Lattice Boltzmann simulation of free convection’s hydrothermal aspects in a finned/multi-pipe cavity filled with CuO-water nanofluid

Abstract

Purpose This paper aims to investigate the natural convection fluid flow and heat transfer in a finned/multi-pipe cavity. Design/methodology/approach The cavity is filled with the CuO-water nanofluid. The Koo–Kleinstreuer–Li model is used to estimate the dynamic viscosity and consider Brownian motion. On the other hand, the effect of the shapes of nanoparticles on the thermal conductivity and related heat transfer rate is presented. Findings In the present investigation, the governing parameters are Rayleigh number, CuO nanoparticle concentration in pure water and the thermal arrangements of internal active fins and solid bodies. Impacts of these parameters on the nanofluid flow, heat transfer rate, total/local entropy generation and heatlines are presented. It is concluded that adding nanoparticles to the pure fluid has a significant positive influence on the heat transfer performance. In addition, the average Nusselt number and total entropy generation have direct a relationship with the Rayleigh number. The thermal arrangement of the internal bodies and fins is a good controlling tool to determine the desired magnitude of heat transfer rate. Originality/value The originality of this paper is to use the lattice Boltzmann method in simulating the nanofluid flow and heat transfer within a cavity included with internal active bodies and fins.

Third-grade non-Newtonian fluid flow and heat transfer in two coaxial pipes with a variable radius ratio with magnetic field

“…Although the subject of MHD non-Newtonian fluid flow and heat transfer in a pipe and coaxial cylinders has been studied (Rahimi et al, 2019;Ulker et al, 2018;Saberinejad et al, 2018;Ban et al, 2018;Malik et al, 2016), concerning the aforementioned research review, little research conducted for solving this kind of problem considering a variable radius ratio, the radial magnetic field, the viscous dissipationand the convection heat transfer boundary conditions. Furthermore, though approximate analytical solutions do not exactly satisfy the problem solution, acceptable results can be obtained by analyzing them.…”

Control of the free convective heat transfer using a U-shaped obstacle in an Al2O3-water nanofluid filled cubic cavity

“…It was found that the obstacle and the magnetic effects collaborate in controlling the flow. Rahimi et al (2019) considered a multipipe enclosure containing Cu-nanofluid at various nanoparticle concentrations. The authors mentioned that the hydrothermal properties are very sensitive to the concentration of nanoparticles.…”

Comprehensive hydrothermal analysis of an inclined mini-channel with fin array: by dual/multi-relaxation-time LBM and experimental process on SiO2-glycol rheological/thermal characteristics

“…For examples, the natural convection can be found in the solar collector, heat exchangers, cooling of electronic devices, nuclear power plants, geothermal systems, HVAC, etc. (Rahimi et al, 2019a(Rahimi et al, , 2019b(Rahimi et al, , 2019c(Rahimi et al, , 2019dHooshmand et al, 2019;Al-Rashed Abdullah et al, 2019;KhakRah et al, 2019).…”

“…The results illustrated the great impact of surface radiation on thermal rate and flow field during natural convection. Rahimi et al (2019aRahimi et al ( , 2019bRahimi et al ( , 2019cRahimi et al ( , 2019d) provided a comprehensive review paper which covers the recent works on natural convection in different types of configurations, numerical methods and operating fluids. A great variety of geometries included with different physical and thermal boundary conditions, heat sources and fluid/ nanofluid media are analyzed.…”

“…It is found that the average Nusselt number has direct relation with Rayleigh number. A three-dimensional natural convection in a cuboid is analyzed using dual-multi-relaxation-time (MRT) model LBM by Rahimi et al (2019aRahimi et al ( , 2019bRahimi et al ( , 2019cRahimi et al ( , 2019d. The enclosure is filled with nanofluid which its properties are predicted using Koo-Kleinstreuer-Li (KKL) model.…”