Effects of physical properties estimation on process design: a case study using AspenPlus

Abstract

This study focuses on the physical property model parameters estimation in order to accurately simulate separation processes for a given set of components. The non-random two-liquid (NRTL) model was chosen and parameters were calculated using different methods: experimental data regression and UNIFAC and COSMO-SAC (conductor-like screening model, segment activity coefficient) predictive models. The vapor-liquid equilibrium (VLE) obtained from these different models was compared and results showed that COSMO-SAC can be a reliable tool when data or functional groups are missing. Results also showed that the use of UNIFAC to estimate activity coefficients at infinite dilution can, in some cases, leads to inaccurate results and strongly impact process simulation results.  2009

Enterprise Ionic Liquids Database (ILUAM) for Use in Aspen ONE Programs Suite with COSMO-Based Property Methods

“…This solution has been addressed by several research groups in different application fields and using rather dissimilar strategies 7,[12][13][14][15][16][17][18][19] . In particular, our group has been worked 20 in the integration of the molecular modeling and the process simulation via the COSMO-based 21,22 In the last five years, we have successfully applied COSMO-based/Aspen Plus (Aspen HYSYS) procedure to the design and analysis of new different processes using ILs: absorption of toluene in packed/tray columns 30 , absorption refrigeration cycles 31 , aromatic-aliphatic separation by liquidliquid extraction 25,32,33 , extractive distillation 34 and CO 2 capture by physical absorption 9 .…”

Integration of COSMO‐based methodologies into commercial process simulators: Separation and purification of reuterin

“…5 Fulfilling the databases of the process simulators experimentally is a largely resource and time-consuming task. [26][27][28][29][30][31] Important success has been achieved in this field: (1) the COSMO-SAC method has been implemented in the Aspen Plus 26,27 process simulator as a method for property estimations, and further the COSMO-SAC sigma-profile database 12,14 has been incorporated into the database of this program, 27 and (2) the COSMOlogic GmbH and Co. KG 32 has developed the COSMOthermCO, 33 a CAPE-OPEN 34,35 interface between the COSMOthermX 36 software and CAPE-OPEN compliant process simulators with the aim to apply thermodynamical data computed by COSMOthermX within process modeling and engineering simulations. 2,3,5 In particular, the COSMO-based methods [6][7][8][9][10][11][12][13][14] such as COSMO-RS 6-10 and COSMO-SAC [11][12][13][14] have been established as a novel way to predict thermophys-ical data for liquid systems on the basis of quantum chemical calculations.…”

“…Therefore, the integration of COSMO-based methodologies into commercial process simulators for developing the conceptual design of new processes results a goal subject for many researchers and engineers. [26][27][28][29][30][31] Important success has been achieved in this field: (1) the COSMO-SAC method has been implemented in the Aspen Plus 26,27 process simulator as a method for property estimations, and further the COSMO-SAC sigma-profile database 12,14 has been incorporated into the database of this program, 27 and (2) the COSMOlogic GmbH and Co. KG 32 has developed the COSMOthermCO, 33 a CAPE-OPEN 34,35 interface between the COSMOthermX 36 software and CAPE-OPEN compliant process simulators with the aim to apply thermodynamical data computed by COSMOthermX within process modeling and engineering simulations. 28,29 However, both the COSMO-based methods and the integration procedures exhibit some theoretical and practical (instrumental) limitations.…”

“…This is especially remarkable when the components to be used in the simulations are not included in the databank of the simulator. To our knowledge, only a few attempts have explored [28][29][30][31] the use of COSMO-based outputs directly into process simulations. In this work, the integration of COSMO-RS methodology into Aspen Technology's commercial process simulators for designing a new process is considered.…”

First‐principles prediction of phase equilibria using the PR + COSMOSAC equation of state

“…The knowledge of thermodynamic properties and phase equilibria of pure and mixture fluids is of great importance in the design and optimization of chemical processes 1, 2. For example, the information regarding temperature, pressure, and composition in vapor–liquid equilibrium (VLE) and liquid–liquid equilibrium (LLE) is crucial for the design of distillation and extraction processes 3–7.…”