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A Novel Approach to Automatically Balance Flow in Profile Extrusion Dies Through Computational Modeling.

Gabriel Wagner¹, João Vidal¹, Pierre Barbat²

¹Institute for Polymers and Composites-IPC, University of Minho, 4800-058 Guimarães, Portugal.

|June 13, 2025

Summary

This summary is machine-generated.

This study introduces an automated computational framework for optimizing extrusion dies, significantly improving flow uniformity and reducing pressure drop. The novel method enhances process efficiency and product quality for complex geometries.

Keywords:

Bayesian optimization OpenFOAM computational fluid dynamics extrusion die optimization flow balancing tire manufacturing

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Area of Science:

Materials Science and Engineering
Computational Fluid Dynamics
Process Optimization

Background:

Extrusion die design is critical for product quality and manufacturing efficiency.
Optimizing complex die geometries for non-isothermal, non-Newtonian flow presents significant challenges.
Current methods often require extensive manual input and iterative design processes.

Purpose of the Study:

To develop a fully automated computational framework for optimizing profile extrusion dies.
To achieve balanced flow at the die outlet and minimize total pressure drop.
To enhance process efficiency and reduce development time for complex die designs.

Main Methods:

Integration of OpenFOAM for non-isothermal, non-Newtonian flow modeling.
Utilized FreeCAD for geometry parameterization and Scikit-Optimize for Bayesian optimization.
Developed a custom solver incorporating the Bird-Carreau-Arrhenius model for temperature-dependent viscosity and viscous dissipation.

Main Results:

Demonstrated significant improvements in outlet velocity uniformity and reduced pressure drop in a tire tread die case study.
Achieved a 72.7% enhancement in the objective function, reducing it from 0.7333 to 0.2001.
The framework effectively navigated complex design spaces with minimal manual intervention.

Conclusions:

The proposed automated framework offers a robust and generalizable approach to extrusion die optimization.
This methodology significantly enhances process efficiency and reduces development time.
The results indicate improved final product quality, especially for complex automotive and tire industry dies.