deep-material-networks-for-efficient-scale-bridging-in-thermomechanical-simulations-of-solids.pdf
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...
| Γλώσσα: | English |
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| Έκδοση: |
KIT Scientific Publishing
2023
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| Διαθέσιμο Online: | https://doi.org/10.5445/KSP/1000155688 |
| Περίληψη: | 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. |
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