SUMMARY

The high cost and data scatter of physical fatigue experiments, particularly in the High Cycle Fatigue (HCF) regime, requires a paradigm shift to efficiently assess the fatigue criticality of metallic components. Integrated Computational Materials Engineering (ICME) presents an attractive alternative that employs microstructure-sensitive simulations given accessible process paths and resulting microstructures. In the proposed research, multilevel scripted workflows will be implemented into the open-source Python programming language to study the effects of intrinsic (crystallographic orientation distribution, grain shape, and grain size distribution) and extrinsic (residual stress and surface roughness) microstructure attributes, boundary conditions (fully periodic vs. traction free), and strain states (e.g., uniaxial, shear, biaxial). Digital microstructure instantiations of Duplex Ti-6Al-4V (Ti64) and Al 7075-T6 (Al7075) are generated for simulation with Crystal Plasticity Finite Element Method (CPFEM) models using the open-source Dream.3D software, with extreme value fatigue response as the primary performance requirement. Fatigue Indicator Parameters (FIPs) are used as surrogate measures of the driving force for fatigue crack formation, and are volume-averaged over regions within grains representative of fatigue damage process zones. These FIPs are fit to know extreme value distributions so that the effects of different microstructure attributes and boundary/strain states may be assessed. Additionally, other extreme FIP characteristics (e.g., proximity to free surface, elastic strain normal to slip plane) will be examined.