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Muon tomography applied to assessment of concrete structures: First experiments and simulations.
(2022)
Non-destructive techniques for reinforced or prestressed concrete inspection such as ultrasound or radar have found regular, successful practical application but sometimes suffer from limited resolution and
accuracy, imaging artefacts or restrictions in detecting certain features. Until the 1980s X-ray transmission was used in case of special demands and showed a much better resolution than other NDT techniques.
However, due to safety concerns and cost issues, this method is almost never used anymore. Muon tomography has received much attention recently. Novel detectors for cosmic muons and tomographic imaging algorithms have opened new fields of application. As a first step towards practical application in civil engineering and as a proof of concept we used an existing system to image the interior of a reference reinforced 600 kg concrete block. Even with a yet not optimized setup for this kind of investigation, the muon imaging results are at least of similar quality compared to ultrasonic and radar imaging, potentially even better. In a second step, we have performed simulations to assess the potential for a set of important testing problems such as grouting defects in tendon ducts. The next steps include the development of mobile detectors and optimizing acquisition and imaging parameters.
Muon tomography applied to assessment of concrete structures: First experiments and simulations.
(2022)
Non-destructive techniques for reinforced or prestressed concrete inspection such as ultrasound or radar have found regular, successful practical application but sometimes suffer from limited resolution and accuracy, imaging artefacts or restrictions in detecting certain features. Until the 1980s X-ray transmission was used in case of special demands and showed a much better resolution than other NDT techniques. However, due to safety concerns and cost issues, this method is almost never used anymore. Muon tomography has received much attention recently. Novel detectors for cosmic muons and tomographic imaging algorithms have opened new fields of application. As a first step towards practical application in civil engineering and as a proof of concept we used an existing system to image the interior of a reference reinforced 600 kg concrete block. Even with a yet not optimized setup for this kind of investigation, the muon imaging results are at least of similar quality compared to ultrasonic and radar imaging, potentially even better. In a second step, we have performed simulations to assess the potential for a set of important testing problems such as grouting defects in tendon ducts. The next steps include the development of mobile detectors and optimizing acquisition and imaging parameters.
Multifaceted developments for pre-disposal management of low and intermediate level radioactive waste are undertaken in the EC funded project PREDIS. In work package 7, innovations in cemented waste handling and pre-disposal storage are advanced by testing and evaluating. To provide better means for safe and effective monitoring of cemented waste packages including prediction tools to assess the future integrity development during pre-disposal activities, several monitoring and digital tools are evaluated and improved. Both safety enhancement (e. g. less exposure of testing personnel) and cost effectiveness are part of the intended impact. Current methods to pack, store, and monitor cemented wastes are identified, analysed and improved. Innovative integrity testing and monitoring techniques applied to evaluate and demonstrate package and storage quality assurance are further developed. The work includes but is not limited to inspection methods such as muon imaging, wireless sensors integrated into waste packages as well as external package and facility monitoring such as remote fiber optical sensors. The sensors applied will go beyond radiation monitoring and include proxy parameters important for long term integrity assessment (e. g. internal pressure). The measured data will be used in digital twins of the packages for specific simulations (geochemical, integrity) providing a prediction of future behaviour. Machine Learning techniques trained by the characterization of older packages will help to connect the models to the actual data. As data handling, processing and fusion are crucial for both the monitoring and the digital twin model, all data (measured and simulated) will be collected in a joint data base and connected to a decision framework. Finally, the implementation of the improved techniques will be tested at actual facilities. An overview about various relevant tools, their interconnections, and first research results will be shown.