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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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Weisz-Patrault, Daniel
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Topics
Publications (11/11 displayed)
- 2020Tensile and ductile fracture properties of as-printed 316L stainless steel thin walls obtained by directed energy depositioncitations
- 2020Fast simulation of grain growth based on Orientated Tessellation Updating Methodcitations
- 2020Energetic upscaling strategy for grain growth. I: Fast mesoscopic model based on dissipationcitations
- 2019Fast simulation of grain growth based on Orientated Tessellation Updating Method
- 2019Fast Mesoscopic Simulation Of Grain Growth And Macroscopic Modeling
- 2019Residual Strains In Directed Energy Deposition Additive Manufacturing
- 2019Fast simulation of temperature and phase transitions in directed energy deposition additive manufacturing
- 2019Fast macroscopic thermal analysis for laser metal deposition. Application to multiphase steels
- 2017Energetic approach coupled with analytic solutions for the evaluation of residual stress.
- 2017Energetic approach coupled with analytic solutions for the evaluation of residual stress
- 2012Finding and using inverse analyic methods for coupled thermo-elastic problems
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document
Fast Mesoscopic Simulation Of Grain Growth And Macroscopic Modeling
Abstract
The Orientated Tessellation Updating Method (OTUM) is a fast mesoscopic model of grain growth that has been published recently for a single phased metal without diffusion or segregation of alloying elements. It is based on tessellation techniques and simple linear algebra. On this basis, some ideas to develop an upscaling strategy are broached in this work. The aim is to develop a macroscopic model of grain growth whose state variables contain for each material point the statistical descriptors of the microstructure (e.g., disorientation, grain size and shape distributions).