Abstract
This research looked at a viscoelastic Bingham hybrid Al2O3-Ag/water nanofluid’s natural convection in an inverted-T-shaped enclosure. It has been done using the mesoscopic simulation via the multiple-relaxation-time (MRT)-lattice Boltzmann method (LBM). And it employed highly effective graphics processing unit (GPU) computing to proceed with the investigation. The hybrid nanofluid’s viscosity is determined by the size of the nanoparticles and the velocity gradient, and the thermal conductivity is the function of fluid temperature. A uniform temperature boundary condition is used to heat the middle of the enclosure’s bottom wall. Other portions of the bottom and top walls are adiabatic, where the right and left walls are kept cold. Different parameters, namely the Bingham number (0≤Bn≤1), Rayleigh number (Ra=104, 105, 106), and nanoparticles volume fraction (ϕ=0,0.02,0.04), and heated sources’ size (ϵ=1/5,2/5,3/5,4/5) are applied to investigate and observe the natural convection of the fluid. Numerical outcomes are attained from the simulation and used to generate contours, figures, graphs of velocity temperature, average Nusselt number, local Nusselt number, isotherms, and streamlines. Based on the outcomes, it is observed that enhancements in Rayleigh number, heated sources’ size (ϵ), and volume fraction (ϕ) speed up the flow of the fluid. On the other hand, the Bingham number’s increment slows down the flow and decreases the value of Nu¯. The average Nusselt number increases 170.25% while increasing the length of bottom heater from ϵ=1/5 to ϵ=4/5 at ϕ=0.02, Bn=1, and Ra=106. This configuration can be applicable to electrical system cooling, ventilation, heat-exchanging system and in many other practical implements.
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