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Modeling large-scale bioreactors with diffusion equations. Part I: Predicting axial diffusivity and mixing times
  • Pauli Losoi,
  • Jukka Konttinen,
  • Ville Santala
Pauli Losoi
Tampereen yliopisto - Hervannan kampus

Corresponding Author:pauli.losoi@tuni.fi

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Jukka Konttinen
Tampereen yliopisto - Hervannan kampus
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Ville Santala
Tampereen yliopisto - Hervannan kampus
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Abstract

Bioreactor scale-up is complicated by dynamic interactions between mixing, reaction, mass transfer, and biological phenomena, the effects of which are usually predicted with simple correlations or case-specific simulations. This two-part study investigated whether axial diffusion equations could be used to calculate mixing times and to model and characterize large-scale stirred bioreactors in a general and predictive manner without fitting the diffusivity parameter. In this first part, a resistances-in-series model analogous to basic heat transfer theory was developed to estimate the diffusivity such that only available hydrodynamic numbers and literature data were needed in calculations. For model validation, over 800 previously published experimentally determined mixing times were predicted with the transient axial diffusion equation. The collected data covered reactor sizes up to 160 m 3, single- and multi-impeller configurations, aerated and non-aerated operation in turbulent and transition flow regimes, and various mixing time quantification methods. The model performed excellently for typical multi-impeller configurations as long as flooding conditions were avoided. Mixing times for single-impeller and few non-standard bioreactors were not predicted equally well. The transient diffusion equation together with the developed transfer resistance analogy proved to be a convenient and predictive model of mixing in typical large-scale bioreactors.
21 Jul 2023Submitted to Biotechnology and Bioengineering
21 Jul 2023Submission Checks Completed
21 Jul 2023Assigned to Editor
21 Jul 2023Review(s) Completed, Editorial Evaluation Pending
25 Aug 2023Reviewer(s) Assigned
30 Oct 2023Editorial Decision: Revise Major
14 Nov 20231st Revision Received
15 Nov 2023Submission Checks Completed
15 Nov 2023Assigned to Editor
15 Nov 2023Review(s) Completed, Editorial Evaluation Pending