Abstract
This study intends to give qualitative results toward the understanding of different slip mechanisms impact on the natural heat transfer performance of nanofluids. The slip mechanisms considered in this study are Brownian diffusion, thermophoretic diffusion, and sedimentation. This study compares three different Eulerian nanofluid models; Single-phase, two-phase, and a third model that consists of incorporating the three slip mechanisms in a two-phase drift-flux. These slip mechanisms are found to have different impacts depending on the nanoparticle concentration, where this effect ranges from negligible to dominant. It has been reported experimentally in the literature that, with high nanoparticle volume fraction the heat transfer deteriorates. Admittingly, classical nanofluid models are known to underpredict this impairment. To address this discrepancy, this study focuses on the effect of thermophoretic diffusion and sedimentation outcome as these two mechanisms turn out to be influencing players in the resulting heat transfer rate using the two-phase model. In particular, the necessity to account for the sedimentation contribution toward qualitative modeling of the heat transfer is highlighted. To this end, correlations relating the thermophoretic and sedimentation coefficients to the nanofluid concentration and Rayleigh number are proposed in this study. Numerical experiments are presented to show the effectiveness of the proposed two-phase model in approaching the experimental data, for the full range of Rayleigh number in the laminar flow regime and for nanoparticles concentration of (0% to 3%), with great satisfaction.
Highlights
This study intends to give qualitative results toward the understanding of different slip mechanisms impact on the natural heat transfer performance of nanofluids
The natural convection flow considered in this study is presumed to be laminar as the Rayleigh number is less than 7 × 106 and three modeling approaches are employed in the simulations
The predicted average Nusselt number at the hot side for Ra = 6 × 1 06 at a nanoparticles volume fraction of 3% shows that variation with grid becomes infinitesimal after the grid size of 100 × 100 as there is less than 0.1% difference in the Nusselt number between the 100 × 100 and 120 × 120 grid size
Summary
The thermal conductivity of the base fluid gets enhanced by the suspended conductive nanoparticles such as Al2O3 with a diameter of less than 100 nm but this could cause an undesirable increase in fluid viscosity as explained by Das et al.. Several correlations have been suggested to generalize the estimation of the thermophysical properties such as thermal conductivity, specific heat capacity, viscosity, and density. Typical correlations for calculating temperature-dependent viscosity and thermal conductivity are reported in the work of Abu-Nada, Abu-Nada and C hamkha, Khanafer and V afai, Bianco et al., and Palm et al.. Typical correlations for calculating temperature-dependent viscosity and thermal conductivity are reported in the work of Abu-Nada, Abu-Nada and C hamkha, Khanafer and V afai, Bianco et al., and Palm et al.34 It is worth mentioning, that dependence of the nanofluids thermophysical properties on the base fluid pH, the surfactant type, and surfactant concentration has been reported in the literature (see Yoo et al. and Das et al.). The exclusion of the physical properties dependence on temperature is further justified by the fact that a low-temperature difference of 1 K is used in the differential heated enclosure considered
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