Parameterized shape adaptive materials for sportswear

Abstract

PurposeConventional sportswear design does not take into account body size changes that many individuals experience (e.g. through pregnancy, puberty, menstruation, etc.). This paper aims to detail both the construction of a novel wearable shape-adaptive composite and a new meso-scale material design method, which enables the optimal creation of these structures.Design/methodology/approachThis work reports the development of a predictive computational model and a corresponding design tool, including results of a tensile testing protocol to validate their outputs. A mathematical model was developed to explore the geometric parameter space of a bi-stable composite system, which then feeds into an optimization design tool.FindingsThe authors found that it is possible to fabricate shape-adaptive composites via 3D printing bi-stable structures, and adhering them to a base textile. Experimental mechanical tensile testing showed good agreement with the predictive model in mid-range unit cell amplitude designs. To illustrate how the optimization design tool works this paper details two design examples, one for expected shape change during pregnancy and one for targeted compression for high performance swimwear. The optimized design parameters are shown to replicate the target parameters, however there is potential for further improvement with a lower stiffness base textile.Originality/valueAlthough there is a wealth of research on multi-stable mechanisms, there is a dearth of studies that apply these structures in the wearable composite space. Additionally, there is a need for design methods which leverage the structurally-programmable capabilities of multi-stable structures to create optimized, high-performance functional composites.