# Nonlinear Elasticity and Damage Prediction in Automated Fiber Placement Composites via Nested Micromechanics

## TL;DR

This paper introduces a modeling framework to predict the mechanical behavior and damage in automated fiber placement composites by accounting for manufacturing-induced structural variations.

## Contribution

A novel nested micromechanics framework using PHFGMC is developed to predict nonlinear elasticity and damage in AFP composites.

## Key findings

- The PHFGMC model accurately predicts effective elastic properties and nonlinear mechanical responses of AFP composites.
- Mesostructural features like tow gaps and resin-rich regions significantly influence global stress–strain behavior.
- The model successfully captures damage initiation and crack propagation linked to manufacturing-induced defects.

## Abstract

Automated fiber placement (AFP) composites exhibit complex mechanical behaviors due to manufacturing-induced mesostructural variations, including resin-rich regions and tow gaps that significantly influence both local stress distributions and global material responses. This study presents a hierarchically nested modeling framework based on the Parametric High-Fidelity Generalized Method of Cells (PHFGMC) to predict the effective elastic properties and nonlinear mechanical response of AFP composites. The PHFGMC model integrates micro- and meso-scale analyses using representative volume elements (RVEs) derived from micrographs of AFP composite laminates to capture these manufacturing-induced characteristics. Multiple RVE configurations with varied gap patterns are analyzed to quantify the influence of mesostructural features on global stress–strain response. Predictions for linear and nonlinear elastic behaviors are validated against experimental results from carbon fiber/epoxy AFP specimens, demonstrating good quantitative agreement with measured responses. A cohesive extension of the PHFGMC framework further captures damage initiation and crack propagation under transverse tensile loading, revealing failure mechanisms specifically associated with tow gaps and resin-rich areas. By systematically accounting for manufacturing-induced variability through detailed RVE modeling, the nested PHFGMC framework enables the accurate prediction of global mechanical performance and localized behavior, providing a robust computational tool for optimizing AFP composite design in aerospace and other high-performance applications.