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

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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Bibliographic Details
Main Authors: Mohammad Zhian Asadzadeh, Klaus Roppert, Peter Raninger
Format: Article
Language:English
Published: MDPI AG 2023-07-01
Series:Materials
Subjects:
neural networks
inverse problems
PINNS
induction heating
material data
Online Access:https://www.mdpi.com/1996-1944/16/14/5013

Internet

https://www.mdpi.com/1996-1944/16/14/5013

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