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

Anee, Meratun Junnut; Siddiqa, Sadia; Hasan, Md Farhad; Molla, Md. Mamun

doi:10.1088/1402-4896/ace704

Cited by 5 publications

(3 citation statements)

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“…Nanofluids have become an essential component of industrial applications in recent years. The base fluid's thermal conductivity is increased when nanoparticles are dissolved in it [1,2]. This particular characteristic of nanofluids has increased their use in various technical services, such as machining and manufacturing [3,4], refrigeration [5,6], and heat and mass transfer [7][8][9].…”

Section: Introductionmentioning

confidence: 99%

“…The lattice Boltzmann method (LBM) is a popular and powerful simulation technique to model complex flow patterns [2,14] numerically. The LBM considers the fluid density on a special lattice formation and develops the analysis through simulation with streaming and collision [15,16].…”

Section: Introductionmentioning

confidence: 99%

“…2 , D f 2 , Br 2 , and φ 2 . The model terms are not considered significant if the value exceeds 0.1000.…”

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confidence: 99%

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Multiple-Relaxation-Time Lattice Boltzmann Simulation of Soret and Dufour Effects on the Thermosolutal Natural Convection of a Nanofluid in a U-Shaped Porous Enclosure

Islam,

Hasan,

Molla

2023

Energies

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This article reports an investigation of the Soret and Dufour effects on the double-diffusive natural convection of Al2O3-H2O nanofluids in a U-shaped porous enclosure. Numerical problems were resolved using the multiple-relaxation-time (MRT) lattice Boltzmann method (LBM). The indented part of the U-shape was cold, and the right and left walls were heated, while the bottom and upper walls were adiabatic. The experimental data-based temperature and nanoparticle size-dependent correlations for the Al2O3-water nanofluids are used here. The benchmark results thoroughly validate the graphics process unit (GPU) based in-house compute unified device architecture (CUDA) C/C++ code. Numeral simulations were performed for a variety of dimensionless variables, including the Rayleigh number, (Ra = 104,105,106), the Darcy number, (Da = 10−2,10−3,10−4), the Soret number, (Sr = 0.0,0.1,0.2), the Dufour number, (Df = 0.0,0.1,0.2), the buoyancy ratio, (−2≤Br≤2), the Lewis number, (Le = 1,3,5), the volume fraction, (0≤ϕ≤0.04), and the porosity, ϵ = (0.2−0.8), and the Prandtl number, Pr = 6.2 (water) is fixed to represent the base fluid. The numerical results are presented in terms of streamlines, isotherms, isoconcentrations, temperature, velocity, mean Nusselt number, mean Sherwood number, entropy generation, and statistical analysis using a response surface methodology (RSM). The investigation found that fluid mobility was enhanced as the Ra number and buoyancy force increased. The isoconcentrations and isotherm density close to the heated wall increased when the buoyancy force shifted from a negative magnitude to a positive one. The local Nu increased as the Rayleigh number increased but reduced as the volume fraction augmented. Furthermore, the mean Nu (Nu¯) decreased by 3.12% and 6.81% and the Sh¯ increased by 83.17% and 117.91% with rising Lewis number for (Ra=105 and Da=10−3) and (Ra=106 and Da=10−4), respectively. Finally, the Br and Sr demonstrated positive sensitivity, and the Ra and ϕ showed negative sensitivity only for higher values of ϕ based on the RSM.

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