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Imitation of a Pre-Designed Irregular 3D Yarn in Given Fabric Structures.
Zheng, Tianyong; Yue, Wenli; Wang, Xiaojiao.
Afiliação
  • Zheng T; School of Textile Science and Engineering, Tiangong University, Tianjin 300387, China.
  • Yue W; School of Textile Science and Engineering, Tiangong University, Tianjin 300387, China.
  • Wang X; School of Textile Science and Engineering, Tiangong University, Tianjin 300387, China.
Polymers (Basel) ; 14(19)2022 Sep 23.
Article em En | MEDLINE | ID: mdl-36235938
ABSTRACT
The 3D CAD software has obvious advantages in appearance imitating and geometric structure modeling for fabrics. In contemporary 3D CAD fabric systems, only uniform yarns are involved in studies on fabric geometric structures, due to technological limitations, whereas objectives such as irregular/uneven 3D yarns have not been considered much. As the fabric structure or the central curve of the yarn changes, it is difficult to reflect the changed positions of the effect spots of the pre-designed uneven 3D yarns accordingly. In this paper, a key-point-mapping algorithm between the source yarn and the target curve is proposed to reflect the position change in effect spots when the fabric structure changes. By using the shape-preserving quasi-uniform cubic B-spline curve, a simple 3D irregular source yarn is designed using key points and setting their corresponding base cross-sections. The mapping is based on the principle that the lengths of the curve between the key points and the contours of the corresponding base cross-sections of the source yarn remain unchanged. Finally, the control grid of the new 3D yarn in the fabric structure is automatically generated. According to the examples and error analysis, the mapping technique can be applied to arbitrary given fabric structures, and the effect spots of the irregular 3D yarn are reasonably distributed as expected.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2022 Tipo de documento: Article