Materials World Network: Physically based approach for predicting and minimizing damage nucleation in metals

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The ability to predict damage nucleation and evaluate whether it will lead to failure is one major goal of computational plasticity. However, most damage modeling is based upon the assumption of pre-existing flaws, and approaches developed so far predict growth rather than nucleation of damage. While heterogeneous deformation is understood to be a precursor to damage nucleation, the step from one to the other is not clearly understood. Certainly, if heterogeneous deformation is not modeled accurately, then it is unlikely that damage nucleation, or damage growth can be confidently predicted. The proposed research seeks to obtain for the first time a suitably detailed set of data from grain ensembles around damage nucleation sites to identify the corresponding mechanisms at polycrystal boundaries. Spatially resolved slip and twin system activity, crystal orientation, lattice rotations, 3D grain boundary stereology, and local surface strain during plastic deformation is measured in situ by electron channeling contrast imaging, electron backscatter diffraction, focused ion beam milling, and digital image correlation. This extensive and unique data set facilitates the evaluation of improvements in mesoscale deformation models. By complementing experimental observations with supplemental results from verified crystal plasticity finite element simulations of the respective grain ensembles new insights into the operating damage nucleation mechanism(s) are possible. Deriving appropriate damage nucleation models from this will allow to bridge from grain-scale simulations of representative volumes where nucleation is captured to continuum-scale simulations of damage growth/propagation.