Deep material networks for efficient scale-bridging in thermomechanical simulations of solids

We investigate deep material networks (DMN). We lay the mathematical foundation of DMNs and present a novel DMN formulation, which is characterized by a reduced number of degrees of freedom. We present a efficient solution technique for nonlinear DMNs to accelerate complex two-scale simulations with...

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Detaylı Bibliyografya

Yazar:	Gajek, Sebastian
Materyal Türü:	Online
Dil:	İngilizce
Baskı/Yayın Bilgisi:	KIT Scientific Publishing 2023
Konular:	deep material networks; data-driven modeling; Two-scale simulations; Deep Material Networks; Datengetriebene Modellierung; Zweiskalensimulationen; micromechanics; Mikromechanik; machine learning; Maschinelles Lernen
Online Erişim:	OCN: 1402511918
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