Revisiting Preparation of Phase Space for Learning Path-Dependent Behavior via Deep Neural Networks

AbstractThis technical note investigates the preparation of a phase space of two simple constitutive laws, von Mises (J2) and Drucker-Prager (DP) models, for deep neural networks with special attention to elastic and plastic data points. The phase space is referred to as a database describing the ma...

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Veröffentlicht in:	Journal of engineering mechanics 2022-12, Vol.148 (12)
Hauptverfasser:	Motevali Haghighi, Ehsan, Na, SeonHong
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial neural networks Data points Machine learning Neural networks Robustness (mathematics) Technical Note Technical Notes
Online-Zugang:	Volltext
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