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Paper des Monats
- ja (11)
Distributed acoustic sensing (DAS) over tens of kilometers of fiber optic cables is well-suited for monitoring extended railway infrastructures. As DAS produces large, noisy datasets, it is important to optimize algorithms for precise tracking of train position, speed, and the number of train cars, The purpose of this study is to compare different data analysis strategies and the resulting parameter uncertainties. We present data of an ICE 4 train of the Deutsche Bahn AG, which was recorded with a commercial DAS system. We localize the train signal in the data either along the temporal or spatial direction, and a similar velocity standard deviation of less than 5 km/h for a train moving at 160 km/h is found for both analysis methods, The data can be further enhanced by peak finding as well as faster and more flexible neural network algorithms. Then, individual noise peaks due to bogie clusters become visible and individual train cars can be counted. From the time between bogie signals, the velocity can also be determined with a lower standard deviation of 0.8 km/h, The analysis methods presented here will help to establish routines for near real-time Train tracking and train integrity analysis.
Effects of laser-induced periodic surface structures on the superconducting properties of Niobium
(2020)
It is well known that the use of ultrashort (fs) pulsed lasers can induce the generation of (quasi-) periodic nanostructures (LIPSS, ripples) on the surface of many materials. Such nanostructures have also been observed in sample’s surfaces irradiated with UV lasers with a pulse duration of 300 ps. In this work, we compare the characteristics of these nanostructures on 1-mm and on 25-μm thick niobium sheets induced by 30 fs n-IR and 300 ps UV pulsed lasers. In addition to conventional continuous or burst mode processing configurations, two-dimensional laser beam and line scanning modes have been investigated in this work. The latter allows the processing of large areas with a more uniform distribution of nanostructures at the surface. The influence of the generated nanostructures on the superconducting properties of niobium has also been explored. For this aim, magnetic hysteresis loops have been measured at different cryogenic temperatures to analyse how these laser treatments affect the flux pinning behaviour and, in consequence, the superconductor’s critical current values. It was observed that laser treatments are able to modify the superconducting properties of niobium samples.
Laser-induced periodic surface structures (LIPSS) are often present when processing solid targets with linearly polarized ultrashort laser pulses. The different irradiation parameters to produce them on metals, semiconductors and dielectrics have been studied extensively, identifying suitable regimes to tailor its properties for applications in the fields of optics, medicine, fluidics and tribology, to name a few. One important parameter widely present when exposing the samples to the high intensities provided by these laser pulses in air environment, that generally is not considered, is the formation of a superficial laser-induced oxide layer. In this paper, we fabricate LIPSS on a layer of the oxidation prone hard-coating material chromium nitride in order to investigate the impact of the laser-induced oxide layer on its formation. A variety of complementary surface analytic techniques were employed, revealing morphological, chemical and structural characteristics of well-known high-spatial frequency LIPSS (HSFL) together with a new type of low-spatial frequency LIPSS (LSFL) with an anomalous orientation parallel to the laser polarization. Based on this input, we performed finite-difference time-domain calculations considering a layered system resembling the geometry of the HSFL along with the presence of a laser-induced oxide layer. The simulations support a scenario that the new type of LSFL is formed at the interface between the laser-induced oxide layer and the non-altered material underneath. These findings suggest that LSFL structures parallel to the polarization can be easily induced in materials that are prone to oxidation.
Among additive manufacturing (AM) technologies, the laser powder bed fusion (L-PBF) is one of the most important technologies to produce metallic components. The layer-wise build-up of components and the complex process conditions increase the probability of the occurrence of defects. However, due to the iterative nature of its manufacturing process and in contrast to conventional manufacturing technologies such as casting, L-PBF offers unique opportunities for in-situ monitoring. In this study, two cameras were successfully tested simultaneously as a machine manufacturer independent process monitoring setup: a high-frequency infrared camera and a camera for long time exposure, working in the visible and infrared spectrum and equipped with a near infrared filter. An AISI 316L stainless steel specimen with integrated artificial defects has been monitored during the build. The acquired camera data was compared to data obtained by computed tomography. A promising and easy to use examination method for data analysis was developed and correlations between measured signals and defects were identified. Moreover, sources of possible data misinterpretation were specified. Lastly, attempts for automatic data analysis by data Integration are presented.
This article deals with the relevance and practical feasibility of micromechanical simulations for their application to general geomechanical problems involving fluid-saturated granular assemblies, whether frictional or cohesive. A set of conceptual and numerical tools is here presented, advocating for a parallel computation using graphical processing units (GPUs) to treat large numbers of degrees of freedom with conventional Desktop computers. The fluid phase is here simulated with a particle-resolved approach in the frame of the Lattice Botzmann Method (LBM) while the granular solid phase is modelled as a collection of discrete particles from a Molecular Dynamics DEM perspective. The range of possible material behaviours for the solid granular phase is intended here to cover a broad spectrum from purely frictional to viscous cohesive materials with either brittle or transient debonding features. Specific details of the implementation and some validation cases are put forward.
Finally, some exemplary applications in the fields of soil erosion and geotechnical profile installation are provided along with a discussion on the parallel performance of the presented models. The results show that a micromechanical approach can be feasible and useful in practice, providing meaningful insights into complex engineering problems like the erosion kinetics of a soil under an impinging jet or the penetration resistance of a deep foundation in a layered soil profile.
