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

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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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Auteur principal: Gajek, Sebastian (auth)
Format: Électronique Chapitre de livre
Langue:anglais
Publié: KIT Scientific Publishing 2023
Collection:Schriftenreihe Kontinuumsmechanik im Maschinenbau
Sujets:
Mechanical engineering & materials
deep material networks; data-driven modeling; Two-scale simulations; Deep Material Networks; Datengetriebene Modellierung; Zweiskalensimulationen; micromechanics; Mikromechanik; machine learning; Maschinelles Lernen
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