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Research and Development of New Molten Salt Technologies for Heat Storage and Transfer Applications
No full textEnergy thickness in turbulent boundary layer flows
No full textIn this study, we investigate the properties of energy thickness δ3 in turbulent boundary layer (TBL) flows, a parameter derived solely from the mean streamwise velocity (U) profile. Through an analysis of the energy integral equation for zero pressure gradient TBLs, we establish a close relationship between turbulent kinetic energy (TKE) production and δ3, offering a practical method to estimate TKE production, which is particularly useful in physical experiments where direct measurements are challenging. The significance of δ3 becomes even more pronounced in TBLs under pressure gradient. Through extensive analysis of numerical and experimental data, we show that the ratio between δ3 and the momentum thickness δ2 is a promising criterion for predicting flow separation. Moreover, we derive a new energy integral equation for TBLs under arbitrary pressure gradients, and provide approximations for TKE productions terms by Ruv ∂U/∂y and Ruu ∂U/∂x, and dissipation term by the mean shear. Here, x, y represent the streamwise and wall-normal directions, respectively, and Ruu and Ruv are the Reynolds normal and shear stresses. The accuracy and robustness of the new energy integral equation and the approximation equations are validated using direct numerical simulations data. Our results show that the TKE production by Ruv ∂U/∂y and the overall productions consistently remain positive, reflecting a continuous conversion of mean kinetic energy into TKE across all TBLs. However, under strong favourable pressure gradients, TKE production by Ruu ∂U/∂x becomes negative, indicating a reverse energy transfer from TKE to mean kinetic energy
Towards Autonomous Data Annotation and System-Agnostic Robotic Grasping Benchmarking with 3D-Printed Fixtures
Get PDFThe interaction of robots with their environment requires robust object-centric perception capabilities, typically achieved using learning-based methods trained on synthetic data. However, real-world deployment demands evaluating these capabilities in relevant environments, often involving extensive manual annotation for a quantitative analysis. Additionally, standardized evaluations for robotic tasks, such as grasping, need reproducible object scene configurations and performance benchmarks. We propose a solution to both problems by temporarily employing 3D-printed components, so-called fixtures, which can be designed for any rigid object. Once the scene is set up and object poses are extracted, the fixtures are removed, leaving the natural scene without any artificial distractions. The presented approach is seemingly applicable for pre-determined configurations of multiple objects, which enables precise re-building of scenes with consistent object-to-object relations. Our suggested annotation procedure achieves strong pose accuracy solely on RGB images without any manual involvement. We evaluate and show the usability of the proposed fixtures for automated real-world data annotation to fine-tune a detector and for benchmarking object pose estimation algorithms for robotic grasping. Code and fixture meshes for 3D printing are available at https://github.com/DLR-RM/fixture generation
Man is not made for flying!? Flugmedizin und Luftverkehrssicherheit
No full textAusflug in die Höhenphysiologie, Klärung der Begriffe Luftdruck, Partialdruck, Gasgesetze, Hämoglobinbindungskurve, Sauerstoffmangel, Phänomen gefangener Gase, Dekompressionssymptome, praktische Anwendungen für Internisten und Hausärzte
Low-power microstructured atomic oven for alkaline-earth-like elements
No full textThe development of miniaturized atomic ovens for quantum sensors is a key advancement in compact optical clocks for portable and space applications. Our novel oven for alkaline-earth-like elements, made from microstructured fused silica, offers low power consumption and sufficient reservoir lifetime. It demonstrates high efficiency atom evaporation below 0.3 W of heating power and achieves loading rates in a magneto-optical trap (MOT) of up to 10^9 atoms/s. The compact design eliminates the need for large deceleration devices and can be integrated into quantum systems with stringent size, weight, and power (SWaP) requirements. Our innovation is critical for advancing quantum technologies in precision metrology to space-based platforms
MMX-Rover: A small Rover for big firsts
Get PDFMMX (Martian Moons eXploration) is a JAXA mission which aims to study the two moons of Mars, Phobos and Deimos. In addition to extensive in-situ scientific observation, the MMX probe is equipped to bring samples back from Phobos to Earth, and to deploy the CNES/DLR rover IDEFIX, onto its surface. IDEFIX mission is to investigate the Phobos surface properties, to secure the landing of the MMX probe itself and for scientific purposes. Another mission objective is to test some technological concepts, such as the use of CubeSat technology in the context of space exploration, the way to move in low gravity, and auto-navigation. To fulfil its mission, IDEFIX brings four scientific instruments: miniRad (Radiometer), RAX (Raman spectrometer), a pair of (stereo) navigation cameras, and two wheelcameras. IDEFIX will be operated by two remote control centers, one in France and one in Germany, in close cooperation with the JAXA MMX ground segment. The MMX mission will be launched in autumn 2026, and the landing of IDEFIX is presently scheduled for end of 2028/beginning 2029, after a first Phobos observation campaign by MMX probe and the selection of a landing site. IDEFIX operations on Phobos surface shall last at least 100 days. IDEFIX mission will be the occasion of several firsts:
- First landing on Phobos,
- First French and German rover,
- First rover aiming at driving, and experimenting auto-navigation, on a low gravity body,
- First dynamic analyzes of regolith at low gravity, thanks to its interaction with the wheels.
