The extended UNIQUAC model has been used for the representation of the thermodynamic behaviour of CO2 absorption in aqueous amine solutions. Based on available experimental data, an identification methodology has been developed to fit the extended‐UNIQUAC model parameters. In the scope of providing a robust methodology, a combination of two successive optimization methods has been chosen: a genetic algorithm and a quasi‐Newton method. The first quasi‐global method allows to screen the entire search space without a precise initialization, and provides an approximate solution which is then refined by the second local method.
The developed multi‐step regression strategy has been successfully applied to the H2O‐ monoethanolamine(MEA)‐CO2 system. The model gives a good agreement with the experimental vapour‐liquid equilibria for CO2 partial pressures and total pressures for all MEA concentrations and for a wide range of temperature with an average absolute relative deviation of around 20 %. Furthermore, the model predicts accurately literature data on excess enthalpy and bubble point of the system.
This identification procedure has been successfully extended on several ternary H2O‐amine‐CO2 solvent systems such as methyldiethanolamine (MDEA) and 2‐amino‐2‐methyl‐1‐propanol (AMP).
The wide variety of operating configurations and solvent types used and presented in this work proves the robustness and the efficiency of the developed identification method.
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