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A model-based framework assisting the design of vapor-liquid equilibrium experimental plans

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  • Duarte, Belmiro P.M.
  • Atkinson, Anthony C.
  • Granjo, Jose F.O
  • Oliveira, Nuno M.C

Abstract

In this paper we propose a framework for Model-based Sequential Optimal Design of Experiments to assist experimenters involved in Vapor-Liquid equilibrium characterization studies to systematically construct thermodynamically consistent models. The approach uses an initial continuous optimal design obtained via semidefinite programming, and then iterates between two stages (i) model fitting using the information available; and (ii) identification of the next experiment, so that the information content in data is maximized. The procedure stops when the number of experiments reaches the maximum for the experimental program or the dissimilarity between the parameter estimates during two consecutive iterations is below a given threshold. This methodology is exemplified with the D-optimal design of isobaric experiments, for characterizing binary mixtures using the NRTL and UNIQUAC thermodynamic models for liquid phase. Significant reductions of the confidence regions for the parameters are achieved compared with experimental plans where the observations are uniformly distributed over the domain.

Suggested Citation

  • Duarte, Belmiro P.M. & Atkinson, Anthony C. & Granjo, Jose F.O & Oliveira, Nuno M.C, 2021. "A model-based framework assisting the design of vapor-liquid equilibrium experimental plans," LSE Research Online Documents on Economics 107448, London School of Economics and Political Science, LSE Library.
    • Handle: RePEc:ehl:lserod:107448
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    References listed on IDEAS

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    1. Duarte, Belmiro P.M. & Atkinson, Anthony C. & Granjo, Jose F.O & Oliveira, Nuno M.C, 2019. "Optimal design of experiments for liquid–liquid equilibria characterization via semidefinite programming," LSE Research Online Documents on Economics 102500, London School of Economics and Political Science, LSE Library.
    2. Belmiro P. M. Duarte & Weng Kee Wong, 2015. "Finding Bayesian Optimal Designs for Nonlinear Models: A Semidefinite Programming-Based Approach," International Statistical Review, International Statistical Institute, vol. 83(2), pages 239-262, August.
    3. Katharina Nöh & Sebastian Niedenführ & Martin Beyß & Wolfgang Wiechert, 2018. "A Pareto approach to resolve the conflict between information gain and experimental costs: Multiple-criteria design of carbon labeling experiments," PLOS Computational Biology, Public Library of Science, vol. 14(10), pages 1-30, October.
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    More about this item

    Keywords

    sequential optimal design of experiments; vapor-liquid equilibrium; semidefinite programming; NRTL model; nonlinear programming;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General

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