Related resources
Search for item elsewhere
University researcher(s)
Academic department(s)
Understanding the microstructural efects in a large grain cast nickel-based superalloy
[Thesis]. Manchester, UK: The University of Manchester; 2018.
Access to files
-
FULL-TEXT.PDF (pdf)
Abstract
Scatter observed in the fatigue test results of a cast nickel-based superalloy may arise from its coarse grain microstructure. With only a few grains through the sample cross-section, it has been postulated that the inherent anisotropy of individual grains results in the different surface strain distributions during testing. Crystal plasticity finite element modelling (CPFEM) was used to model the deformation of a fat test piece containing a few grains in the cross-section. The mesh was generated using EBSD maps from the surfaces of samples that were subjected to monotonic and cyclic loading at two different temperatures. Digital image correlation (DIC) was used to study the local strain the same sur- faces. Heterogeneous strain distribution, that could be responsible for scatter in the fatigue test results, was observed both in the model and experimentally. However, they were quantitatively different. These differences are attributed to the simplistic microstructural representation in the model and its inability to accurately represent intergranular deformation. The inherent anisotropy within grains resulted in different surface strain distributions during cyclic loading and it was observed that the fatigue life of the test specimens could be correlated to the maximum plastic strain in the sample at the end of the first cycle. As the CPFE model captured the maximum strain measured experimentally, the maximum strain at the end of the first cycle was determined as a fatigue indicator parameter (FIP) for the number of cycles to failure. Randomly generated synthetic microstructures were then loaded in tension and it was observed that when using local strain as a FIP, the scatter in orientations of individual grains resulted in scatter in the expected fatigue life.