3d imaging and analysis of cracks in loaded concrete samples

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.

Riesz Networks: Scale-Invariant Neural Networks in a Single Forward Pass

“…We decided to keep the sampling scheme as similar as possible to the one from U-net. The reason is that U-net with downscaling was more extensively tested on the crack segmentation task [8,45]. As for the U-net, we test several configurations, now specified by the number N of consecutive σ values used, starting at the smallest (1.5).…”

“…Figure 18 shows a sample of high-performance concrete (HPC) with polypropylene fibers as reinforcement. See [45] for more details on sample and crack initiation. In this image, fibers are long and appear dark and hence interfere with the crack in the center.…”

Investigation of the Crack Behavior of CRC Using 4D Computed Tomography, Photogrammetry, and Fiber Optic Sensing

“…Three-dimensional data sets can be obtained by using computed tomography (CT). This measurement technique distinguishes itself from the previously mentioned methods as it provides spatially resolved information about the internal structure [27] and enables a full 3D characterization of the crack geometry [28][29][30]. Over the last few decades, CT has become an increasingly relevant tool in the construction industry, especially for composite materials, yielding studies that were previously unimaginable by generating high quality 3D representations of the internal structure of the material, as covered in comprehensive reviews by Brisard et al [31], Vicente et al [32], and du Plessis and Boshoff [33].…”