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Parameter identification of 3D yield functions based on a virtual material testing procedure

: Butz, A.; Wessel, A.; Pagenkopf, J.; Helm, D.

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International Deep Drawing Research Group -IDDRG-:
38th International Deep Drawing Research Group Annual Conference, IDDRG 2019 : Forming 4.0: Big Data - Smart Solutions, 3-7 June 2019, Enschede, Netherlands
Bristol: IOP Publishing, 2019 (IOP conference series. Materials science and engineering 651)
Paper 012078, 8 S.
International Deep Drawing Research Group (IDDRG Conference) <38, 2019, Enschede>
Bundesministerium fur Wirtschaft und Energie BMWi (Deutschland)
18810 BG
Bundesminsterium für Wirtschaft und Energie BMWi
19707 N
Konferenzbeitrag, Elektronische Publikation
Fraunhofer IWM ()
3D yield model; deep drawing steel; virtual material testing; DX56; virtual test

The parameter identification of anisotropic 3D yield functions for sheet metals based on experimental data is very difficult, because material properties associated to the out-of-plane stress states cannot be directly measured. An alternative and promising approach for identifying parameters of anisotropic yield models, and particularly for 3D yield models, is the concept of virtual testing. Within the presented work, a full-field microstructure simulation framework based on a crystal plasticity (CP) model is used to determine macroscopic mechanical properties of a ferritic deep drawing steel DX56 within 3D stress space. The results are utilized to identify the parameter of anisotropic 2D and 3D yield models according to Hill [1] and Barlat [2, 3].