A novel modeling method for the mechanical behavior of 3D woven fabrics considering yarn distortion. (10th November 2022)

• Record Type: Journal Article
• Authors: Li, Mengran; Liu, Kai; Ge, Jingran; Xie, Junbo; Liu, Zengfei; Zhang, Binbin; Huang, Jian; Liang, Jun
• Is Part Of: Composites science and technology. Volume 230(2022)Part 1
• Publication Date: 2022-11-10
• Subjects: Fabrics -- Mechanical properties -- Material modeling -- Finite element analysis (FEA) -- Fiber directional orientation; Composite materials -- Periodicals; Composite materials; Fibrous composites; Periodicals; 620.118
• DOI: 10.1016/j.compscitech.2022.109691
• Languages: English
• ISSNs: 0266-3538

Abstract

Abstract: Three-dimensional woven fabrics feature complex meso-architectures, such as yarn torsion and cross-section variation. This paper aims to developing a novel numerical modeling method to simulate the mechanical behaviors of reinforcements considering realistic yarn geometries. The initial as-woven unit cell is first simulated by the digital element analysis. A reconstruction algorithm is then used to generate mesoscale high-fidelity solid geometric models from digital chains. Fiber directional orientation within torsional yarns of the high-fidelity model is described by a digital-chain tracing method and analyzed in detail. Furthermore, based on the high-fidelity model, a hyper-elastic constitutive model is employed for the numerical analysis of the mechanical properties of reinforcements. The finite element analysis (FEA) of transverse compression, tensile deformation and in-plane shearing deformation combined with in-situ Micro-CT experiments are carried out to verify the method. The proposed method agrees well with experimental tests. Defining fiber orientations of torsional yarns using the digital-chain tracing method leads to more accurate simulation results. The developed numerical method can be extended for the composites design and structure optimization due to its high-fidelity simulation capabilities. Graphical abstract: Image 1