Identification of Swift Law Parameters Using FEMU by a Synthetic Image DIC-Based Approach

Computer-aided engineering systems rely on constitutive models and their parameters to describe the material behaviour. The calibration of more elaborated with a larger number becomes very time cost consuming. development image-based technology has enhanced interest in inverse identification methods, which, when coupled full-field measurements, have potential reduce experimental tests required accurately identify properties. This work aims Swift hardening law dual-phase steel using tensile test heterogeneous dogbone specimen under uniaxial quasi-static loading conditions finite element model updating (FEMU) technique. numerical results were used generate synthetic images, which then processed by digital image correlation (DIC) as reference procedure. Two different approaches tested: (i) directly comparing reference; (ii) DIC-levelled data iteratively generating images DIC filter same settings (virtual experiment). obtained from both are compared discussed.