SUMMARY

Computational models, including physics-based models such as the crystal plasticity finite element method (CPFEM), and top-down preliminary design search algorithms like the Inductive Design Exploration Method (IDEM), are increasingly being fused with experimental methods to increase the pace of decision support in materials design and development. However, connecting these types of models with experiments, rapid inverse property/response estimates, and design decision-making via integrated workflows has yet to become well-established in the materials community for certain scientific and engineering challenges. This dissertation implements a simulation-based workflow that aids the materials design exploration process for fatigue resistance, strength, and elastic stiffness of Ti-6Al-4V, an α+β Ti alloy, with the advancement of CPFEM models and the IDEM methodology. Spherical nanoindentation (SNI) experimental datasets are used for calibration purposes because of their ability to extract individual phase and grain properties. The materials knowledge system (MKS) has proven to be extremely computationally efficient for generating spatially local results of polycrystalline materials. In this work, the MKS is coupled with an explicit integration scheme to generate extreme value distributions of fatigue indicator parameters (FIPs) relevant to High Cycle Fatigue resistance. These datasets are assessed with a new, Python scripted generalized framework of IDEM to assess robust solutions for specific design scenarios. The significance of this research spans multiple domains, with the common focus of improving computational tools for extension to rapid decision making in material design and optimization. The objectives of this research are to: 1. Develop FEM models of the SNI process to explore the coupling of CPFEM simulations with similar experimental data for the α and α+β phases of Ti-64 primarily for model parameter extraction, but additionally for model validity. 2. Extend CPFEM modeling and local deformation fatigue simulations results for the MKS model calibration. 3. Utilize the IDEM with microstructure-sensitive simulation data for local (grain level) and global (polycrystalline) properties/response to pursue robust material designs for ranged sets of specified performance objectives. 4. Explore the viability of concepts from existing slip transfer correlations with regard to formulation of constitutive relations to address the behavior of slip transfer across grain and phase boundaries in α+β titanium alloys.