Mechanistic Models for Process Development and Optimization of Fed-batch Fermentation Systems

Lisa Mears, Stuart M. Stocks, Mads O. Albæk, Gürkan Sin, Krist Gernaey

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

Abstract

This work discusses the application of mechanistic models to pilot scale filamentous fungal fermentation systems operated at Novozymes A/S. For on-line applications, a state estimator model is developed based on a stoichiometric balance in order to predict the biomass and product concentration. This is based on on-line gas measurements and ammonia addition flow rate measurements. Additionally, a mechanistic model is applied offline as a tool for batch planning, based on definition of the process back pressure, aeration rate and stirrer speed. This allows the batch starting fill to be planned, taking into account the oxygen transfer conditions, as well as the evaporation rates of the system. Mechanistic models are valuable tools which are applicable for both process development and optimization. The state estimator described will be a valuable tool for future work as part of control strategy development for on-line process control and optimization.
Original languageEnglish
Title of host publicationProceedings of the 26th European Symposium on Computer Aided Process Engineering
EditorsZdravko Kravanja, Miloš Bogataj
Volume38
PublisherElsevier
Publication date2016
Pages1311–1316
ISBN (Electronic)978-0-444-63428-3
DOIs
Publication statusPublished - 2016
Event26th European Symposium on Computer-Aided Process Engineering - Grand Hotel Bernardin Congress Centre, Portorož , Slovenia
Duration: 12 Jun 201615 Jun 2016
http://escape26.um.si/

Conference

Conference26th European Symposium on Computer-Aided Process Engineering
LocationGrand Hotel Bernardin Congress Centre
CountrySlovenia
CityPortorož
Period12/06/201615/06/2016
Internet address
SeriesComputer Aided Chemical Engineering
Volume38
ISSN1570-7946

Keywords

  • Fermentation
  • Modelling
  • Process Optimization
  • State estimation (SE)

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