Recent research contributions concerning use of nanofluids in heat exchangers: A critical review

In recent years, the study of rheological behavior and heat transfer of nanofluids in the industrial equipment has become widespread among the researchers and their results have led to great advancements in this field. In present study, the laminar flow and heat transfer of water/functional multi-walled carbon nanotube nanofluid have been numerically investigated in weight percentages of 0.00, 0.12 and 0.25 and Reynolds numbers of 1–150 by using finite volume method (FVM). The analyzed geometry is a two-dimensional backward-facing contracting channel and the effects of various weight percentages and Reynolds numbers have been studied in the supposed geometry. The results have been interpreted as the figures of Nusselt number, friction coefficient, pressure drop, velocity contours and static temperature. The results of this research indicate that, the enhancement of Reynolds number or weight percentage of nanoparticles causes the reduction of surface temperature and the enhancement of heat transfer coefficient. By increasing Reynolds number, the axial velocity enhances, causing the enhancement of momentum. By increasing fluid momentum at the beginning of channel, especially in areas close to the upper wall, the axial velocity reduces and the possibility of vortex generation increases. The mentioned behavior causes a great enhancement in velocity gradients and pressure drop at the inlet of channel. Also, in these areas, Nusselt number and local friction coefficient figures have a relative decline, which is due to the sudden reduction of velocity. In general, by increasing the mass fraction of solid nanoparticles, the average Nusselt number increases and in Reynolds number of 150, the enhancement of pumping power and pressure drop does not cause any significant changes. This behavior is an important advantage of choosing nanofluid which causes the enhancement of thermal efficiency.

The numerical modeling of water/FMWCNT nanofluid flow and heat transfer in a backward-facing contracting channel

In the present numerical study, mixed flow of the non-Newtonian water/Al2O3 nanofluid with 0–4% nanoparticles volume fractions (φ) inside a two-dimensional square cavity with hot and cold lid-driven motion and porous media is simulated at Richardson numbers (Ri) of 0.01, 10 and 100 and Darcy numbers (Da) of 10−4 ≤ Da ≤ 10−2 using Fortran computer code. The obtained results for temperature domain, velocity, Nusselt number and streamlines indicate that by increasing Richardson number and decreasing axial velocity parameter of walls and similarity of flow behavior to natural flow mechanism, variations of velocity are reduced, which is due to the reduction in fluid momentum. By increasing Darcy number, penetrability of fluid motion enhances and fluid lightly moves along the cavity. Figuration of streamlines at lower Richardson numbers highly depends on the Darcy number changes. In case (2), due to the counterflow motion and buoyancy force, distinction of flow domain profiles is more obvious. On the other hand, this issue causes more velocity gradients and vortexes in special sections of cavity (central regions of cavity). In case (2), the behavior of streamlines is affected by some parameters such as variations of Darcy number, nanoparticles volume fraction and Richardson number more than case (1). By increasing Darcy number, flow lightly passes among hot and cold sources and leads to improve the heat transfer. Moreover, reduction in flow penetrability in cavity results in the reduction in fluid flow in its direction, sectional distribution and regions with higher temperature. Consequently, in these regions the growth of thermal boundary layer is more significant. In case (2), at lower Richardson numbers compared to higher ones, the affectability of lid-driven motion contrary to buoyancy force caused by density variations is less because of higher fluid momentum. At Ri = 0.01, because of the strength of lid-driven motion, flow direction is compatible with lid-driven motion. Also, temperature distribution is not uniform, and in these regions, fluid has the minimum velocity which leads to the enhancement of dimensionless temperature. In both studied cases, the increment of nanoparticles volume fraction as well as Darcy number and reduction in Richardson number result in the improvement of temperature distribution and decrease in dimensionless temperature.

Numerical study on mixed convection of a non-Newtonian nanofluid with porous media in a two lid-driven square cavity

In the present study, heat transfer and fluid flow of a pseudo-plastic non-Newtonian nanofluid over permeable surface has been solved in the presence of injection and suction. Similarity solution method is utilized to convert the governing partial differential equations into ordinary differential equations, which then is solved numerically using Runge–Kutta–Fehlberg fourth–fifth order (RKF45) method. The Cu, CuO, TiO2 and Al2O3 nanoparticles are considered in this study along with sodium carboxymethyl cellulose (CMC)/water as base fluid. Validation has been done with former numerical results. The influence of power-law index, volume fraction of nanoparticles, nanoparticles type and permeability parameter on nanofluid flow and heat transfer was investigated. The results of the study illustrated that the flow and heat transfer of non-Newtonian nanofluid in the presence of suction and injection has different behaviors. For injection and the impermeable plate, the non-Newtonian nanofluid shows a better heat transfer performance compared to Newtonian nanofluid. However, changing the type of nanoparticles has a more intense influence on heat transfer process during suction. It was also observed that in injection, contrary to the other two cases, the usage of non-Newtonian nanofluid can decrease heat transfer in all cases.

Flow and heat transfer in non-Newtonian nanofluids over porous surfaces

In this paper, the experimental data on the thermal conductivity of EG based hybrid nanofluid containing zinc oxide and titanium oxide have been used. At the first, three two-variable correlations have been proposed using curve-fitting on experimental data. After that, the best transfer function for training the artificial neural network has been selected. The input variables of neural network were temperature and solid volume fraction, while the output variable was the thermal conductivity enhancement of the nanofluid. Moreover, the correlation outputs, ANN results and experimental data have been compared. The results showed that there is a good agreement between experimental data and neural network results so that the resulting model of the neural network is able to predict the thermal conductivity enhancement of the nanofluid. The findings also indicated that the accuracy of the neural network is much greater than the curve fitting method to predict thermal conductivity enhancement of ZnO-TiO2/EG hybrid nanofluid.

Evaluating the effect of temperature and concentration on the thermal conductivity of ZnO-TiO2/EG hybrid nanofluid using artificial neural network and curve fitting on experimental data

Investigation of turbulent heat transfer and nanofluid flow in a double pipe heat exchanger

This paper aims to study forced convection in a double tube heat exchanger using nanofluids with constant and variable thermophysical properties.,The cold fluid was distilled water flowing in the annulus and the hot fluid was aluminum oxide/water nanofluid which flows in the inner tube. Thermal conductivity and viscosity were taken as variable thermophysical properties, and the results were compared against runs with constant values. Finite volume method was used for solving the governing equations. For distilled water, Re = 500 was used, while for nanofluid, nanoparticles volume fraction equal to 2.5-10 per cent and Re = 100-1,500 were used.,Heat transfer rate can be enhanced by increasing the volume fraction of nanoparticles and Reynolds number. Thermal efficiency is better with constant thermophysical characteristics and the average Nusselt number is better for variable characteristics.,Heat exchanger efficiency is evaluated by using distilled water and nanofluid bulk temperature, thermal efficiency and average and local Nusselt numbers for both variable and constant thermophysical characteristics.

Mohammad Hussein Bahmani

Papers

Investigation of turbulent heat transfer and nanofluid flow in a double pipe heat exchanger

Forced convection in a double tube heat exchanger using nanofluids with constant and variable thermophysical properties