Physics-informed machine learning-based real-time long-horizon temperature fields prediction in metallic additive manufacturing

Guardat en:

Dades bibliogràfiques
Publicat a:	Communications Engineering vol. 4, no. 1 (Dec 2025), p. 168
Autor principal:	Tian, Mingxuan
Altres autors:	Mu, Haochen, Liu, Tao, Li, Mengjiao, Ding, Donghong, Zhao, Jianping
Publicat:	Springer Nature B.V.
Matèries:	Temperature distribution Finite element method Finite volume method Accuracy Fluid dynamics Parameter identification Quality assurance Boundary conditions Data processing Manufacturing Machine learning Low carbon steel Additive manufacturing Efficiency Simulation Physics Partial differential equations Residual stress Temperature Neural networks Process controls Recurrent neural networks Data collection Finite element analysis Errors Real time
Accés en línia:	Citation/Abstract Full Text Full Text - PDF
Etiquetes:	Afegir etiqueta Sense etiquetes, Sigues el primer a etiquetar aquest registre!

Sigues el primer a deixar un comentari!