Turbulent Forced Convection Of Nanofluids Research Articles

Thermal prediction of turbulent forced convection of nanofluid using computational fluid dynamics coupled genetic algorithm with fuzzy interface system

Computational fluid dynamics (CFD) simulating is a useful methodology for reduction of experiments and their associated costs. Although the CFD could predict all hydro-thermal parameters of fluid flows, the connections between such parameters with each other are impossible using this approach. Machine learning by the artificial intelligence (AI) algorithm has already shown the ability to intelligently record engineering data. However, there are no studies available to deeply investigate the implicit connections between the variables resulted from the CFD. The present investigation tries to conduct cooperation between the mechanistic CFD and the artificial algorithm. The genetic algorithm is combined with the fuzzy interface system (GAFIS). Turbulent forced convection of Al2O3/water nanofluid in a heated tube is simulated for inlet temperatures (i.e., 305, 310, 315, and 320 K). GAFIS learns nodes coordinates of the fluid, the inlet temperatures, and turbulent kinetic energy (TKE) as inputs. The fluid temperature is learned as output. The number of inputs, population size, and the component are checked for the best intelligence. Finally, at the best intelligence, a formula is developed to make a relationship between the output (i.e. nanofluid temperatures) and inputs (the coordinates of the nodes of the nanofluid, inlet temperature, and TKE). The results revealed that the GAFIS intelligence reaches the highest level when the input number, the population size, and the exponent are 5, 30, and 3, respectively. Adding the turbulent kinetic energy as the fifth input, the regression value increases from 0.95 to 0.98. This means that by considering the turbulent kinetic energy the GAFIS reaches a higher level of intelligence by distinguishing the more difference between the learned data. The CFD and GAFIS predicted the same values of the nanofluid temperature.

Turbulent forced convection of nanofluid in an elliptic cross-sectional pipe

In this study, numerical analysis of forced convection in a thee dimensional pipe with elliptic cross-section is considered by using CNT-water nanofluid as working fluid. Three dimensional steady flow and heat transfer equations with k- ϵ turbulence model is solved by using finite element method. Effects of aspect ratio of elliptic cross-section and solid nanoparticle volume fraction on the heat transfer performance were analyzed. An experimental validation of the numerical study was performed and comparisons were made with other existing correlations for turbulent flow in a pipe. It was observed that significant enhancements in the heat transfer rate are achieved with the use of CNT nanoparticles which are in the range of 59% to 84% depending on the mass flow rate. The average Nusselt number deteriorates for higher values of aspect ratio in turbulent three dimensional configuration while the trends are similar for fluid and nanofluid. When the aspect ratio enhances from 0.5 to 1.67, approximately 53% reduction of average Nusselt number is obtained both for water and for nanofluid. Finally, a practical modeling strategy for estimating the average Nusselt number is proposed which uses linear interpolation among polynomial model coefficients for water and for nanofluid at the highest solid particle volume fraction.

Experimental and numerical study of nanofluid forced convection in a channel with artificial roughness

The turbulent forced convection of nanofluids with ZrO2 nanoparticles in a channel with artificial roughness was experimentally and numerically investigated. Nanoparticle concentration in the experiments was equal to 4 vol. %. The nanoparticle size ranged from 44 to 105 nm. Numerical simulation of turbulent forced convection of nanofluids in a channel with annular knurls was carried out. A homogeneous model with experimentally determined transport coefficients was used to describe the nanofluid.

Turbulent forced convection of nanofluids downstream an abrupt expansion

Turbulent forced convection of Nanofluids through an axisymmetric abrupt expansion is investigated numerically in the present study. The governing equations are solved by ANYS 14.0 CFD code based on the finite volume method by implementing the thermo-physical properties of each nanofluid. All results are analyzed through the evolutions of skin friction coefficient and Nusselt number. For each nanofluid, the effect of both volume fraction and Reynolds number on this type of flow configuration, are examined. An increase on average Nusselt number with the volume fraction and Reynolds number, are highlighted and correlated. Two relationships are proposed. The first one, determines the average Nusselt number versus Reynolds number, volume fraction and the ratio of densities of the solid particles to that of the base fluid ( $$ \overline{Nu}=f\left(\operatorname{Re},\phi, \frac{\rho_s}{\rho_f}\right) $$ ). The second one varies according Reynolds number, volume fraction and the conductivities ratio of solid particle to that of the base fluid ( $$ \overline{Nu}=f\left(\operatorname{Re},\phi, \frac{k_s}{k_f}\right) $$ ).

