@article{JungNowackaBarisinetal., author = {Jung, Christian and Nowacka, Anna and Barisin, Tin and Meinel, Dietmar and Paetsch, Olaf and Grzesiak, Szymon and Salamon, Michael and Schladitz, Katja and Redenbach, Claudia and Pahn, Matthias}, title = {3d imaging and analysis of cracks in loaded concrete samples. 12th Conference on Industrial Computed Tomography (iCT) 2023, 27 February - 2 March 2023 in F{\"u}rth, Germany}, series = {e-Journal of Nondestructive Testing}, volume = {28}, journal = {e-Journal of Nondestructive Testing}, number = {3}, doi = {10.58286/27721}, abstract = {Concrete plays a central role as the standard building material in civil engineering. Experimental characterization of the concrete microstructure and a description of failure mechanisms are important to understand the concrete's mechanical properties. Computed tomography is a powerful source of information as it yields 3d images of concrete specimens. However, complete visual inspection is often infeasible due to very large image sizes. Hence, automatic methods for crack detection and segmentation are needed. A region-growing algorithm and a 3d U-Net showed promising results in a previous study. Cracks in normal concrete and high-performance concrete that were initiated via tensile tests were investigated. Here, the methods are validated on a more diverse set of concrete types and crack characteristics. Adequate adaptions of the methods are necessary to deal with the complex crack structures. The segmentation results are assessed qualitatively and compared to those of a template matching algorithm which is well-established in industry.}, language = {en} }