SUMMARY

Hot section components of land-based gas turbines are subject to extremely harsh, high temperature environments and require the use of advanced materials. Directionally solidified Ni-base superalloys are often chosen as materials for these hot section components due to their excellent creep resistance and fatigue properties at high temperatures. These blades undergo complex thermomechanical loading conditions throughout their service life, and the influences of blade geometry and variable operation can make life prediction difficult. Accurate predictions of material response under thermomechanical loading conditions is essential for life prediction of these components. Complex crystal viscoplasticity models are often used to capture the behavior of Ni-base superalloys. While accurate, these models are computationally expensive and are not suitable for all phases of design. This work involves the calibration of a previously developed reduced-order, macroscale transversely isotropic viscoplasticity model to a directionally solidified Ni-base superalloy. The unified model is capable of capturing isothermal and thermomechanical responses in addition to secondary creep behavior. An extreme reduced order microstructure-sensitive constitutive model is also developed using an artificial neural network to provide a rapid first-order approximation of material response under various temperatures, rates of loading, and material orientation from the axis of solidification.