Discrete element modeling for continuous powder feeding operation: Calibration and system analysis.

Area of Science:

• Pharmaceutical Engineering
• Computational Fluid Dynamics
• Materials Science

Background:

• Extensive research focuses on predictive models and digital twins for pharmaceutical continuous manufacturing.
• Current models often lack detailed understanding of how powder material properties affect unit operations.
• Pharmaceutical powder feeding is a critical unit operation where material properties significantly influence performance.

Purpose of the Study:

• To investigate the impact of pharmaceutical powder material properties on feeder performance using discrete element modeling (DEM).
• To gain particle-level insights into powder flow and mixing dynamics within a feeder unit.
• To establish correlations between material properties and feeder operation for improved process understanding.

Main Methods:

• Application of discrete element modeling (DEM) combined with bulk material calibration.
• Simulation of a feeder unit to analyze particle flow and powder mixing.
• Investigation of different refill scenarios to assess powder mixing at the outlet.

Main Results:

• DEM simulations provided detailed physical insights into powder mechanics during feeding.
• Correlations between specific material properties and feeder performance were identified.
• Particle-scale information elucidated the influence of material properties on flow and mixing.

Conclusions:

• DEM with material calibration is effective for simulating pharmaceutical powder feeding operations.
• Understanding material property effects is essential for optimizing feeder performance in continuous manufacturing.
• This approach offers valuable particle-scale data for enhancing predictive models and digital twins.