A framework for model-based optimization of bioprocesses under uncertainty: Identifying critical parameters and operating variables

Ricardo Morales Rodriguez, Anne S. Meyer, Krist Gernaey, Gürkan Sin

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

Abstract

This study presents the development and application of a systematic model-based framework for bioprocess optimization, evaluated on a cellulosic ethanol production case study. The implementation of the framework involves the use of dynamic simulations, sophisticated uncertainty analysis (Monte-Carlo technique) and sensitivity analysis (such as global techniques). The results of the case study point towards the enzyme loading as the most significant variable influencing the operational cost of additives in the conversion of lignocellulose to ethanol. Moreover, the results also show that there is an opportunity for further process optimization of bioethanol production from lignocellulose.
Original languageEnglish
Title of host publication21st European Symposium on Computer Aided Process Engineering
PublisherElsevier
Publication date2011
Pages1455-1459
ISBN (Print)978-0-444-53895-6
DOIs
Publication statusPublished - 2011
Event21st European Symposium on Computer Aided Process Engineering - Chalkidiki, Greece
Duration: 29 May 20111 Jun 2011
http://www.escape-21.gr/

Conference

Conference21st European Symposium on Computer Aided Process Engineering
CountryGreece
CityChalkidiki
Period29/05/201101/06/2011
Internet address
SeriesComputer Aided Chemical Engineering
Volume29
ISSN1570-7946

Keywords

  • Critical process parameters
  • Sensitivity analysis
  • Bioethanol production
  • Monte-Carlo
  • Uncertainty analysis

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