06 Fakultät Luft- und Raumfahrttechnik und Geodäsie
Permanent URI for this collectionhttps://elib.uni-stuttgart.de/handle/11682/7
Browse
Search Results
Item Open Access Science planning for the DESTINY+ Dust Analyzer : leveraging the potential of a space exploration instrument(2024) Sommer, Maximilian; Srama, Ralf (Apl. Prof. Dr.-Ing.)The DESTINY+ Dust Analyzer (DDA) is a highly sophisticated planetary science instrument to provide cutting-edge in-situ characterization of individual cosmic dust grains, with respect to their composition, as well as their physical and dynamical properties. As such, it constitutes a critical component of the upcoming JAXA mission DESTINY+, which is scheduled to launch in 2025. After a three-year cruise phase, the spacecraft will perform a flyby of the target asteroid 3200 Phaethon, with the goal of observing the enigmatic Geminids parent body with two camera instruments, and sampling particles released from its surface with the DDA. Until that flyby, DESTINY+ will execute a highly diverse, ion-engine-driven flight plan that allows DDA to extensively study the dust environments of the Earth, Moon, and interplanetary space - a breadth of science opportunities that is unique to this mission and instrument. This dissertation provides a comprehensive study of the dust types and phenomena possibly encountered by DDA during its journey to Phaethon and applies the principles and methods of science planning to prepare for the operational phase of the mission. The work synthesizes technical considerations and scientific analyses of relevant cosmic dust populations, aiming to optimize DDA’s scientific potential. Detailed examinations of spacecraft and instrument factors, such as the dynamic spacecraft attitude during the near-Earth phase or the instrument’s two-axis pointing mechanism, lay the groundwork for the scientific planning. The thorough analysis of known (and lesser known) dust populations in the inner solar system and of previous relevant measurements by other dust instruments form the core of the study. Finally, the findings are consolidated into a draft science activity plan for the entire mission, as well as exemplary pointing timelines to be executed by the instrument for optimal scientific return. The latter is accomplished with the DOPE tool, which aids in intuitive and efficient planning of DDA observations, having been developed in the scope of this project. The presented work builds the foundation for the scientific operations of DDA, setting it up for a successful and scientifically impactful mission. The findings of this study also provide a valuable perspective for other ventures of in-situ dust astronomy to the inner solar system and contribute to the field of cosmic dust as a whole.Item Open Access Experiments on laminar separation bubbles under inflow conditions of atmospheric turbulence(2024) Greiner, Michael; Krämer, Ewald (Prof. Dr.-Ing.)Natural laminar flow (NLF) airfoils have been largely responsible for the performance advances of today's general aviation aircraft and wind turbines. In the design of these airfoils, atmospheric turbulence has received little attention, although specific atmospheric conditions are often present during their operation. One reason for this is that the effect of atmospheric turbulence on the boundary layer, and in particular on laminar separation bubbles (LSB), has only been possible to be estimated from experience. This study addresses this issue based on the example of sailplanes. In the first part of this work, the inflow conditions during typical cross-country flights of sailplanes are studied. Avoiding laminar separation bubbles at high lift coefficients is one of the challenges in the design of NLF airfoils. Therefore, the focus is on circling in thermals and thus on the convective boundary layer of the atmosphere. Continuous measurements of free-stream turbulent velocity fluctuations have been made during cross-country flights, with resolutions well into the dissipation range of the turbulence spectrum. The second part studies the effect of free-stream turbulence on mid-chord laminar separation bubbles that may appear on the upper surface of low speed NLF airfoils typically used in general aviation or wind turbines. For this purpose, the relevant conditions found in the first part were transferred to the Laminar Wind Tunnel (Re = 880,000, Tu = 0.01%-0.38%) for detailed experimental investigation. A distinction is made between small-scale turbulence, which acts via the classical vortex receptivity, and large-scale turbulence, which corresponds to inflow angle fluctuations and acts on the evolution of the boundary layer via the transient change in stability properties. The insights gained in flight permit the modelling of the free stream turbulence to be expected in flight through the convective atmosphere. The results of the wind tunnel experiments allow to better regard these turbulent conditions during the design of NLF airfoils.Item Open Access Forecasting next year's global land water storage using GRACE data(2024) Li, Fupeng; Kusche, Jürgen; Sneeuw, Nico; Siebert, Stefan; Gerdener, Helena; Wang, Zhengtao; Chao, Nengfang; Chen, Gang; Tian, KunjunExisting approaches for predicting total water storage (TWS) rely on land surface or hydrological models using meteorological forcing data. Yet, such models are more adept at predicting specific water compartments, such as soil moisture, rather than others, which consequently impedes accurately forecasting of TWS. Here we show that machine learning can be used to uncover relations between nonseasonal terms of Gravity Recovery and Climate Experiment (GRACE) derived total water storage and the preceding hydrometeorological drivers, and these relations can subsequently be used to predict water storage up to 12 months ahead, and even exceptional droughts on the basis of near real‐time observational forcing data. Validation by actual GRACE observations suggests that the method developed here has the capability to forecast trends in global land water storage for the following year. If applied in early warning systems, these predictions would better inform decision‐makers to improve current drought and water resource management.