PREDICTION OF AZEOTROPE BY ACTIVITY-COEFFICIENT MODELS WITHOUT PARAMETERS

Citation
Ls. Lee et al., PREDICTION OF AZEOTROPE BY ACTIVITY-COEFFICIENT MODELS WITHOUT PARAMETERS, Journal of the Chinese Institute of Chemical Engineers, 27(4), 1996, pp. 295-315
Citations number
16
Categorie Soggetti
Engineering, Chemical
ISSN journal
03681653
Volume
27
Issue
4
Year of publication
1996
Pages
295 - 315
Database
ISI
SICI code
0368-1653(1996)27:4<295:POABAM>2.0.ZU;2-A
Abstract
Distillation is important that it is still the first separation proces s to be considered for liquid mixtures separation in petroleum, petroc hemical, and chemical industries. Some unique and interesting characte ristics of this process such as tray arrangement, packing structure, h andling of azeotropic mixtures make distillation still be full of chal lenge in design, control, and operation. The full acknowledge of the e xistence of azeotropic point and properties of a mixture would be very advantageous to design the apparatus and control systems for separati ng this mixture. In this study, a prediction methodology was proposed for determining the possible azeotropes of binary and ternary mixtures . This prediction procedure was based on the rigorous thermodynamic co nsideration and the parameter-free activity coefficient models of Scat chard-Hildebrand, UNIQUAC, Vetere-NRTL, and Ash-Wilson. The mathematic al techniques of pseudo-archlength continuation and homotopy were used to locate the azeotropic compositions and temperatures of mixtures. A bout 262 azeotropic mixtures obtained from the work of Horsley (1973) were grouped into 8 categories and tested by the present prediction me thod. In this study, the vapor-liquid equilibrium experiments of the b inary mixtures of isobutanol-n-pentanol, isobutanol-n-hexane, and n-pe ntanol-n-hexane were conducted and correlated by UNIQUAC, NRTL, and Wi lson models. Then the predicted azeotropic behavior of these three mix tures by the proposed method was compared to the experimental data. Th e results of this study showed that the proposed method was about 97% success in predicting azeotrope for mixtures obtained from literature and from our experiments.