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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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Radhakrishnan, Arjun
University of Bristol
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (8/8 displayed)
- 2024Effect of pre-curing on thermoplastic-thermoset interphasescitations
- 2023A Feasibility Study for Additively Manufactured Composite Tooling
- 2023Manufacturing Multi-Matrix Composites
- 2023Additively manufactured cure tools for composites manufacturecitations
- 2023The influence of key processing parameters on thermoset laminate curingcitations
- 2022Tracking consolidation of out-of-autoclave prepreg corners using pressure sensorscitations
- 2022A FEASIBILITY STUDY OF ADDITIVELY MANUFACTURED COMPOSITE TOOLING
- 2019Matrix-graded and fibre-steered composites to tackle stress concentrationscitations
Places of action
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article
The influence of key processing parameters on thermoset laminate curing
Abstract
The many uncertainties in thermoset composite laminate processing can have undesirable consequences. It is impractical to address the uncertainties individually. A methodology is introduced in this study that ranks parameters by an influence metric to give insights into how to reduce variability in cure time most effectively. The presented example considers a range of parameters from the material, geometry, and processing conditions within a thermochemical model of composite laminate curing. Due to the nonlinearities in the process, the influence metric must include representative parameter uncertainty. In the example considered here of a high-performance aerospace grade epoxy system, dwell temperature and diffusion terms in the cure kinetics model were most influential. This was a result of a long dwell period and a post-vitrification final degree of cure. Therefore, the best investment to reduce curing variability is processing equipment with repeatable and uniform temperature.