Experimental and numerical analysis of virtual fabrics shapeability on convex areas of the human body

Virtual prototyping is integral to modern apparel design, yet a gap persists between a virtual material’s input mechanical properties and its ability to conform to complex anatomical shapes. This study develops a novel framework to quantify the shapeability of virtual textiles on convex body areas. A library of thirteen parametrically-defined, body-mimicking forms was created, approximating the chest, stomach, blade and buttocks across standard male ASTM sizes. A regimen of 3468 simulations tested 34 virtual materials, deforming them with varied dart widths. Fabric conformity was measured using the Hausdorff distance. The results yielded a new shapeability index (Sp), which normalises conformity by surface density. Validation through digital and physical experiments confirmed the index’s consistency across body sizes and areas. A predictable relationship was found between Sp and surface density, enabling a new classification of materials into four shapeability groups. This framework provides a practical tool for assessing virtual material performance, streamlining the digital garment workflow.