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Beschreibung
We present a Fast-Fourier-Transform (FFT) based computational approach to computing the viscous stress response of rigid fibers suspended in a non-Newtonian medium. We identify closed-form models for the fiber suspension viscosity from data obtained with the FFT-based computational approach by leveraging supervised machine learning techniques. Furthermore, we present a novel Deep Material Network architecture capable of treating suspensions of rigid particles with high computational efficiency.
Details
| Verlag | KIT Scientific Publishing |
| Ersterscheinung | 24. November 2025 |
| Maße | 21 cm x 14.8 cm |
| Gewicht | 390 Gramm |
| Format | Softcover |
| ISBN-13 | 9783731514213 |
| Auflage | 1. Auflage |
| Seiten | 206 |
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