scholarly journals Meso-FE modelling of textile composites and X-ray tomography

2020 ◽  
Vol 55 (36) ◽  
pp. 16969-16989
Author(s):  
N. Naouar ◽  
D. Vasiukov ◽  
C. H. Park ◽  
S. V. Lomov ◽  
P. Boisse
Keyword(s):  
Textile Composites ◽  
Fe Modelling ◽  
X Ray

scholarly journals Durable Antimicrobial Behaviour from Silver-Graphene Coated Medical Textile Composites

Polymers ◽  
2019 ◽  
Vol 11 (12) ◽  
pp. 2000 ◽  
Author(s):  
Nuruzzaman Noor ◽  
Suhas Mutalik ◽  
Muhammad Waseem Younas ◽  
Cheuk Ying Chan ◽  
Suman Thakur ◽  
...  
Keyword(s):  
Soft Matter ◽  
Optical Emission ◽  
Textile Composites ◽  
Reducing Agent ◽  
Metallic Silver ◽  
Silver Nanostructures ◽  
Ion Release ◽  
Electron Microscopic ◽  
Host Matrix ◽  
X Ray

Silver nanoparticle (AgNP) and AgNP/reduced graphene oxide (rGO) nanocomposite impregnated medical grade polyviscose textile pads were formed using a facile, surface-mediated wet chemical solution-dipping process, without further annealing. Surfaces were sequentially treated in situ with a sodium borohydride (NaBH4) reducing agent, prior to formation, deposition, and fixation of Ag nanostructures and/or rGO nanosheets throughout porous non-woven (i.e., randomly interwoven) fibrous scaffolds. There was no need for stabilising agent use. The surface morphology of the treated fabrics and the reaction mechanism were characterised by Fourier transform infrared (FTIR) spectra, ultraviolet-visible (UV–Vis) absorption spectra, X-ray diffraction (XRD), Raman spectroscopy, dynamic light scattering (DLS) energy-dispersive X-ray analysis (EDS), and scanning electron microscopic (SEM). XRD and EDS confirmed the presence of pure-phase metallic silver. Variation of reducing agent concentration allowed control over characteristic plasmon absorption of AgNP while SEM imaging, EDS, and DLS confirmed the presence of and dispersion of Ag particles, with smaller agglomerates existing with concurrent rGO use, which also coincided with enhanced AgNP loading. The composites demonstrated potent antimicrobial activity against the clinically relevant gram-negative Escherichia coli (a key causative bacterial agent of healthcare-associated infections; HAIs). The best antibacterial rate achieved for treated substrates was 100% with only a slight decrease (to 90.1%) after 12 equivalent laundering cycles of standard washing. Investigation of silver ion release behaviours through inductively coupled plasmon optical emission spectroscopy (ICP-OES) and laundering durability tests showed that AgNP adhesion was aided by the presence of the rGO host matrix allowing for robust immobilisation of silver nanostructures with relatively high stability, which offered a rapid, convenient, scalable route to conformal NP–decorated and nanocomposite soft matter coatings.

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

Materials ◽  
2020 ◽  
Vol 13 (4) ◽  
pp. 936 ◽  
Author(s):  
Yuriy Sinchuk ◽  
Pierre Kibleur ◽  
Jan Aelterman ◽  
Matthieu N. Boone ◽  
Wim Van Paepegem
Keyword(s):  
Deep Learning ◽  
Textile Composites ◽  
Fiber Reinforced Polymers ◽  
Woven Composites ◽  
Imaging Data ◽  
Low Contrast ◽  
X Ray ◽  
Computed Tomography Images ◽  
Segmentation Accuracy ◽  
Ct Data

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.

scholarly journals Meso-FE modelling of textile composites: Road map, data flow and algorithms

2007 ◽  
Vol 67 (9) ◽  
pp. 1870-1891 ◽  
Author(s):  
S LOMOV ◽  
D IVANOV ◽  
I VERPOEST ◽  
M ZAKO ◽  
T KURASHIKI ◽  
...  
Keyword(s):  
Data Flow ◽  
Textile Composites ◽  
Fe Modelling ◽  
Road Map ◽  
Map Data

