Volumetric Homogenization for Knitwear Simulation
<|reference_start|>Volumetric Homogenization for Knitwear Simulation: This paper presents volumetric homogenization, a spatially varying homogenization scheme for knitwear simulation. We are motivated by the observation that macro-scale fabric dynamics is strongly correlated with its underlying knitting patterns. Therefore, homogenization towards a single material is less effective when the knitting is complex and non-repetitive. Our method tackles this challenge by homogenizing the yarn-level material locally at volumetric elements. Assigning a virtual volume of a knitting structure enables us to model bending and twisting effects via a simple volume-preserving penalty and thus effectively alleviates the material nonlinearity. We employ an adjoint Gauss-Newton formulation to battle the dimensionality challenge of such per-element material optimization. This intuitive material model makes the forward simulation GPU-friendly. To this end, our pipeline also equips a novel domain-decomposed subspace solver crafted for GPU projective dynamics, which makes our simulator hundreds of times faster than the yarn-level simulator. Experiments validate the capability and effectiveness of volumetric homogenization. Our method produces realistic animations of knitwear matching the quality of full-scale yarn-level simulations. It is also orders of magnitude faster than existing homogenization techniques in both the training and simulation stages.<|reference_end|>
@article{yuan2024volumetric,
    title={Volumetric Homogenization for Knitwear Simulation},
    author={Chun Yuan, Haoyang Shi, Lei Lan, Yuxing Qiu, Cem Yuksel, Huamin Wang,
  Chenfanfu Jiang, Kui Wu, Yin Yang},
    journal={arXiv preprint arXiv:2405.12484},
    year={2024},
    archivePrefix={arXiv},
    eprint={2405.12484},
    primaryClass={cs.GR}
}