Data-Based Approach to Hyperelastic Membranes
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_ | 1866918143963693056 |
|---|---|
| author | Grabs, Claudia Wirges, Werner |
| author_facet | Grabs, Claudia Wirges, Werner |
| contents | We study large deformations of hyperelastic membranes using a purely two-dimensional formulation derived from basic balance principles within a modern geometric setting, ensuring a framework that is independent of an underlying three-dimensional formulation. To assess the predictive capabilities of membrane theory, we compare numerical solutions to experimental data from axisymmetric deformations of a silicone rubber film. Five hyperelastic models - Neo-Hookean, Mooney-Rivlin, Gent, Yeoh, and Ogden - are evaluated by fitting their material parameters to our experimental data using TensorFlow. Our results provide a systematic comparison of these models based on their accuracy in capturing observed deformations, establishing a framework for integrating theory, experiment, and data-based parameter identification. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_07120 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Data-Based Approach to Hyperelastic Membranes Grabs, Claudia Wirges, Werner Soft Condensed Matter 74B20, 74K15, 53A05 We study large deformations of hyperelastic membranes using a purely two-dimensional formulation derived from basic balance principles within a modern geometric setting, ensuring a framework that is independent of an underlying three-dimensional formulation. To assess the predictive capabilities of membrane theory, we compare numerical solutions to experimental data from axisymmetric deformations of a silicone rubber film. Five hyperelastic models - Neo-Hookean, Mooney-Rivlin, Gent, Yeoh, and Ogden - are evaluated by fitting their material parameters to our experimental data using TensorFlow. Our results provide a systematic comparison of these models based on their accuracy in capturing observed deformations, establishing a framework for integrating theory, experiment, and data-based parameter identification. |
| title | Data-Based Approach to Hyperelastic Membranes |
| topic | Soft Condensed Matter 74B20, 74K15, 53A05 |
| url | https://arxiv.org/abs/2504.07120 |