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CFD predicted pH gradients in lactic acid bacteria cultivations
Zitatschlüssel Spann.2019
Autor Spann, Robert and Glibstrup, Jens and Pellicer-Alborch, Klaus and Junne, Stefan and Neubauer, Peter and Roca, Christophe and Kold, David and Lantz, Anna Eliasson and Sin, Gürkan and Gernaey, Krist V. and Krühne, Ulrich
Seiten 769–780
Jahr 2019
ISSN 0006-3592
DOI 10.1002/bit.26868
Journal Biotechnology and bioengineering
Jahrgang 116
Nummer 4
Zusammenfassung The formation of pH gradients in a 700 L batch fermentation of Streptococcus thermophilus was studied using multi-position pH measurements and computational fluid dynamics (CFD) modeling. To this end, a dynamic, kinetic model of S. thermophilus and a pH correlation were integrated into a validated one-phase CFD model, and a dynamic CFD simulation was performed. First, the fluid dynamics of the CFD model were validated with NaOH tracer pulse mixing experiments. Mixing experiments and simulations were performed whereas multiple pH sensors, which were placed vertically at different locations in the bioreactor, captured the response. A mixing time of about 46 s to reach 95% homogeneity was measured and predicted at an impeller speed of 242 rpm. The CFD simulation of the S. thermophilus fermentation captured the experimentally observed pH gradients between a pH of 5.9 and 6.3, which occurred during the exponential growth phase. A pH higher than 7 was predicted in the vicinity of the base solution inlet. Biomass growth, lactic acid production, and substrate consumption matched the experimental observations. Moreover, the biokinetic results obtained from the CFD simulation were similar to a single-compartment simulation, for which a homogeneous distribution of the pH was assumed. This indicates no influence of pH gradients on growth in the studied bioreactor. This study verified that the pH gradients during a fermentation in the pilot-scale bioreactor could be accurately predicted using a coupled simulation of a biokinetic and a CFD model. To support the understanding and optimization of industrial-scale processes, future biokinetic CFD studies need to assess multiple types of environmental gradients, like pH, substrate, and dissolved oxygen, especially at industrial scale.
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