High fidelity modelling of the compression behaviour of 2D woven fabrics

Thompson, Adam J.; Said, Bassam El; Ivanov, Dmitry; Belnoue, Jonathan P.-H.; Hallett, Stephen R.

doi:10.1016/j.ijsolstr.2017.06.027

Cited by 46 publications

(25 citation statements)

References 27 publications

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“…On the other hand, in [28], it was reported than epoxy composites filled with twill weave CFs showed lower tensile characteristics than composites reinforced with plain and satin weave CFs, both in static and dynamic test modes. Furthermore, twill weave CFs are often used as the model object in theoretical investigations [29,30] and can be a suitable material for the elaboration of new polymer based composites.…”

Section: Introductionmentioning

confidence: 99%

Structure and Properties of Polysulfone Filled with Modified Twill Weave Carbon Fabrics

et al. 2019

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Carbon fabrics are widely used in polymer based composites. Nowadays, most of the advanced high-performance composites are based on thermosetting polymer matrices such as epoxy resin. Thermoplastics have received high attention as polymer matrices due to their low curing duration, high chemical resistance, high recyclability, and mass production capability in comparison with thermosetting polymers. In this paper, we suggest thermoplastic based composite materials reinforced with carbon fibers. Composites based on polysulfone reinforced with carbon fabrics using polymer solvent impregnation were studied. It is well known that despite the excellent mechanical properties, carbon fibers possess poor wettability and adhesion to polymers because of the fiber surface chemical inertness and smoothness. Therefore, to improve the fiber–matrix interfacial interaction, the surface modification of the carbon fibers by thermal oxidation was used. It was shown that the surface modification resulted in a noticeable change in the functional composition of the carbon fibers’ surface and increased the mechanical properties of the polysulfone based composites. Significant increase in composites mechanical properties and thermal stability as a result of carbon fiber surface modification was observed.

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Section: Introductionmentioning

confidence: 99%

Structure and Properties of Polysulfone Filled with Modified Twill Weave Carbon Fabrics

et al. 2019

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“…Such approaches have been validated by comparison to CT data. For example, in the work [7], the resulting geometry is sufficiently close to the reference µ-CT data. However, the difficulty of such methods could be the adjustment of the model parameters needed to get the desired shape.…”

Section: Introductionmentioning

confidence: 56%

Variational and Deep Learning Segmentation of Very-Low-Contrast X-ray Computed Tomography Images of Carbon/Epoxy Woven Composites

et al. 2020

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The purpose of this work is to find an effective image segmentation method for lab-based micro-tomography (µ-CT) data of carbon fiber reinforced polymers (CFRP) with insufficient contrast-to-noise ratio. The segmentation is the first step in creating a realistic geometry (based on µ-CT) for finite element modelling of textile composites on meso-scale. Noise in X-ray imaging data of carbon/polymer composites forms a challenge for this segmentation due to the very low X-ray contrast between fiber and polymer and unclear fiber gradients. To the best of our knowledge, segmentation of µ-CT images of carbon/polymer textile composites with low resolution data (voxel size close to the fiber diameter) remains poorly documented. In this paper, we propose and evaluate different approaches for solving the segmentation problem: variational on the one hand and deep-learning-based on the other. In the author’s view, both strategies present a novel and reliable ground for the segmentation of µ-CT data of CFRP woven composites. The predictions of both approaches were evaluated against a manual segmentation of the volume, constituting our “ground truth”, which provides quantitative data on the segmentation accuracy. The highest segmentation accuracy (about 4.7% in terms of voxel-wise Dice similarity) was achieved using the deep learning approach with U-Net neural network.

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“…Nonetheless, neither of these element shapes is completely acceptable. Generally, the hexahedral elements are numerically more efficient, and they are well adapted to describe the yarn in the fiber direction [88]. However, it is problematic to mesh the transverse section of the yarn in a suitable manner [82].…”

Section: Geometry Extraction and Meshingmentioning

confidence: 99%

A Review of Current Challenges and Case Study toward Optimizing Micro-Computed X-Ray Tomography of Carbon Fabric Composites

et al. 2020

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X-ray computed tomography provides qualitative and quantitative structural and compositional information for a broad range of materials. Yet, its contribution to the field of advanced composites such as carbon fiber reinforced polymers is still limited by factors such as low imaging contrast, due to scarce X-ray attenuation features. This article, through a review of the state of the art, followed by an example case study on Micro-computed tomography (CT) analysis of low X-ray absorptive dry and prepreg carbon woven fabric composites, aims to highlight and address some challenges as well as best practices on performing scans that can capture key features of the material. In the case study, utilizing an Xradia Micro-CT-400, important aspects such as obtaining sufficient contrast, an examination of thin samples, sample size/resolution issues, and image-based modeling are discussed. The outcome of an optimized workflow in Micro-CT of composite fabrics can assist in further research efforts such as the generation of surface or volume meshes for the numerical modeling of underlying deformation mechanisms during their manufacturing processes.

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High fidelity modelling of the compression behaviour of 2D woven fabrics

Cited by 46 publications

References 27 publications

Structure and Properties of Polysulfone Filled with Modified Twill Weave Carbon Fabrics

Structure and Properties of Polysulfone Filled with Modified Twill Weave Carbon Fabrics

Variational and Deep Learning Segmentation of Very-Low-Contrast X-ray Computed Tomography Images of Carbon/Epoxy Woven Composites

A Review of Current Challenges and Case Study toward Optimizing Micro-Computed X-Ray Tomography of Carbon Fabric Composites

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