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Using real-time data analysis to conduct next-generation synchrotron fatigue studies
Next-generation experimental techniques, like high energy X-ray diffraction microscopy (HEDM), usher in new opportunities to collect the grain-scale data necessary for understanding the evolving processes that drive fatigue failure. In this study, we present a framework for monitoring the evolution...
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Published in: | International journal of fatigue 2022-11, Vol.164 (C), p.107113, Article 107113 |
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Main Authors: | , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Next-generation experimental techniques, like high energy X-ray diffraction microscopy (HEDM), usher in new opportunities to collect the grain-scale data necessary for understanding the evolving processes that drive fatigue failure. In this study, we present a framework for monitoring the evolution of a deforming polycrystal, in real-time, by applying principal component analysis (PCA) to raw X-ray diffraction image data. We applied this framework to inform in-situ HEDM measurements of a cyclically loaded Inconel-718 superalloy. We discovered correlations between PCA of the diffraction data and the physical processes in the polycrystal. Lastly, we discuss extending this framework in future HEDM fatigue studies.
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•Track grain evolution during cyclic loading with in-situ X-ray diffraction.•Novel framework analyzes real-time raw data using Principal Component Analysis.•Employ framework to infer grain evolution in real-time to inform measurements.•Present a case study of using framework to model behavior in future cycles. |
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ISSN: | 0142-1123 1879-3452 |
DOI: | 10.1016/j.ijfatigue.2022.107113 |