A Novel Multi-Region, Multi-Phase, Multi-Component-Mixture Modeling Approach to Predicting the Thermodynamic...

Area of Science:

• Materials Science and Engineering
• Computational Fluid Dynamics
• Polymer Processing

Background:

• The consolidation step is critical in thermoplastic composite processing for reducing porosity and enhancing final component quality.
• Accurate modeling of thermodynamic behavior during hot-press consolidation is essential for process control and optimization.
• Existing models may lack the multi-phase, multi-component capabilities needed for complex composite systems.

Purpose of the Study:

• To develop and validate a multi-region, multi-phase, multi-component-mixture model for simulating thermoplastic composite hot-press consolidation.
• To assess the model's sensitivity to thermal parameters and mesh resolution, ensuring its robustness.
• To provide a tool for precise prediction of temperature evolution within the composite core.

Main Methods:

• Development of a custom model using the OpenFOAM® simulation toolbox.
• Implementation of a multi-region, multi-phase, and multi-component-mixture approach.
• Validation against experimental data for polycarbonate/carbon fiber and polypropylene/glass fiber composites.

Main Results:

• The developed model demonstrated robustness through sensitivity analyses on thermal parameters and mesh resolution.
• Simulation results closely matched experimental data, with a maximum deviation of 2.84% in predicting core temperature evolution.
• The model accurately estimates the time to reach critical temperatures like glass transition and melting points.

Conclusions:

• The validated thermodynamic model is highly suitable for optimizing thermoplastic composite hot-press consolidation processes.
• The model provides a strong foundation for future enhancements, including the development of a digital twin.
• Precise temperature prediction capabilities enable better control over composite quality and performance.