Inverse Design of Tightly Woven Smart Fabrics

TL;DR

This paper introduces a geometric framework for the inverse design of smart woven fabrics that can be programmed to conform to arbitrary 3D shapes upon actuation, using a reduction to a single scalar degree of freedom.

Contribution

It develops a novel inverse design method for smart fabrics based on a geometric reduction and nonlinear PDE, enabling programmable shape transformation.

Findings

Validated the framework with exact solutions for symmetric shapes.

Demonstrated numerical optimization for complex freeform surfaces.

Confirmed the practicality of designing fabrics for arbitrary 3D shapes.

Abstract

We present a geometric framework for the inverse design of smart woven fabrics composed of non-uniformly shrinking threads. A sufficiently tight weaving structure imposes strong local criteria on the material deformation and reduces the local geometry to a single scalar degree of freedom. Control over this degree of freedom can be achieved through simple calibration for each specific material system, via either mechanical experiments or numerical simulations. This reduction allows us to inverse-design a woven smart fabric, that conforms to an arbitrary target geometry when actuated, by solving a nonlinear hyperbolic partial differential equation. We validate this approach by deriving the thread-level actuation required for specific target geometries. We present both exact analytic solutions for symmetric shapes and a numerical optimization method for arbitrary freeform surfaces. These results confirm the practicality of our framework in achieving programmable, complex three-dimensional shaping.