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Research Article

GPU-optimized LBM-MRT simulation of free convection and entropy generation of non-Newtonian power-law nanofluids in a porous enclosure at REV scale

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Pages 995-1016 | Received 07 Jun 2022, Accepted 28 Nov 2022, Published online: 29 Dec 2022
 

Abstract

The present research investigates the heat transfer and entropy generation of a non-Newtonian power-law Cu-water nanofluid in a square porous enclosure at a representative elementary volume (REV) scale using the multiple-relaxation-time lattice Boltzmann method (MRT-LBM). The Graphics Processing Unit (GPU) accelerated the computations involved. The Brinkman-Forchheimer-extended Darcy model and the shear rate dependent power-law viscosity model were taken into account to characterise the non-Newtonian fluid flow in porous medium. Three types of model validations have been conducted, followed by the mandatory grid independence test, to demonstrate the precision and accuracy of the computational code. The numerical results were obtained by varying five key parameters namely, Darcy number (Da = 10−3, 10−2, 10−1); power-law index (n = 0.6–1.0); Rayleigh number (Ra = 104, 105, 106); porosity parameter (ϵ = 0.6); volume fraction of nanoparticles (ϕ  = 0.0–0.05), and the Darcy Rayleigh number (Ram = 100, 1000). The numerically simulated outcomes were presented in terms of streamlines, isotherms, velocity, and temperature profiles as well as the Nusselt (Nu) numbers. Furthermore, a correlation among the parameters to determine the average Nu was developed using the Levenberg-Marquardt (LM) algorithm. The mathematical correlation was also subject to validations, and, in general, good correlation coefficients were obtained.

Acknowledgments

The last author would like to thank the NVIDIA Corporation, USA, for granting a TESLA K40 GPU.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The data are available based on request.

Additional information

Funding

The last author acknowledges gratefully to the North South University for the financial support as a Faculty research grant (CTRG-22-SEPS-09) and the Ministry of Science and Technology (MOST), the Government of Bangladesh, for providing the financial support for this research (grant number: EAS/SRG-222427).

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