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Cheney, Suzanne
(2023).
DOI: https://doi.org/10.21954/ou.ro.00016991
Abstract
When placing metallic components in safety-critical environments, such as nuclear reactors, it is important to be able to accurately predict their service lifetime. For these predictions to be reliable in safety-critical environments they need to accommodate behaviour at the microscale as well as the macroscale. Micro-scale strain development can be measured during mechanical loading and then used to help predict failure within such components.
In this thesis, neutron diffraction (ND) was used to measure bulk-scale lattice strains for grains with orientations that correlate to the diffraction peaks. However, ND is expensive and only available at several national facilities. Therefore, high-resolution digital image correlation (HR-DIC) has been proposed as a cheaper and more accessible alternative. This project therefore compares the strain data collected from both ND and HR-DIC to evaluate the effectiveness of using HR-DIC as a bulk grain-scale technique.
To evaluate the effectiveness of HR-DIC as a bulk strain measurement technique, the effect of stacking fault energy (SFE) on deformation mechanics was selected as a comparable phenomenon. The materials were selected to represent a range of stacking fault energy, stainless steel 316 (SS316), INVAR and pure nickel. The samples were prepared to be tested in both in situ neutron diffraction tensile tests and in situ HR-DIC tensile tests, with post-mortem EBSD analysis performed on the neutron diffraction samples to investigate EBSD metrics.
For the SS316 sample, the HR-DIC showed three distinct orientation peaks, showing that the technique was able to accurately distinguish and divide the data into the orientation subsets. The 111-, 220-, and 200-orientation subsets show a broader range of strain behaviour in the low SFE materials (SS316 and INVAR) compared to the high SFE material (nickel). This was in good agreement with the results of the neutron diffraction tests and the EBSD metric analysis.
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CORE (COnnecting REpositories)
