06 Fakultät Luft- und Raumfahrttechnik und Geodäsie
Permanent URI for this collectionhttps://elib.uni-stuttgart.de/handle/11682/7
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Item Open Access Evaluate the performance of a camber controlled cycloidal rotor(2022) Huang, DoudouThe curvature of the airfoil has a significant effect on the performance of the cycloidal rotor system. This paper aims to improve the aerodynamic performance of the cycloidal rotor system by utilizing dynamical morphing blades in a CFD model. Particularly, three different camber morphing concepts, including leading edge deflection, trailing edge deformation, and cambered NACA profile, are employed to a baseline 2-bladed system with rotating and pitching NACA0015 aerofoils. Based on these three camber concepts, a series of URANS 2-D numerical simulations in OpenFOAM are conducted for blades with different morphing degrees and positions. The simulation results verified that the flow field condition could be optimized and thus significant improvement in thrust and efficiency could be achieved by properly tuning the morphing control.Item Open Access Item Open Access Understanding the hydrological signature in gravity data(2023) Schollmeier, PhilippOver the past two decades, the subsequent advancements in Superconducting Gravimeters (SGs) have ushered in a level of precision that enables the measurement of the impact of ground water and soil water on gravity. Because of the challenging nature of monitoring the total water volume and the relatively subtle amplitude of the hydrological signal, a comprehensive understanding of the precise hydrological signature in continuous gravity data remains elusive. In this study, I use SG data in conjunction with hydrological measurements from a geoscientific observatory in Germany to find the signature of hydrological signals in gravity data. I scrutinize the various steps involved in extracting this signal, presenting new methodologies, including a technique to eliminate oscillations in gravity residuals that are likely attributed to remaining tidal signals due to an imperfect tidal model. A major contribution of this work involves constructing a data-driven model that incorporates precipitation and soil moisture measurements to elucidate gravity variations. I address critical questions such as the impact of utilizing soil moisture data on the model’s performance, determining the optimal model for achieving the closest fit with gravity measurements, and assessing the applicability of computed model parameters to new epochs. Furthermore, I provide recommendations for refining the model-building process in future investigations. Results show that a convolution of the different hydrological timeseries with one half of a Gaussian bell curve leads to a strong agreement with the gravity measurements. The use of soil moisture data significantly improves the fit, especially when the measurement stations are spatially well distributed. This fit becomes less strong when the computed parameters are applied to new events, but the approach showed promise for some of the events. Enhancing our comprehension of the hydrological influence on gravity measurements holds promising implications, potentially positioning SGs as instruments for monitoring soil and ground water in the future. Moreover, this improved understanding could elevate the pre cision of analyzing other subtle signals, such as the effects of Polar Motion.Item Open Access Understanding the limitations of Sentinel-3 inland altimetry through validation over the Rhine River(2022) Schneider, Nicholas M.Satellite altimetry is developing into one of the most powerful measurement techniques for long-term water body monitoring thanks to its high spatial resolution and its increasing level of precision. Although the principle of satellite altimetry is very straightforward, the retrieval of correct water levels remains rather difficult due to various factors. Waveform retracking is an approach to optimize the initially determined range between the satellite and the water body on Earth by exploiting the information within the power-signal of the returned radar pulse to the altimeter. Several so-called retrackers have been designed to this end, yet remain one of the most open study areas in satellite altimetry due to their crucial role they play in water level retrieval. Moreover, geophysical properties of the stratified atmosphere and the target on Earth have an effect on the travel time of the transmitted radar pulse and can amount to severalmeters in range. In this study we provide an overall analysis of the performances of the retrackers dedicated to the Sentinel-3 mission and the applied geophysical corrections. For this matter, we focus on nine different locations within the Rhine River basin where locally gauged data is available to validate the Sentinel-3 level-2 products. Furthermore, we present a reverse retracking approach in the sense that we use the given in-situ data to determine the offset to each altimetry-derived measurement of every epoch. Under the assumption that these offsets are legitimate, they can be seen as an a-posteriori correction which we project onto the range and thus on a waveform level. Further analyses consist in the investigation of the relationship these a-posteriori corrections have to the waveform properties of the same epoch. Later, the question whether the a-posteriori corrections to the initial retracking gates are appropriate for the retrieval of correct water levels, drives us to assign a probability to each and every bin of the waveform. Following this idea, we design stochastic-based retrackers which determine the retracking gate for water level retrieval from the bin with the highest probability assigned to it. To distribute the probabilities across all bins of the waveform, we consider three empirical approaches that take both the waveform itself and its first derivative into account: Addition, multiplication and maximum of both signals. For all three of the new retrackers, we generate the water level timeseries over the aforementioned sites and validate them against in-situ data and the retrackers dedicated to the Sentinel-3 mission.Item Open Access Estimation of inter-satellite and inter-track biases of satellite altimetry missions over lakes and reservoirs using surface area from satellite imagery(2022) Yu, ShuhuaIncluding lakes, reservoirs, and rivers, inland water bodies cover only a small portion of the Earth’s surface. However, they play an important role in maintaining life on Earth, the global water cycle, and climate change. Due to the declining number of gauge stations that provide the in-situ data, the muti-mission satellite altimetry has been applied to the monitoring of medium to large lakes and reservoirs, which enables computing a water-level time series with impro ved temporal and spatial resolution. However, inter-satellite and inter-track biases are still a problem for multi-mission. There have been studies conducted to determine absolute altimetry biases at calibration locations and global altimetry biases. But we still don’t know everything about how satellites are biased over inland waters. This thesis is dedicated to developing a method to resolve the biases between satellites and tracks over lakes and reservoirs. Our strategy for calculating the biases between overlapping and non-overlapping