Numerical generation of random fiber bundles and the influence of microstructural properties on mechanical behavior

TL;DR

This paper presents a numerical method to generate random fiber bundles that accurately reflect microstructural properties and influence their mechanical behavior, aiding in the development of better composite materials.

Contribution

A validated numerical generator for fiber bundles was developed, enabling detailed parametric studies of microstructure effects on mechanical response.

Findings

Increasing fiber waviness increases transverse stiffness.

Generated bundles match experimental compaction responses.

Microstructural properties significantly influence mechanical behavior.

Abstract

Understanding the mechanical behavior of quasi-parallel fiber networks is essential for improving the manufacturing processes of fiber-reinforced composites. Mesoscale models of dry yarns and reinforcements require constitutive laws that accurately reflect the heterogeneous microstructure of fiber bundles. This study aims to develop a numerical generator of random fiber bundles for microscopic parametric studies of compaction behavior. A real fiber bundle was first reconstructed from X-ray microtomography data, and the numerical strategy was validated by tracking fiber cross-sections along the bundle length, with a fiber-position error of 5.2%. Based on this validated framework, an experiment-independent generator was established to create parameterized fiber bundles. The generated bundles reproduced the experimental compaction response with good agreement. Parametric results showed that increasing fiber waviness enhances inter-fiber interactions, increases transverse stiffness, and requires a higher load to reach the same fiber volume fraction. This framework provides a useful microscopic basis for studying fiber-bundle deformation mechanisms and for developing future mesoscopic constitutive laws.