This repository offers a collection of simulation datasets from mechanical simulations of metamaterials. Jupyter notbooks demonstrate how the datasets can be loaded.
Maintainer: Dominik Klein email
Contributors:
- Mauricio Fernández (Website, GitHub, Google Scholar)
- Mostafa Jamshidian (Google Scholar)
- Oliver Weeger (Website, Google Scholar)
- Huy Do
- Dominik Klein
The following Jupyter notebooks and readme files illustrate the provided datasets.
- Data on the effective constitutive behavior of soft 3D beam-lattice metamaterials
- This dataset was used in the work "Anisotropic hyperelastic material models for finite deformations combining material theory and data-driven approaches with application to cubic lattice metamaterials" by M. Fernández, M. Jamshidian, T. Böhlke, K. Kersting and O. Weeger. Comput Mech (2020) DOI 10.1007/s00466-020-01954-7.
- Data on the multiscale simulation of graded knitted textiles
- This dataset was used in the work "Nonlinear isogeometric multiscale simulation for design and fabrication of functionally graded knitted textiles" by H. Do, Y.Y. Tan, N. Ramos, J. Kiendl and O. Weeger. Composites Part B: Engineering, 202, p. 108416 (2020) DOI 10.1016/j.compositesb.2020.108416.
- Data on the effective constitutive behavior of parametric soft 3D beam-lattice metamaterials
- This dataset was used in the work "Material modeling for parametric, anisotropic finite hyperelasticity based on machine learning with application in optimization of metamaterials" by M. Fernández, F. Fritzen and O. Weeger, submitted 02/2021, pre-print: DOI 10.13140/RG.2.2.21536.10242.
- Data for second-gradient linear elastic homogenization of 3D beam lattices
- This dataset was used in the work "Numerical homogenization of second gradient, linear elastic constitutive models for cubic 3D beam-lattice metamaterials" by O. Weeger. International Journal of Solids and Structures, 224, p. 111037 (2021), DOI 10.1016/j.ijsolstr.2021.03.024.
- Data for the stochastic homogenization and ANN-based nonlinear multiscale simulation of a BCC lattice
- This dataset was used in the work "Nonlinear multiscale simulation of elastic beam lattices with anisotropic homogenized constitutive models based on artificial neural networks" by T. Gärtner, M. Fernández, and O. Weeger, submitted 03/2021, pre-print: DOI 10.13140/RG.2.2.18450.17604.
- Polyconvex constitutive models with neural networks for beam-lattice metamaterials
- These neural networks were used in the work "Polyconvex anisotropic hyperelasticity with neural networks" by D. K. Klein, M. Fernández, R. J. Martin, P. Neff and O. Weeger, accepted in the Journal of the Mechanics and Physics of Solids, DOI: 10.1016/j.jmps.2021.104703, see also arxiv.org/abs/2106.14623.
- Finite electro-elasticity with physics-augmented neural networks
- These neural networks were used in the work "Finite electro-elasticity with physics-augmented neural networks" by D. K. Klein, R. Ortigosa, J. Martínez-Frutos and O. Weeger, accepted in Computer Methods in Applied Mechanics and Engineering, DOI: 10.1016/j.cma.2022.115501, see also arxiv.org/abs/2206.05139.
Shield:
This work is licensed under a Creative Commons Attribution 4.0 International License.
