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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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書誌詳細
第一著者:	Gajek, Sebastian (auth)
フォーマット:	電子媒体図書の章
言語:	英語
出版事項:	KIT Scientific Publishing 2023
シリーズ:	Schriftenreihe Kontinuumsmechanik im Maschinenbau 26
主題:	Mechanical engineering & materials deep material networks; data-driven modeling; Two-scale simulations; Deep Material Networks; Datengetriebene Modellierung; Zweiskalensimulationen; micromechanics; Mikromechanik; machine learning; Maschinelles Lernen
オンライン･アクセス:	OAPEN Library: download the publication OAPEN Library: description of the publication
タグ:	タグ追加タグなし, このレコードへの初めてのタグを付けませんか!

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