RLN_Elasticity_Localization

Published: 12 February 2021| Version 2 | DOI: 10.17632/v6dt8dwrh8.2
Contributor:
Conlain Kelly

Description

Dataset for training and testing models described in Recurrent Localization Networks applied to the Lippmann-Schwinger Equation (https://arxiv.org/abs/2102.00063), accepted in Computational Materials Science. Contains 3D synthetic microstructures and strain fields (generation described in paper) for elastic stiffness contrast ratios 10 and 50. All fields are 31x31x31 voxels.

Files

Steps to reproduce

Microstructures generated using PyMKS. Strain fields generated using Abaqus. See paper for generation details.

Institutions

Georgia Institute of Technology

Categories

Computational Materials Science, Machine Learning

Licence