Tensile and Compression Strength Prediction and Validation in 3D-Printed Short-Fiber-Reinforced Polymers

Area of Science:

• Materials Science
• Mechanical Engineering
• Additive Manufacturing

Background:

• 3D printing, particularly large area additive manufacturing (LAAM), enables the production of large composite components.
• Short-fiber-reinforced polymers exhibit spatially varying microstructural behavior, influencing mechanical properties.
• Accurate prediction of anisotropic stiffness and strength is crucial for reliable component design.

Purpose of the Study:

• To validate a methodology for predicting internal, spatially varying strength properties in 3D-printed acrylonitrile butadiene styrene (ABS) composite beads.
• To develop a modeling framework for characterizing local anisotropic stiffness and strength.
• To integrate these local properties into a finite element framework for bulk property estimation.

Main Methods:

• A methodology was developed and validated for predicting spatially varying mechanical properties within a single 3D-printed bead.
• Characterization of spatially varying microstructural behavior was performed.
• A finite element framework was utilized to integrate local properties for effective stiffness and strength estimation.

Main Results:

• The modeling framework accurately predicted effective strength and stiffness, aligning closely with experimental data.
• Effective longitudinal compressive strength was predicted within ~1% and tensile strength within ~10%.
• Effective longitudinal compressive stiffness was predicted within ~3% and tensile stiffness within ~50%.

Conclusions:

• The validated methodology provides a reliable approach for predicting mechanical properties in 3D-printed short-fiber-reinforced polymers.
• The developed finite element framework enables accurate bulk property estimation for LAAM components.
• This work contributes to improved design and performance prediction of additively manufactured composite structures.