Mechanical MNIST - Confined Compression
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Citation (published version)Lejeune, E., 2020, Mechanical MNIST - Confined Compression. OpenBU, https://hdl.handle.net/2144/39427
Each dataset in the Mechanical MNIST collection contains the results of 70,000 (60,000 training examples + 10,000 test examples) finite element simulation of a heterogeneous material subject to large deformation. Mechanical MNIST is generated by first converting the MNIST bitmap images (http://www.pymvpa.org/datadb/mnist.html) to 2D heterogeneous blocks of material. Consistent with the MNIST bitmap ($28 \times 28$ pixels), the material domain is a $28 \times 28$ unit square. In "Mechanical MNIST - Equibiaxial Extension," the material is Neo-Hookean with a varying modulus. The top of the domain is free horizontally and moved vertically to a set of given fixed displacements (d = [-0.0, -0.001, -0.01, -0.1, -0.5, -1.0, -1.5, -2.0, -2.5, -3.0, -3.5] ), the right and left sides of the domain are free vertically and fixed horizontally, and the bottom of the domain is free horizontally and fixed vertically. The results of the simulations include: (1) change in strain energy at each step, (2) total reaction force at the top and right boundaries at each step, and (3) full field displacement at each step. All simulations are conducted with the FEniCS computing platform (https://fenicsproject.org). The code to reproduce these simulations is hosted on GitHub (https://github.com/elejeune11/Mechanical-MNIST/tree/master/generate_dataset).
The paper "Mechanical MNIST: A benchmark dataset for mechanical metamodels" can be found at https://doi.org/10.1016/j.eml.2020.100659. All code necessary to reproduce the metamodels demonstrated in the manuscript is available on GitHub (https://github.com/elejeune11/Mechanical-MNIST). For questions, please contact Emma Lejeune (firstname.lastname@example.org).
RightsThis dataset is distributed under the terms of the Creative Commons Attribution-ShareAlike 4.0 License. The original MNIST bitmaps are from Yann LeCun (Courant Institute, NYU) and Corinna Cortes (Google Labs, New York) on PyMVPA (http://www.pymvpa.org/datadb/mnist.html) licensed with https://creativecommons.org/licenses/by-sa/4.0/. The finite element simulations were conducted by Emma Lejeune using the open source software FEniCS (https://fenicsproject.org/).