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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Bibliografische gegevens
Hoofdauteur: Gajek, Sebastian (auth)
Formaat: Elektronisch Hoofdstuk
Taal:Engels
Gepubliceerd in: KIT Scientific Publishing 2023
Reeks:Schriftenreihe Kontinuumsmechanik im Maschinenbau 26
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Samenvatting: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 minimal computational effort. A new interpolation technique is presented enabling the consideration of fluctuating microstructure characteristics in macroscopic simulations.
Fysieke beschrijving:1 electronic resource (326 p.)
ISBN:KSP/1000155688
Toegang:Open Access