Application of Statistical Association Fluid Theory to Predict the Amount of Asphaltene of Bitumen and Hydrocarbon Systems

Nowadays a very large majority of the roads are constructed using a mixture of bitumen and mineral aggregates. The chemical composition of the bitumen has a significant effect on its viscoelastic properties and hence its performance as road paving material in asphalts. Bitumen from crude oil distillation processes, is a complex mixture of chemical compounds that can be classified into two fraction : the maltenes and asphaltenes. It is generally believed that bitumen is a multiphasic system, better described as a colloidal dispersion in which the asphaltenes are dispersed into a matrix of the remaining components, the maltenes. The ratio of asphaltenes to the other components (aromatics, paraffins and resins) has a significant effect on viscoelastic properties of bitumens and hence on their performance on road paving binders. Therefore, the prediction of the amount of asphatene of bitumen could be significant to evaluate its quality. In this work, a thermodynamic model based on statistical association fluid theory (SAFT) was developed to predict the phase behavior of mixtures containing asphaltene components. Statistical mechanics is a molecular approach to describe macroscopic systems. The SAFT equation of state is a good candidate for closing that gap between statistical mechanic models and the classical models dominated by cubic equation of state. The essence of this theory is that the residual Helmholts enery is given by sum of expressions to account not only the effects of short-range repulsions and a long-range forces but also two other effects : chemically bonded aggregation and association and/or salvation between different molecules. A robust, fast and accurate computational algorithm was also developed to calculate the density (which is required to do phase behavior calculations and prediction of the amount of the asphaltene) using SAFT equation of state. The proposed algorithm is based on Chebyshev polynomials and is able to calculate the density of SAFT model with a relative error of less than 10-9. The application of the proposed model to several hydrocarbon mixtures and shows that there is a good agreement between the predicted values of the amount of asphaltene and those obtained using experimental procedures.

Application of Statistical Association Fluid Theory to Predict the Amount of Asphaltene of Bitumen and Hydrocarbon Systems Keywords:

Asphalt , Asphaltene , Bitumen , SAFT Equation of State , Maltenes