Non-destructive evaluation of stacking sequence in textile composite: different techniques and experimental verification

2014 ◽  
Vol 34 (3) ◽  
pp. 264-274 ◽  
Author(s):  
A. Saboktakin ◽  
T. Vu-Khanh ◽  
Y. Bonnefon
Keyword(s):  
Finite Element ◽  
Finite Element Modeling ◽  
Frequency Response ◽  
Textile Composites ◽  
Textile Composite ◽  
Content Type ◽  
X Ray ◽  
Layer Orientation ◽  
Non Destructive ◽  
Composite Samples

Purpose – The purpose of this paper is to experimentally investigate the capability of four non-destructive testing (NDT) techniques to detect the layer orientation in textile composite laminates. The aerospace industry has been the primary driving force in the use of textile composites. Design/methodology/approach – Woven glass fiber composite samples were inspected using C-scan ultrasonic, vibration analyzer, X-ray micro-tomography and ultraviolet technique. In a complementary study, mechanical testing was carried out to investigate the effect of mid-layer orientation on in-plane tensile strength and their failure modes using microscopic imagining. Findings – During C-scan ultrasonic, the high attenuation and scattering of ultrasonic waves caused by the textile fabric layers limited its application to only detect the first layer of samples. Frequency response tests of composite samples were also conducted to investigate the effect of mid-layer orientation on dynamic responses. The same trend was observed in the finite element modeling results with a clear effect of the fiber orientation defect seen in frequency response function response and higher mode shapes. Moreover, the results of micro computed tomography demonstrate that this technique could definitely detect the orientation of each layer; however, X-ray imaging at small scales introduced some challenges. Images obtained from ultraviolet technique did not reveal mid-layer orientation. Originality/value – In this paper, the application of different NDT techniques along with finite element modeling to inspect two-dimensional textile composites was presented. Hopefully, the research results presented here will lead to much published papers in inspection of textile composites.

Space and Time Distribution of Hard X-Ray Emission in a Loop at the Beginning of a Flare

1994 ◽  
Vol 144 ◽  
pp. 275-277
Author(s):  
M. Karlický ◽  
J. C. Hénoux
Keyword(s):  
Time Distribution ◽  
Electron Bombardment ◽  
Spatial Evolution ◽  
Superthermal Electrons ◽  
Flare Loop ◽  
X Ray ◽  
Superthermal Electron ◽  
Flare Loops ◽  
Chromospheric Evaporation ◽  
Temporal And Spatial

AbstractUsing a new ID hybrid model of the electron bombardment in flare loops, we study not only the evolution of densities, plasma velocities and temperatures in the loop, but also the temporal and spatial evolution of hard X-ray emission. In the present paper a continuous bombardment by electrons isotropically accelerated at the top of flare loop with a power-law injection distribution function is considered. The computations include the effects of the return-current that reduces significantly the depth of the chromospheric layer which is evaporated. The present modelling is made with superthermal electron parameters corresponding to the classical resistivity regime for an input energy flux of superthermal electrons of 109erg cm−2s−1. It was found that due to the electron bombardment the two chromospheric evaporation waves are generated at both feet of the loop and they propagate up to the top, where they collide and cause temporary density and hard X-ray enhancements.

Some Problems in Understanding the Solar Corona

1994 ◽  
Vol 144 ◽  
pp. 1-9
Author(s):  
A. H. Gabriel
Keyword(s):  
Solar Corona ◽  
Solar Atmosphere ◽  
Theoretical Modelling ◽  
Total System ◽  
Major Advance ◽  
X Ray ◽  
Proper Perspective ◽  
Space Observations

The development of the physics of the solar atmosphere during the last 50 years has been greatly influenced by the increasing capability of observations made from space. Access to images and spectra of the hotter plasma in the UV, XUV and X-ray regions provided a major advance over the few coronal forbidden lines seen in the visible and enabled the cooler chromospheric and photospheric plasma to be seen in its proper perspective, as part of a total system. In this way space observations have stimulated new and important advances, not only in space but also in ground-based observations and theoretical modelling, so that today we find a well-balanced harmony between the three techniques.

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