Microstructural indicators of transition mechanisms in time-dependent fatigue crack growth in nickel base superalloys.

摘要

Gas turbine engines are an important part of power generation in modern society, especially in the field of aerospace. Aerospace engines are design to last approximately 30 years and the engine components must be designed to survive for the life of the engine or to be replaced at regular intervals to ensure consumer safety. Fatigue crack growth analysis is a vital component of design for an aerospace component. Crack growth modeling and design methods date back to an origin around 1950 with a high rate of accuracy. The new generation of aerospace engines is designed to be efficient as possible and require higher operating temperatures than ever seen before in previous generations. These higher temperatures place more stringent requirements on the material crack growth performance under creep and time dependent conditions. Typically the types of components which are subject to these requirements are rotating disk components which are made from advanced materials such as nickel base superalloys.;Traditionally crack growth models have looked at high temperature crack growth purely as a function of temperature and assumed that all crack growth was either controlled by a cycle dependent or time dependent mechanism. This new analysis is trying to evaluate the transition between cycle-dependent and time-dependent mechanism and the microstructural markers that characterize this transitional behavior. The physical indications include both the fracture surface morphology as well as the shape of the crack front. The research will evaluate whether crack tunneling occurs and whether it consistently predicts a transition from cycle-dependent crack growth to time-dependent crack growth. The study is part of a larger research program trying to include the effects of geometry, mission profile and environmental effects, in addition to temperature effects, as a part of the overall crack growth system. The outcome will provide evidence for various transition types and correlate those physical attributes back to the material mechanisms to improve predictive modeling capability.