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Multi-criteria optimization for parametrizing excess Gibbs energy models

: Forte, E.; Kulkarni, A.; Burger, J.; Bortz, M.; Küfer, K.-H.; Hasse, H.


Fluid phase equilibria 522 (2020), Art. 112676
ISSN: 0378-3812
Journal Article
Fraunhofer ITWM ()

Thermodynamic models contain parameters which are adjusted to experimental data. Usually, optimal descriptions of different data sets require different parameters. Multi-criteria optimization (MCO) is an appropriate way to obtain a compromise. This is demonstrated here for Gibbs excess energy (GE) models. As an example, the NRTL model is applied to the three binary systems (containing water, 2-propanol, and 1-pentanol). For each system, different objectives are considered (description of vapor-liquid equilibrium, liquid-liquid equilibrium, and excess enthalpies). The resulting MCO problems are solved using an adaptive numerical algorithm. It yields the Pareto front, which gives a comprehensive overview of how well the given model can describe the given conflicting data. From the Pareto front, a solution that is particularly favorable for a given application can be selected in an instructed way. The examples from the present work demonstrate the benefits of the MCO approach for parametrizing GE-models.