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Bonding of polymer-based microfluidics to polymer substrates still poses a challenge for Lab-On-a-Chip applications. Especially, when sensing elements are incorporated, patterned deposition of adhesives with curing at ambient conditions is required. Here, we demonstrate a fabrication method for fully printed microfluidic systems with sensing elements using inkjet and stereolithographic 3D-printing.
Operational Modal Analysis (OMA) is a promising candidate for flutter testing and Structural Health Monitoring (SHM) of aircraft wings that are passively excited by wind loads. However, no studies have been published where OMA is tested in transonic flows, which is the dominant condition for large civil aircraft and is characterized by complex and unique aerodynamic phenomena. We use data from the HIRENASD large-scale wind tunnel experiment to automatically extract modal parameters from an ambiently excited wing operated in the transonic regime using two OMA methods: Stochastic Subspace Identification (SSI) and Frequency Domain Decomposition (FDD). The system response is evaluated based on accelerometer measurements. The excitation is investigated from surface pressure measurements. The forcing function is shown to be non-white, non-stationary and contaminated by narrow-banded transonic disturbances. All these properties violate fundamental OMA assumptions about the forcing function. Despite this, all physical modes in the investigated frequency range were successfully identified, and in addition transonic pressure waves were identified as physical modes as well. The SSI method showed superior identification capabilities for the investigated case. The investigation shows that complex transonic flows can interfere with OMA. This can make existing approaches for modal tracking unsuitable for their application to aircraft wings operated in the transonic flight regime. Approaches to separate the true physical modes from the transonic disturbances are discussed.
Ground or aerial robots equipped with advanced sensing technologies, such as three-dimensional laser scanners and advanced mapping algorithms, are deemed useful as a supporting technology for first responders. A great deal of excellent research in the field exists, but practical applications at real disaster sites are scarce. Many projects concentrate on equipping robots with advanced capabilities, such as autonomous exploration or object manipulation. In spite of this, realistic application areas for such robots are limited to teleoperated reconnaissance or search. In this paper, we investigate how well state-of-the-art and off-the-shelf components and algorithms are suited for reconnaissance in current disaster-relief scenarios. The basic idea is to make use of some of the most common sensors and deploy some widely used algorithms in a disaster situation, and to evaluate how well the components work for these scenarios. We acquired the sensor data from two field experiments, one from a disaster-relief operation in a motorway tunnel, and one from a mapping experiment in a partly closed down motorway tunnel. Based on these data, which we make publicly available, we evaluate state-of-the-art and off-the-shelf mapping approaches. In our analysis, we integrate opinions and replies from first responders as well as from some algorithm developers on the usefulness of the data and the limitations of the deployed approaches, respectively. We discuss the lessons we learned during the two missions. These lessons are interesting for the community working in similar areas of urban search and rescue, particularly reconnaissance and search.
Entwicklung eines Kletterroboters zur Diagnose und Instandsetzung von Windenergieanlagen (SMART)
(2016)
Im Jahr 2015 wurden in Deutschland über drei Millionen Benzinautos und lediglich 12.363 Elektroautos neu zugelassen. Das ursprünglich von der Bundesregierung vorgegebene Ziel, dass bis 2020 eine Million E-Autos auf deutschen Straßen fahren (und bis 2030 sechs Millionen), rückt damit in immer weitere Ferne. Um das Ziel dennoch zu erreichen, plant die Bundesregierung nun eine staatliche Prämie für den Kauf von Elektroautos: Umwelt-, Verkehrs- und Wirtschaftsministerium haben gemeinsam ein Konzept entworfen, dem zufolge private Käufer zukünftig einen Zuschuss von 5.000 Euro beim Erwerb eines Elektroautos bekommen sollen. 40 Prozent dieses Zuschusses soll von den Autoherstellern getragen werden. Das Programm, das weitere ausgabenwirksame öffentliche Maßnahmen vorsieht, würde Kosten in Milliardenhöhe verursachen. Die beabsichtigte Subventionierung wirft die Frage auf, ob diese wirtschaftlich sinnvoll sind.
A comparative performance analysis of the CFD platforms OpenFOAM and FLOW-3D is presented, focusing on a 3D swirling turbulent flow: a steady hydraulic jump at low Reynolds number. Turbulence is treated using RANS approach RNG k-ε. A Volume Of Fluid (VOF) method is used to track the air–water interface, consequently aeration is modeled using an Eulerian–Eulerian approach. Structured meshes of cubic elements are used to discretize the channel geometry. The numerical model accuracy is assessed comparing representative hydraulic jump variables (sequent depth ratio, roller length, mean velocity profiles, velocity decay or free surface profile) to experimental data. The model results are also compared to previous studies to broaden the result validation. Both codes reproduced the phenomenon under study concurring with experimental data, although special care must be taken when swirling flows occur. Both models can be used to reproduce the hydraulic performance of energy dissipation structures at low Reynolds numbers.
Visualization of the recovery process of defects in a cultured cell layer by chemical imaging sensor
(2016)
The chemical imaging sensor is a field-effect sensor which is able to visualize both the distribution of ions (in LAPS mode) and the distribution of impedance (in SPIM mode) in the sample. In this study, a novel cell assay is proposed, in which the chemical imaging sensor operated in SPIM mode is applied to monitor the recovery of defects in a cell layer brought into proximity of the sensing surface. A reduced impedance at a defect formed artificially in a cell layer was successfully visualized in a photocurrent image. The cell layer was cultured over two weeks, during which the temporal change of the photocurrent distribution corresponding to the recovery of the defect was observed.