Reinforced concrete structures are subjected to significant loads. These structures must endure the weight and vibrations from high-speed and freight trains, as well as the forces acting on high-rise buildings. Therefore, it is crucial to regularly inspect the entire structure and assess the condition of the building material.
Until now, monitoring has relied on complex material tests that are time-consuming, labor-intensive, and costly. For instance, inspectors often tap bridges by hand with hammers to check for cavities, which can require temporarily closing the bridges. Despite these regular tests, serious material failures, such as the collapse of the Carola Bridge in Dresden, cannot be completely ruled out.
This is why research into ultrasonic testing methods has been going on for a long time. The CoDA (Concrete Damage Assessment by Coda Waves) research group has now presented promising results for a new method: ultrasound-based, highly sensitive coda wave interferometry (CWI).
This method enables not only selective testing of structures but also continuous and comprehensive monitoring. As a result, critical changes to buildings can be detected early, allowing for timely measures to prevent closures or evacuations.
Measurements under real conditions
CWI is a method for monitoring and analyzing material changes, particularly suitable for concrete and prestressed concrete components. It uses ultrasonic waves to detect very small changes in the material structure. This technique is particularly useful for detecting stress states and potential damage at an early stage.
The CoDA research group (DFG FOR 2825), consisting of researchers from the Technical University of Munich (TUM), the Bundesanstalt fΓΌr Materialforschung und -prΓΌfung (BAM), Ruhr-UniversitΓ€t Bochum (RUB) and Bochum University of Applied Sciences (BO), is now testing the application of CWI for monitoring reinforced concrete structures in long-term tests on two structures.
Since 2021, the researchers have been using ultrasonic sensors to assess the condition of the GΓ€nstor Bridge, which spans 96 meters between Ulm and Neu-Ulm. In 2022, measurements also commenced at the Scheidplatz subway station in Munich, where the sensors monitor the load on the ceiling caused by the streetcar traffic above.
The collaborative efforts and findings from the ongoing research on the GΓ€nstor Bridge were presented at the International Conference on Bridges in Danube Basin (ICBDB 2024) on 21 November at TUM.
Computer-aided models interpret sensor signals
The tubular sensors, measuring just 75 millimeters in length and 20 millimeters in diameter, are permanently installed in boreholes or directly within structures during production. They continuously provide data on the current load and any age-related changes in the material. However, the signals from the ultrasonic sensors do not immediately reveal the extent or exact location of any damage. They must undergo a process of translation and interpretation.
When combined with machine learning, ultrasound data can be interpreted to reveal changes in the physical properties of materials, such as stiffness, across different scales. Not only can these methods determine the extent of damage, but they can also identify its location. The data collected from the sensors is transmitted to a server, enabling remote monitoring of the structure. This advancement allows for centralized monitoring of multiple structures in the future.
‘Permanent monitoring with minimal intrusion’
The spokesperson for the CoDA project, Christoph Gehlen, Professor of Materials and Materials Testing in Civil Engineering at TUM, says, “The results of our years of testing under real conditions are clear: We have succeeded in refining the CWI measurement method to such an extent that we can use our sensors and complex evaluation models to monitor even large buildings in the future with minimal intrusion in the structure.
“The decisive factor here is our systematic and holistic approachβwhich takes into account everything from external influences such as temperature and humidity to a variety of different factors for evaluating the signals.”
Provided by
Technical University Munich
