Abstract

Spatial variation of microorganism populations in stirred-tank bioreactors, caused by the interactions of complex multiphase flows and microorganism metabolism, results in undesirable performance characteristics and significant challenges in scale-up activities. In this work, a novel modelling approach is developed to investigate these coupled processes in bioreactors, which involves the integration of a computational fluid dynamics-informed compartmental hydrodynamic and a dynamic flux balance (DFB) model. This coupling poses significant computational challenges especially when dealing with transient scenarios. To tackle these challenges we developed a fast point-location algorithm to solve the DFB model at different bioreactor locations. To validate the presented modelling approach, a binary search tree-based metabolic model for E. coli was developed and integrated with a flow-informed compartmental model of a large-scale four-impeller aerated bioreactor in fed-batch operation. The model results exhibit favorable agreement with the concentration profiles reported in literature for both lab-scale and industrial scale bioreactors. Furthermore, the ability of the approach to deal with transient scenarios permitted to study the effect of oxygen closed loop control responses and the occurrence of oscillatory behaviour which were crucial to explain part of the data.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.