| People | Locations | Statistics |
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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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Belnoue, Jonathan P.-H.
University of Bristol
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (35/35 displayed)
- 2024An accurate forming model for capturing the nonlinear material behaviour of multilayered binder-stabilised fabrics and predicting fibre wrinklingcitations
- 2024That’s how the preform crumples: Wrinkle creation during forming of thick binder-stabilised stacks of non-crimp fabricscitations
- 2024Virtual data-driven optimisation for zero defect composites manufacturecitations
- 2024Parametric study on the effect of material properties, tool geometry, and tolerances on preform quality in wind turbine blade manufacturingcitations
- 2024Process models: A cornerstone to composites 4.0citations
- 2024But how can I optimise my high-dimensional problem with only very little data? – A composite manufacturing applicationcitations
- 2023A comprehensive modelling framework for defect prediction in automated fibre placement of composites
- 2023Thickness Control of Autoclave-Molded Composite Laminatescitations
- 2022Intelligent Composites Forming - Simulations For Faster, Higher Quality Manufacture
- 2022A MODELLING FRAMEWORK FOR THE EVOLUTION OF PREPREG TACK UNDER PROCESSING CONDITIONS
- 2022Understanding tack behaviour during prepreg-based composites’ processingcitations
- 2021On the physical relevance of power law-based equations to describe the compaction behaviour of resin infused fibrous materialscitations
- 2021Consolidation-driven wrinkling in carbon/epoxy woven fabric prepregscitations
- 2021Compaction behaviour of continuous fibre-reinforced thermoplastic composites under rapid processing conditionscitations
- 2021Modelling compaction behavior of toughened prepreg during automated fibre placement
- 2021Lab-based in-situ micro-CT observation of gaps in prepreg laminates during consolidation and curecitations
- 2021Hypo-viscoelastic modelling of in-plane shear in UD thermoset prepregscitations
- 2020Predicting consolidation-induced wrinkles and their effects on composites structural performancecitations
- 2020Experimental characterisation of the in-plane shear behaviour of UD thermoset prepregs under processing conditionscitations
- 2020A rapid multi-scale design tool for the prediction of wrinkle defect formation in composite componentscitations
- 2019Modelling of the in-plane shear behavior of uncured thermoset prepreg
- 2019A numerical study of variability in the manufacturing process of thick composite partscitations
- 2019Machine-driven experimentation for solving challenging consolidation problems
- 2019Mitigating forming defects by local modification of dry preformscitations
- 2018Modelling process induced deformations in 0/90 non-crimp fabrics at the meso-scalecitations
- 2018Experimental Characterisation of In-plane Shear Behaviour of Uncured Thermoset Prepregs
- 2018Multi-scale modelling of non-uniform consolidation of uncured toughened unidirectional prepregscitations
- 2016Predicting wrinkle formation in components manufactured from toughened UD prepreg
- 2016Understanding and prediction of fibre waviness defect generation
- 2016Cohesive/Adhesive failure interaction in ductile adhesive joints Part Icitations
- 2016An experimental investigation of the consolidation behaviour of uncured prepregs under processing conditionscitations
- 2015The compaction behaviour of un-cured prepregs
- 2012A numerical model for thick composite-metallic adhesive joints
- 2011Adaptive calibration of a nonlocal coupled damage plasticity model for aluminium alloy AA6082 T0
- 2007Modeling crack initiation and propagation in nickel base superalloys
Places of action
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conferencepaper
Machine-driven experimentation for solving challenging consolidation problems
Abstract
The paper presents a new modelling concept for characterisation of the consolidation in composite precursors. Consolidation is a central process in composites manufacturing, it affects defects formation, dimensional tolerances and the final quality of the composite part. Due to the nonlinear and coupled nature of the process the characterisation of consolidation is a nontrivial task. The proposed concept of the consolidation sensor is not limited by a subjective judgement about material behavior from the experimental testing. It is capable of designing loading programmes and distinguishing between dominant deformation mechanisms rather than imposing rigid framework of arbitrarily selected consolidation models. The sensor is self-developing, adaptable and capable of capturing the main characteristics of the consolidation process by interrogating the material in the way it independently decides. The proposed system is set to recognise the flow/deformation modes by their characteristic signatures and make an assumption about the current flow mode during the test. The consolidation sensor was validated against a number of different phenomenological models.