Material Data Identification in an Induction Hardening Test Rig with Physics-Informed Neural Networks

Physics-Informed neural networks (PINNs) have demonstrated remarkable performance in solving partial differential equations (PDEs) by incorporating the governing PDEs into the network’s loss function during optimization. PINNs have been successfully applied to diverse inverse and forward problems. T...

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Detalles Bibliográficos
Autores principales: Asadzadeh, Mohammad Zhian, Roppert, Klaus, Raninger, Peter
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10384654/
https://www.ncbi.nlm.nih.gov/pubmed/37512288
http://dx.doi.org/10.3390/ma16145013

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10384654/
https://www.ncbi.nlm.nih.gov/pubmed/37512288
http://dx.doi.org/10.3390/ma16145013

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