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| Autori principali: | , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2026
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| Soggetti: | |
| Accesso online: | https://arxiv.org/abs/2605.20161 |
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| _version_ | 1866911698739265536 |
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| author | Song, Xinling Hivet, Gilles Hivet, Audrey Shanwan, Anwar |
| author_facet | Song, Xinling Hivet, Gilles Hivet, Audrey Shanwan, Anwar |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2605_20161 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Numerical generation of random fiber bundles and the influence of microstructural properties on mechanical behavior Song, Xinling Hivet, Gilles Hivet, Audrey Shanwan, Anwar Classical Physics 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. |
| title | Numerical generation of random fiber bundles and the influence of microstructural properties on mechanical behavior |
| topic | Classical Physics |
| url | https://arxiv.org/abs/2605.20161 |