Inverse identification strategies for the characterization of transformation-based anisotropic plasticity models with the non-linear VFM

Abstract The Virtual Fields Method (VFM) is a well established inverse technique used to identify the constitutive parameters of material models using heterogeneous full-field strain data. When VFM is employed to retrieve the coefficients of advanced plasticity models, including non linear hardening and anisotropy, however, the procedure may become computationally intensive. Furthermore, the impact of experimental uncertainties is still not entirely scrutinized. In this paper, an identification strategy based on uncoupling the hardening behaviour and the anisotropic yield function is proposed. The approach, based on VFM, allows to carry on the identification with low computational time, and provides also indications on the optimal smoothing level to use in the full-field measurement. The identification framework is applied on the linear transformation-based yield condition Yld2000-2D, employing numerical data for the validation and, afterwards, using actual experimental data on a bake-hardenable steel, i.e. BH340. Moreover, several aspects of the identification procedure are investigated in dept, namely, the effect of smoothing, the influence of VFM settings (type of virtual fields used, discretization method) and the computational time. The identification results are compared with the standard calibration process, demonstrating that the proposed strategy is capable of identifying properly the material anisotropic behaviour using only three tests on notched specimens.