| People | Locations | Statistics |
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| Naji, M. |
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| Motta, Antonella |
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| Aletan, Dirar |
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| Mohamed, Tarek |
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| Ertürk, Emre |
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| Taccardi, Nicola |
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| Kononenko, Denys |
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| Petrov, R. H. | Madrid |
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| Alshaaer, Mazen | Brussels |
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| Bih, L. |
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| Casati, R. |
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| Muller, Hermance |
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| Kočí, Jan | Prague |
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| Šuljagić, Marija |
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| Kalteremidou, Kalliopi-Artemi | Brussels |
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| Azam, Siraj |
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| Ospanova, Alyiya |
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| Blanpain, Bart |
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| Ali, M. A. |
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| Popa, V. |
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| Rančić, M. |
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| Ollier, Nadège |
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| Azevedo, Nuno Monteiro |
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| Landes, Michael |
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| Rignanese, Gian-Marco |
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Liu, Yang
Imperial College London
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (25/25 displayed)
- 2024Lead‐free halide perovskite materials and optoelectronic devices: progress and prospectivecitations
- 2024Characterization of AlGaAs/GeSn heterojunction band alignment via X-ray photoelectron spectroscopy
- 2023Exploring the hydride-slip interaction in zirconium alloyscitations
- 2023Demonstration of a monocrystalline GaAs-$β$-Ga$_2$O$_3$ p-n heterojunction
- 2023Lead-Free Halide Perovskite Materials and Optoelectronic Devices: Progress and Prospectivecitations
- 2023Open-source environmental data as an alternative to snail surveys to assess schistosomiasis risk in areas approaching elimination
- 2023Lead‐Free Halide Perovskite Materials and Optoelectronic Devices: Progress and Prospectivecitations
- 2022Photon Drag Currents and Terahertz Generation in α-Sn/Ge Quantum Wellscitations
- 2022Simulation of crystal plasticity in irradiated metals: a case study on Zircaloy-4citations
- 2021Characterisation of microstructural creep, strain rate and temperature sensitivity and computational crystal plasticity in Zircaloy-4citations
- 2019Quantifying the mechanical properties of polymeric tubing and scaffold using atomic force microscopy and nanoindentationcitations
- 2019Texture and phase variation of ALD PbTiO3 films crystallized by rapid thermal annealcitations
- 2019Screening Approach for the Discovery of New Hybrid Perovskites with Efficient Photoemissioncitations
- 2019Mechanical and chemical characterisation of bioresorbable polymeric stent over two-year in vitro degradationcitations
- 2018Cellular response to cyclic compression of tissue engineered intervertebral disk constructs composed of electrospun polycaprolactonecitations
- 2018Enhanced Water Barrier Properties of Surfactant-Free Polymer Films Obtained by MacroRAFT-Mediated Emulsion Polymerizationcitations
- 2017Prediction of linear and non-linear behavior of 3D woven composite using mesoscopic voxel models reconstructed from X-ray micro-tomographycitations
- 2017174 Comparison of the mechanical performance of polymeric and metallic scaffolds – testing and modelling
- 2017Numerical Modelling of Effects of Biphasic Layers of Corrosion Products to the Degradation of Magnesium Metal In Vitrocitations
- 2017Bandgap Control via Structural and Chemical Tuning of Transition Metal Perovskite Chalcogenidescitations
- 2017Compact Brillouin devices through hybrid integration on siliconcitations
- 2017A numerical approach to reconstruct mesoscopic yarn section of textile composites based upon X-ray micro-tomography
- 2016Effects of Annealing on GaAs/GaAsSbN/GaAs Core-Multi-shell Nanowires
- 2015Film thickness of vertical upward co-current adiabatic flow in pipescitations
- 2014Bifunctional organic/inorganic nanocomposites for energy harvesting, actuation and magnetic sensing applicationscitations
Places of action
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conferencepaper
A numerical approach to reconstruct mesoscopic yarn section of textile composites based upon X-ray micro-tomography
Abstract
Mesoscopic model has been proven to impose crucial influence on predicting the damage and failure behavior of textile composites. In classical mesoscopic models, the section of yarn is usually simplified as circular, lenticular, ellipsoidal or more sophisticated shapes defined by power ellipse. A numeric tool is proposed in this work to reconstruct the yarn section based upon realistic geometry via X-ray micro-tomography techniques. The sectional shape of yarn is fit as polygon by connecting the selected key boundary points with Graham Scan convex hull algorithm. Improved Lubachevsky-Stillinger algorithm is then employed to drive the motion and growth of the fiber sections, which are considered as circles here, within the yarn boundary until the pre-assigned fiber volume fraction is reached. The proposed method shows excellent performance to model the localized fiber distribution. A representative size of the numeric model is determined following by a strength-geometry sensitivity research on different section models. Further investigation is completed to study the influence of fiber-matrix interface on the damage and failure behavior of the yarn. This approach can be used for arbitrary textile composite where the fiber can be taken as circle at microscale, as long as the real geometry of yarn is provided no matter by micro-tomography or other experimental observation techniques.