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View all- Ando R(2024)A Cubic Barrier with Elasticity-Inclusive Dynamic StiffnessACM Transactions on Graphics10.1145/368790843:6(1-13)Online publication date: 19-Dec-2024
Neural-Assisted Homogenization of Yarn-Level Cloth
Authors: 
Xudong Feng, 
Huamin Wang, 
Yin Yang, Weiwei XuAuthors Info & Claims
Article No.: 80, Pages 1 - 10
Abstract
Real-world fabrics, composed of threads and yarns, often display complex stress-strain relationships, making their homogenization a challenging task for fast simulation by continuum-based models. Consequently, existing homogenized yarn-level models frequently struggle with numerical stability without line search at large time steps, forcing a trade-off between model accuracy and stability. In this paper, we propose a neural-assisted homogenized constitutive model for simulating yarn-level cloth. Unlike analytic models, a neural model is advantageous in adapting to complex dynamic behaviors, and its inherent smoothness naturally mitigates stability issues. We also introduce a sector-based warm-start strategy to accelerate the data collection process in homogenization. This model is trained using collected strain energy datasets and its accuracy is validated through both qualitative and quantitative experiments. Thanks to our model’s stability, our simulator can now achieve two-orders-of-magnitude speedups with large time steps compared to previous models.
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Published: 13 July 2024
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View all- Ando R(2024)A Cubic Barrier with Elasticity-Inclusive Dynamic StiffnessACM Transactions on Graphics10.1145/368790843:6(1-13)Online publication date: 19-Dec-2024
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