| 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
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document
Measurement of Laser Absorptivity by Calibrated Melt Pool Simulation
Abstract
In recent years there has been considerable progress in developing AM simulation capabilities aimed at process optimization, component qualification and process control. The amount of energy transferred to the part by the laser or electron beam is, of course, a critical factor. However, at least for selective laser melting (SLM), the published literature contains surprisingly little data on laser absorptivity that apply to the actual operating conditions.To address this gap, we report the results of a detailed investigation of the factors affecting laser absorption by Ti-6Al-4V during SLM. By calibrating melt pool CFD simulations against single track experiments conducted over a range of energy densities, we have been able to determine the intrinsic laser absorptivity of Ti-6Al-4V during SLM. Our simulations incorporate multiple laser reflections and cover the transition from conduction to keyhole mode. We also discuss physical mechanisms that may be responsible for an increase in the effective laser absorptivity at high energy density which is observed in this and other work.