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Crack Identification and Characterization in Deformed Nb3Sn Rutherford Cable Stacks Using Machine Learning
An investigation of instance segmentation of cracks in Nb3Sn 4-stack 40-strand Rutherford cables using machine learning is presented. Three samples were uniaxially and biaxially loaded before metallographic inspections were performed. The Mask R-CNN model was used in the Detectron2 framework with pr
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