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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| Format: | Electronic Book Chapter |
| Language: | English |
| Published: |
KIT Scientific Publishing
2023
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| Series: | Schriftenreihe Kontinuumsmechanik im Maschinenbau
26 |
| Subjects: | |
| Online Access: | OAPEN Library: download the publication OAPEN Library: description of the publication |
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| 245 | 1 | 0 | |a Deep material networks for efficient scale-bridging in thermomechanical simulations of solids |
| 260 | |b KIT Scientific Publishing |c 2023 | ||
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| 490 | 1 | |a Schriftenreihe Kontinuumsmechanik im Maschinenbau |v 26 | |
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| 520 | |a 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. | ||
| 540 | |a Creative Commons |f https://creativecommons.org/licenses/by-sa/4.0/ |2 cc |4 https://creativecommons.org/licenses/by-sa/4.0/ | ||
| 546 | |a English | ||
| 650 | 7 | |a Mechanical engineering & materials |2 bicssc | |
| 653 | |a 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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| 856 | 4 | 0 | |a www.oapen.org |u https://library.oapen.org/handle/20.500.12657/76126 |7 0 |z OAPEN Library: description of the publication |