Experimental study of turbulent forced convection of nanofluid in channels with cylindrical and spherical hollows

Experimental study of forced turbulent convection of water-based nanofluids with nanoparticles of zirconium oxide (ZrO2) was carried out in smooth tubes and channels with wall heat transfer enhancers. Nanopowders with average particle size of 44 and 105nm were used in the experiments. The Reynolds number ranged from 3000 to 8000. It is revealed that the increments in the heat transfer coefficient and the pressure drop when using nanofluids depend on the surface shape of the channel. It is shown that nanofluids allow reaching thermal-hydraulic efficiency comparable to that of the channels with artificial heat transfer enhancers.

Analysis of heat transfer of different nanofluids flow through an abrupt expansion pipe

Turbulent forced convection of nanofluids through an axisymmetric abrupt expansion is investigated numerically in the present study. Finite volume method is used to solve the governing equations. All results are analyzed through the thermal and dynamic fields, particularly the evolutions of skin friction coefficient and Nusselt number. The influence of nanofluid’s volume fraction and Reynolds number on this type of flow configuration was examined. The analysis is detailed for pure water and four nanofluids (Ag-water, Cu-water, CuO-water and Al2O3-water). All results evidence an increase of average Nusselt number with increasing the volume fraction and Reynolds number. Two correlations of average Nusselt number are proposed. The first correlation expresses the average Nusselt number versus Reynolds number, volume fraction and the ratio of densities of solid particles to that of the base fluid Nu‾=fRe,ϕ,ρsρf. The second one relates Reynolds number, volume fraction and the conductivity ratio of solid particle to that of the base fluid Nu‾=fRe,ϕ,kskf.

Numerical simulation and optimization of turbulent nanofluids in a three-dimensional arc rib-grooved channel

ABSTRACTIn this study, numerical simulations by single- and two-phase models of nanofluids turbulent forced convection in a three-dimensional arc rib-grooved channel with constant wall temperature are investigated. The elliptical, coupled, steady-state, three-dimensional governing partial differential equations for turbulent forced convection of nanofluids are solved numerically using the finite volume approach. The average Nusselt number of arc rib-grooved channels is found to improve more with smaller rib-grooved height ratios, and some ratios of arc rib-grooved pitch. In addition, the optimization of this problem is also presented by using the response surface methodology (RSM) and the genetic algorithm (GA) method. It is found that the objective function E is better at Re = 10,000, and the arc rib-groove has a 42.1% enhancement.

Study of turbulent heat transfer of the nanofluids in a cylindrical channel

The experiment investigation of turbulent forced convection of nanofluids with SiO2 and Al2O3 nanoparticles was carried out. Nanoparticle concentration varied in the range from 0.5 to 2vol.% in the experiments. The nanoparticle size ranged from 10 to 100nm. The dependence of heat transfer coefficient and pressure drop from the concentration, size, material of the nanoparticles and temperature was studied. It was shown that adding nanoparticles to the coolant significantly influences the heat transfer coefficient in the turbulent flow regime. It is shown that with increasing nanoparticles concentration, the local and average heat transfer coefficients at a fixed Reynolds number increase. Decrease in heat transfer coefficient with increasing particles concentration may take place at a fixed flow rate. It is shown that, the heat transfer coefficient of the nanofluid in turbulent regime increases with increasing nanoparticles size at a fixed flow rate, while has a certain maximum at a fixed Reynolds number. The effect of nanoparticles material on the heat transfer coefficient and pressure loss has been also demonstrated. It is found that the inlet temperature is another factor having a significant effect on turbulent heat transfer performance of nanofluids.

