Group Contribution Prediction of Vapor Pressure with Statistical Associating Fluid Theory, Perturbed-Chain Statistical Associating Fluid Theory, and Elliott−Suresh−Donohue Equations of State

2008 ◽  
Vol 47 (21) ◽  
pp. 8401-8411 ◽  
Author(s):  
Fateme Sadat Emami ◽  
Amir Vahid ◽  
J. Richard Elliott ◽  
Farzaneh Feyzi
Keyword(s):  
Vapor Pressure ◽  
Equations Of State ◽  
Group Contribution ◽  
Statistical Associating Fluid Theory ◽  
Fluid Theory

scholarly journals Modelling of Diesel fuel properties through its surrogates using Perturbed-Chain, Statistical Associating Fluid Theory

2018 ◽  
Vol 21 (7) ◽  
pp. 1118-1133 ◽  
Author(s):  
Alvaro Vidal ◽  
Carlos Rodriguez ◽  
Phoevos Koukouvinis ◽  
Manolis Gavaises ◽  
Mark A McHugh
Keyword(s):  
Equation Of State ◽  
Diesel Fuel ◽  
Group Contribution ◽  
Operating Conditions ◽  
Fuel Properties ◽  
Liquid Density ◽  
Theory Approach ◽  
Statistical Associating Fluid Theory ◽  
Diesel Fuels ◽  
Fluid Theory

The Perturbed-Chain, Statistical Associating Fluid Theory equation of state is utilised to model the effect of pressure and temperature on the density, volatility and viscosity of four Diesel surrogates; these calculated properties are then compared to the properties of several Diesel fuels. Perturbed-Chain, Statistical Associating Fluid Theory calculations are performed using different sources for the pure component parameters. One source utilises literature values obtained from fitting vapour pressure and saturated liquid density data or from correlations based on these parameters. The second source utilises a group contribution method based on the chemical structure of each compound. Both modelling methods deliver similar estimations for surrogate density and volatility that are in close agreement with experimental results obtained at ambient pressure. Surrogate viscosity is calculated using the entropy scaling model with a new mixing rule for calculating mixture model parameters. The closest match of the surrogates to Diesel fuel properties provides mean deviations of 1.7% in density, 2.9% in volatility and 8.3% in viscosity. The Perturbed-Chain, Statistical Associating Fluid Theory results are compared to calculations using the Peng–Robinson equation of state; the greater performance of the Perturbed-Chain, Statistical Associating Fluid Theory approach for calculating fluid properties is demonstrated. Finally, an eight-component surrogate, with properties at high pressure and temperature predicted with the group contribution Perturbed-Chain, Statistical Associating Fluid Theory method, yields the best match for Diesel properties with a combined mean absolute deviation of 7.1% from experimental data found in the literature for conditions up to 373°K and 500 MPa. These results demonstrate the predictive capability of a state-of-the-art equation of state for Diesel fuels at extreme engine operating conditions.

scholarly journals Application of PC-SAFT and cubic equations of state for the correlation of solubility of some pharmaceutical and statin drugs in SC-CO2

2013 ◽  
Vol 19 (3) ◽  
pp. 449-460 ◽  
Author(s):  
El Abdallah ◽  
C. Si-Moussa ◽  
S. Hanini ◽  
M. Laidi
Keyword(s):  
Experimental Data ◽  
Equations Of State ◽  
Van Der Waals ◽  
Energy Parameter ◽  
Pure Component ◽  
Binary Interaction ◽  
Statistical Associating Fluid Theory ◽  
Binary Interaction Parameters ◽  
Fluid Theory ◽  
Statin Drugs

In this work, the solubilities of some anti-inflammatory (nabumetone, phenylbutazone and salicylamide) and statin drugs (fluvastatin, atorvastatin, lovastatin, simvastatin and rosuvastatin) were correlated using the Perturbed-Chain Statistical Associating Fluid Theory (PC-SAFT) with one-parameter mixing rule and commonly used cubic equations of state Peng-Robinson (PR) and Soave-Redlich-Kwong (SRK) combining with van-der Waals-1 parameter (VDW1) and van-der Waals-2 parameters (VDW2) mixing rules. The experimental data for studied compounds were taken from literature at temperature and pressure in ranges (308-348 K) and (100-360 bar) respectively. The critical properties required for the correlation with PR and SRK were estimated using Gani and Noonalol contribution group methods whereas, PC-SAFT pure-component parameters; segment number (m), segment diameter (?) and energy parameter (?/k) have been estimated by tihic?s group contribution method for nabumetone. For phenylbutazone and salicylamide those parameters were determined using a linear correlation. For statin drugs, PC-SAFT parameters were fitted to solubility data, and binary interaction parameters (kij and lij) have been obtained by fitting the experimental data. The result was found to be in good agreement with the experimental data and showed that PC-SAFT approach can be used to model solid-SCF equilibrium with better correlation accuracy than cubic equations of state.

Extended statistical associating fluid theory (SAFT) equations of state for dipolar fluids

AIChE Journal ◽  
2005 ◽  
Vol 51 (8) ◽  
pp. 2328-2342 ◽  
Author(s):  
Eirini K. Karakatsani ◽  
Theodora Spyriouni ◽  
Ioannis G. Economou
Keyword(s):  
Equations Of State ◽  
Statistical Associating Fluid Theory ◽  
Dipolar Fluids ◽  
Fluid Theory
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