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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 minimal computational effort. A new interpolation technique is presented enabling the consideration of fluctuating microstructure characteristics in macroscopic simulations.
Umfang: XI, 297 S.
Preis: 42.00 €
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Gajek, S. 2023. Deep material networks for efficient scale-bridging in thermomechanical simulations of solids. Karlsruhe: KIT Scientific Publishing. DOI: https://doi.org/10.5445/KSP/1000155688
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Veröffentlicht am 25. August 2023
Englisch
326
| Paperback | 978-3-7315-1278-3 |