Benchmarking of Surrogate Models for the Conceptual Process Design of Biorefineries

Nikolaus I. Vollmer*, Resul Al, Gürkan Sin

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

Surrogate models are an efficient method to expedite the process design by superstructure optimization. For their application in biorefineries’ process design, several surrogate models are benchmarked in a case study regarding their validation metrics and their performance in a reference superstructure optimization problem. Despite good validation metrics for most surrogate models, their prediction quality in the superstructure optimization does not reflect this. For the use of surrogate models in superstructure optimization, the need for a profound assessment of options, and the possible use of dynamic sampling strategies become evident.
Original languageEnglish
Title of host publicationProceedings of the 31th European Symposium on Computer Aided Process Engineering (ESCAPE30)
EditorsMetin Türkay, Rafiqul Gani
Place of PublicationAmsterdam
PublisherElsevier
Publication date2021
Pages475-480
ISBN (Electronic)978-0-323-98325-9
DOIs
Publication statusPublished - 2021
Event31st European Symposium on Computer Aided Process Engineering - Istanbul, Turkey
Duration: 6 Jun 20219 Jun 2021

Conference

Conference31st European Symposium on Computer Aided Process Engineering
Country/TerritoryTurkey
CityIstanbul
Period06/06/202109/06/2021
SeriesComputer Aided Chemical Engineering
ISSN1570-7946

Keywords

  • Biorefinery
  • Process Design
  • Superstructure Optimization
  • Surrogate Modelling
  • Machine Learning

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