Physics-based modeling of the effective gas transport properties of single jersey knitted fabrics based on images

Abstract

In many processes and applications, the performance of textiles relies heavily on fluid transport; for example, the in-plane distribution of water and the through-plane permeation of water vapor and air. Prediction of knitted fabrics’ effective transport characteristics can enhance development workflows and bring them to new applications. Effective transport parameters that are particularly important are the permeability and diffusive mass transfer. Usually, experiments are used to determine these parameters. It is desirable to conduct a thorough investigation into how yarn structure and knitting gauge influence these properties to tailor knitted fabrics for a particular application. Our contribution in this context describes a consistent workflow to forecast the effective mass transfer characteristics of single jersey fabrics. Single jersey fabrics have been chosen for they are the simplest patterning, and are widely used in body-near worn garments. The proposed approach involves visualizing fabric samples with a light microscope, and subsequently determining relevant geometric parameters through automated image processing algorithms. With these parameters in hand, a representative elementary volume of the fabric is constructed. The yarn is modeled as an effective medium to reduce calculation time. The representative elementary volume is then used for numerical predictions of air permeability and the diffusive water vapor transport. The predicted through-plane gas transport properties are compared with experimental data to validate the approach. Six different single jersey polyester fabrics were analyzed, with different yarn structures and machine gauges. The comparison shows a good agreement between simulated and measured transport properties.