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Scale-down studies on the hydrodynamics of two-liquid phase biocatalytic reactors
S G Cull1, J W Lovick, G J Lye
1The Advanced Centre for Biochemical Engineering, Department of Biochemical Engineering, University College London, Torrington Place, London WC1E 7JE, UK.
Bioprocess and Biosystems Engineering
|September 26, 2003
Summary
Scaling up two-liquid bioconversion processes requires maintaining constant interfacial area. Constant power input per unit volume is the best method for scale-up, ensuring consistent drop size and distributions between reactors.
Area of Science:
- Biochemical Engineering
- Chemical Engineering
- Process Scale-up
Background:
- Successful scale-up of two-liquid phase bioconversion relies on maintaining constant interfacial area per unit volume.
- Limited hydrodynamic data and undefined scale-up bases hinder the advancement of these processes.
Purpose of the Study:
- To investigate the hydrodynamics of a whole-cell bioconversion process.
- To define and verify a suitable basis for scaling up two-liquid phase bioconversion reactors.
- To compare scale-up strategies based on constant power input per unit volume versus constant tip speed.
Main Methods:
- Performed experiments in geometrically similar 3-L and 75-L reactors with Rushton turbine impellers.
- Measured power input using an air-bearing technique for single-phase and two-phase mixing.
- Utilized in-situ light-backscattering to measure drop size distributions and Sauter mean diameters (d32) on-line.
Main Results:
- Power number reached a constant value of 11 at Re>10,000 for both single-phase and two-phase systems.
- Drop size diameter (d32) decreased with increasing agitation rate, with values ranging from 30-50 micrometers.
- Constant power input per unit volume proved to be the most effective scale-up basis, yielding identical d32 values and drop size distributions at both scales.
Conclusions:
- Constant power input per unit volume is the optimal scale-up parameter for two-liquid phase bioconversion processes.
- The study provides correlations for predicting d32 values, aiding process design.
- The developed scale-down methodology allows for rapid evaluation of other bioconversion processes, identifying potential scale-up issues early.