Euler-Lagrange computational fluid dynamics for (bio)reactor scale down

Euler-Lagrange computational fluid dynamics for (bio)reactor scale down: An analysis of organism lifelines

Haringa, C. (TU Delft ChemE/Transport Phenomena)
Tang, Wenjun (East China University of Science and Technology)
Deshmukh, Amit T. (DSM)
Xia, Jianye (East China University of Science and Technology)
Reuss, Matthias (University of Stuttgart)
Heijnen, J.J. (TU Delft OLD BT/Cell Systems Engineering)
Noorman, H.J. (TU Delft BT/Bioprocess Engineering)
Mudde, R.F. (TU Delft ChemE/Transport Phenomena; DSM)

2016

The trajectories, referred to as lifelines, of individual microorganisms in an industrial scale fermentor under substrate limiting conditions were studied using an Euler-Lagrange computational fluid dynamics approach. The metabolic response to substrate concentration variations along these lifelines provides deep insight in the dynamic environment inside a large-scale fermentor, from the point of view of the microorganisms themselves. We present a novel methodology to evaluate this metabolic response, based on transitions between metabolic “regimes” that can provide a comprehensive statistical insight in the environmental fluctuations experienced by microorganisms inside an industrial bioreactor. These statistics provide the groundwork for the design of representative scale-down simulators, mimicking substrate variations experimentally. To focus on the methodology we use an industrial fermentation of Penicillium chrysogenum in a simplified representation, dealing with only glucose gradients, single-phase hydrodynamics, and assuming no limitation in oxygen supply, but reasonably capturing the relevant timescales. Nevertheless, the methodology provides useful insight in the relation between flow and component fluctuation timescales that are expected to hold in physically more thorough simulations. Microorganisms experience substrate fluctuations at timescales of seconds, in the order of magnitude of the global circulation time. Such rapid fluctuations should be replicated in truly industrially representative scale-down simulators.

CFD
Euler-Lagrange
Fermentation
Industrial scale
Scale down

http://resolver.tudelft.nl/uuid:fe12f418-2ed6-4285-ad82-fe59d1a43b11

https://doi.org/10.1002/elsc.201600061

1618-0240

Engineering in Life Sciences, 16 (7), 652-663

Institutional Repository

journal article

© 2016 C. Haringa, Wenjun Tang, Amit T. Deshmukh, Jianye Xia, Matthias Reuss, J.J. Heijnen, H.J. Noorman, R.F. Mudde