Euler‐Lagrange computational fluid dynamics for (bio)reactor scale down: An analysis of organism lifelines. Issue 7 (14th September 2016)

• Record Type: Journal Article
• Authors: Haringa, Cees; Tang, Wenjun; Deshmukh, Amit T.; Xia, Jianye; Reuss, Matthias; Heijnen, Joseph J.; Mudde, Robert F.; Noorman, Henk J.
• Is Part Of: Engineering in life sciences. Volume 16:Issue 7(2016)
• Page Start: 652
• Page End: 663
• Publication Date: 2016-09-14
• Subjects: CFD -- Euler‐Lagrange -- Fermentation -- Industrial scale -- Scale down; Bioengineering -- Periodicals; 660.605
• DOI: 10.1002/elsc.201600061
• Languages: English
• ISSNs: 1618-0240

Abstract

Abstract : 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.