Abstract
The fluids containing nanoparticles have enhanced thermo-physical characteristics in comparison with conventional fluids without nanoparticles. Thermal conductivity and viscosity are thermo-physical properties that strongly determine heat transfer and momentum. In this study, the response surface method was firstly used to derive an equation for the thermal conductivity and another one for the viscosity of bioglycol/water mixture (20:80) containing silicon dioxide nanoparticles as a function of temperature as well as the volume fraction of silicon dioxide. Then, NSGA-II algorithm was used for the optimization and maximizing thermal conductivity and minimizing the nanofluid viscosity. Different fronts were implemented and 20th iteration number was selected as Pareto front. The highest thermal conductivity (0.576 W/m.K) and the lowest viscosity (0.61 mPa.s) were obtained at temperature on volume concentration of (80 °C and 2%) and (80 °C without nanoparticle) respectively. It was concluded that the optimum thermal conductivity and viscosity of nanofluid could be obtained at maximum temperature (80 °C) or a temperature close to this temperature. An increase in the volume fraction of silicon dioxide led to the enhancement of thermal conductivity but the solution viscosity was also increased. Therefore, the optimum point should be selected based on the system requirement.
Highlights
Optimization is the art of finding the best answer among existing conditions
The experimental data reported in the literature (Abdolbaqi et al, 2016) was used to derive thermal conductivity and dynamic viscosity equations as a function of operating parameters
The equations were obtained for the thermal conductivity and dynamic viscosity as function of operating condition using response surface method
Summary
Optimization is the art of finding the best answer among existing conditions. It is highly important in the engineering systems design to minimize the cost and maximizing the net profit (Hemmat Esfe et al, 2017b). Determination of nanofluid viscosity containing SiO2 or Al2O3 was experimentally conducted and response surface model was used to generate an equation for the viscosity as a function of volume concentration ad temperature. Effect of temperature (26 – 50 °C) and the hybrid nanoparticles volume fraction (SWCNT-ZnO (30%70%)) (0.05% À1.6%) in ethylene glycol–water (60%-40%) base fluid on the nanofluid thermal conductivity was studied by Safe et al (Hemmat Esfe et al, 2017a). Zyla and Fal (Z_ yła and Fal, 2017) investigated thermophysical properties of SiO2–ethylene glycol nanofluids and there was a linear increase in thermal conductivity and viscosity with an increase in the nanoparticle volume fraction. The experimental data was used to determine the thermal conductivity and viscosity equations as function of temperature and volume fraction by the response surface method
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