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Erschienen in: International Journal of Material Forming 5/2020

10.06.2020 | Review

Optimized and validated prediction of plastic yielding supported by cruciform experiments and crystal plasticity

verfasst von: Holger Hippke, Sebastian Hirsiger, Bekim Berisha, Pavel Hora

Erschienen in: International Journal of Material Forming | Ausgabe 5/2020

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Abstract

The predictability of strain distributions and the related prediction of hardening and failure plays a central role in tool and process design for any metal forming process. Studying yielding behaviour, it was discovered that for various well established yield loci no satisfying agreement between DIC (digital image correlation) measurement of strain distribution and simulation result could be obtained, even after optimization of parameters based on associated flow assumption. In parallel, crystal plasticity simulations were investigated with the objective to predict the relation between stress and strain ratios for a large number of load cases based on texture measurement. To include macroscopic data, a secondary strategy uses cruciform tension specimen as defined in ISO16842 to obtain strain and stress ratios. The resulting relations were then applied separately as input parameters for the plastic yield description. Both approaches reach high agreement between forming experiment and simulation. Against the previous assumption, the output can be obtained with either anisotropic or free shape yield loci and associated flow description. The methodology discussed provides an alternative and challenges to rethink the definition of yielding for aluminium alloys on the example of an AA6014-T4 aluminium alloy.

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Metadaten
Titel
Optimized and validated prediction of plastic yielding supported by cruciform experiments and crystal plasticity
verfasst von
Holger Hippke
Sebastian Hirsiger
Bekim Berisha
Pavel Hora
Publikationsdatum
10.06.2020
Verlag
Springer Paris
Erschienen in
International Journal of Material Forming / Ausgabe 5/2020
Print ISSN: 1960-6206
Elektronische ISSN: 1960-6214
DOI
https://doi.org/10.1007/s12289-020-01569-6

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