Performance prediction of industrial centrifuges using scale-down models.

Area of Science:

• Biochemical Engineering
• Fluid Dynamics
• Separation Science

Background:

• Centrifugal separation is crucial for processing shear-sensitive biomolecules like protein precipitates.
• Accurate scale-down models are needed to predict large-scale centrifuge performance.
• Existing pilot-scale methods may not fully capture the complex fluid dynamics in production centrifuges.

Purpose of the Study:

• To develop and validate a novel scale-down device for modeling high flow forces in centrifuge feed zones.
• To assess the predictive capability of this device for various continuous-flow centrifuges.
• To compare the accuracy of ultra scale-down centrifugation with pilot-scale centrifugation for performance prediction.

Main Methods:

• Computational fluid dynamics (CFD) was employed to model flow forces within a multichamber-bowl centrifuge.
• A small, high-speed rotating disc device was engineered to replicate these modeled forces.
• The device was integrated into a scale-down centrifugation process to evaluate different centrifuge types (disc stack, multichamber bowl, CARR Powerfuge).

Main Results:

• The scale-down device successfully reproduced the high flow forces characteristic of centrifuge feed zones.
• Scale-down centrifugation using this device provided accurate performance estimations for continuous-flow centrifuges.
• Ultra scale-down centrifugation proved to be a significantly better predictor of production multichamber-bowl centrifuge performance compared to pilot-scale centrifugation.

Conclusions:

• A novel high-speed rotating disc device, informed by CFD, enables accurate simulation of centrifuge feed zone hydrodynamics.
• Ultra scale-down centrifugation offers superior prediction accuracy for protein precipitate separation in production centrifuges.
• This approach enhances the reliability of scaling up bioprocesses involving shear-sensitive materials.