Macroscale fracture surface segmentation via semi-supervised learning considering the structural similarity

arXiv:2403.18337v1 Announce Type: new
Abstract: To this date the safety assessment of materials, used for example in the nuclear power sector, commonly relies on a fracture mechanical analysis utilizing macroscopic concepts, where a global load quantity K or J is compared to the materials fracture toughness curve. Part of the experimental effort involved in these concepts is dedicated to the quantitative analysis of fracture surfaces. Within the scope of this study a methodology for the semi-supervised training of deep learning …

abstract analysis arxiv assessment concepts cs.lg example global materials nuclear nuclear power part power safety sector segmentation semi-supervised semi-supervised learning supervised learning surface type via