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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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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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Ospanova, Alyiya |
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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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Rashvand, Kaveh
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- 2024Fabric compaction and fibre volume fraction evaluation for vacuum-assisted resin infusion modelling
- 2024In-situ and adhesive repair of continuous fiber composites using 3D printingcitations
- 2023Parametric and numerical Finite Element simulation of wind turbine blades subjected to thermal residual stresses
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document
Fabric compaction and fibre volume fraction evaluation for vacuum-assisted resin infusion modelling
Abstract
To consistently achieve high-quality and reliable composite laminates, reducing the defects introduced while manufacturing is crucial. One of the methods to help is obtaining an optimal infusion strategy that considers the local compressed state during the vacuum infusion process. To create a unique digital twin for infusion processing planning, both accurate and practical methods must be used to obtain the geometry of the preform. This study has considered blue-light scanning, digital image correlation and laser sensor measurements for non-destructive in-situ fibre volume fraction assessments. The obtained results have also been compared with post-mortem burn-off testing of specimens and subsequently evaluated for filling time calculations with PAM-RTM compared against the actual filling duration.