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Applying multiple approaches to deepen understanding of mixing and mass transfer in large-scale aerobic fermentations

Navraj Hanspal, Ning Chai, B. R. Allen, D.A. Brown

2020Journal of Industrial Microbiology & Biotechnology15 citationsDOIOpen Access PDF

Abstract

Agriscience to improve our understanding of mixing in large-scale mechanically agitated fermentors. These include (a) use of classical empirical correlations, (b) use of small-scale models, and (c) computational fluid dynamics (CFD). Each of these approaches has its own inherent strengths and limitations. Classic empirical or semi-empirical correlations can provide insights into mass transfer, blending, shear, and other important factors but are dependent on the geometry and condition used to develop the correlations. Laboratory-scale modelling can be very useful to study mixing and model the effect of heterogeneity on the culture, but success is highly dependent on the methodology applied. CFD provides an effective means to accelerate the exploration of alternative design strategies through physics-based computer simulations that may not be adequately described by existing knowledge or correlations. However, considerable time and effort is needed to build and validate these models. In this paper, we review the various approaches used at Corteva Agriscience to deepen our understanding of mixing in large-scale fermentation processes.

Topics & Concepts

Mixing (physics)Computational fluid dynamicsScale (ratio)Mass transferEmpirical modellingEmpirical researchComputer scienceSCALE-UPBiochemical engineeringIndustrial engineeringManagement scienceMathematicsEngineeringSimulationMechanicsAerospace engineeringPhysicsStatisticsClassical mechanicsQuantum mechanicsGranular flow and fluidized bedsFluid Dynamics and MixingMicrobial Metabolic Engineering and Bioproduction
Applying multiple approaches to deepen understanding of mixing and mass transfer in large-scale aerobic fermentations | Litcius