| 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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Nguyen, Vu
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (16/16 displayed)
- 2024Advances in Additive Manufacturing of Auxetic Structures for Biomedical Applicationscitations
- 2024Analysis of self-supporting conformal cooling channels additively manufactured by hybrid directed energy deposition for IM toolingcitations
- 2023Advances in Multiscale Modelling of Metal Additive Manufacturing
- 2023Osseointegrability of 3D-printed porous titanium alloy implant on tibial shaft bone defect in rabbit modelcitations
- 2022Directed-energy deposition (DED) of Ti-6Al-4V alloy using fresh and recycled feedstock powders under reactive atmosphere
- 2021Progress Towards a Complete Model of Metal Additive Manufacturingcitations
- 2019Measurement of Laser Absorptivity by Calibrated Melt Pool Simulation
- 2019Residual Stress in Additive Manufacture
- 2018Accelerating Experimental Design by Incorporating Experimenter Hunchescitations
- 2017Modelling Powder Flow in Metal Additive Manufacturing Systems
- 2017A desktop computer model of the arc, weld pool and workpiece in metal inert gas weldingcitations
- 2017Aiming for modeling-assisted tailored designs for additive manufacturingcitations
- 2015A desktop computer model of arc welding using a CFD approach
- 2015Prediction of springback in anisotropic sheet metals: The effect of orientation and frictioncitations
- 2011Modelling die filling in ultra-thin aluminium die castings
- 20113D thermo-mechanical modelling of wheel and belt continuous castingcitations
Places of action
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document
Modelling die filling in ultra-thin aluminium die castings
Abstract
This work aims to develop flow and thermal control methods for the high pressure die casting (HPDC) of very thin-walled aluminium components where thicknesses are predominantly less than 1 mm. One specific aim includes developing advanced modelling capability using CFD software to predict the complex structure of the metal flow in the die and the casting solidification. The modelling based on FLOW-3D started initially with a fluidity die study to establish several key parameters in HPDC modelling through experimental validation. A new test casting geometry has been designed in the form of a shallow tray with other features such as changes in curvature, fins and bosses. The casting thickness can be made variable in the die. The experimental work was conducted on a 250-tonne HPDC machine. Initial models of molten metal flow in the die cavity based on a runner design for casting thicknesses between 1.5 mm and 1 mm are presented. The detailed model required a very large mesh of very small elements, and more accurate physical parameters which may not have been previously available.