Data-driven physics-constrained recurrent neural networks for multiscale damage modeling of metallic alloys with process-induced porosity.
Saved in:
| Title: | Data-driven physics-constrained recurrent neural networks for multiscale damage modeling of metallic alloys with process-induced porosity. |
|---|---|
| Authors: | Deng, Shiguang1,2 (AUTHOR), Hosseinmardi, Shirin3 (AUTHOR), Wang, Libo1 (AUTHOR), Apelian, Diran1 (AUTHOR), Bostanabad, Ramin3 (AUTHOR) Raminb@uci.edu |
| Source: | Computational Mechanics. Jul2024, Vol. 74 Issue 1, p191-221. 31p. |
| Database: | Academic Search Ultimate |
|
Full text is not displayed to guests.
Login for full access.
|
|
Be the first to leave a comment!
