Data-driven physics-constrained recurrent neural networks for multiscale damage modeling of metallic alloys with process-induced porosity (Q6584871)
From MaRDI portal
 | This is the item page for this Wikibase entity, intended for internal use and editing purposes. Please use this page instead for the normal view: Data-driven physics-constrained recurrent neural networks for multiscale damage modeling of metallic alloys with process-induced porosity |
scientific article; zbMATH DE number 7893937
| Language | Label | Description | Also known as |
|---|---|---|---|
| English | Data-driven physics-constrained recurrent neural networks for multiscale damage modeling of metallic alloys with process-induced porosity |
scientific article; zbMATH DE number 7893937 |
Statements
Data-driven physics-constrained recurrent neural networks for multiscale damage modeling of metallic alloys with process-induced porosity (English)
0 references
8 August 2024
0 references
deep learning model
0 references
microscale simulation
0 references
irreversible elasto-plastic hardening/softening
0 references
path dependence
0 references
training data generation
0 references
0 references
0 references
0 references
0 references
0 references
0 references
0 references
0 references
0 references
0 references
0 references
0 references
0 references
0 references
