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This study challenges the capabilities of artificial neural network (ANN) as well as response surface methodology (RSM) in estimating the viscosity (μ) and thermal conductivity (k) of β − SiC/EG and β − SiC/PG nanofluids. The implementation of these methods is performed by defining statistical criteria with a great obsession to forecast viscosity ratio as well as thermal conductivity ratio with the least error. The nanoparticle of β − SiC has a bigger effect on μEG and μPG so that they increase up to 78.71% and 56%, while kEG and kPG improve under the best conditions up to 14.64% and 4.85%, respectively. Statistical calculations show that for RSM, R-square is 0.987 for μ β − SiC / EG μ EG , 0.975 μ β − SiC / PG μ PG , 0.99 k β − SiC / EG k EG and 0.987 k β − SiC / PG k PG . This figure for ANN is 0.994, 0.992, 0.994 and 0.991. This implies that ANN ability is superior. Although β − SiC nanoparticles increase the viscosity by 78.7% (for EG) and 56% (for PG) which is not desirable, fortunately, fluid mechanics-based calculations reveal that in turbulent regime, the pumping power increases by only 17.2% and 13.5% under worst conditions.

The quiddity of ethylene glycol (EG) surface tension is attributed to the cohesive forces between EG molecules. The presence of tungsten oxide (WO3) nanoparticles certainly affects the cohesive forces and the surface tension will be affected. In this study, SITA dynotester was utilized for measuring surface tension at 20–50°C and 0.005–5 wt%. Loading nanoparticles intensified the adhesive force between EG and WO3 molecules and simultaneously attenuated cohesive forces between EG molecules. According to the results, the positive effect of the adhesive force was overcome by the negative effect of reducing the adhesion force and therefore the surface tension was weakened. At 20 ° C the EG surface tension was attenuated up to 15.57% by adding WO3 nanoparticles (5 wt%). Performing response surface methodology and artificial neural network for navigating the surface tension was successful. The acceptable R-squared for RSM (0.982) and ANN (0.99) led to maximum error of 1.43% and 0.95%.

The present investigation aims to experimentally examine the effects of shear rate, temperature, and solid concentration of nanoparticles on the rheological properties of TiO2-MWCNT (80%–20%)/oil (5 W50) nanofluid. The rheological behavior of the nanofluid, whether it is a Newtonian or non-Newtonian fluid, has been studied in different temperatures, shear rates, and solid concentrations. It is found that the nanofluid behaves as a Newtonian fluid under the conditions of the present study. In addition, the increasing trend in the dynamic viscosity of the nanofluid has been observed as the solid concentration increases. The maximum increase has been observed at the solid concentration and temperature of 2% and 50 °C, respectively, by 42%. Moreover, employing the experimental results, a new correlation for estimating the dynamic viscosity of the nanofluid in terms of temperature and solid concentrations has been proposed with the accuracy of 4%.