Comparison of Empirical Models to Predict Viscosity of Secondary Vacuum Gas Oils

Dicho S Stratiev,Sotir Sotirov,Ivelina K Shishkova,Vassia Atanassova,Evdokia Sotirova,Dobromir Yordanov,Danail D Stratiev,Liliana Todorova-Yankova,Rosen K Dinkov,Kamen Zlatanov,Krassimir Atanassov,Svetoslav Nenov

doi:10.3390/resources10080082

Abstract

This work presents characterization data and viscosity of 34 secondary vacuum gas oils (H-Oil gas oils, visbreaker gas oils, and fluid catalytic cracking slurry oils) with aromatic content reaching up to 100 wt.%. Inter-criteria analysis was employed to define the secondary VGO characteristic parameters which have an effect on viscosity. Seven published empirical models to predict viscosity of the secondary vacuum gas oils were examined for their prediction ability. The empirical model of Aboul-Seud and Moharam was found to have the lowest error of prediction. A modification of Aboul-Seoud and Moharam model by separating the power terms accounting for the effects of specific gravity and average boiling point improves the accuracy of viscosity prediction. It was discovered that the relation of slope of viscosity decrease with temperature enhancement for the secondary vacuum gas oil is not a constant. This slope increases with the average boiling point and the specific gravity augmentation, a fact that has not been discussed before.

Highlights

Being an important input parameter in the chemical engineering design, viscosity prediction has concentrated the effort of many researchers on the development of various models that could estimate the viscosity of pure components and mixtures [1,2,3]
In order to evaluate the relations of the characteristics of the studied vacuum gas oils (VGOs) from Table 1 and to define these having the strongest impact on VGO viscosity, inter-criteria analysis (ICrA) was performed
Following the suggestion to separate the power term for VGO average boiling point and the specific gravity we explored the empirical model in the form: Vis = ee aABPb .D15c − d where, Vis = kinematic viscosity at 80 ◦ C, mm2 /s; ABP = VGO average boiling point, K; D15 = VGO density at 15 ◦ C, g/cm3 ; a, b, c, d, f = regression coefficients

Summary

Introduction

Being an important input parameter in the chemical engineering design, viscosity prediction has concentrated the effort of many researchers on the development of various models that could estimate the viscosity of pure components and mixtures [1,2,3]. The methods of corresponding states are based on one or more reference fluids and rely on the principle that under the same reduced conditions, the same reduced viscosity is obtained for any of the fluids in a group [24] These methods predict viscosities as functions of temperature, pressure, composition, pseudo-critical properties, and the viscosity of a reference fluid at a reference temperature and pressure. The equation of state (EOS) concept involves a mathematical relationship between volume, pressure, and temperature that includes compositional information when dealing with mixtures It can be used for different states of matter but is mostly used for gases, and no EOS application has been found for petroleum fluids [22]. Sánchez-Minero et al [17]

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Conclusion