Deng, Shiguang, Hosseinmardi, Shirin, Wang, Libo, Apelian, Diran, and Bostanabad, Ramin. Data-driven physics-constrained recurrent neural networks for multiscale damage modeling of metallic alloys with process-induced porosity. Retrieved from https://par.nsf.gov/biblio/10520580. Computational Mechanics 74.1 Web. doi:10.1007/s00466-023-02429-1.

Deng, Shiguang, Hosseinmardi, Shirin, Wang, Libo, Apelian, Diran, & Bostanabad, Ramin. Data-driven physics-constrained recurrent neural networks for multiscale damage modeling of metallic alloys with process-induced porosity. Computational Mechanics, 74 (1). Retrieved from https://par.nsf.gov/biblio/10520580. https://doi.org/10.1007/s00466-023-02429-1

Deng, Shiguang, Hosseinmardi, Shirin, Wang, Libo, Apelian, Diran, and Bostanabad, Ramin. "Data-driven physics-constrained recurrent neural networks for multiscale damage modeling of metallic alloys with process-induced porosity". Computational Mechanics 74 (1). Country unknown/Code not available: Springer. https://doi.org/10.1007/s00466-023-02429-1. https://par.nsf.gov/biblio/10520580.

@article{osti_10520580,
place = {Country unknown/Code not available}, title = {Data-driven physics-constrained recurrent neural networks for multiscale damage modeling of metallic alloys with process-induced porosity}, url = {https://par.nsf.gov/biblio/10520580}, DOI = {10.1007/s00466-023-02429-1}, abstractNote = {}, journal = {Computational Mechanics}, volume = {74}, number = {1}, publisher = {Springer}, author = {Deng, Shiguang and Hosseinmardi, Shirin and Wang, Libo and Apelian, Diran and Bostanabad, Ramin}, }