LAPSE:2019.1344
Published Article
LAPSE:2019.1344
Surrogate Modeling for Liquid−Liquid Equilibria Using a Parameterization of the Binodal Curve
December 10, 2019
Computational effort and convergence problems can pose serious challenges when employing advanced thermodynamic models in process simulation and optimization. Data-based surrogate modeling helps to overcome these problems at the cost of additional modeling effort. The present work extends the range of methods for efficient data-based surrogate modeling of liquid−liquid equilibria. A new model formulation is presented that enables smaller surrogates with box-constrained input domains and reduced input dimensions. Sample data are generated efficiently by using numerical continuation. The new methods are demonstrated for the surrogate modeling and optimization of a process for the hydroformylation of 1-decene in a thermomorphic multiphase system.
Record ID
Keywords
liquid–liquid equilibrium, multistage extraction, numerical continuation, Optimization, parameterization, surrogate modeling
Subject
Suggested Citation
Kunde C, Keßler T, Linke S, McBride K, Sundmacher K, Kienle A. Surrogate Modeling for Liquid−Liquid Equilibria Using a Parameterization of the Binodal Curve. (2019). LAPSE:2019.1344
Author Affiliations
Kunde C: Chair for Automation/Modelling, Otto von Guericke University Magdeburg, Universitätsplatz 2, 39106 Magdeburg, Germany [ORCID]
Keßler T: Chair for Automation/Modelling, Otto von Guericke University Magdeburg, Universitätsplatz 2, 39106 Magdeburg, Germany [ORCID]
Linke S: Chair for Process Systems Engineering, Otto von Guericke University Magdeburg, Universitätsplatz 2, 39106 Magdeburg, Germany [ORCID]
McBride K: Max Planck Institute for Dynamics of Complex Technical Systems, Process Systems Engineering, Sandtorstraße 1, 39106 Magdeburg, Germany [ORCID]
Sundmacher K: Chair for Process Systems Engineering, Otto von Guericke University Magdeburg, Universitätsplatz 2, 39106 Magdeburg, Germany; Max Planck Institute for Dynamics of Complex Technical Systems, Process Systems Engineering, Sandtorstraße 1, 39106 Magdeburg, [ORCID]
Kienle A: Chair for Automation/Modelling, Otto von Guericke University Magdeburg, Universitätsplatz 2, 39106 Magdeburg, Germany; Max Planck Institute for Dynamics of Complex Technical Systems, Process Synthesis and Process Dynamics, Sandtorstraße 1, 39106 Magdebu
Keßler T: Chair for Automation/Modelling, Otto von Guericke University Magdeburg, Universitätsplatz 2, 39106 Magdeburg, Germany [ORCID]
Linke S: Chair for Process Systems Engineering, Otto von Guericke University Magdeburg, Universitätsplatz 2, 39106 Magdeburg, Germany [ORCID]
McBride K: Max Planck Institute for Dynamics of Complex Technical Systems, Process Systems Engineering, Sandtorstraße 1, 39106 Magdeburg, Germany [ORCID]
Sundmacher K: Chair for Process Systems Engineering, Otto von Guericke University Magdeburg, Universitätsplatz 2, 39106 Magdeburg, Germany; Max Planck Institute for Dynamics of Complex Technical Systems, Process Systems Engineering, Sandtorstraße 1, 39106 Magdeburg, [ORCID]
Kienle A: Chair for Automation/Modelling, Otto von Guericke University Magdeburg, Universitätsplatz 2, 39106 Magdeburg, Germany; Max Planck Institute for Dynamics of Complex Technical Systems, Process Synthesis and Process Dynamics, Sandtorstraße 1, 39106 Magdebu
Journal Name
Processes
Volume
7
Issue
10
Article Number
E753
Year
2019
Publication Date
2019-10-16
Published Version
ISSN
2227-9717
Version Comments
Original Submission
Other Meta
PII: pr7100753, Publication Type: Journal Article
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Published Article
LAPSE:2019.1344
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External Link
doi:10.3390/pr7100753
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Version History
[v1] (Original Submission)
Dec 10, 2019
Verified by curator on
Dec 10, 2019
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v1
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https://psecommunity.org/LAPSE:2019.1344
Original Submitter
Calvin Tsay
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