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Global sensitivity based estimability analysis for the parameter identification of Pitzer’s thermodynamic model

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  • Bouchkira, Ilias
  • Latifi, Abderrazak M.
  • Khamar, Lhachmi
  • Benjelloun, Saad

Abstract

This paper deals with parameter estimability analysis and identification of the Pitzer model used in the prediction of thermodynamic properties and phase equilibria of electrolytic solutions. The estimability analysis method used is based on the orthogonalization of a sensitivity matrix to rank the unknown parameters from the most estimable to the least estimable. Although the obtained results are interesting, the algorithm shows its limits since it is based on the local sensitivities of the outputs with respect to the unknown parameters of the model and may significantly affect the reliability of the model. In this work, the algorithm is improved by computing the sensitivities by means of the method of global sensitivity analysis. For demonstration purposes, different sets of experimental measurements of sulfuric acid solutions are carried out at different temperatures and acid concentrations. They mainly consist of pH, density, conductivity and molality measurements. The improved algorithm is then applied to each of the experimental sets. The most estimable parameters are determined and identified using a branch-and-reduce optimization method and their accuracy is assessed by means of confidence intervals. Finally, the quality of the model is quantified by computing the Pearson product-moment coefficient, its high values show a very good agreement between the predictions and the measurements.

Suggested Citation

  • Bouchkira, Ilias & Latifi, Abderrazak M. & Khamar, Lhachmi & Benjelloun, Saad, 2021. "Global sensitivity based estimability analysis for the parameter identification of Pitzer’s thermodynamic model," Reliability Engineering and System Safety, Elsevier, vol. 207(C).
    • Handle: RePEc:eee:reensy:v:207:y:2021:i:c:s0951832020307626
    DOI: 10.1016/j.ress.2020.107263
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    References listed on IDEAS

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    1. Sudret, Bruno, 2008. "Global sensitivity analysis using polynomial chaos expansions," Reliability Engineering and System Safety, Elsevier, vol. 93(7), pages 964-979.
    2. Kucherenko, Sergei & Feil, Balazs & Shah, Nilay & Mauntz, Wolfgang, 2011. "The identification of model effective dimensions using global sensitivity analysis," Reliability Engineering and System Safety, Elsevier, vol. 96(4), pages 440-449.
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