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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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Ali, Muhammad Adil
Ruhr University Bochum
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (9/9 displayed)
- 2024Highly complex materials processes as understood by phase-field simulations
- 2024Automated Workflow for Phase‐Field Simulations: Unveiling the Impact of Heat‐Treatment Parameters on Bainitic Microstructure in Steelcitations
- 2023Coherency loss marking the onset of degradation in high temperature creep of superalloyscitations
- 20233D phase-field simulations to machine-learn 3D information from 2D micrographscitations
- 2022Microstructure property classification of nickel-based superalloys using deep learningcitations
- 2022Schmid rotations during high temperature creep in Ni-based superalloys related to coherency losscitations
- 202045-degree rafting in Ni-based superalloys citations
- 2019Studying Grain Boundary Strengthening by Dislocation-Based Strain Gradient Crystal Plasticity Coupled with a Multi-Phase-Field Modelcitations
- 2019Studying grain boundary strengthening by dislocation-based strain gradient crystal plasticity coupled with a multi-phase-field model
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article
3D phase-field simulations to machine-learn 3D information from 2D micrographs
Abstract
A novel approach is developed to support retrieval of 3D information from 2D experimental micrographs. The approach utilizes 3D phase-field simulations to train an artificial intelligence machine. In a first step, the phase-field simulations have to be validated to reproduce microstructural features which characterize elementary processes which govern processing and high temperature service exposure. The qualified 3D simulation setup is then applied to produce a high number of 2D simulated micrographs by automated sectioning. These simulated micrographs are then used to train a gradient boosting regression model together with the 3D information from the simulations. In the final step, the model is applied to 2D experimental micrographs to retrieve the hidden 3D features. The approach is generally applicable to all kinds of metallic materials, minerals or ceramics which can be treated quantitatively by phase-field simulations. In this paper we concentrate on the process of directional coarsening, referred to as "rafting", in the field of creep of single crystal Ni-base superalloys. The experimental and modeling aspects of the evolution of the volume fraction of the \(\) phase during long term creep are discussed.