Effects of different models of thermal conductivity on turbulent nanofluid flow through rectangular cavity in duct

This article concerns the turbulent forced convection of nanofluids confined in a shallow cavity heated from all sides with a uniform temperature. This study aims to make a numerical analysis on the performance of a nanofluid composed of solid particles of alumina (Al2O3) dispersed in a base fluid (pure water) for various models of the thermal conductivity. The governing equations of the hydrodynamic flow and heat transfer are discretized by the finite volume method using a drawing power law. Numerical simulations are performed for a Reynolds number ranging from 4×104–105 and a volume fraction of the nanoparticles between 0 and 0.04. The obtained results show that the heat transfer is enhanced with the studied parameters for all models of thermal conductivity.

Numerical simulation and optimization of turbulent nanofluids in a three-dimensional rectangular rib-grooved channel

In this study, numerical simulations by single and two-phase models of nanofluids turbulent forced convection in a three-dimensional rectangular rib-grooved channel with constant wall temperature are investigated. The elliptical, coupled, steady-state, three-dimensional governing partial differential equations for turbulent forced convection of nanofluids are solved numerically using the finite volume approach. The standard k−ε turbulence model is applied to solve the turbulent governing equations. The interactive influences of rectangular rib-groove geometrical ratios and nanofluid volume concentration on the average Nusselt number are provided in this study. The average Nusselt number of rib-grooved channel is found to improve more with smaller rib-grooved height ratios, and some ratios of rib-grooved pitch. Furthermore, the numerical results of the single and two-phase models show that there are some differences in simulated flow filed and turbulent convective heat transfer characteristics.In addition, the optimization of this problem is also presented by using the response surface methodology (RSM) and the genetic algorithm method (GA). The objective function E defined as the performance factor has developed a correlation function with four design parameters. It is found that the objective function E is better at Re=10,000, and rectangular rib-grooved has an 18.2% enhancement.

Turbulent forced convection of nanofluid over a heated shallow cavity in a duct

This work presents a numerical investigation of turbulent forced convection of a nanofluid over a heated cavity in a horizontal duct. The objective of this study is to show the effects of nanofluid on heat transfer in such a configuration. The two-dimensional Cartesian coordinate system is used to solve the governing equations which are conservations of mass, momentum and energy. The numerical predictions based on finite volume method are performed by ANSYS FLUENT 14.0 CFD code. Numerical simulations are carried out for pure water and four different nanofluids (water–Cu, water–CuO, water–Ag and water–Al2O3). The results are analyzed through the thermal and dynamical fields with a particular interest to the kinetic energy, skin friction coefficient and Nusselt number evolutions. The range of parameters of Reynolds number is 40,000≤Re≤100,000 and different nanoparticle volume fractions. The maximum shear stress is obtained for the lightest nanoparticle of smaller thermal conductivity (Al2O3). It is found that the average Nusselt number increases with the volume fraction of nanoparticles for the whole tested range of Reynolds number. The nanoparticle type on average Nusselt number has an insignificant effect; the smallest values are obtained for the heavier particle with greatest value of thermal conductivity (Ag). Two correlations of average Nusselt number versus Reynolds number and volume fraction of each type of nanoparticles over the cavity wall are proposed in this paper.

Turbulent forced convection of nanofluid in a wavy channel using two phase model

Two phase mixture model is used to numerically simulate the turbulent forced convection of Al2O3-Water nanofluid in a channel with corrugated wall under constant heat flux. Both mixture and single phase models are implemented to study the nanofluid flow in such a geometry and the results have been compared. The effects of the volume fraction of nanoparticles, Reynolds number and amplitude of the wavy wall on the rate of heat transfer are investigated. The results showed that with increasing the volume fraction of nanoparticles, Reynolds number and amplitude of wall waves, the rate of heat transfer increases. Also the results showed that the mixture model yields to higher Nusselt numbers than the single phase model in a similar case.