Increasing traffic volume on the one hand and ageing infrastructure on the other hand have created many new challenges for maintenance and structural health monitoring of roads and bridges. In the past, many bridges and road structures have been neglected, often resulting in traffic congestion, road closure, and increased repair costs.
This research is concerned with the development of a system to improve the challenge of maintenance and early detection of damage, particularly moisture penetration and corrosion of steel reinforced concrete components. The objective is to develop a method that will also work after 30 years and longer. Many new IoT solutions are equipped with internal energy storage elements (accumulators or batteries) which are inappropriate here, since most relevant signs of concrete degradation occur after decades, where the functioning of such elements are more than questionable. The presented technology approach uses radio-frequency identification (RFID) and enables connectivity to sensors. It offers the advantage of an passive, completely independent energy supply without any energy storage components.
Since the system should be permanently embedded in concrete, it is crucial to develop a long-term stable device which is adapted to the environmental influences of the structure, e.g., long-term resistance in very alkaline environment of pH 13. In numerous experiments, the robustness of the system was tested and evaluated. Various tests with encapsulations to protect the electronics were performed, and for long-term validation different concrete specimens were instrumented with RFID-sensor-systems. Their operating time is now around two years and investigations for signs of fatigue and damage to the encapsulation and the electronics are ongoing.
The Lycurgus cup is an ancient glass artefact that shows dichroism as it looks green when a white light is reflected on it and a red colouring appears when a white light is transmitted through it. This peculiar dichroic effect is due to silver and gold nanoparticles present in the glass. In this research we show the synthesis of dichroic silver nanoparticles and their embedding in a 3D printable nanocomposite. The addition of gold nanoparticles to the silver nanoparticle composite, gave a 3D printable nanocomposite with the same dichroism effect of the Lycurgus cup.
Almost 500 municipal solid waste incineration plants in the EU, Norway and Switzerland generate about 17.6 Mt/a of incinerator bottom ash (IBA). IBA contains minerals and metals. Metals are mostly separated and sold to the scrap market and minerals are either disposed of in landfills or utilised in the construction sector. Since there is no uniform regulation for IBA utilisation at EU level, countries developed own rules with varying requirements for utilisation. As a result from a cooperation network between European experts an up-to-date overview of documents regulating IBA utilisation is presented. Furthermore, this work highlights the different requirements that have to be considered. Overall, 51 different parameters for the total content and 36 different parameters for the emission by leaching are defined. An analysis of the defined parameter reveals that leaching parameters are significantly more to be considered compared to total content parameters. In order to assess the leaching behaviour nine different leaching tests, including batch tests, up-flow percolation tests and one diffusion test (monolithic materials) are in place.
A further discussion of leaching parameters showed that certain countries took over limit values initially defined for landfills for inert waste and adopted them for IBA utilisation. The overall utilisation rate of IBA in construction works is approximately 54 wt%. It is revealed that the rate of utilisation does not necessarily depend on how well regulated IBA utilisation is, but rather seems to be a result of political commitment for IBA recycling and economically interesting circumstances.
Machine learning based multi-sensor fusion for the nondestructive testing of corrosion in concrete
(2020)
Half-cell potential mapping (HP) is the most popular non-destructive testing method (NDT) for locating corrosion damage in concrete. It is generally accepted that HP is susceptible to environmental factors caused by salt-related deterioration, such as different moisture and chloride gradients. Additional NDT methods are able to identify distinctive areas but are not yet used to estimate more accurate test results. We present a Supervised Machine Learning (SML) based approach to data fusion of seven different signal features to obtain higher quality information. SMLs are methods that explore (or learn) relationships between different (sensor) data from predefined data labels. To obtain a representative, labelled data set we conducted a comprehensive experiment simulating the deterioration cycle of a chloride exposed device in the laboratory. Our data set consists of 18 measurement campaigns, each containing HP, Ground Penetrating- Radar, Microwave Moisture and Wenner resistivity data. We compare the performance of different ML approaches. Many outperform the best single method, HP. We describe the intrinsic challenges posed by a data-driven approach in NDT and show how future work can help overcome them.
The ISO 16000 standard series provide guidelines for emission measurements of volatile organic compounds (VOCs) from building materials. However, polymer-based consumer products such as toys may also release harmful substances into indoor air. In such cases, the existing standard procedures are unsuitable for official control laboratories due to high costs for large emission testing chambers. This paper aims at developing and comparing alternative and more competitive methods for the emission testing of consumer products. The influence of the emission chamber size was investigated as smaller chambers are more suited to the common size of consumer products and may help to reduce the costs of testing. Comparison of the performance of a 203 l emission test chamber with two smaller chambers with the capacity of 24 l and 44 ml, respectively, was carried out by using a polyurethane reference material spiked with 14 VOCs during the course of 28 days. The area-specific emission rates obtained in the small chambers were always similar to those of the 203 l reference chamber after a few hours. This implies that smaller chambers can provide at least useful numbers on the extent of polymer-based consumer product emissions into indoor air, thereby supporting meaningful exposure assessments.