Decoupling plasticity- and damage-induced property changes by an elasto-plasticity framework coupled with a data-driven damage evolution model

Le résumé fourni par la source

In one approach in damage mechanics, deterioration of mechanical properties with plastic deformation is attributed to ductile damage in the form of void nucleation and growth. However, the quantitative relationship between damage and these properties remains unclear, primarily due to the difficulty of isolating damage from work-hardening and residual stresses of plastically deformed parts. This study integrates a validated data-driven damage evolution model, which incorporates high-resolution experimental void data obtained by scanning electron microscopy of dual-phase steel DP800, into an elasto-plasticity framework for finite element simulations. By incorporating a strain- and damage-dependent Young’s modulus, the framework distinguishes between damage- and plasticity-induced effects. Model parameters are identified through a combined direct and inverse optimization procedure using integral force data and full-field displacement data. The calibrated model provides, to the best of the authors’ knowledge, the first framework for quantitatively evaluating the potential effect of experimentally observed void evolution on elastic stiffness in dual-phase steels. The results show that the initial reduction in apparent elastic stiffness is not caused by void evolution. Following the onset of localization, these results further demonstrate that, even at pronounced deformation states close to macroscopic failure, the evolved void area fraction has no measurable influence on the apparent elastic stiffness or on plastic softening. • Development of a novel data-driven microscale related damage evolution model. • It is found that the initial decrease in elastic stiffness is not related to damage. • Quantitative proof that void evolution mainly occurs within martensite bands. • Dislocation-based microplasticity is the main cause of elastic stiffness degradation. • Calibration uses a combined direct and inverse parameter optimization strategy.

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