Microstructure-Sensitive Notch Root Analysis for Ni-Base Superalloys (Preprint)

摘要

Macroscopic viscoplastic constitutive models for y-y Ni-base superalloys typically do not contain an explicit dependence on the underlying microstructure. Microstructure dependent models are of interest since the sizes, volume fractions, and morphologies of primary, secondary, and tertiary precipitates can substantially affect the stress-strain response. The principle microstructural features that can significantly affect the stress-strain response of y-y Ni-base superalloys are the grain size and precipitate volume fraction and size distributions. An Artificial Neural Network (ANN) is used to correlate the material parameters in an internal state variable cyclic viscoplasticity model with these microstructure plasticity calculations performed on other microstructures within the range characterized experimentally. The trained model is applied to an example of component notch root analyses to explore the potential impact of microstructure-sensitive constitutive models in fatigue design of structures.