In this study, the effect off adding SiO2 nanoparticles on the Viscosity of base fluid is investigated experimentally. Base fluids are chosen among common heat transfer fluids such as ethylene glycol, transformer oil and water. In addition different volume percentages of ethylene glycol in water are used as ethylene glycol-water solution. In every base fluid different volume fractions of SiO2 nanoparticles is added. It is shown that the Viscosity of solution enhance by adding nanoparticles. The effect of cooling and heating process on the Viscosity of nanofluid is also discussed. The presented data show that as the temperature increases the Viscosity of base fluid and nanofluid decrease. It is also revealed that there are very little differences between the Viscosity of nanofluid in a specific temperature at cooling and heating cycles. According to the experimental results new correlations for predicting the Viscosity of nanofluids is presented. These correlations relate the Viscosity of nanofluid to the particle volume fraction and temperature.

Dilution is one of the various existing methods in reducing heavy crude oil Viscosity. In this method, heavy crude oil is mixed with a solvent or lighter oil in order to achieve a certain Viscosity. Thus, precise mixing rules are needed to estimate the Viscosity of blend. In this work, new empirical models are developed for the calculation of the kinematic Viscosity of crude oil and diluent blends. Genetic algorithm (GA) is utilized to determine the parameters of the proposed models. 850 data points on the Viscosity of blends (i. e. 717 weight fraction-based data and 133 volume fraction-based data) were obtained from the literature. The prediction result for the volume fraction-based model in terms of the absolute average relative deviation (AARD (%)) was 8. 73. The AARD values of the binary and ternary blends of the weight fraction-based model (AARD %) were 7. 30 and 10. 15 respectively. The proposed correlations were compared with other available correlations in the literature such as Koval, Chevron, Parkash, Maxwell, Wallace and Henry, and Cragoe. The comparison results confirm the better prediction accuracy of the newly proposed correlations.

In this work, the activation energy in the Viscosity equation derived on the basis of Eyring's absolute irate theory is expressed in terms of a simple two-parameter linear function of temperature. The Viscosity data of 111 pure components are used to evaluate the parameters of activation energy and, then they are correlated in terms of each component characteristics, such as reduced boiling point and acentric factor. The results of Viscosity calculations are compared with those of the other models and are how a higher accuracy of the results obtained by the Viscosity equation used in this work.    

AHaake viscometer was used for Viscosity measurements of aqueous polyvinyl alcohol mixtures at temperatures of 288, 298, and 308 K. It was observed that at low concentration of polyvinyl alcohol, variations of the measured shear stress (τ) versus shear rate (γ) were linear and therefore, the Newtonian behaviour of the studied mixtures is considered. The modified Eyring Viscosity model previously proposed by the authors was used to test the measured data for aqueous polyvinyl alcohol mixtures. It was shown that the model is well capable to fit the data and the parameters, of the modle are evaluated.