A novel technique to simulate and characterize yarn mechanical behavior based on a geometrical fiber model extracted from microcomputed tomography imaging

Abstract

Textiles and their production machines are increasingly designed using simulations of the textile production process. These simulations require reliable structural yarn models. In practice, these models are often based on simplifying assumptions concerning the underlying geometry. However, in recent years more realistic geometrical fiber models have been developed, but have not been used to estimate the structural properties of yarns. The current contribution presents a new methodology to obtain a structural yarn model through numerical simulations based on a high-fidelity geometrical yarn model. Starting from microcomputed tomography data of a real-life natural fiber yarn used in air-jet weaving, a geometrical yarn model is constructed by tracing the individual fibers. This geometry is then incorporated in a computational finite-element analysis framework to obtain the yarn tensile and bending behavior through a simulated tensile test and Peirce cantilever test. Finally, the results are validated by comparison with experimental data. It is shown that this new technique succeeds to estimate the tensile and bending behavior. The presented methodology allows one to gain fundamental insight into the internal deformations and stresses in the yarn. Moreover, it is an important first step toward statistical studies on the structural yarn behavior on the microscale level and toward homogenized macro-models originating from a fully digital workflow.