Recommended Citation
Wei Q, Zhang D. A textile architecture-based discrete modeling approach to simulating fabric draping processes. Journal of Industrial Textiles. 2023;53. doi:10.1177/15280837231159678
DOI
https://doi.org/10.1177/15280837231159678
Date of this Version
5-9-2023
Abstract
Fabric draping, which is referred to as the process of forming of textile reinforcements over a 3D mold, is a critical stage in composites manufacturing since it determines the fiber orientation that affects subsequent infusion and curing processes and the resulting structural performance. The goal of this study is to predict the fabric deformation during the draping process and develop in-depth understanding of fabric deformation through an architecture-based discrete Finite Element Analysis (FEA). A new, efficient discrete fabric modeling approach is proposed by representing textile architecture using virtual fiber tows modeled as Timoshenko beams and connected by the springs and dashpots at the intersections of the interlaced tows. Both picture frame and cantilever beam bending tests were carried out to characterize input model parameters. The predictive capability of the proposed modeling approach is demonstrated by predicting the deformation and shear angles of a fabric subject to hemisphere draping. Key deformation modes, including bending and shearing, are successfully captured using the proposed model. The development of the virtual fiber tow model provides an efficient method to illustrate individual tow deformation during draping while achieving computational efficiency in large-scale fabric draping simulations. Discrete fabric architecture and the inter-tow interactions are considered in the proposed model, promoting a deep understanding of fiber tow deformation modes and their contribution to the overall fabric deformation responses.
Comments
This is the published version of the Wei Q, Zhang D. A textile architecture-based discrete modeling approach to simulating fabric draping processes. Journal of Industrial Textiles. 2023;53. doi:10.1177/15280837231159678