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• W853395891 abstract "Defect Detection Microscopy Stuart C. Rogers Department of Mechanical Engineering Master of Science The automotive industry‟s search for stronger lighter materials has been hampered in its desire to make greater use of Magnesium alloys by their poor formability below 150°C. One current challenge is to identify the complex structure and deformation mechanisms at work and determine which of these are primary contributors to the nucleation of defects. Orientation Imaging Microscopy has been the most accessible tool for microstructural analysis over the past 15 years. However, using OIM to analyze defect nucleation sites requires prior knowledge of where the defects will occur because once the defects nucleate the majority of microstructural information is destroyed. This thesis seeks to contribute to the early detection of nucleation sites via three mechanisms: 1. Detection of cracks that have already nucleated, 2. Detection of surface topography changes that may indicate imminent nucleation and 3. Beam control strategies for efficiently finding areas of interest in a scan. Successive in-situ OIM scans of a consistent sample region while strain is increased, while using the three techniques developed in this thesis, will be employed in future work to provide a powerful defect analysis tool. By analyzing retrieved EBSD patterns we are able to locate defect / crack sites via shadowing on the EBSD patterns. Furthermore, topographical features (and potentially regions of surface roughening) can be detected via changes in intensity metrics and image quality. Topographical gradients are currently only detectable in line with the beam incidence. It is therefore suggested that the tensile specimens to be examined are orientated such that the resulting shear bands occur preferentially to this direction. The ability to refine the scan around these areas of interest has been demonstrated via an off-line adaptive scan routine that is implemented via the custom scan tool. A first attempt at a defect detection framework has been outlined and coded into MATLAB. These tools offer a first step to accessing the information about defect nucleation that researchers are currently seeking." @default.
• W853395891 created "2016-06-24" @default.
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• W853395891 date "2010-01-01" @default.
• W853395891 modified "2023-09-27" @default.
• W853395891 title "Defect Detection Microscopy" @default.
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