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  An Artificial Neural Network for Surrogate Modeling of Stress Fields in Viscoplastic Polycrystalline Materials

Khorrami, M. S., Mianroodi, J. R., Siboni, N. H., Goyal, P. K., Svendsen, B., Benner, P., et al. (2023). An Artificial Neural Network for Surrogate Modeling of Stress Fields in Viscoplastic Polycrystalline Materials. npj Computational Materials, 9: 37. doi:10.1038/s41524-023-00991-z.

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Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.

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Khorrami, Mohammad S.1, Author
Mianroodi, Jaber R.1, Author
Siboni, Nima H.1, Author
Goyal, Pawan Kumar2, Author           
Svendsen, Bob1, 3, Author
Benner, Peter2, Author                 
Raabe, Dierk1, Author
Affiliations:
1Max-Planck-Institut für Eisenforschung, ou_persistent22              
2Computational Methods in Systems and Control Theory, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society, ou_1738141              
3RWTH Aachen University, ou_persistent22              

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 Dates: 2022-08-292023
 Publication Status: Issued
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 Rev. Type: Peer
 Identifiers: arXiv: 2208.13490
DOI: 10.1038/s41524-023-00991-z
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Title: npj Computational Materials
Source Genre: Journal
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Pages: - Volume / Issue: 9 Sequence Number: 37 Start / End Page: - Identifier: -