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

Islam, Mashnoon; Hasan, Md Farhad; Bhowmick, Sidhartha; Kamrujjaman, Md.; Molla, Md. Mamun

doi:10.1080/01430750.2022.2160811

Cited by 12 publications

(4 citation statements)

References 75 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The second law of thermodynamics asserts that in any spontaneous activity, the overall entropy of a system either grows or remains constant; it never decreases. Total entropy, S S ¯, is computed by adding entropy by fluid friction, heat transfer and magnetic field S F ¯, S T ¯and S M ¯, respectively [27,39,40]:…”

Section: Local and Average Nusselt Numbermentioning

confidence: 99%

“…The impact of volume fraction of nanoparticles and viscous parameters has been discussed in some of the published works across different applications such as Brinkman model [44], Brinkman-Forchheimer-extended Darcy model [27], Jeffrey's fluid model [45] to investigate fluid materials. This part of the results aimed to investigate the changes in streamlines and isotherms as functions of viscous parameter (δ * ) and volume fraction of the nanoparticle (f).…”

Section: Impacts Of Viscous Parameter and Volume Fractionmentioning

confidence: 99%

“…Lattice Boltzmann method (LBM) is a popular numerical technique to investigate fluid flow and heat transfer applications [23][24][25][26]. LBM has been credited to be robust and highly accurate due to its versatility in different applications under different computational platforms The combination of LBM in high performance computing (HPC) has been reported in recent studies which is highly effective in terms of saving computational time and increasing numerical accuracy [27]. In MHD study, Hartmann (Ha) number is a parameter representing the ratio of electromagnetic force and viscous force.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

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

et al. 2023

View full text Add to dashboard Cite

The multiple-relaxation-time (MRT) lattice Boltzmann method (LBM) was considered in this study to numerically analyse the effects of magnetic field dependent (MFD) viscosity on the natural convection of ethylene glycol (C$_2$H$_6$O$_2$)-alumina (Al$_2$O$_3$) 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. The numerical solutions were presented by varying volume fraction of nanoparticles, Rayleigh numbers, viscous parameters, magnetic inclination angles, and Hartman numbers on streamlines, isotherm, 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. The findings from this study provide major evidence that the inclusion of nanofluid can be a great alternative fluid to improve the heat transfer efficiency under the influence of magnetic field strength, which can be implemented and further investigated in electronic cooling system and chip designing industry which extensively work with C-shaped equipment.

show abstract

Section: Local and Average Nusselt Numbermentioning

confidence: 99%

Section: Impacts Of Viscous Parameter and Volume Fractionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

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

et al. 2023

View full text Add to dashboard Cite

show abstract

“…LBM is one of the popular simulation techniques in nanofluid flow and heat transfer applications [21][22][23][24]. LBM has been proven to be an efficient approach through a parallel computing framework that reduces computational timescale with improved accuracy [25,26]. LBM can be efficiently integrated with GPU computing to determine solutions at the mesoscale or microscale.…”

Section: Introductionmentioning

confidence: 99%

MHD Natural Convection and Sensitivity Analysis of Ethylene Glycol Cu-Al2O3 Hybrid Nanofluids in a Chamber with Multiple Heaters: A Numerical Study of Lattice Boltzmann Method

Anee,

Hasan,

Siddiqa

et al. 2024

International Journal of Energy Research

Self Cite

View full text Add to dashboard Cite

The present work investigates the magnetohydrodynamic (MHD) convective heat transport of hybrid nanofluids in a chamber with multiple heaters (such as hot microchips). The multiple-relaxation-time (MRT) lattice Boltzmann method (LBM) and graphics processing unit (GPU) computing are used here. The present study is important due to its relevance to real-world applications, the use of advanced simulation techniques, the consideration of hybrid nanofluids, the inclusion of magnetohydrodynamics, and the identification of critical parameters influencing heat transfer. Thermally homogeneous blocks are set at the bottom of a rectangular enclosure filled with ethylene glycol Cu-Al2O3 hybrid nanofluids with temperature-dependent viscosity. The cold temperature of the enclosure’s left and right walls and the bottom and top surfaces is kept at adiabatic conditions. The numerical outcomes for the various parameters Rayleigh number (104≤Ra≤106), volume fraction (0.00≤ϕ≤0.04), Hartmann number (0≤Ha≤60), and viscosity variation parameter (0≤ε∗≤5) are presented in terms of streamlines, isotherms, and the peripheral local and average Nusselt numbers for the heated chips. The results demonstrated that inside the chamber, the Rayleigh number (Ra), the Hartmann number (Ha), and the volume fraction of nanoparticles (ϕ) have the highest impact on the heat transfer rate for hybrid nanofluid. For increased Ha from 0 to 20, while ϕ=0.0 and Ra=106, average Nusselt number decreased with 13.65%. For the same case, if the volume fraction was increased to ϕ=0.04, then the average Nusselt number decreased 14%. Finally, a sensitivity analysis was done to analyze the system’s correctness and effectiveness to determine the significance of the specified parameters.

show abstract

Mesoscopic CUDA 3D MRT-LBM Simulation of Natural Convection of Power-Law Fluids in a Differentially Heated Cubic Cavity with a Machine Learning Cross-Validation

Hasan,

Molla,

Siddiqa

et al. 2023

Arab J Sci Eng

View full text Add to dashboard Cite

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

Cited by 12 publications

References 75 publications

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

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

MHD Natural Convection and Sensitivity Analysis of Ethylene Glycol Cu-Al2O3 Hybrid Nanofluids in a Chamber with Multiple Heaters: A Numerical Study of Lattice Boltzmann Method

Mesoscopic CUDA 3D MRT-LBM Simulation of Natural Convection of Power-Law Fluids in a Differentially Heated Cubic Cavity with a Machine Learning Cross-Validation

Contact Info

Product

Resources

About