(148e) Distillation Curve and Vapor Pressure Predictions of Alcohol-Gasoline Mixtures Using an Advanced Equation of State
AIChE Annual Meeting
2020
2020 Virtual AIChE Annual Meeting
Fuels and Petrochemicals Division
Properties and Phase Equilibria for Fuels and Petrochemicals: Model Development
Monday, November 16, 2020 - 9:00am to 9:15am
Process simulators of petroleum process rely on equation of state (EoS) predictions of the phase behavior of petroleum pseudo-components defined by normal boiling point Tb, specific gravity SG, and MW. For gasoline blending these pseudo-components are typically generated from D86 curves. Hence, any method to be widely used in the prediction of alcohol / gasoline blending in refining processes should be accurate for petroleum pseudo-components.
In this work, we present a fundamental methodology for alcohol / gasoline blend property prediction using the polar PC-SAFT EoS1 combined with the recently developed petroleum parameterization methodology, TAPPS (formerly referred to as EMPETRO)2-6. TAPPS is a highly accurate methodology used to determine hydrocarbon PC-SAFT parameters for petroleum species defined solely by Tb, SG, and MW. In addition to highly accurate predictions for pure component vapor pressures and densities, TAPPS accounts for polar features of petroleum such as the fact that aromatic species receive hydrogen bonds. This makes it well suited to describe alcohol / gasoline blending.
The approach presented here employs the base gasoline D86, average gasoline SG, and dry vapor pressure equivalent (DVPE) to generate gasoline pseudo-components. Using these pseudo-components, it is demonstrated the PC-SAFT / TAPPS approach allows for the quantitative prediction of the D86 and DVPE of alcohol / gasoline mixtures. We validate the approach by reproducing both literature7,8 and ExxonMobil refinery data9 for various blends. This work demonstrates the strength of PC-SAFT / TAPPS in predicting the physical properties of non-traditional blends of petroleum streams and lays the foundation for the development of a predictive blending tool that will be valuable when considering emerging biofuel markets.
References
[1] J. Gross; G. Sadowski, Ind. Eng. Chem. Res., 40 (2001) 1244.
[2] B. D. Marshall; C. P. Bokis, Fluid Ph. Equilibria, 489 (2019) 83.
[3] B. D. Marshall; C. P. Bokis, Fluid Ph. Equilibria, 478 (2018) 34.
[4] B. D. Marshall, Fluid Ph. Equilibria, 493 (2019) 153.
[5] B. D. Marshall, Fluid Ph. Equilibria, 497 (2019) 79.
[6] B. D. Marshall, Fluid Ph. Equilibria, 507 (2020) 112420.
[7] V. F. Andersen; J. E. Andersen; T. J. Wallington; S. A. Mueller; O. J. Nielsen, Energy Fuels, 24 (2010) 2683.
[8] V. F. Andersen; J. E. Andersen; T. J. Wallington; S. A. Mueller; O. J. Nielsen, Energy Fuels, 24 (2010) 3647.
[9] J. R. Vella; B. D. Marshall, Ind. Eng. Chem. Res. (2020) accepted.