It is not possible today to predict when, where, or how metallic materials will fail during dynamic loading conditions of interest to the Air Force. We know only qualitatively that material defects or structural features (differing types) are attributed to damage nucleation. The stress conditions necessary to nucleate damage at specific defect or feature sites remains largely unquantified. For example, the conditions for pore nucleation at inclusions, phase boundaries, or grain boundaries may be very different. We also know that polycrystalline metals are aggregates of anisotropic grains which interact strongly during deformation to create very heterogeneous internal stress fields. This local stress drives damage nucleation at defects or structural features, not the mean stress which is measured experimentally and used in nearly all macro-scale damage models. This project seeks to fundamentally change how we approach the design and manufacture of materials by control of both defect/feature character and internal stress state. We begin this fundamental change by focusing on one defect/feature type – grain boundaries – and quantifying the conditions for pore nucleation. For this purpose, we have selected the BCC refractory model material tantalum (Ta) which has been demonstrated to predominantly nucleate and grow damage from grain and twin-grain boundary junctions. This material also displays important non-Schmid asymmetry in the motion of screw dislocations, similar to other refractory metals for extreme environment applications. This project also intends for this approach and the tools developed in this project be extended to other defect/feature types and materials in the future as this project extends earlier Air Force work with the focus here upon damage and material design/manufacture for extreme loading conditions (strain rates up to 104 s-1 in this project). This project will also contribute to training of next generation scientists and engineers (four Ph.D. and several undergraduate students) in advanced cross-disciplinary scientific study on topics of strong relevance to the Air Force Research Laboratory (AFRL) and our nation. Achieving the proposal objective will involve new and innovative modeling, statistical analysis, uncertainty reduction, and computational simulations, validated and verified through sample preparation, characterization, and demonstration at multiple length scales along with iterative feedback between these tasks and processing.
