This thesis describes innovative methods used to predict high-stress amplitude, low cycle fatigue (LCF) behavior of a material commonly used in gas turbine blade design with the absence of such data. A combination of extrapolation and estimation techniques from both prior and current studies has been explored with the goal of developing a method to accurately characterize such high-temperature fatigue of IN738LC, a dual-phase Ni-base superalloy. A method capable of predicting high-stress (or strain) amplitude fatigue from incessantly available low-stress amplitude, high cycle fatigue (HCF) would lower the costs of inspection, repair, and replacement on certain turbine components. Three sets of experimental data at different temperatures are used to evaluate and examine the validity of extrapolation methods such as anchor points and hysteresis energy trends. Stemming from extrapolation techniques developed earlier by Coffin, Manson, and Basquin, the techniques exercised in this study purely implement tensile test and HCF data with limited plastic strain during the estimation processes. A standard practice in engineering design necessitates mechanical testing closely resembling planned service conditions; for design against fatigue failure, HCF and tensile data are the experiments of choice. High stress amplitude data points approaching the ultimate strength of the material were added to the pre-existing HCF base data to achieve a full-range data set that could be used to test the legitimacy of the different prediction methods. While some methods proved to be useful for bounding estimates, others provided for superior estimation.
| Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:honorstheses1990-2015-1990 |
| Date | 01 January 2010 |
| Creators | Daubenspeck, Brian R. |
| Publisher | STARS |
| Source Sets | University of Central Florida |
| Language | English |
| Detected Language | English |
| Type | text |
| Source | HIM 1990-2015 |
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