| 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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Tinga, Tiedo
Netherlands Defence Academy
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (28/28 displayed)
- 2024Corrosion classification through deep learning of electrochemical noise time-frequency transient informationcitations
- 2022Dynamics-based impact identification method for composite structures
- 2020Ultrasonic inline inspection of a cement-based drinking water pipelinecitations
- 2020Effects of powder reuse on the microstructure and mechanical behaviour of Al-Mg-Sc-Zr alloy processed by laser powder bed fusion (LPBF)citations
- 2020Effects of powder reuse on the microstructure and mechanical behaviour of Al-Mg-Sc-Zr alloy processed by laser powder bed fusion (LPBF)citations
- 2020Measuring the spreadability of pre-treated and moisturized powders for laser powder bed fusioncitations
- 2019Revealing the effects of powder reuse for selective laser melting by powder characterizationcitations
- 2019Drying strategies to reduce the formation of hydrogen porosity in Al alloys produced by Additive Manufacturing
- 2019Melt Pool Monitoring for the Laser Powder Bed Fusion Process
- 2019Revealing the Effects of Powder Reuse for Selective Laser Melting by Powder Characterizationcitations
- 2019Towards the development of a hybrid methodology of head checks in railway infrastructure
- 2018Mechanical properties of aluminum alloys produced by Metal Additive Manufacturing
- 2018Utilizing Force-State Mapping for Detecting Fatigue Damage Precursors in Aerospace Applications
- 2018The Detection of Fatigue Damage Accumulation in a Thick Composite Beam Using Acousto Ultrasonics
- 2017Powder Characterization and Optimization for Additive Manufacturing
- 2017Modal strain energy-based structural health monitoring validation on rib stiffened composite panels
- 2016Modal Strain Energy Based Structural Health Monitoring on Rib Stiffened Composite Panels
- 2016Monitoring dynamic stiffness that predicts concrete structure degradation
- 2015Experimental evaluation of vibration-based damage identification methods on a composite aircraft structure with internallymounted piezo diaphragm sensorscitations
- 2014Detection of microbiologically influenced corrosion by electrochemical noise transientscitations
- 2014Aligning PHM, SHM and CBM by understanding the physical system failure behaviour
- 2013The influence of abrasive body dimensions on single asperity wearcitations
- 2013Application of transient analysis using Hilbert spectra of electrochemical noise to the identification of corrosion inhibitioncitations
- 2013Transient analysis through Hilbert spectra of electrochemical noise signals for the identification of localized corrosion of stainless steelcitations
- 2012Investigating the influence of sand particle properties on abrasive wear behaviourcitations
- 2011Application of a multiscale constitutive framework to real gas turbine componentscitations
- 2010Cube slip and non-Schmid effects in single crystal Ni-base superalloyscitations
- 2008Incorporating strain gradient effects in a multiscale constitutive framework for nickel-base superalloyscitations
Places of action
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document
Powder Characterization and Optimization for Additive Manufacturing
Abstract
Achieving the optimal quality for Additive Manufactured (AM) parts does not only depend on setting the right process parameters. Material feedstock also plays an important role when aiming for high performance products. The metal AM processes that are most applicable to industry, Powder Bed Fusion and Directed Energy Deposition, use metal powder as raw material. Therefore, controlling the quality and correctly characterizing the particles used in the process is a key step to successfully apply metal AM techniques. A correct flow of the powder and a constant apparent density over the build plate/substrate ensure a smooth process, less porosity and better surface resolution. In the present paper a methodology for AM powder characterization will be proposed, based on parameters like particle size distribution and shape, and experimental results will be presented. A series of representative materials from the above-mentioned techniques are studied to find the optimal particle parameters required in the metal AM processes.