Integrating Experimental Crystallization Kinetics into Autodesk Moldflow: Validation and Crystallinity Prediction for...

Area of Science:

• Polymer Science
• Materials Engineering
• Computational Modeling

Background:

• Accurate prediction of semi-crystalline part properties in injection molding necessitates robust crystallization kinetics models.
• Existing models, like the Avrami-Hoffman-Lauritzen formulation, may not capture complex nucleation behaviors observed in all polymers.

Purpose of the Study:

• To present two practical strategies for incorporating experimentally derived crystallization kinetics into Autodesk Moldflow.
• To address limitations of the native Avrami-Hoffman-Lauritzen formulation for specific polymer crystallization behaviors.
• To validate the proposed methods using real-world polymer examples.

Main Methods:

• Developed two methods to integrate experimental crystallization data into Autodesk Moldflow.
• Applied methods to isotactic polypropylene (iPP T30G) with heterogeneous nucleation and polyoxymethylene (POM) with combined nucleation.
• Optimized Moldflow parameters by matching isothermal half-crystallization times (t0.5) and adjusting flow-induced nucleation terms.

Main Results:

• Successfully incorporated non-native crystallization kinetics into Moldflow simulations.
• Achieved good agreement between calculated and experimentally measured crystallinity evolution for iPP and POM.
• Reproduces measured spherulite diameters, indicating accurate prediction of microstructural development.

Conclusions:

• The presented strategies enhance the predictive accuracy of injection molding simulations for semi-crystalline polymers.
• These methods provide a practical approach to model complex crystallization behaviors beyond standard formulations.
• Improved simulation accuracy facilitates better prediction of final part properties and material selection.