Published June 21, 2020 | Version v1
Dataset Open

Data of A recurrent neural network-accelerated multi-scale model for elasto-plastic heterogeneous materials subjected to random cyclic and non-proportional loading paths

Creators

  • 1. University of Liege

Description

Data related to the publication (we would be grateful if you could cite the paper in the case in which you are using the data) 
title = "A recurrent neural network-accelerated multi-scale model for elasto-plastic heterogeneous materials subjected to random cyclic and non-proportional loading paths",
journal = "Computer Methods in Applied Mechanics and Engineering",
pages = " 113234",
year = "2020",
issn = "0045-7825",
doi = "https://doi.org/10.1016/j.cma.2020.113234",
author = "Wu, Ling and Nguyen, Van Dung and Kilingar, Nanda Gopala and Noels, Ludovic"

Notes

This project has received funding from the European Unions Horizon 2020 research and innovation programme under grant agreement No 862015 for the project "Multi-scale Optimisation for Additive Manufacturing of fatigue resistant shock-absorbing MetaMaterials (MOAMMM)" of the H2020-EU.1.2.1. -FET Open Programme. N.G. Kilingar was financed by the EnlightenIt project, grant number PDR T.0038.16 of FRS-FNRS. V.D. Nguyen was a Postdoctoral Researcher at the Belgian National Fund for Scientific Research (FNRS)

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moammmpublic-master-publicationsData-2020_CMAME_RNN.zip

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Additional details

Related works

Is documented by
Journal article: 10.1016/j.cma.2020.113234 (Handle)

Funding

European Commission
MOAMMM – Multi-scale Optimisation for Additive Manufacturing of fatigue resistant shock-absorbing MetaMaterials 862015