A Parametric Study of the Virtual Fields Method for Identification of Anisotropic Plasticity

Abstract Accurately characterizing plastic anisotropy in metals is crucial for modeling sheet metal forming processes. One effective approach for calibrating this complex behavior is to use the Virtual Fields Method (VFM), a full-field inverse method based on the principle of virtual work, with a small number of experiments with spatially-heterogeneous fields, and utilizing both experimentally measured loads and full-field displacements. These measurements are used in calculating the internal and external virtual work by assuming a constitutive model and iteratively updating the material model constants until a sufficiently small equilibrium-gap is achieved. The current standard for applying VFM to large-strain plasticity problems is sensitivity-based virtual fields; stress-fields are calculated with initial and slightly perturbed material constants, which are then converted back into virtual strain fields to assess the virtual work balance. Several critical decisions regarding various parameters for the analysis must be made, beginning with the experimental setup and post-processing regarding spatial and temporal data density and filtering. Additional parameters are introduced into the analysis, including perturbation size and scaling of sensitivity-based virtual fields, frequency of virtual field updating, virtual mesh size, and convergence tolerance. This work focuses on a parametric study of these parameters in the analysis of simulated plane-strain tension experiments for AA6061-T6 in three in-plane directions, to identify parameters for the Yld2000-2D yield function. This work provides a framework for assessing the sensitivity of parameter values used in VFM analyses for yield function identification, leading to improved material models and enhanced predictive capabilities in modeling sheet metal forming processes.