This publication presents a digital image correlation (DIC) based technique applied to a shear test on a carbon-reinforced concrete member. DIC methods are based on image sequences where the first image is recorded under zero-load without deformations while further images are taken from deformed stages. The image processing starts with the computation of subpixel-precise displacement vector fields using photogrammetric image matching algorithms. In our method, instead of computing strains, another approach is used to quantify deformations and to detect cracks. The matching points are triangulated into a triangular mesh. Then, a deformation model is used that includes a split of the triangle into two parts. The relative translation between these parts is computed and is considered as deformation vector. The detection of cracks is performed by a thresholding applied to the norm of the deformation vectors. Furthermore, the deformation vector is decomposed into the components parallel and perpendicular to the crack. The decomposition requires the knowledge of the crack normal, for which a possible estimation scheme is proposed. The presented method is suitable for brittle material, and it was applied to a monocular image sequence of a shear test of a carbon reinforced concrete member. The test specimen was made of high-strength concrete and was reinforced with a multilayer carbon reinforcement. The selected shear test was intended to analyze the shear behavior of a multi-span system with a distributed load.
|Building for the Future
|Alper Ilki, Derya Çavunt, Yavuz Selim Çavunt
|Springer Science and Business Media B.V.
|Veröffentlicht - 2023
|Lecture notes in civil engineering
|fib Symposium 2023
|Building for the Future: Durable, Sustainable, Resilient
|5 - 7 Juni 2023
|Istanbul Technical University Süleyman Demirel Cultural Center
ASJC Scopus Sachgebiete
- Carbon reinforced concrete (CRC), Crack detection, Deformation measurement, Digital Image Correlation (DIC), Image Sequence Analysis, Shear test