads to pulling down the total entropy generation and its corresponding components. All simulations have been performed on the Graphical Processing Unit (GPU) using NVIDIA CUDA and employing the High-Performance Computing (HPC) facility.

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