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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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Caglar, Baris
Delft University of Technology
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (32/32 displayed)
- 2024Self-catalysed frontal polymerisation enables fast and low-energy processing of fibre reinforced polymer compositescitations
- 2024Friction Dynamics In Mechanical Bar Spreading For Unidirectional Thin-Ply Carbon Fiber
- 2024Microstructural Analysis Of Unidirectional Composites
- 2024A methodology for microstructural evaluation of unsaturated flow phenomena by in‐situ UV‐flow freezing
- 2024An Image-Based Ai Model For Micro-Flow Field Prediction During Resin Transfer Molding
- 2024Saturated transverse permeability of unidirectional rovings for pultrusion: The effect of microstructural evolution through compactioncitations
- 2023ECCM Research Topic on advanced manufacturing of composites
- 2023Thermal management in radical induced cationic frontal polymerisation for optimised processing of fibre reinforced polymerscitations
- 2023Effect of wettability and textile architecture on fluid displacement and pore formation during infiltration of carbon fibrous preformscitations
- 2023Measurement and modelling of dynamic fluid saturation in carbon reinforcementscitations
- 2022A new virtual fiber modeling approach to predict the kinematic and mechanical behavior of through-thickness fabric compression
- 2022A new virtual fiber modeling approach to predict the kinematic and mechanical behavior of through-thickness fabric compression
- 2022A new virtual fiber modeling approach to predict the kinematic and mechanical behavior of through-thickness fabric compression
- 2022Deep learning based prediction of fibrous microstructure permeability
- 2022Processing of Fibre Reinforced Polymers by Controlled Radical Induced Cationic Frontal Polymerisation
- 2022Development and characterization of hybrid thin-ply composite materials
- 2022On the durability of surgical masks after simulated handling and wearcitations
- 2022A life cycle analysis of novel lightweight composite processescitations
- 2022Radical Induced Cationic Frontal Polymerization for Rapid Out-of-Autoclave Processing of Carbon Fiber Reinforced Polymers
- 2022Dual-scale visualization of resin flow for liquid composite molding processes
- 2022Community Masks-from an Emergency Solution to an Innovation Booster for the Textile Industrycitations
- 2022Deep learning accelerated prediction of the permeability of fibrous microstructurescitations
- 2022Capillary Effects in Fiber Reinforced Polymer Composite Processing: A Reviewcitations
- 2021In-operando dynamic visualization of flow through porous preforms based on X-ray phase contrast imagingcitations
- 2021Functionalized Fiber Reinforced Composites via Thermally Drawn Multifunctional Fiber Sensorscitations
- 2021Kinematic and mechanical response of dry woven fabrics in through-thickness compression: Virtual fiber modeling with mesh overlay technique and experimental validationcitations
- 2021In-series sample methodology for permeability characterization demonstrated on carbon nanotube-grafted alumina textilescitations
- 2021Resin Transfer molding of High-Fluidity Polyamide-6 with modified Glass-Fabric preformscitations
- 2019Assessment of Capillary Phenomena in Liquid Composite Moldingcitations
- 20193D Spacers Enhance Flow Kinetics in Resin Transfer Molding with Woven Fabricscitations
- 2018In-plane permeability distribution mapping of isotropic mats using flow front detectioncitations
- 2017Permeability of textile fabrics with spherical inclusionscitations
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document
Microstructural Analysis Of Unidirectional Composites
Abstract
This study presents the first steps of a benchmarking exercise on image processing of composite materials. Employing three distinct imaging protocols and five different image processing algorithms, the research explains the variability in capturing microstructural features of common micrograph dataset. Results highlight the sensitivity of different methods to factors like illumination inhomogeneities and pixel density, influencing the accuracy and consistency of obtained results. By comparing methodologies from different researchers in a blind format, the study identifies strengths and limitations, laying the groundwork for future benchmarking activities. Moving forward, this research sets the stage for standardized protocols and guidelines, aiming to enhance the reproducibility and reliability of microstructural analysis in composite materials. Such efforts are crucial for advancing material design and development, ultimately creating tailored composite materials with enhanced performance and functionality.