Search results

This paper aims to investigate numerically buoyancy-induced convection from a pair of differentially heated horizontal circular cylinders set side by side in a nanofluid-filled adiabatic square enclosure, inclined with respect to gravity so that the heated cylinder is located below the cooled one, using a two-phase model based on the double-diffusive approach assuming that the Brownian diffusion and thermophoresis are the only slip mechanisms by which the solid phase can develop a significant relative velocity with respect to the liquid phase.

The system of the governing equations of continuity, momentum and energy for the nanofluid, and continuity for the nanoparticles, is solved by a computational code based on the SIMPLE-C algorithm. Numerical simulations are performed for Al₂O₃ + H₂O nanofluids using the average volume fraction of the suspended solid phase, the tilting angle of the enclosure, the nanoparticle size, the average nanofluid temperature and the inter-cylinder spacing, as independent variables.

The main results obtained may be summarized as follows: at high temperatures, the nanofluid heat transfer performance relative to that of the pure base liquid increases with increasing the average volume fraction of the suspended solid phase, whereas at low temperatures it has a peak at an optimal particle loading; the relative heat transfer performance of the nanofluid has a peak at an optimal tilting angle of the enclosure; the relative heat transfer performance of the nanofluid increases notably as the average temperature is increased, and just moderately as inter-cylinder spacing is increased and the nanoparticle size is decreased.

The two-phase computational code used in the present study incorporates three empirical correlations for the evaluation of the effective thermal conductivity, the effective dynamic viscosity and the coefficient of thermophoretic diffusion, all based on a high number of literature experimental data.

The purpose of this study is to investigate numerically the laminar natural convection from a pair of horizontal heated cylinders, set one above the other, inside a water-filled rectangular enclosure cooled at sides, with perfectly insulated top and bottom walls, through a control-volume formulation of the finite-difference method, with the main aim to evaluate the effects of the center-to-center cylinder spacing, the size of the cavity and the temperature difference imposed between the cylinders and the cavity sides.

The system of the conservation equations of the mass, momentum and energy, expressed in dimensionless form, is solved by a specifically developed computer code based on the SIMPLE-C algorithm for the pressure-velocity coupling. Numerical simulations are executed for different values of the Rayleigh number based on the cylinder diameter, as well as the center-to-center cylinder spacing and the width of the cavity normalized by the cylinder diameter.

The main results obtained may be summarized as follows: the existence of an optimum cylinder spacing for maximum heat transfer rate is found at any investigated Rayleigh number; as a consequence of the downstream confinement, a periodic flow arises at sufficiently high Rayleigh numbers; the amplitude of oscillation of the periodic heat transfer performance of the cylinder array decreases as the cylinder spacing is increased and the cavity width is decreased, whereas the frequency of oscillations remains almost the same; at very small cavity widths, a transition from the typical two-cell to a four-cell flow pattern occurs.

The computational code used in the present study incorporates an original composite polar/Cartesian discretization grid scheme.

Laminar natural convection of nanofluids in a square cooled cavity enclosing a heated horizontal cylinder is studied numerically. This paper aims to investigate in what measure the nanoparticle size and average volume fraction, the cavity width, the cylinder diameter and position, the average temperature of the nanofluid and the temperature difference imposed between the cylinder and the cavity walls, affects the basic heat and fluid flow features, as well as the thermal performance of the nanofluid relative to that of the base liquid.

The four-equation system of the mass, momentum and energy transfer governing equations has been solved using a computational code incorporating three empirical correlations for the evaluation of the effective thermal conductivity, the effective dynamic viscosity and the coefficient of thermophoretic diffusion, all based on a high number of experimental data available in the literature. The SIMPLE-C algorithm has been used to handle the pressure-velocity coupling. Simulations have been performed using Al₂O₃ + H₂O, for different values of the average volume fraction of the suspended solid phase in the range 0-0.04, the diameter of the nanoparticles in the range 25-75 nm, the temperature difference imposed between the cylinder and the cavity walls in the range 5-20 K, the average nanofluid temperature in the range 300-330 K, the ratio between the cylinder diameter and the cavity width in the range 0.1-0.5 m, the ratio between the distance of the cylinder axis from the bottom wall and the cavity width in the range 0.2-0.8 and the ratio between the distance of the cylinder axis from the left sidewall and the cavity width in the range 0.2-0.5.

The main results obtained may be summarized as follows: the overall solid phase migration from hot to cold results in a cooperating solutal buoyancy force which tends to compensate the friction increase consequent to the viscosity growth due to the dispersion of the nanoparticles into the base fluid; the effect of the increased thermal conductivity consequent to the nanoparticle dispersion into the base fluid plays the major role in determining the heat transfer enhancement of the nanofluid, at least in the upper range of the investigated average temperatures; at high temperatures, the nanofluid heat transfer performance relative to that of the pure base liquid increases with increasing the average volume fraction of the suspended solid phase, whereas at low temperatures, it has a peak at an optimal particle loading; the relative heat transfer performance of the nanofluid increases notably with increasing the average temperature, and just moderately as the imposed temperature difference, the width of the cavity and the distance of the cylinder from the bottom of the cavity, are increased; the relative heat transfer performance of the nanofluid increases as the nanoparticle size, the cylinder diameter and the distance of the cylinder from the sidewall, are decreased; as a consequence of the local competition between the thermal and the solutal buoyancy forces, a periodic flow arises when the cylinder is located in the vicinity of one of the cooled walls of the enclosure.

Framed in this general background, a comprehensive numerical study on buoyancy-driven convection of alumina-water nanofluids inside a cooled square cavity containing a heated circular cylinder is executed by the way of a two-phase model based on the double-diffusive approach accounting for the effects of the Brownian diffusion and thermophoresis.

The purpose of this paper is to focus on the advanced solution of the parametric non-linear model related to the Rayleigh-Benard laminar flow involved in the modeling of natural thermal convection. This flow is fully determined by the dimensionless Prandtl and Rayleigh numbers. Thus, if one could precompute (off-line) the model solution for any possible choice of these two parameters the analysis of many possible scenarios could be performed on-line and in real time.

In this paper both parameters are introduced as model extra-coordinates, and then the resulting multidimensional problem solved thanks to the space-parameters separated representation involved in the proper generalized decomposition (PGD) that allows circumventing the curse of dimensionality. Thus the parametric solution will be available fast and easily.

Such parametric solution could be viewed as a sort of abacus, but despite its inherent interest such calculation is at present unaffordable for nowadays computing availabilities because one must solve too many problems and of course store all the solutions related to each choice of both parameters.

Parametric solution of coupled models by using the PGD. Model reduction of complex coupled flow models. Analysis of Rayleigh-Bernard flows involving nanofluids.