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| Auteurs principaux: | , , , |
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| Format: | Preprint |
| Publié: |
2025
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| Sujets: | |
| Accès en ligne: | https://arxiv.org/abs/2501.16194 |
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| _version_ | 1866909466993098752 |
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| author | Jung, Anne Redenbach, Claudia Schladitz, Katja Staub, Sarah |
| author_facet | Jung, Anne Redenbach, Claudia Schladitz, Katja Staub, Sarah |
| contents | Image acquisition techniques such as micro-computed tomography are nowadays widely available. Quantitative analysis of the resulting 3D image data enables geometric characterization of the micro-structure of materials. Stochastic geometry models can be fit to the observed micro-structures. By alteration of the model parameters, virtual micro-structures with modified geometry can be generated. Numerical simulation of elastic properties in realizations of these models yields deeper insight on the influence of particular micro-structural features. Ultimately, this allows for an optimization of the micro-structure geometry for particular applications. Here, we present this workflow at the example of open cell foams. Applicability is demonstrated using an aluminum alloy foam sample. The structure observed in a micro-computed tomography image is modeled by the edge system of a random Laguerre tessellation generated by a system of closely packed spheres. Elastic moduli are computed in the binarized micro-CT image of the foam as well as in realizations of the model. They agree well with the results of a compression test on the real material. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2501_16194 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | 3D image based stochastic micro-structure modelling of foams for simulating elasticity Jung, Anne Redenbach, Claudia Schladitz, Katja Staub, Sarah Numerical Analysis 60D05 Image acquisition techniques such as micro-computed tomography are nowadays widely available. Quantitative analysis of the resulting 3D image data enables geometric characterization of the micro-structure of materials. Stochastic geometry models can be fit to the observed micro-structures. By alteration of the model parameters, virtual micro-structures with modified geometry can be generated. Numerical simulation of elastic properties in realizations of these models yields deeper insight on the influence of particular micro-structural features. Ultimately, this allows for an optimization of the micro-structure geometry for particular applications. Here, we present this workflow at the example of open cell foams. Applicability is demonstrated using an aluminum alloy foam sample. The structure observed in a micro-computed tomography image is modeled by the edge system of a random Laguerre tessellation generated by a system of closely packed spheres. Elastic moduli are computed in the binarized micro-CT image of the foam as well as in realizations of the model. They agree well with the results of a compression test on the real material. |
| title | 3D image based stochastic micro-structure modelling of foams for simulating elasticity |
| topic | Numerical Analysis 60D05 |
| url | https://arxiv.org/abs/2501.16194 |