Directionally solidified (DS) nickel-base superalloys are used in high temperature gas turbine engines because of their high yield strength at extreme temperatures and strong low cycle fatigue (LCF) and creep resistance. Costly inspecting, servicing, and replacing of damaged components has precipitated much interest in developing models to better predict service life. Turbine blade life modeling is complicated by the presence of notches, dwells, high temperatures and temperature gradients, and highly anisotropic material behavior. This work seeks to develop approaches for predicting the life of hot sections of gas turbines blade material CM247LC DS subjected to LCF, dwells, and stress concentrations while taking into consideration orientation and notch effects. Experiments were conducted on an axial servo-hydraulic MTSĀ® testing machine. High temperature LCF tests were performed on smooth and notched round-bar specimens in both longitudinal and transverse orientations with and without dwells. Experimental results were used to develop and validate an analytical life prediction model. An analytical model based on a multiaxial Neuber approach predicts the local stress-strain response at a notch and other geometric stress concentrations. This approach captures anisotropy through a multiaxial generalization of the Ramberg-Osgood relation using a Hill's type criterion. The elastic notch response is determined using an anisotropic elastic finite element analysis (FEA) of the notch. The limitations of the simpler analytical life-modeling method are discussed in light of FEA using an anisotropic elastic-crystal viscoplastic material model. This life-modeling method provides a quick alternative to time demanding elastic-plastic FEA allowing engineers more design iterations to improve reliability and service life.
Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/24813 |
Date | 19 May 2008 |
Creators | Moore, Zachary Joseph |
Publisher | Georgia Institute of Technology |
Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
Detected Language | English |
Type | Thesis |
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