Wallpaper Group-Based Mechanical Metamaterials: Dataset Including Mechanical Responses
Fuente:
arXiv
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866911167481380864 |
|---|---|
| author | Hendriks, Fleur Menkovski, Vlado Doškář, Martin Geers, Marc G. D. Verbeek, Kevin Rokoš, Ondřej |
| author_facet | Hendriks, Fleur Menkovski, Vlado Doškář, Martin Geers, Marc G. D. Verbeek, Kevin Rokoš, Ondřej |
| contents | Mechanical metamaterials often exhibit pattern transformations through instabilities, enabling applications in, e.g., soft robotics, sound reduction, and biomedicine. These transformations and their resulting mechanical properties are closely tied to the symmetries in these metamaterials' microstructures, which remain under-explored. Designing such materials is challenging due to the unbounded design space, and while machine learning offers promising tools, they require extensive training data. Here, we present a large dataset of 2D microstructures and their macroscopic mechanical responses in the hyperelastic, finite-strain regime, including buckling. The microstructures are generated using a novel method, which covers all 17 wallpaper symmetry groups and employs Bézier curves for a rich parametric space. Mechanical responses are obtained through finite element-based computational homogenization. The dataset includes 1,020 distinct geometries, each subjected to 12 loading trajectories, totaling 12,240 trajectories. Our dataset supports the development and benchmarking of surrogate models, facilitates the study of symmetry-property relationships, and enables investigations into symmetry-breaking during pattern transformations, potentially revealing emergent behavior in mechanical metamaterials. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_11195 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Wallpaper Group-Based Mechanical Metamaterials: Dataset Including Mechanical Responses Hendriks, Fleur Menkovski, Vlado Doškář, Martin Geers, Marc G. D. Verbeek, Kevin Rokoš, Ondřej Soft Condensed Matter Computational Physics Mechanical metamaterials often exhibit pattern transformations through instabilities, enabling applications in, e.g., soft robotics, sound reduction, and biomedicine. These transformations and their resulting mechanical properties are closely tied to the symmetries in these metamaterials' microstructures, which remain under-explored. Designing such materials is challenging due to the unbounded design space, and while machine learning offers promising tools, they require extensive training data. Here, we present a large dataset of 2D microstructures and their macroscopic mechanical responses in the hyperelastic, finite-strain regime, including buckling. The microstructures are generated using a novel method, which covers all 17 wallpaper symmetry groups and employs Bézier curves for a rich parametric space. Mechanical responses are obtained through finite element-based computational homogenization. The dataset includes 1,020 distinct geometries, each subjected to 12 loading trajectories, totaling 12,240 trajectories. Our dataset supports the development and benchmarking of surrogate models, facilitates the study of symmetry-property relationships, and enables investigations into symmetry-breaking during pattern transformations, potentially revealing emergent behavior in mechanical metamaterials. |
| title | Wallpaper Group-Based Mechanical Metamaterials: Dataset Including Mechanical Responses |
| topic | Soft Condensed Matter Computational Physics |
| url | https://arxiv.org/abs/2507.11195 |