Automated Optimization of Mixing Elements for Single-Screw Extrusion Using CFD Simulations.

Area of Science:

• Polymer processing
• Materials science
• Chemical engineering

Background:

• Modern materials demand high mechanical performance and cost-effective production.
• Achieving this requires homogeneous material distribution and splitting via single-screw extrusion.
• Current computational fluid dynamics (CFD) methods often optimize dispersive or distributive mixing independently, neglecting their interplay.

Purpose of the Study:

• To develop an automated optimization tool for holistic single-screw extrusion mixing.
• To simultaneously optimize dispersive and distributive mixing processes.
• To consider pressure drop, temperature gradients, and quantitative mixing metrics.

Main Methods:

• Development of an automated optimization tool utilizing a genetic algorithm.
• Holistic optimization of mixing elements considering geometry and process conditions.
• Evaluation of pressure drop, temperature gradient, and quantitative metrics for dispersive and distributive mixing.

Main Results:

• Identification of compromises between geometry and metrics for improved dispersive mixing with moderate temperature gradients and pressure drops.
• Demonstrated dependencies between mixing metrics and geometry for dispersive mixing elements.
• Lack of clear correlations between mixing metrics and geometry for distributive mixing elements.

Conclusions:

• The developed genetic algorithm tool enables holistic optimization of single-screw extrusion mixing.
• The study highlights the complex interplay between geometry, process conditions, and mixing efficiency.
• Findings provide insights into designing more efficient and cost-effective polymer processing.