Bioprocess Scale-Up: A Computational Fluid Dynamics Approach for the Bioproduction of Succinic Acid from Glycerol

In this work, we present the scale-up of a batch anaerobic fermentation system for the production of succinic acid from glycerol using A. succinogenes. The system has been successfully scaled up from an initial bioreactor working volume of 1 L (laboratory scale) to a working volume of 100 L (pilot scale). At the same time, we have developed a hybrid model, combining the intrinsic kinetics of the microbial growth, with a computational fluid dynamics model (CFD) of the bioreactor. The proposed model is able to predict the productivity drop, usually observed while scaling up a bioprocess. In our process, this is a result of the limitations on the mass transfer of CO2 between the gas and the liquid phase of the system. The model is successfully used to predict the amount of aeration needed in order to achieve increased succinic acid productivity. Using the model, the final succinic acid increased by 4.3%, and the succinic acid productivity increased by 8.5%, while the fermentation by-products decreased by approxiamtely 3% each.

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Journal
Processes
Published
2026-03-09
DOI
https://doi.org/10.3390/pr14050870
Primary Topic
Microbial Metabolic Engineering and Bioproduction
Type
article
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article

Bioprocess Scale-Up: A Computational Fluid Dynamics Approach for the Bioproduction of Succinic Acid from Glycerol

Ioannis Zacharopoulos, Constantinos
Processes
Microbial Metabolic Engineering and Bioproduction
article

Bioprocess Scale-Up: A Computational Fluid Dynamics Approach for the Bioproduction of Succinic Acid from Glycerol

Ioannis Zacharopoulos, Constantinos
article en

Abstract

In this work, we present the scale-up of a batch anaerobic fermentation system for the production of succinic acid from glycerol using A. succinogenes. The system has been successfully scaled up from an initial bioreactor working volume of 1 L (laboratory scale) to a working volume of 100 L (pilot scale). At the same time, we have developed a hybrid model, combining the intrinsic kinetics of the microbial growth, with a computational fluid dynamics model (CFD) of the bioreactor. The proposed model is able to predict the productivity drop, usually observed while scaling up a bioprocess. In our process, this is a result of the limitations on the mass transfer of CO2 between the gas and the liquid phase of the system. The model is successfully used to predict the amount of aeration needed in order to achieve increased succinic acid productivity. Using the model, the final succinic acid increased by 4.3%, and the succinic acid productivity increased by 8.5%, while the fermentation by-products decreased by approxiamtely 3% each.

ProcessesVol. 14(5)
University of Manchester (GB)
Openalex Percentile: Top 29%
Microbial Metabolic Engineering and Bioproduction
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