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

Norbert Asprion, Roger Böttcher, Jan Schwientek, Johannes Höller, Patrick Schwartz, Charlie Vanaret, Michael Bortz

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PDF(4304 KB)
Front. Chem. Sci. Eng. ›› 2022, Vol. 16 ›› Issue (2) : 210-220. DOI: 10.1007/s11705-021-2046-x
RESEARCH ARTICLE
RESEARCH ARTICLE

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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decision support / multicriteria optimization / model validation / dynamic model / sensitivity analysis

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Norbert Asprion, Roger Böttcher, Jan Schwientek, Johannes Höller, Patrick Schwartz, Charlie Vanaret, Michael Bortz. Decision support for the development, simulation and optimization of dynamic process models. Front. Chem. Sci. Eng., 2022, 16(2): 210‒220 https://doi.org/10.1007/s11705-021-2046-x

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Electronic Supplementary Material

Supplementary material is available in the online version of this article at https://dx.doi.org/10.1007/s11705-021-2046-x and is accessible for authorized users.

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