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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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Wittig, Jan
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Publications (4/4 displayed)
- 2024Structural integrity of aging steel bridges by 3D laser scanning and convolutional neural networkscitations
- 2024Vibration-based ice monitoring of composite blades using artificial neural networks under different icing conditions
- 2024Failure mode and load prediction of steel bridge girders through 3D laser scanning and machine learning methodscitations
- 2021On the Temperature Dependent Mechanical Response of Dynamically-loaded Shear-dominated Adhesive Structures
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article
On the Temperature Dependent Mechanical Response of Dynamically-loaded Shear-dominated Adhesive Structures
Abstract
<jats:p>A mode II mechanical characterisation of the adhesive joints is performed testing shear lap joint specimens in a Split Hopkinson Tensile Bar (SHTB), equipped with a temperature chamber. The experimentallyobtained traction-separation curves were used to develop a Cohesive Zone Model (CZM) capable of representing the strain-rate and temperaturedependent mechanical response of the adhesive joints. To validate the model, End Notch Flexure (ENF) multi-material specimens made from titanium and carbon fibre reinforced polymer composite laminates were tested at different temperatures using a Split Hopkinson Pressure Bar setup with an in-house made temperature chamber. The finite element (FE) simulations of such tests employing the developed CZM showed the model’s ability to accurately predict the adhesive joints’ failure as well as to understand the failure sequence of multi-material adhesive joint combinations.</jats:p>