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Composite materials used in aerospace applications are made of carbon fibre reinforcements impregnated with polymeric resin. These materials can be manufactured by Resin Transfer Molding (RTM) in which resin is injected and flows into a fibrous preform.
Composite materials reinforced with 3D fibrous architectures are often well-suited for applications involving severe thermo-mechanical loads. To improve their performance, the 3D composite materials are further functionalized by two means: (i) adding particles to the resin and (ii) generating a particles’ content gradient in the fibrous preform. Therefore, the challenge consists in controlling this process, which involves a multiphase flow of particle-filled resin through a three-dimensional fibrous media (Figure 1).
In order to control the particle content during an injection, one must develop a model that couples flow in porous media, particle filtration, and the evolution of material properties (e.g., viscosity and permeability) induced by the filtration phenomenon [1], [2], [3], [4]. A 1D coupled flow-filtration model is assessed and validated using material data generated from characterization and experimental protocols.
Previous research was limited to 1D flow and thin fibrous media [2], [4], [5].This study developed experimental protocols to parametrize and validate the coupled flow and filtration model at Darcy scale. A new methodology based on capacitive sensors was developed to monitor particle content during a particle-filled flow in 3D fibrous media. Capacitive sensors measure changes in impedance related to a dielectric medium between two electrodes in a transient, in-line, non-invasive and non-destructive way. This method is already used to measure resin curing, flow front evolution or saturation during a composite manufacturing processes like RTM injection [6], [7]. It is adapted to the materials of this study through modelling and calibration (Figure 2) to correlate the sensor signal with the particle content within the fibrous preform.
The perspective is to extend and assess the 2D model to predict the gradient of particle content in the final 3D particle-filled composite.
| References | [1] S. P. Fernberg, E. J. Sandlund, et T. S. Lundstrom, « Mechanisms Controlling Particle Distribution in Infusion Molded Composites », Journal of Reinforced Plastics and Composites, vol. 25, no 1, p. 59‑70, 2006, doi: 10.1177/0731684406055455. [2] N. A. A. Siddig, « Experimental and numerical modeling of the impregnation of fibrous media by suspensions in LCM processes », PhD thesis, Université Le Havre Normandie, 2021. [3] H. A. Barnes, J. F. Hutton, et K. Walters, An Introduction to Rheology. Elsevier, 1989. [4] D. Lefèvre, « Étude expérimentale, modélisation et simulation de la filtration lors de l’écoulement d’une résine chargée de particules à travers un renfort fibreux dans les technologies LCM », PhD thesis, Ecole des Mines de Douai, 2007. [5] M. Chohra, S. G. Advani, A. Gokce, et S. Yarlagadda, « Modeling of filtration through multiple layers of dual scale fibrous porous media », Polymer Composites, vol. 27, no 5, p. 570‑581, 2006, doi: 10.1002/pc.20228. [6] G. Gambarini, G. Valdés-Alonzo, C. Binetruy, S. Comas-Cardona, E. Syerko, et M. Waris, « Directional saturation of a strongly bimodal pore size distribution carbon interlock fabric: Measurement and multiphase flow modeling », Composites Part B: Engineering, vol. 281, p. 111532, juill. 2024, doi: 10.1016/j.compositesb.2024.111532. [7] A. A. Skordos, P. I. Karkanas, et I. K. Partridge, « A dielectric sensor for measuring flow in resin transfer moulding », Measurement Science and Technology, vol. 11, no 1, p. 25, 2000. |
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| Country | France |
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