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Plastic anisotropy of rolled aluminum using CP-FFT methods in comparison with statistical CP models

By Seventekidis Panagiotis (KU Leuven, Department of Materials Engineering)
Co-authors: Diarmuid Shore (KU Leuven, Department of Materials Engineering)
Marc Seefeldt (KU Leuven, Department of Materials Engineering)
Dirk Roose (KU Leuve, Department of Computer Science)
Albert Van Bael (KU Leuven, Department of Materials Engineering)


Grain texture and morphology of polycrystalline materials plays an important role in the anisotropic plastic behaviour of sheet rolled metals. For the prediction of materials behaviour, various statistical CP models (TAYLOR, ALAMEL, VPSC) have been widely used in multi-scale simulations of forming processes. Statistical CP models consider consecutive virtual experiments on single grains or clusters of grains, randomly chosen within a range of orientations present in the material. CP-FFT methods on the other hand consider a full multi-grain Representative Volume Element (RVE) of the material microstructure, and use Fast Fourier Transformations, in order to speed up the process of solution of the Boundary Value Problem (BVP) in crystal plasticity. In this work focus will be given on the construction of accurate RVEs of rolled aluminium samples as input for CP-FFT methods, with the RVEs being used after in virtual experiments for the calibration of the anisotropic FACET yield locus into a FEM cup-drawing process. Comparison against experimental and statistical CP results for rolled aluminium sheets will be given. Finally the results will be discussed, about the accuracy and the computational cost of the simulations.

Ⓒ Photos:Toerisme Leuven