Industrial & Engineering Chemistry Research, Vol.54, No.45, 11448-11465, 2015
Determination of Perturbed-Chain Statistical Association Fluid Theory Parameters for Pure Substances, Single Carbon Number Groups, and Petroleum Fractions Using Cubic Equations of State Parameters
A new-generation equation of state, perturbed-chain statistical association fluid theory (PC-SAFT), has attracted much attention to modeling the phase behavior of fluids using molecular-based equations of state. A set of three pure component parameters is needed for non-associative compounds, conventionally determined by fitting vapor pressure and liquid density data simultaneously. Unfortunately, experimental data are scarce, and the number of pure substances is too large. Thus, it is indispensable for developing predictive methods to determine the pure component parameters. In the present paper, a new model has been developed to estimate PC-SAFT parameters for different pure components, single carbon number (SCN) groups, and petroleum fractions through the connection established between classical and molecular corresponding states theories and creating a relationship between cubic equation-of-state parameters (critical pressure, critical temperature, and acentric factor) and PC-SAFT parameters. Accordingly, the proposed model requires five input parameters: critical pressure (P-c), critical temperature (T-c), acentric factor (omega), mass density at 288 K (Rho m*), and molecular weight (M-w). A comparison is performed between the proposed model and the existing correlations used to estimate pure component PC-SAFT parameters. Moreover, experimental vapor pressure and liquid phase density data of 53 pure substances from 14 diverse families of compounds (in addition to data applied for the development of model) were collected to verify the accuracy of parameters estimated by the proposed model in the calculation of vapor pressure and liquid phase density. Experimental bubble pressure and liquid density data of three oil samples were also collected in order to check the reliability of the proposed model in the estimation of PC-SAFT parameters for SCN groups and petroleum fractions. Results of the comparison show that the proposed model is capable of estimating PC-SAFT parameters for both pure substances and SCN groups with average absolute deviations less than 1.21% and 1.05% of saturation pressure and liquid density, respectively.