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https://doi.org/10.21256/zhaw-22798| Publikationstyp: | Beitrag in wissenschaftlicher Zeitschrift |
| Art der Begutachtung: | Peer review (Publikation) |
| Titel: | Influence of interfacial force models and population balance models on the kLa value in stirred bioreactors |
| Autor/-in: | Seidel, Stefan Eibl, Dieter |
| et. al: | No |
| DOI: | 10.3390/pr9071185 10.21256/zhaw-22798 |
| Erschienen in: | Processes |
| Band(Heft): | 9 |
| Heft: | 7 |
| Seite(n): | 1185 |
| Erscheinungsdatum: | 7-Jul-2021 |
| Verlag / Hrsg. Institution: | MDPI |
| ISSN: | 2227-9717 |
| Sprache: | Englisch |
| Schlagwörter: | Bioreactor characterization; CFD simulation; Drag force; Interfacial force; kLa value; Multiphase modeling; Oxygen transfer rate; Population balance model |
| Fachgebiet (DDC): | 660: Technische Chemie |
| Zusammenfassung: | Optimal oxygen supply is vitally important for the cultivation of aerobically growing cells, as it has a direct influence on cell growth and product formation. A process engineering parameter directly related to oxygen supply is the volumetric oxygen mass transfer coefficient kLa. It is the influences on kLa and computing time of different interfacial force and population balance models in stirred bioreactors that have been evaluated in this study. For this investigation, the OpenFOAM 7 open-source toolbox was utilized. Firstly, the Euler–Euler model with a constant bubble diameter was applied to a 2L scale bioreactor to statistically examine the influence of different interfacial models on the kLa value. It was shown that the kL model and the constant bubble diameter have the greatest influence on the calculated kLa value. To eliminate the problem of a constant bubble diameter and to take effects such as bubble breakup and coalescence into account, the Euler–Euler model was coupled with population balance models (PBM). For this purpose, four coalescence and five bubble breakup models were examined. Ultimately, it was established that, for all of the models tested, coupling computational fluid dynamics (CFD) with PBM resulted in better agreement with the experimental data than using the Euler–Euler model. However, it should be noted that the higher accuracy of the PBM coupled models requires twice the computation time. |
| URI: | https://digitalcollection.zhaw.ch/handle/11475/22798 |
| Volltext Version: | Publizierte Version |
| Lizenz (gemäss Verlagsvertrag): | CC BY 4.0: Namensnennung 4.0 International |
| Departement: | Life Sciences und Facility Management |
| Organisationseinheit: | Institut für Chemie und Biotechnologie (ICBT) |
| Enthalten in den Sammlungen: | Publikationen Life Sciences und Facility Management |
Dateien zu dieser Ressource:
| Datei | Beschreibung | Größe | Format | |
|---|---|---|---|---|
| 2021_Seidel-Eibl_Influences-on-kLa-value-in-stirred-bioreactors.pdf | 12.47 MB | Adobe PDF |  Öffnen/Anzeigen |
Zur Langanzeige
Seidel, S., & Eibl, D. (2021). Influence of interfacial force models and population balance models on the kLa value in stirred bioreactors. Processes, 9(7), 1185. https://doi.org/10.3390/pr9071185
Seidel, S. and Eibl, D. (2021) ‘Influence of interfacial force models and population balance models on the kLa value in stirred bioreactors’, Processes, 9(7), p. 1185. Available at: https://doi.org/10.3390/pr9071185.
S. Seidel and D. Eibl, “Influence of interfacial force models and population balance models on the kLa value in stirred bioreactors,” Processes, vol. 9, no. 7, p. 1185, Jul. 2021, doi: 10.3390/pr9071185.
SEIDEL, Stefan und Dieter EIBL, 2021. Influence of interfacial force models and population balance models on the kLa value in stirred bioreactors. Processes. 7 Juli 2021. Bd. 9, Nr. 7, S. 1185. DOI 10.3390/pr9071185
Seidel, Stefan, and Dieter Eibl. 2021. “Influence of Interfacial Force Models and Population Balance Models on the kLa Value in Stirred Bioreactors.” Processes 9 (7): 1185. https://doi.org/10.3390/pr9071185.
Seidel, Stefan, and Dieter Eibl. “Influence of Interfacial Force Models and Population Balance Models on the kLa Value in Stirred Bioreactors.” Processes, vol. 9, no. 7, July 2021, p. 1185, https://doi.org/10.3390/pr9071185.
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