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Data-driven analysis for damage assessment has a large potential in structural health monitoring (SHM) systems, where sensors are permanently attached to the structure, enabling continuous and frequent measurements. In this contribution, we propose a machine learning (ML) approach for automated damage detection, based on an ML toolbox for industrial condition monitoring. The toolbox combines multiple complementary algorithms for feature extraction and selection and automatically chooses the best combination of methods for the dataset at hand. Here, this toolbox is applied to a guided wave-based SHM dataset for varying temperatures and damage locations, which is freely available on the Open Guided Waves platform. A classification rate of 96.2% is achieved, demonstrating reliable and automated damage detection. Moreover, the ability of the ML model to identify a damaged structure at untrained damage locations and temperatures is demonstrated.
Ultrasonic testing is a widely applied measurement method in materials research and medicine. Commonly, a transducer is coupled to the specimen directly or via a liquid coupling agent. While reducing acoustic transmission losses significantly, this procedure is time-consuming and cannot be used for sensitive specimens. Air-coupled ultrasound is a viable alternative in such cases, although suffering from very high acoustic transmission losses between transducer, air and specimen. The recently introduced fluidic transducer (FT) generates ultrasound by utilizing the instability of a supersonic air jet switched inside a fluidic amplifier. Since only air is used as the working medium and no vibrating surfaces are used for ultrasound generation, the transducer is able to efficiently generate large acoustic pressure amplitudes. The resulting acoustic field shares its directivity with the ejected high-velocity air jet. Thus, the acoustic energy needs to be redirected from the jet axis in order to make the fluidic transducer applicable to sensitive specimens. In this study, the effectivity of using sonic crystals (SCs) for this redirection is investigated using acoustic and flow measurements. SCs are air-permeable while being reflective to large acoustic frequency bands. It was shown that both a defect waveguide and a mirroring strategy successfully redirected the acoustic field from the air jet. Furthermore, the interaction of flow and SC showed strong acoustic quenching if the SC was placed too close to the FT outlet. Blockage of the jet entrainment due to the SC may result in slightly higher off-axis flow velocities locally, which should be considered in sensitive applications.
"The reassessment of bridges continues to take great importance both nationally and internationally. A major challenge is to find computation models reflecting the actual properties of the considered structures sufficiently accurate. Besides regular inspections, the conduction of advanced measurements is suitable to generate reliable information about a structure to be assessed. Prior to incorporating measurement results in reassessment, the relevance, the trueness, and the precision of the measured information needs to be stated. On the one hand, the use of information whose quality has not been assessed can lead to errors with serious consequences. On the other, the measurement of irrelevant information is inefficient. Although the use of measured data in assessment is currently mostly unregulated, their appreciation in reliability analyses is beneficial since the built environment can be assessed more realistically. Utilizing NDT in reassessment has the potential to extend remaining lifetimes of a structure, save resources, and improve infrastructural availabilities. The power of judgment regarding the decision on the reliability of an existing structure can be increased.
In this contribution, an approach is outlined to process non-destructively gathered measurement data in a comparableway in order to include themeasured information in probabilistic reliability assessments of existing structures. An essential part is the calculation of measurement uncertainties. The effect of incorporating evaluated NDT-results is demonstrated by means of a prestressed concrete bridge and GPR measurements conducted on this bridge as a case-study. The bridge is assessed regarding SLS Decompression using the NDT-results."
Corrosion of concrete reinforcement is one of the major damage mechanisms affecting both the load-bearing capacity and the serviceability of re-inforced concrete structures significantly. When externally discernible damages are observed during visual inspections on the structure, the extent of the damage inside the concrete is often already significant. Corrosion caused by carbonation often leads to severe discoloration of the surface or even large-area spalling of the concrete cover. In contrast, chloride-induced corrosion is usually difficult to observe visually but can cause much more serious damage in less time. The effect occurs locally and can lead to weakening of the cross-section of the reinforce-ment. This, in turn, can cause sudden structural collapses without prior notice.
In the meanwhile, various non-destructive and minimally invasive testing methods are available to evaluate the resistance to penetration of corrosion-pro-moting pollutants and to detect active corrosion. In this paper, a bridge crossing the river Regen is used as a case-study to demonstrate how the information ob-tained applying different testing methods can be combined and evaluated in the context of structural reassessments. Both the results of the permeability testing and the electrical resistance measurement are considered, as well as active corro-sion areas are localized using the half-cell potential mapping combined with the concrete cover measurement with the eddy current method and ground penetrat-ing radar. The results are evaluated using drill cores and in addition laser-induced breakdown spectroscopy was applied to obtain information about possible chlo-ride ion transport into the concrete.
Given the central role of fatty acids in cancer pathophysiology, the exploitation of fatty acid metabolism as a potential antineoplastic therapy has gained much attention. Several natural and synthetic compounds targeting fatty acid metabolism were hitherto identified, and their effectiveness against cancer cell proliferation and survival was determined. This review will discuss the most clinically viable inhibitors or drugs targeting various proteins or enzymes mapped on nine interconnected fatty acid metabolism-related processes. We will discuss the general significance of each of these processes and the effects of their inhibition on cancer cell progression. Moreover, their mechanisms of action, limitations, and future perspectives will be assessed.
Air-coupled ultrasonic (ACU) testing has proven to be a valuable method for increasing the speed in non-destructive ultrasonic testing and the investigation of sensitive specimens. A major obstacle to implementing ACU methods is the significant signal power loss at the air–specimen and transducer–air interfaces. The loss between transducer and air can be eliminated by using recently developed fluidic transducers. These transducers use pressurized air and a natural flow instability to generate high sound power signals. Due to this self-excited flow instability, the individual pulses are dissimilar in length, amplitude, and phase. These amplitude and angle modulated pulses offer the great opportunity to further increase the signal-to-noise ratio with pulse compression methods.
In practice, multi-input multi-output (MIMO) setups reduce the time required to scan the specimen surface, but demand high pulse discriminability. By applying envelope removal techniques to the individual pulses, the pulse discriminability is increased allowing only the remaining phase information to be targeted for analysis. Finally, semi-synthetic experiments are presented to verify the applicability of the envelope removal method and highlight the suitability of the fluidic transducer for MIMO setups.