Geometric quantification for nonlinear deformation in knitted fabrics
Jiani Fang, Xiaoxiao Ding, Gary P. T. Choi

TL;DR
This paper introduces a geometric quantification framework that reconstructs yarn and fabric surfaces from sparse data, enabling detailed analysis of nonlinear deformation in knitted fabrics.
Contribution
It provides a novel geometric description method that captures stitch-resolved deformation and deformation evolution, linking geometry to mechanical behavior in knitted textiles.
Findings
Reconstructs yarn centerlines and fabric surfaces from sparse data.
Analyzes how deformation distributes among stitch reorientation, loop bending, and surface dilation.
Defines a geometric state space for comparing and analyzing knitted structures.
Abstract
Knitted fabrics exemplify a broad class of architected materials capable of large deformations, enabling shape morphing, mechanical biocompatibility, and embedded multifunctionality without material damage. Although geometric nonlinearity has been intuitively utilized in their design, a quantitative description of stitch-resolved deformation and its temporal evolution remains lacking. Here, we introduce a geometric quantification framework that reconstructs smooth yarn centerlines and fabric surfaces from sparse yarn-level representations and extracts interpretable descriptors across dimensions. Applied to representative knitted structures, this framework resolves how global deformation is distributed among stitch reorientation, loop bending, surface bending, and dilation. Moreover, it reveals how regions of large geometric variation emerge, persist, and redistribute over time. Rather…
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