Open AccessCrystal plasticity as complementary modelling technique for improved simulations results of anisotropic sheet metal behaviour in forming processes
Author(s) -
Sebastian Hirsiger,
Bekim Berisha,
Holger Hippke,
Pavel Hora
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.179
H-Index - 26
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/967/1/012067
Subject(s) - anisotropy , calibration , materials science , sheet metal , plasticity , crystal plasticity , hardening (computing) , yield (engineering) , inverse , mechanics , statistical physics , mathematics , geometry , physics , composite material , optics , statistics , layer (electronics)
The accuracy of the simulation results in terms of metal sheet forming strongly depends on the capability of modelling the anisotropic material behaviour. In addition, predictive capabilities of the models are strongly influenced by the way how the constitutive model parameters are calibrated. Macroscopic models lean towards to become more complex in order to map the material behaviour more precisely. As consequence the amount and complexity of the experiments is increasing as well. In addition, it is well known that, some of the experiments, for example the equibiaxial compression test, are difficult to perform and therefore, a reasonable coupling of crystal plasticity (CP) modelling and macroscopic models is proposed. It is worth to mention that, in the domain of CP, arbitrary load cases are possible and therefore, any stress ratio of the yield criterion can be used for calibration. Prediction of anisotropic material behaviour of AA6016-T4 and DC05 sheets based on CP simulations were previously presented and compared with the macroscopic Yld2000-2d model. Their data set is now used for the calibration of the parameters of the macroscopic model, where in contrast to the classical procedure, the exponent of the yield locus is defined as a fitting parameter. The strain distributions predicted by the models have been compared with DIC-measurements of Nakajima samples. The predictive capabilities of the CP-based fitting procedure, compared to the classical fitting, are highlighted. Additionally, a comparison of the strain distribution prediction between all model variants is performed on a cruciform shaped deep drawing part. It underlines the importance of the correct prediction of the yield normal, as it is given by the crystal plasticity computation.