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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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Park, Chung Hae
IMT Nord Europe
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (18/18 displayed)
- 2024Fusion Bonding/Welding of Polymer Composites
- 2023Autoencoder-accelerated computational homogenization of unsteady flows in porous media
- 2023Fusion Bonding/Welding of Polymer Composites
- 2023In-situ monitoring of consolidation process for high-performance thermoplastic composites by Fibre Bragg Grating
- 2023Fiber Reinforced Thermoplastic Composites: Processing/Structure/Performance Inter-relationships
- 2023In-situ monitoring of consolidation process for high-performance thermoplastic composites by Fibre Bragg Grating ; Suivi in-situ du processus de consolidation de composite thermoplastique hautes performances par fibre à réseau de Bragg
- 2022Reactive processing of acrylic-based thermoplastic composites: A mini-reviewcitations
- 2022Investigation of Fatigue Behavior of Three Dimensional Interlock Composites by Time-Lapse Micro-Computed Tomography
- 2022Influence of prepreg parameters on the interlaminar consolidation of fiber reinforced thermoplastic laminates manufactured by vacuum-bag-only process ; Influence des paramètres matériaux sur la consolidation interlaminaire de stratifiés thermoplastiques consolidés par VBOcitations
- 2020In-situ Monitoring of the Out-Of-Autoclave Consolidation of Carbon/Poly-Ether-Ketone-Ketone Prepreg Laminatecitations
- 2020In-situ Monitoring of the Out-Of-Autoclave Consolidation of Carbon/Poly-Ether-Ketone-Ketone Prepreg Laminate ; Suivi in-situ de la consolidation hors-autoclave de stratifiés PEKK/fibres de carbonecitations
- 2019Analysis of impregnation mechanism of weft-knitted commingled yarn composites by staged consolidation and laboratory X-ray computed tomographycitations
- 2019A FFT solver for variational phase-field modeling of brittle fracturecitations
- 2018Characterization and modeling of composite vacuum infusion process : Influence of fabric type, resin viscosity and strain ratecitations
- 2011Intra/inter-ply shear behaviors of continuous fiber reinforced thermoplastic composites in thermoforming processescitations
- 2009Integrated optimization for weight, Performance and cost of composite structurescitations
- 2008IDENTIFICATION OF PREFORM COMPRESSIBILITY BY INVERSE METHOD
- 2008Hydromechanical loading and compressibility of fibrous reinforcements
Places of action
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conferencepaper
IDENTIFICATION OF PREFORM COMPRESSIBILITY BY INVERSE METHOD
Abstract
The identification of the transverse properties of fabrics is becoming an important topic, as the transverse flow is significant in advanced liquid composite molding processes such as resin film infusion, vacuum assisted resin transfer molding process and compression resin transfer molding process. However, it is not easy to characterize the transverse permeability and the compressibility of preform, since the fluid flow and the mechanical response of fabrics simultaneously occur in the transverse direction. Due to the strong hydro-mechanical coupling, hence, it has been a common approach to identify the transverse properties either under the simplified assumption (uniform resin pressure in the transverse direction) or under the ideal case where the closed form solution is known. In the previous works, we developed a numerical code to simulate the resin film infusion process and an experimental device to for the measurement of transverse compressibility and permeability considering different compression conditions; either imposed force or imposed speed of compression. In this work, we characterize the material behaviors in the transverse direction by incorporating the material model into the full numerical simulation of an actual filling process. To identify the model coefficients, inverse method is applied with experimental measurements.