Abstract
The extended UNIQUAC model has been used to simulate the absorption of carbon dioxide (CO 2 ) absorption by methylethylamine (MEA), using differential evolution algorithm method to regress UNIQUAC parameters. The model was successfully applied to correlate simultaneously total pressure versus CO 2 concentration and MEA more fraction, water activity coefficient and the excess properties. Good results were obtained compared to other regression methods such as Levenberg-Marquardt (LM).
Highlights
Design, and optimization of the CO2 capture processes start with modeling of the thermodynamic properties, vapor-liquid equilibrium (VLE) and chemical reaction equilibrium, as well as calorimetric properties
A thermodynamic property model capable of accurate representation of the vapor-liquid equilibrium (VLE) of the aqueous MEA-CO2 system is essential for a successful computer simulation of the process
In the last few decades, considerable progress has been made in modeling VLE of the acid gas (CO2 and H2S) in aqueous alkanolamine systems, including the aqueous MEA-CO2 system
Summary
Design, and optimization of the CO2 capture processes start with modeling of the thermodynamic properties, vapor-liquid equilibrium (VLE) and chemical reaction equilibrium, as well as calorimetric properties. Accurate modeling of thermodynamic properties requires availability of reliable experimental data and a good model and accurate model to simulate VLE data. A thermodynamic property model capable of accurate representation of the vapor-liquid equilibrium (VLE) of the aqueous MEA-CO2 system is essential for a successful computer simulation of the process. In the last few decades, considerable progress has been made in modeling VLE of the acid gas (CO2 and H2S) in aqueous alkanolamine systems, including the aqueous MEA-CO2 system. Many models have been applied to predict the adsorption of CO2 by MEA, some of them have been successful and others can be applied in a specific range of parameters such as temperature and concentration. We will be using this model using a different approach of regressing its parameters, and not based on the traditional regression methods but on multiple objective function using differential evolution algorithm
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