Mechanical Metamaterial: Square Array of Circular Holes Under Deformation
DOI10.5281/zenodo.14229619Zenodo14229619MaRDI QIDQ6693572
Dataset published at Zenodo repository.
Author name not available (Why is that?)
Publication date: 27 November 2024
Copyright license: No records found.
This repository contains data for a research project involving graph neural networks (GNNs) applied to mechanical metamaterials and their deformations. The mechanical metamaterials of interest consist of a flexible rubber-like material with a square grid of almost-circular holes in it, of various diameters. The holes are not quite circular, because they were made slightly elliptic to avoid the bifurcation point. This data was used to obtain the results in the paper 'Similarity Equivariant Graph Neural Networks for Homogenization of Metamaterials'. The data includes PyTorch Geometric Graph objects, raw data from MATLAB simulations, and files describing the finite element mesh. The Jupyter notebook 'data_create_graphs.ipynb' in the GitHub repository can be used to turn the raw data and mesh information into the graph objects. GitHub repository with the code:https://github.com/FHendriks11/SimEGNN ArXiv link to the corresponding paperSimilarity Equivariant Graph Neural Networks for Homogenization of Metamaterials:https://arxiv.org/abs/2404.17365 The .pkl files are pickle files and can be opened in Python using the standard pickle library. The mesh files, which have the extension .mat, are MatLab files and can be opened either in MatLab or in Python using scipy.io.loadmat from the scipy library.
This page was built for dataset: Mechanical Metamaterial: Square Array of Circular Holes Under Deformation
