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According to the NBI database, more than 21,000 in-service U.S. bridges lack sufficient structural documentation necessary for analytical load rating. Among these are a significant proportion of older prestressed concrete bridges. Given the lack of documentation on the reinforcing layout, such structures cannot be load rated analytically and are often subject to engineering judgement as the basis for rating. Otherwise, the typical approach for load rating such bridges is to conduct costly proof load testing and destructive probing together with making conservative assumptions. Therefore, any improvement to current practices will benefit DOTs and taxpayers alike. Accurately reconstructed 3D images of the girders to reflect the internal reinforcement could mitigate the need for costly, if not impractical, destructive testing and proof load testing, and help reduce dependency on conservative assumptions. This study examines a comprehensive NDE approach using ultrasonic tomography and GPR to aid in gathering structural information for load rating purposes. Different types of AASHTO and hollow core girders were tested.
Die B1 Brücke am Altstädter Bahnhof in Brandenburg an der Havel wurde im Dezember 2019 aufgrund von während einer turnusmäßigen Inspektion entdeckten Rissen und Hohlstellen entlang der vorgespannten Längsträger gesperrt und im Mai 2021 abgebrochen. In der Zwischenzeit wurde die Brücke detailliert überwacht. Vor dem Abriss wurden zudem umfangreiche Untersuchungen zur Bestandsaufnahme und Schadensanalyse sowie Tests moderner Sensorik vorgenommen. Dabei konnte sowohl die richtige, zuvor nicht sicher bekannte Anzahl von Spanngliedern in den Querträgern sicher ermittelt werden als auch durch moderne Varianten der Schwingungsmessungen und der faseroptischen Sensorik zusätzliche Kenntnisse püber das Bauwerksverhalten ermittelt werden . In dem Beitrag werden die Verfahren mit ihren Möglichkeiten und Grenzen vorgestellt, die Ergebnissee an der Brücke in Brandenburg erläutert und zukünftige Einsatzmöglichkeiten diskutiert.
Die B1 Brücke am Altstädter Bahnhof in Brandenburg an der Havel wurde im Dezember 2019 aufgrund von während einer turnusmäßigen Inspektion entdeckten Rissen und Hohlstellen entlang der vorgespannten Längsträger gesperrt und im Mai 2021 abgebrochen. In der Zwischenzeit wurde die Brücke detailliert überwacht. Vor dem Abriss wurden zudem umfangreiche Untersuchungen zur Bestandsaufnahme und Schadensanalyse sowie Tests moderner Sensorik vorgenommen. Dabei konnte sowohl die richtige, zuvor nicht sicher bekannte Anzahl von Spanngliedern in den Querträgern sicher ermittelt werden als auch durch moderne Varianten der Schwingungsmessungen und der faseroptischen Sensorik zusätzliche Kenntnisse püber das Bauwerksverhalten ermittelt werden . In dem Beitrag werden die Verfahren mit ihren Möglichkeiten und Grenzen vorgestellt, die Ergebnissee an der Brücke in Brandenburg erläutert und zukünftige Einsatzmöglichkeiten diskutiert.
Muon Tomography of the Interior of a Reinforced Concrete Block: First Experimental Proof of Concept
(2021)
Quality assurance and condition assessment of concrete structures is an important topic world-wide due to the aging infrastructure and increasing traffic demands. Common topics include, but are not limited to, localisation of rebar or tendon ducts, geometrical irregularities, cracks, voids, honeycombing or other flaws. Non-destructive techniques 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 up new fields of application, such as the investigation of freight containers. Muon imaging also has the potential to fill some of the gaps currently existing in concrete NDT. As a first step towards practical use 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. The data acquisition takes more time and signals contain more noise, but the images allowed to detect the same important features that are visible in conventional high energy X-ray tomography. In our experiment, we have shown that muon imaging has potential for concrete inspection. The next steps include the development of mobile detectors and optimising acquisition and imaging parameters.
News from NDT@BAM
(2021)
The presentation summarizes some recent research at BAM in the field of NDT in civil engineering. the firste xample decribes lab experiments on the degardation of concrete during tunnel fires. Radar measuremenst were sucessfully used to detect interior damage. The second example decribes the first ever experiment on using muon imaging to evaluate concrete constructions.
This paper reviews state-of-the-art in nondestructive testing (NDT) and semidestructive testing (SDT) methods applicable for imaging the condition of structural timber. Both NDT and SDT imaging reveal defects, damages, and decay, while the extent of wood decay can also be quantified. Combined with an appropriate data interpretation concerning the internal defects, the mechanical properties of the material can also be assessed. The possibilities and limitations of the most relevant individual NDT and SDT methods, also in combination with each other, are outlined and compared. To facilitate comparison, many observations are reported based on the same test specimen.
The capabilities of non-destructive testing (NDT) methods for defect detection in civil engineering are characterized by their different penetration depth, resolution and sensitivity to material properties. Therefore, in many cases multi-sensor NDT has to be performed, producing large data sets that require an efficient data evaluation framework. In this work an image fusion methodology is proposed based on unsupervised clustering methods. Their performance is evaluated on ground penetrating radar and infrared thermography data from laboratory concrete specimens with different simulated near-surface defects. It is shown that clustering could effectively partition the data for further feature level-based data fusion by improving the detectability of defects simulating delamination, voids and localized water. A comparison with supervised symbol level fusion shows that clustering-based fusion outperforms this, especially in situations with very limited knowledge about the material properties and depths of the defects. Additionally, clustering is successfully applied in a case study where a multi-sensor NDT data set was automatically collected by a self-navigating mobile robot system.
At BAM a multi-sensor robot system BetoScan is used for the investigation of reinforced concrete floors affected by corrosion in parking garages.
Potential maps, as well as the distribution of concrete cover and moisture can be assessed simultaneously and data can be collected contactlessly. In order to evaluate the extent of degradation adequately and to divide the investigated structure into zones with defined damage classes, large data sets have to be collected and interpreted manually. Thus, to promote an efficient data evaluation framework, which could speed up and simplify the evaluation of large data sets, an unsupervised data fusion is of major interest. However, taking into account that collected data do not certainly coincide in space, a scattered data interpolation method should be applied prior data fusion.
In the paper, a case study involving a BetoScan data set acquired from a reinforced concrete floor of a parking garage in Germany is presented. The data set includes potential mapping, covermeter based on eddy current, as well as microwave moisture measurements. Among the examined methods for interpolation of scattered data, kriging shows to yield smooth interpolated data plots even in the case of very sparse data. In the post-processing step, the investigated structure is efficiently segmented into zones using clustering based data fusion methods, which prove to be robust enough also for handling noisy data. Based on the minimization of the XB validity index, an unsupervised selection of optimal segmentation into damage classes is derived.
Ground penetrating radar (GPR) and infrared (IR) thermography techniques have been used in many civil engineering applications for the structural visualization and defect detection.
However, validation tests of the methods performance for the defection of defects in the nearsurface region with respect to the defects different material and depth below the surface are lacking. To overcome this, we performed GPR and IR thermography tests where the different material properties, shape and depth of defects were studied on concrete and the evaluation of seismic related damage propagation was assessed on stone masonry walls. The results showed that IR thermography, though being greatly affected by the presence of water in the specimen, outperformed GPR in the detection of defects very close to the surface. However, already at the depth of 3 cm and further up till almost 7.5 cm, the performance of GPR resembles the one of IR thermography for the detection of polystyrene (air) voids. On the plastered masonry walls, IR thermography could detect an air gap resulting from plaster delamination as small as 2 mm.
Moreover, structural cracking resulting from the induced lateral load could be detected at an early stage.