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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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Wang, Yi
University of Birmingham
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (27/27 displayed)
- 2024Virtual data-driven optimisation for zero defect composites manufacturecitations
- 2024CNC-Machined and 3D-Printed Metal G-band Diplexers for Earth Observation Applicationscitations
- 2023A comprehensive modelling framework for defect prediction in automated fibre placement of composites
- 2023A monolithically printed filtering waveguide aperture antennacitations
- 2023Lightweight, High-Q and High Temperature Stability Microwave Cavity Resonators Using Carbon-Fiber Reinforced Silicon-Carbide Ceramic Compositecitations
- 2023Modelling the Effect of Process Conditions on Steering-Induced Defects in Automated Fibre Placement (AFP)citations
- 2023Compact Self-Supportive Filters Suitable for Additive Manufacturingcitations
- 2023Compact Monolithic 3D-Printed Wideband Filters Using Pole-Generating Resonant Irisescitations
- 2023Evaluation of 3D printed monolithic G-band waveguide componentscitations
- 2022A MODELLING FRAMEWORK FOR THE EVOLUTION OF PREPREG TACK UNDER PROCESSING CONDITIONS
- 2022A 3D printed 300 GHz waveguide cavity filter by micro laser sinteringcitations
- 2022D-band waveguide diplexer fabricated using micro laser sinteringcitations
- 2022A Narrowband 3-D Printed Invar Spherical Dual-Mode Filter With High Thermal Stability for OMUXscitations
- 2022Understanding tack behaviour during prepreg-based composites’ processingcitations
- 2022Compact monolithic SLM 3D-printed filters using pole-generating resonant irisescitations
- 2022Thermal stability analysis of 3D printed resonators using novel materialscitations
- 2021Characterization of Biofilm Formation by Mycobacterium chimaera on Medical Device Materialscitations
- 2021125 GHz frequency doubler using a waveguide cavity produced by stereolithographycitations
- 20213D printed re-entrant cavity resonator for complex permittivity measurement of crude oilscitations
- 2021Two‐GHz hybrid coaxial bandpass filter fabricated by stereolithography 3‐D printing
- 20213D printed coaxial microwave resonator sensor for dielectric measurements of liquidcitations
- 2021Investigation of a 3D-printed narrowband filter with non-resonating nodescitations
- 2021Hypo-viscoelastic modelling of in-plane shear in UD thermoset prepregscitations
- 2020180 GHz Waveguide Bandpass Filter Fabricated by 3D Printing Technologycitations
- 2020Experimental characterisation of the in-plane shear behaviour of UD thermoset prepregs under processing conditionscitations
- 2019Modelling of the in-plane shear behavior of uncured thermoset prepreg
- 2018Experimental Characterisation of In-plane Shear Behaviour of Uncured Thermoset Prepregs
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document
A MODELLING FRAMEWORK FOR THE EVOLUTION OF PREPREG TACK UNDER PROCESSING CONDITIONS
Abstract
Tack, which is an expression used to characterise prepreg’s stickiness, is one of the key material parameters controlling product quality in automated composites manufacturing. More specifically in the automated fibre placement (AFP) process, the tack level of prepreg directly affects the generation of defects, i.e. a higher tack value can provide a larger resistant force to out-of-plane deformation and tape buckling. Hence, the number of defects, such as wrinkles, could be mitigated if prepreg’s tack performance could be adjusted. Therefore, a better understanding of tack is fundamental to the digitalisation of the AFP process which would lead to the production of parts of better quality and higher production rates.<br/>However, despite its significance, there are no standard characterisation methods and the modelling frameworks for tack are few and far between. There is even a disagreement within the community on what physical quantity needs to be measured. This is, in part, due to the complexity of the phenomenon as highlighted in the literature (i.e., prepreg tack depends on a number of variables such as temperature, pressure, deformation rate and the measured quantities, namely peak traction and separation energy, are associated with large variability levels).<br/>In the present contribution, a comprehensive prepreg tack modelling framework (inspired by Gutowski and Forghani) is proposed (as shown in Figure 1). A modified probe tack test is developed to perform the experimental characterisation of prepreg tack at different test conditions consistent with the AFP process. The obtained database forms the basis of the proposed modelling framework. The results demonstrate the model’s ability to capture the non-monotonic evolution of tack with process conditions. This provides one of the building blocks for the development of an AFP simulation platform.