Euler-Lagrange computational fluid dynamics for (bio)reactor scale down: An analysis of organism lifelines
| Autor: | Joseph J. Heijnen, Cees Haringa, Jianye Xia, Henk J. Noorman, Amit T. Deshmukh, Wenjun Tang, Matthias Reuss, Robert F. Mudde |
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| Rok vydání: | 2016 |
| Předmět: |
0106 biological sciences
0301 basic medicine Engineering Environmental Engineering Flow (psychology) Bioengineering Industrial fermentation Computational fluid dynamics Industrial scale 01 natural sciences 03 medical and health sciences 010608 biotechnology Component (UML) Bioreactor Representation (mathematics) Research Articles Scale down business.industry Euler-Lagrange Control engineering Euler‐Lagrange Substrate (biology) 030104 developmental biology Fermentation Biochemical engineering CFD business Order of magnitude Research Article Biotechnology |
| Zdroj: | Engineering in Life Sciences Engineering in Life Sciences, 16(7) |
| ISSN: | 1618-0240 |
| DOI: | 10.1002/elsc.201600061 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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