Yarn Model

Yarn modeling focuses on creating realistic computational representations of yarn structures and their behavior, aiming to improve the simulation and design of textiles. Current research employs neural networks, often ensembles, trained on synthetic or real yarn image datasets to infer yarn parameters from images and build procedural models capable of generating fiber-level detail. A key trend involves developing differentiable physics models that incorporate fine-grained yarn-level interactions and forces, enabling more accurate and efficient simulations of fabric dynamics. This work has implications for textile design, virtual prototyping, and a deeper understanding of material properties at the yarn scale.