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Nonlinear Elasticity and Damage Prediction in Automated Fiber Placement Composites via Nested Micromechanics
Hadas Hochster1, Gal Raanan1, Eyal Tiosano1
1School of Mechanical Engineering, Tel Aviv University, Tel Aviv 6997801, Israel.
Materials (Basel, Switzerland)
|July 30, 2025
Summary
This study introduces a new modeling framework to predict the mechanical behavior of automated fiber placement (AFP) composites, accounting for manufacturing defects like gaps and resin-rich areas. The model accurately predicts composite performance, aiding in optimizing designs for demanding applications.
Area of Science:
- Materials Science
- Mechanical Engineering
- Computational Mechanics
Background:
- Automated fiber placement (AFP) composites exhibit complex mechanical behaviors due to manufacturing-induced mesostructural variations.
- Variations such as resin-rich regions and tow gaps significantly influence local stress distributions and global material responses in AFP composites.
Purpose of the Study:
- To present a hierarchically nested modeling framework based on the Parametric High-Fidelity Generalized Method of Cells (PHFGMC) for predicting the effective elastic properties and nonlinear mechanical response of AFP composites.
- To quantify the influence of mesostructural features on the global stress-strain response of AFP composites.
Main Methods:
- The PHFGMC model integrates micro- and meso-scale analyses using representative volume elements (RVEs) derived from micrographs of AFP composite laminates.
- Multiple RVE configurations with varied gap patterns were analyzed to capture manufacturing-induced characteristics.
- A cohesive extension of the PHFGMC framework was used to capture damage initiation and crack propagation.
Main Results:
- Predictions for linear and nonlinear elastic behaviors were validated against experimental results from carbon fiber/epoxy AFP specimens, showing good quantitative agreement.
- The study revealed failure mechanisms associated with tow gaps and resin-rich areas under transverse tensile loading.
- The framework accurately predicts both global mechanical performance and localized behavior.
Conclusions:
- The nested PHFGMC framework provides a robust computational tool for accurately predicting the mechanical performance of AFP composites.
- Systematically accounting for manufacturing-induced variability through detailed RVE modeling is crucial for optimizing AFP composite design.
- This approach supports the design of advanced composite materials for aerospace and other high-performance applications.
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