This paper will introduce the MMX rover mission objectives, the rover design, overall system composition and mission profile, with the outlines and principal constraints of the three main mission phases (Cruise, Landing, and Phobos Exploration). It will provide as well an overview of the mission calendar and main milestones
Leveraging a Discrete-Time-Crystal to Solve Classification Problems with a Quantum Extreme Learning Machine
Get PDFThis thesis explores the field of Quantum Extreme Learning Machines based on manybody localized discrete time crystals. This approach holds two advantages: Leveraging
an exponentially large Hilbert states while not relying on error-corrected quantum gates.
Firstly, the concept of discrete time crystals and the theoretical framework behind QELMs
are presented. After some introductory results to test the potentials and limitations of
unitary evolution, the method’s phase dependency is discussed to observe the melting of
the discrete time crystal also in the classification accuracies. The remainder of the thesis
can be split into two categories: Investigating effects on the classification accuracies when
changing the quantum layer and an investigation of amendments in the readout layer.
Both parts contain a comparison for thermal and discrete time crystal phase as well as
reasonable comparisons with classical results. In the readout layer analysis new readout
methods are presented that hold the potential of increasing the classification accuracies
based on random shuffling. The work concludes with a combination of all methods and an
evaluation of their combined performance. Overall, the thesis provides a comprehensive
overview of the exciting field of Quantum Extreme Learning Machines, offering new insights
as well as new pathways for further advancements in the field
A cloud-based framework for the quantification of the spatially-explicit uncertainty of remotely sensed benthic habitats
Get PDFStrategische Neuausrichtung von Wheels Up: Eine Optimierungsempfehlung basierend auf den Erfolgsfaktoren führender Wettbewerber
No full textDie Business Aviation profilierte sich in den vergangenen Jahren – nicht zuletzt durch die Auswirkungen der COVID-19-Pandemie – als wachstumsstarker Bereich der Luftfahrt. Gestiegene Anforderungen an Flexibilität, Individualisierung und Sicherheit eröffneten der privaten Luftfahrt neue Marktchancen. Auch künftig sind die Marktaussichten trotz globaler Unsicherheiten positiv.
Vor diesem Hintergrund steht Wheels Up, eines der führenden Unternehmen dieser Branche, im Fokus dieses Beratungsberichtes. Trotz starker Marktposition und innovativer Angebotsmodelle
sieht sich Wheels Up mit wachsenden wirtschaftlichen Herausforderungen konfrontiert. Ziel der vorliegenden Analyse ist es daher, fundierte Handlungsempfehlungen für eine strategische Neuausrichtung zu entwickeln. Im Zentrum steht die Frage, wie das bestehende Geschäftsmodell weiterentwickelt werden kann, um langfristig wettbewerbsfähig zu bleiben. Auf Basis einer systematischen Analyse des Marktumfelds sowie eines strukturierten internen Wettbewerbsvergleichs werden zentrale Handlungsfelder identifiziert. Die Ergebnisse zeigen signifikante Defizite in strategisch relevanten Bereichen – von der operativen Effizienz über Kundenbindung und Servicequalität bis hin zur wirtschaftlichen Resilienz. Diese Handlungsfelder sind eng miteinander verknüpft und erfordern ein konsistentes, übergeordnetes strategisches Gesamtkonzept. Die strategische Analyse bildet hierfür die Grundlage. Im nächsten Schritt gilt es, diese Optimierungsempfehlungen systematisch weiter zu priorisieren, zu vertiefen und in konkrete Maßnahmen zu überführen