Characterization and Modelling of the Microstructure and Texture Evolution in AlMgSi-Extrusions

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The properties and surface appearance of aluminium extrusion are critically dependent on the microstructure and texture of the extruded profiles, and the requirements with respect to these aspects may vary with applications. Moreover it is often a challenge to produce extrusions with a consistent and homogenous grain structure and texture along as well as through the cross section of the profiles. It is thus vital to understand and be able to predict (model) how different microstructures and textures are formed and how they evolve during and after extrusion. In the present work a model framework has been implemented which includes a FEM model to account for the strain, strain rate and temperature along a set of particle paths during extrusion. From these the deformation texture and grain structure are calculated with an appropriate deformation texture model and a sub-structure evolution model, respectively. The sub-structure model have in the present work been coupled to a crystal plasticity model to provide an orientation dependent subgrain size and dislocation density during deformation which provides the driving force for the post-extrusion recovery and possible recrystallization behaviour. The post-extrusion microstructure and texture evolution is calculated with a recovery and recrystallization model, which is accompanied by a recrystallization texture model. The framework and its constituent models and their interplay are presented, and some preliminary results when applying this modelling framework to Al-Mg-Si extrusions are presented and discussed in view of corresponding experimental results.

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Edited by:

C. Sommitsch, M. Ionescu, B. Mishra, E. Kozeschnik and T. Chandra

Pages:

1239-1244

DOI:

10.4028/www.scientific.net/MSF.879.1239

Citation:

K. Zhang et al., "Characterization and Modelling of the Microstructure and Texture Evolution in AlMgSi-Extrusions", Materials Science Forum, Vol. 879, pp. 1239-1244, 2017

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November 2016

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$35.00

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