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Decision support for the development, simulation and optimization of dynamic process models

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Abstract

Simulation is besides experimentation the major method for designing, analyzing and optimizing chemical processes. The ability of simulations to reflect real process behavior strongly depends on model quality. Validation and adaption of process models are usually based on available plant data. Using such a model in various simulation and optimization studies can support the process designer in his task. Beneath steady state models there is also a growing demand for dynamic models either to adapt faster to changing conditions or to reflect batch operation. In this contribution challenges of extending an existing decision support framework for steady state models to dynamic models will be discussed and the resulting opportunities will be demonstrated for distillation and reactor examples.

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Authors and Affiliations

  1. BASF SE, 67063, Ludwigshafen, Germany

    Norbert Asprion & Roger Böttcher

  2. Fraunhofer ITWM, 67663, Kaiserslautern, Germany

    Jan Schwientek, Johannes Höller, Patrick Schwartz, Charlie Vanaret & Michael Bortz

Authors
  1. Norbert Asprion
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  2. Roger Böttcher
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  3. Jan Schwientek
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  4. Johannes Höller
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  5. Patrick Schwartz
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  6. Charlie Vanaret
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  7. Michael Bortz
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Corresponding author

Correspondence to Norbert Asprion.

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Asprion, N., Böttcher, R., Schwientek, J. et al. Decision support for the development, simulation and optimization of dynamic process models. Front. Chem. Sci. Eng. 16, 210–220 (2022). https://doi.org/10.1007/s11705-021-2046-x

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  • DOI: https://doi.org/10.1007/s11705-021-2046-x

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