4.6 Article

Influence of Interfacial Force Models and Population Balance Models on the kLa Value in Stirred Bioreactors

Journal

PROCESSES
Volume 9, Issue 7, Pages -

Publisher

MDPI
DOI: 10.3390/pr9071185

Keywords

bioreactor characterization; CFD simulation; drag force; interfacial force; k(L)a value; lift force; multiphase modeling; numerical simulation; oxygen transfer rate; population balance model

Funding

  1. Zurich University of Applied Sciences

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Optimal oxygen supply is crucial for the cultivation of aerobically growing cells, with the volumetric oxygen mass transfer coefficient k(L)a playing a direct role in cell growth and product formation. This study evaluated the influences of different interfacial force and population balance models on k(L)a, with results showing better agreement with experimental data when coupling computational fluid dynamics (CFD) with population balance models (PBM).
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 k(L)a. It is the influences on k(L)a 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 2 L scale bioreactor to statistically examine the influence of different interfacial models on the k(L)a value. It was shown that the k(L) model and the constant bubble diameter have the greatest influence on the calculated k(L)a 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.

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