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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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Mandal, Parthasarathi
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Publications (5/5 displayed)
- 2022Numerical modelling of friction stir welding of pipes:Effect of tool shoulder on mechanical property and metallurgical characterizationcitations
- 2020Emissions of volatile organic compounds from crude oil processing - global emission inventory and environmental releasecitations
- 2020Numerical modelling of microstructure in friction stir welding of aluminium alloyscitations
- 2012Drilling of woven glass fiber-reinforced plastic - An experimental and finite element studycitations
- 2012Drilling of woven glass fiber-reinforced plastic - An experimental and finite element studycitations
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article
Numerical modelling of microstructure in friction stir welding of aluminium alloys
Abstract
Mechanical properties like strength and hardness depend largely on microstructure. The conventional methods to evaluate microstructure such as optical and electron-based microscopy require a substantial amount of time and are expensive as well. To deal with this issue, the present work reports evaluation of the microstructure via numerical modelling in friction stir welding (FSW). This includes a 3-D thermo-mechanical model built on the Lagrangian implicit formulation. It has been experimentally validated for different processing conditions. A coupled approach combining Cellular Automaton (CA) and Laasraoui and Jonas (LJ) with the thermo-mechanical model is followed. Temperature, strain and strain rate form the inputs from the developed model to predict the microstructure. Nucleation and grain growth have also been considered in the model. The results have been validated by comparing the experimentally obtained grain size results at the weld zones namely stir zone, thermo-mechanically affected zone and heat-affected zone; and the percentage errors are 7.3%, 10.6%, and 8.5%, respectively. The effects of two key process parameters (tool rotation (ω) and welding speed (v)) on temperature and effective strain have been investigated and correlated with the obtained grain size.