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Multi-criteria Optimization for Parametrizing Excess Gibbs Energy Models

Author

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  • Forte, Ester
  • Kulkarni, Aditya
  • Burger, Jakob
  • Bortz, Michael
  • Küfer, Karl-Heinz
  • Hasse, Hans

Abstract

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 conicting 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.

Suggested Citation

  • Forte, Ester & Kulkarni, Aditya & Burger, Jakob & Bortz, Michael & Küfer, Karl-Heinz & Hasse, Hans, 2021. "Multi-criteria Optimization for Parametrizing Excess Gibbs Energy Models," OSF Preprints 4fp9w, Center for Open Science.
  • Handle: RePEc:osf:osfxxx:4fp9w
    DOI: 10.31219/osf.io/4fp9w
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    References listed on IDEAS

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    1. Matthias Ehrgott, 2005. "Multicriteria Optimization," Springer Books, Springer, edition 0, number 978-3-540-27659-3, September.
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