Assessing Crimp of Fibres in Random Networks with 3D Imaging

Abstract

The analysis of fibrous structures using micro-computer tomography (µCT) is becoming more important as it provides an opportunity to characterise the mechanical properties and performance of materials. This study is the first attempt to provide computations of fibre crimp for various random fibrous networks (RFNs) based on µCT data. A parametric algorithm was developed to compute fibre crimp in fibres in a virtual domain. It was successfully tested for six different X-ray µCT models of nonwoven fabrics. Computations showed that nonwoven fabrics with crimped fibres exhibited higher crimp levels than those with non-crimped fibres, as expected. However, with the increased fabric density of the non-crimped nonwovens, fibres tended to be more crimped. Additionally, the projected fibre crimp was computed for all three major 2D planes, and the obtained results were statistically analysed. Initially, the algorithm was tested for a small-size, nonwoven model containing only four fibres. The fraction of nearly straight fibres was computed for both crimped and non-crimped fabrics. The mean value of the fibre crimp demonstrated that fibre segments between intersections were almost straight. However, it was observed that there were no perfectly straight fibres in the analysed RFNs. This study is applicable to approach employing a finite-element analysis (FEA) and computational fluid dynamics (CFD) to model/analyse RFNs.

Algorithm to determine local basis weight of random fibrous networks with X-ray microtomography and SEM images

“…After the pruning operation, short branches were removed. 3,4 In Figure 6, blue lines represent fibers, with the orange color showing the spurious fiber segments. After the pruning operation, short branches were removed.…”

“…In contrast, a high-resolution X-ray micro-computed tomography (µCT) system was used to detect fibers precisely and accurately in three-dimensional (3D) space at micron level. 3,4 In addition, image-processing algorithms were used to characterize many different aspects of random fibrous networks (RFNs). For instance, fused images obtained with digital optical microscopy were used to measure the fiber diameter, porosity and orientation distribution function of nonwovens.…”

Methodological Aspects and Mesh Convergence in Numerical Analysis of Athermal Fiber Network Material Deformation

“…The primary objective of this article is to provide guidelines for the modeling and simulation of network materials using discrete models. To this end, we investigate the elastic response of two idealized network architectures: cellular [26,34,35] and fibrous networks [21,25] with initially straight and crimped fibers [19,[36][37][38] for varying levels of mesh refinements. We additionally consider the effect of the discretization on the viscoelastic relaxation of network models [39][40][41], following a recent study on this topic [42].…”