| 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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Sedighiani, Karo
Delft University of Technology
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (11/11 displayed)
- 2024Comparative analysis of crystal plasticity models in predicting deformation texture in IF-Steelcitations
- 2024Anisotropic power diagrams for polycrystal modelling: efficient generation of curved grains via optimal transportcitations
- 2022Coupling crystal plasticity and cellular automaton models to study meta-dynamic recrystallization during hot rolling at high strain ratescitations
- 2022Crystal plasticity simulation of in-grain microstructural evolution during large deformation of IF-steelcitations
- 2022Determination and analysis of the constitutive parameters of temperature-dependent dislocation-density-based crystal plasticity modelscitations
- 2022Crystal Plasticity Simulation of in-grain Microstructural Evolution during Large Plastic Deformation
- 2021Topological aspects responsible for recrystallization evolution in an IF-steel sheet – Investigation with cellular-automaton simulationscitations
- 2021Large-deformation crystal plasticity simulation of microstructure and microtexture evolution through adaptive remeshingcitations
- 2020Current Challenges and Opportunities in Microstructure-Related Properties of Advanced High-Strength Steelscitations
- 2020Current challenges and opportunities in microstructure-related properties of advanced high-strength steelscitations
- 2020An efficient and robust approach to determine material parameters of crystal plasticity constitutive laws from macro-scale stress-strain curvescitations
Places of action
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article
An efficient and robust approach to determine material parameters of crystal plasticity constitutive laws from macro-scale stress-strain curves
Abstract
A severe obstacle for the routine use of crystal plasticity models is the effort associated with determining their constitutive parameters. Obtaining these parameters usually requires time-consuming micromechanical tests that allow probing of individual grains. In this study, a novel, computationally efficient, and fully automated approach is introduced which allows the identification of constitutive parameters from macroscopic tests. The approach presented here uses the response surface methodology together with a genetic algorithm to determine an optimal set of parameters. It is especially suited for complex models with a large number of parameters. The proposed approach also helps to develop a quantitative and thorough understanding of the relative influence of the different constitutive parameters and their interactions. Such general insights into parameter relations in complex models can be used to improve constitutive laws and reduce redundancy in parameter sets. The merits of the methodology are demonstrated on the examples of a dislocation-density-based crystal plasticity model for bcc steel, a phenomenological crystal plasticity model for fcc copper, and a phenomenological crystal plasticity model incorporating twinning deformation for hcp magnesium. The approach proposed is, however, model-independent and can be also used to identify parameters of, for instance, fatigue, creep and damage models. The method has been implemented into the Düsseldorf Advanced Material Simulation Kit (DAMASK) and is available as free and open-source software. The capability of translating complex material response into a micromechanical digital twin is an essential precondition for the ongoing digitalization of material property prediction, quality control of semi-finished parts, material response in manufacturing and the long-term behavior of products and materials when in service. ; (OLD) MSE-3 ; Materials Science and Engineering