Lattice Boltzmann simulation of natural convection of ethylene glycol-alumina nanofluid in a C-shaped enclosure with MFD viscosity through a parallel computing platform and quantitative parametric assessment

Abstract

Abstract There has been a strong interest to design and optimise thermally efficient heating and cooling equipment. The conventional fluids such as oil and water have limited thermal efficiency. Therefore, researchers have been seeking alternatives to the conventional fluids to improve the efficacy of heat exchanging and electronic cooling devices and nanofluid has been identified as a great option in this regard. Although nanofluid is a great alternative, certain specifications, geometries, and pertinent parameters need to be thoroughly investigated for a comprehensive understanding with the aid of robust computational technique. The aim of this study was to investigate the multiple-relaxation-time (MRT) lattice Boltzmann method (LBM) to numerically analyse the effects of magnetic field dependent (MFD) viscosity on the natural convection of ethylene glycol (C2H6O2)-alumina (Al2O3) nanofluid in a side heated two-dimensional C-shaped enclosure using graphics processing unit (GPU) by a computing unified device architecture (CUDA) C parallel computing platform. Numerical simulations were performed at multifarious Rayleigh numbers, Hartmann numbers, and the different magnetic field inclination angles to study the heat transfer and various flow patterns under magnetic field-dependent (MFD) viscosity, solutions were presented by varying volume fraction of nanoparticles, Rayleigh numbers, viscous parameters, magnetic inclination angles, and Hartman numbers on streamlines, isotherms, local and average Nusselt number and temperature. Further correlation developments were conducted through Levenberg-Marquardt data-driven algorithm to investigate the influence of all the parameters on average Nusselt numbers, entropy generation, and fluid irreversibility parameter. The findings demonstrated that as the Rayleigh numbers augmented, the average Nusselt number increased significantly due to the influence of buoyancy, whereas under the influence of Hartmann numbers, average Nusselt numbers decreased due to the dominance of magnetic field strength and Lorentz force. However, the heat transfer continued to improve if the concentration of the nanoparticles increased, thus showcasing the importance of hybrid nanofluid. In addition, the entropy generation impact across the cavity for the ethylene glycol-alumina nanofluid was greatly enhanced by a stronger buoyancy influence.