Abstract
Nanofluid is a colloidal solution of nano-sized particles which enhances the thermal performance, but their viscosity put the limitation for their effective use in many industrial applications as it adversely affects the pumping power. In the present work, response surface methodology (RSM) with three-level factorial design and desirability approach was utilized to optimize thermal conductivity and viscosity of TiO2-water nanofluid simultaneously. In this regard, the impact of temperature of nanofluid (T), the concentration of nanoparticle in base fluid (phi) and diameter of nanoparticle (d(p)) on the viscosity (nu) and thermal conductivity (k) of TiO2-water nanofluid was studied. According to the results, the predicted values were in smart agreement with the experimental data. The maximum percentage error was found to be only 1.67 and 8.23 for viscosity and thermal conductivity of nanofluid, respectively, which demonstrate the preciseness of the applied model. The most dominant factors which affect the viscosity and thermal conductivity of nanofluids were found to be the temperature, concentration and the diameter of nanoparticles. The optimized values of the temperature, concentration of nanoparticles and diameter of nanoparticle obtained according to desirability approach for multi-objective optimization were T = 60 degrees C, phi = 1.41 vol% and d(p) = 60 nm.