06 Fakultät Luft- und Raumfahrttechnik und Geodäsie

Permanent URI for this collectionhttps://elib.uni-stuttgart.de/handle/11682/7

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Publication Type: search.filters.UBSTyp.Abschlussarbeit (Bachelor)Start date: 2023

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Now showing 1 - 6 of 6
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    Water level monitoring at SAPOS stations through GNSS-IR : a case study at the station Iffezheim
    (2023) Wagner, Sven B.
    The German SAPOS-Network comprises approximately 270 permanent GNSS receivers, capturing signals from Global Navigation Satellite Systems such as GPS, GLONASS, Galileo, and BeiDou. Primarily employed for generating kinematic, mathematical, and physical models within their respective regions, these receivers hold untapped potential for alternative applications. GNSS receivers capture multipath errors, typically considered unwanted interferences resulting from signal reflections off surfaces beneath the antenna. Despite their potential to adversely affect data precision, these interferences contain valuable information about the reflecting surface. As satellites pass through the receivers’ field of view at specific elevation angles, the interference between the direct and reflected signals leads to constructive and destructive patterns. This phenomenon occurs due to variations in signal phase between the direct and reflected signal, enhancing or dampening the signal strength. These variations in signal strength are captured in the satellites Signal-to-Noise Ratio (SNR) data. Spectral analysis of the SNR data can be used to determine the frequency of the interference pattern. Combining this frequency with the corresponding signal wavelength and satellite elevation angles allows the calculation of the vertical distance between the antenna phase centre and the reflecting surface on Earth. This method, known as GNSS Interferometric Reflectometry (GNSS-IR), provides a valuable means of monitoring surface information, including soil moisture, snow depth, and water levels. At SAPOS stations near rivers and water bodies, GNSS-IR offers a cost-effective, accessible, and innovative opportunity to gather water level information using the already existing infrastructure. This research explores the potential of GNSSIR for water level monitoring at SAPOS stations focusing on the Iffezheim station along the Rhine River near the City of Karlsruhe in southern Germany.
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    Create an automated structured mesh generation method for rotor blades using exclusively open source software
    (2023) Heider, Michael Andreas
    The generation of high-quality CFD meshed wings for wind energy turbines currently requires either a very laborious process of building each wing by hand or requires the purchase of very expensive software. With university budgets and the advantages of open-source in mind, an open-source solution is desirable. The following thesis tackles this problem via a grid generation code in Python with Gmsh and extrusion via Pyhyp. However, designing software that has all of the features of commercial software with open source software leads to situations in which the intended way of usage is not the best way for the given task. An example of another open-source approach is the MACH-AERO framework which is an aerodynamic shape optimization tool that creates a grid along the way and extrudes it. However, this does not cover the intended usage of openblademesh for purely structured grid generation for predefined wings. Here we show one way to achieve an open-source solution with Gmsh and Pyhyp. All the necessary software, the versions needed, and installation instructions are described. Also how the wing generation process is achieved with special concentration on the wing-tip is part of the following thesis. The thesis also describes how to use the presented software Openblademesh and how to achieve the best results. The tool uses various automatisms to take the workload off of the user and helps to achieve the best mesh. Finally, the advantages and limitations of the tool are assessed and future extensions are described.
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    Cross-over analysis of altimetry over ocean and investigating the orbital error’s effect on inter-mission/track bias in inland altimetry
    (2024) Kappich, Oliver
    The largest part of Earth’s surface (approximately 71%) is covered with water. Given the constantly changing environment, particularly amidst accelerated climate change, it is crucial to continuously measure the water levels of oceans and lakes. Therefore, satellite altimetry becomes essential. The orbits of the altimetry satellites are selected in a way that allows satellites to pass over the same locations after a specific interval. These orbits are termed as repeat orbits, facilitating the creation of time series measurements. Over the past 40 years, numerous altimetry satellite missions have been launched. When multi-mission monitoring of water bodies is targeted, each satellite altimeter possesses its own biases, which should be removed for comparability among different missions. This ensures the creation of long-term data records by combining data from various missions. Over open oceans, this is typically achieved through a cross-calibration method. However, these methods prove effective for ocean data but not for inland altimetry. In this thesis, I investigated the reasons for the bias among water values measured by different satellites. Additionally, I explored potential solutions to merge the data. The main focus lays on the tandem phases of Jason 1 and 2, as well as Jason 2 and 3. The study area focused on Lake Erie, situated in the Great Lakes region in the northwest of the US. To reduce the bias, I employed a cross-calibration method to estimate and reduce radial error components. As this approach does not resolve the entire bias problem, I investigated the retracking algorithms by comparing their results. Differences between height measurements of Jason 2 and Jason 3, both using MLE4, were identified. It could be determined that MLE4 in Jason 3 finds systematically lower values compared to Jason 2. Over the whole tandem phase, Jason 3 finds the retracking point approximately 20%, in respect to the leading edge, lower than Jason 2. The influence of this systematic difference on the SSH/LLH remains unclear, as no further investigations are done. To get a better understanding if the bias can be reduced when the mid-height point is used, two simple threshold retracking algorithms are employed. The outcome is, that the difference between Jason 2 and Jason 3 increased to 18.3 cm on average. Lastly, I examined the corrections that need to be added to the range measurement of the satellite. This includes the geoid undulation, tidal height variations, the ocean surface response caused by atmospheric pressure and propagation delay due to the atmosphere. I found differences of 5 to 8 cm over Lake Erie in the atmosphere corrections. Employing the same corrections for two satellites yielded the most effective bias reduction. However, employing this technique, necessitates satellites passing the same location within a few minutes of each other. Consequently, the Jason satellites were selected during their tandem phases. On average the bias could be reduced from 7 cm to 2.4 cm. The study delved into understanding and reducing biases in satellite altimetry measurements, particularly focusing on the tandem phases of Jason satellites, revealing challenges and promising methods to significantly reduce biases.
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    Study on constraining turbulence to met mast data from the WINSENT complex terrain test site for use as inflow for CFD simulations
    (2025) Müller, Carsten
    This work presents a method for generating time-resolved, three-dimensional turbulent inflow conditions for URANS/DDES simulations using the flow solver FLOWer. Turbulent inflow fields are generated using the Mann Turbulence Model via python’s Hipersim package and are applied as boundary conditions in the solver. The inflow is to reproduce both the absolute values and spectral characteristics of single-point time series and 3D velocity fields represented in atmospheric turbulence. A dedicated toolchain, InFlow, was developed to process and adapt turbulence input data from the WINSENT test site near Stötten, Germany. The approach is designed to be computationally efficient, straightforward to apply, and accurate enough for use in practical wind energy simulations. Its performance and limitations are evaluated across varying inflow scenarios and setups.