English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT

Released

Journal Article

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

MPS-Authors
/persons/resource/persons130594

Goyal,  Pawan Kumar
Computational Methods in Systems and Control Theory, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society;

/persons/resource/persons86253

Benner,  Peter       
Computational Methods in Systems and Control Theory, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society;

External Resource
No external resources are shared
Fulltext (restricted access)
There are currently no full texts shared for your IP range.
Fulltext (public)

2208.13490.pdf
(Preprint), 4MB

goyal_3424118.pdf
(Publisher version), 3MB

Supplementary Material (public)
There is no public supplementary material available
Citation

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.


Cite as: https://hdl.handle.net/21.11116/0000-000B-1C62-8
Abstract
There is no abstract available