Surrogate modeling of thermodynamic equilibria: applications, sampling and optimization

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dc.contributor.authorWinz, Joschka
dc.contributor.authorNentwich, Corina
dc.contributor.authorEngell, Sebastian
dc.date.accessioned2022-03-16T10:30:29Z
dc.date.available2022-03-16T10:30:29Z
dc.date.issued2021-09-27
dc.description.abstractModels based on first principles are an effective way to model chemical processes. The quality of these depends critically on the accurate description of thermodynamic equilibria. This is provided by modern thermodynamic models, e.g., PC-SAFT, but they come with a high computational cost, which makes process optimization challenging. This can be addressed by using surrogate models to approximate the equilibrium calculations. A high accuracy of the surrogate model can be achieved by carefully choosing the points at which the original function is evaluated to create data for the training of the surrogate models, called sampling. Using a case study, different approaches to sampling are discussed and evaluated with a focus on new approaches to adaptive sampling.en
dc.identifier.urihttp://hdl.handle.net/2003/40798
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-22655
dc.language.isoende
dc.relation.ispartofseriesChemie - Ingenieur - Technik;93(12)
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectMachine learningen
dc.subjectProcess optimizationen
dc.subjectSurrogate modelingen
dc.subjectThermodynamic equilibriaen
dc.subject.ddc660
dc.titleSurrogate modeling of thermodynamic equilibria: applications, sampling and optimizationen
dc.typeTextde
dc.type.publicationtypearticlede
dcterms.accessRightsopen access
eldorado.secondarypublicationtruede
eldorado.secondarypublication.primarycitationWinz, J., Nentwich, C. and Engell, S. (2021), Surrogate Modeling of Thermodynamic Equilibria: Applications, Sampling and Optimization. Chemie Ingenieur Technik, 93: 1898-1906. https://doi.org/10.1002/cite.202100092de
eldorado.secondarypublication.primaryidentifierhttps://doi.org/10.1002/cite.202100092de

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