| 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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Carvalho, Marta
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (6/6 displayed)
- 2024Evaluation of self-sensing material behaviourcitations
- 2023Self-sensing metallic material based on piezoelectric particlescitations
- 2023Granting Sensorial Properties to Metal Parts through Friction Stir Processingcitations
- 2023Self-sensing metallic material based on PZT particles produced by friction stir processing envisaging structural health monitoring applicationscitations
- 2022Numerical Analysis on the Bond Performance of Different Anchored Joints under Monotonic and Cyclic Pull-push Loading
- 2013Corrosion Behavior of Friction Stir Welded automotive aluminium alloys
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article
Granting Sensorial Properties to Metal Parts through Friction Stir Processing
Abstract
Structural Health Monitoring systems assess the part's current condition. This can be performed with a monitoring system comprising sensors, on the surface or embedded, in the monitored parts. However, surface sensors are subject to damage, and embedding the sensors may result in a weakened part. An innovative Self-Sensing Material and its manufacturing process were developed and are presented herein. As proof of concept, Barium Titanate particles were introduced and dispersed into an AA5083-H111 part by Friction Stir Processing (FSP). The particles’ distribution and concentration was evaluated by a set of characterization techniques, demonstrating that greater concentrations, grant enhanced sensitivity to the material. The use of FSP and the embedded particles improved the part’s mechanical behaviour in the processed zone. The sensorial properties were assessed and the response to a set of dynamic loads was measured, being coherent with the solicitations provided. The developed self-sensing material revealed an electrical sensitivity of12.0 × 10-4 uV/MPa.