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Monitoring of structural performance of cracked reinforced concrete using DIC and CMfM
KTH, School of Architecture and the Built Environment (ABE), Civil and Architectural Engineering, Concrete Structures.ORCID iD: 0000-0001-8375-581X
Sapienza University of Rome. (Divison of Geoinformatics)ORCID iD: 0000-0003-4765-0281
KTH, School of Architecture and the Built Environment (ABE), Civil and Architectural Engineering, Concrete Structures.ORCID iD: 0000-0003-1096-2177
Statik och Form.ORCID iD: 0009-0004-6121-0965
2023 (English)Data set
Physical description [en]

Complete information on data collection and the dataset can be found in the paper: Experimental dataset to assess the structural performance of cracked reinforced concrete using Digital Image Correlation techniques with fixed and moving cameras published in Data in Brief.

https://doi.org/10.1016/j.dib.2023.109703

Abstract [en]

This dataset contains data from three-point bending test of uncracked and cracked reinforced concrete in a laboratory environment.First, uncracked beams were tested to a load level close to the maximum capacity. The cracks were thereafter mapped before the beams were tested until failure. During the second test, the crack propagation was monitored using four fixed cameras and one non-fixed camera. The data contains measured force and displacement from the test, imagery from the fixed and non-fixed cameras as well as documentation of initial cracks and structural testing of reinforcement. A full description of the dataset is provided in the paper "Experimental dataset to assess the structural performance of cracked reinforced concrete using Digital Image Correlation techniques with fixed and moving cameras" published in Data in Brief.

Place, publisher, year
Mendeley Data , 2023.
Version
4.0
Keywords [en]
Experimental testing, Reinforced concrete, Monitoring of cracks, DIC, CMfM, Data for assessment of concrete
National Category
Infrastructure Engineering
Research subject
Civil and Architectural Engineering, Concrete Structures; Geodesy and Geoinformatics, Geoinformatics
Identifiers
URN: urn:nbn:se:kth:diva-338760DOI: 10.17632/z3yc9z84tk.4OAI: oai:DiVA.org:kth-338760DiVA, id: diva2:1808876
Projects
TACK -Tunnel Automatic CracK Detection
Funder
EU, Horizon 2020, 101012456Vinnova, InfraSweden 2030
Note

QC 20240102

Available from: 2023-11-01 Created: 2023-11-01 Last updated: 2024-01-02

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Sjölander, AndreasPeterson, Viktor

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