time series of water levels from various missions and tracks is based on satellite-derived time series of water area. With the help of the estimated area by the image ry, the relative biases can be estimated by modeling the area-height relationship. With water level observations and water area observations, the Gauss-Helmert model is chosen to ad just the area-height relationship. Due to the possible interpolating error and the gross error in both observations, two robust estimation methods have been used to deal with outliers. One is the expectation maximization method, which provides a robust estimate by iteratively down weighting the observation with large residuals, and another one is an outlier rejection method based on Baardas’ data snooping, which detects outliers in the observations with statistical hypothesis tests. In the end, we also discuss the influence of the topography on the inter-track and inter-satellite biases. We calculate the standard deviation of the DEM of the intersaction area between the 2 km region along the track and the 5 km region along the lake to determine the relationship between topography and biases. The results show a high correlation between the inter-track biases and the topography. We have employed the developed methodology on a number of lakes and reservoirs, and the findings are compared to in-situ water level data. The results reveal the existence of the inter-satellite and inter-track biases, which vary from the global bias estimates.Item Open Access Using URANS CFD to optimize the pitching motion and path of the cycloidal rotor blades(2022) Kasper, KorbinianThis master thesis describes the procedure for optimisation of the pitching and the trajectory for cyclorotor blades to increase the efficiency based on 2D CFD calculations. The open-source software OpenFOAM with URANS is used for these CFD analyses. Considering various numbers of blades (one to four), the use of the chimera technique is necessary using the built-in OpenFOAM solver overPimpleDyMFoam. B-splines describe the arbitrary pitching and trajectory implemented in separate OpenFOAM motion classes. Two possible modes of drive are investigated for the cycloidal system; ’constant velocity’ and ’constant angular velocity’. The Dakota toolkit performs the parametric optimisation with an evolutionary algorithm. A Python script initialises, monitors and evaluates each CFD case. Fourteen optimisation setups are carried out. An increase in the efficiency for each run is achieved. The main reason for the improvement is the better alignment of the blade forces to the global thrust. Another reason is that the optimised motion induces force peaks, which leads to an increase in thrust. The best result is captured for a four-blade case with a circular motion and a pitching path optimisation. The figure of merit is 0.758. Two further optimisation runs with higher Reynolds numbers are carried out for the two-blade case with a circular motion. Despite the pitching paths’ similarity, the figure of merit can be significantly increased (+8.8% for double Reynolds number and +17.7% for fourfold Reynolds number). Due to a false precalculation of the trajectory, the optimisation results for the ’constant angular velocity’ drive are invalid.Item Open Access Validating Sentinel 3 altimetry over the Neckar River using GNSS Interferometric Reflectometry(2023) Yu, ZiqingGNSS-IR is a technique that enables the constant observation of water surface height using reflected GNSS signals from water surface. It offers a simple monitoring approach compared to other techniques, requiring only a GNSS receiver near the water. The principle of the technique involves analyzing signal-to-noise data by converting signals from the time domain to the frequency domain. Satellite altimetry is another powerful technique for long-term water monitoring, providing extensive spatial coverage. The retrieval of water level from altimetry waveforms, known as retracking, is susceptible to errors due to various factors, despite the development of multiple retracking algorithms for different waveform types. The Sentinel-3 satellite mission, operated by ESA and EUMETSAT, is designed to monitor Earth’s surface topography and climate while providing altimetry data. In this study, the altimetry results for the Neckar river from Sentinel-3 mission will be validated using the GNSS-IR technique. Due to the absence of a permanent GNSS receiver at the ideal measurement point, the measurement campaigns have a limited duration of a few hours each time. To better receive the reflected signals from water, GNSS antennas are rotated in the last 2 campaigns. To maximize the utilization of GNSS signal-to-noise ratio (SNR) data and capture the dynamic water level changes during observations, a novel technique is developed. This technique involves splitting the data according to time and multiplying the Lomb-Scargle Periodograms(LSP) from different satellites within specific time ranges. By extracting the peaks of the multiplied periodograms, a time series can be generated. The altimetry results from the Sentinel-3 mission will then be validated using this time series. To enhance the quality of GNSS-IR results, various methods have been implemented, including selecting different campaign locations, rotating GNSS receivers, and applying data filters such as elevation angle. GNSS-IR is proved to be a able to monitor the inland small water body and rotating the GNSS antenna can improve the result quality. All seven retrackers from the Sentinel-3 mission are validated using water level data obtained from GNSS-IR. The altimetry water level is higher as the result from GNSS-IR and this offset varies for different retrackers from about 0.1 to 0.4 meters. In the challenging Neckar area with a narrow river width and complex environment, OCOG has demonstrated the best performance in terms of both availability and accuracy, the difference is from 0.03 to 0.17 meters in all experiments.Item Open Access Surface water extent monitoring using the Global WaterPack product: automated extraction, refinement, and analysis(2025) Jalali Jirandehi, MasoudMonitoring and analyzing surface water dynamics is critical for understanding hydrological variations, climate change impacts, and water resource management. Traditional methods of surface water storage monitoring rely on in-situ measurements, which are often spatially and temporally limited. Remote sensing has revolutionized this field by enabling large-scale, consistent, and continuous observations of area and height water storages. This study presents a methodology for generating accurate water area time series using the Global WaterPack (GWP), a monthly satellite-derived dataset. Developed by the German Aerospace Center (DLR), the GWP dataset is specifically designed for monitoring surface water dynamics on a global scale. A Python-based processing tool is developed to systematically extract and analyze lake and river water extents, mitigating key challenges such as cloud contamination, defining proper threshold, and classification inaccuracies. By integrating high-frequency surface water observations from GWP with the Prior Lake Database PLD (a static dataset for extracting the initial search area), and the SWOT (The Surface Water and Ocean Topography) prior River Database (SWORD), which provides a standardized framework of high-resolution river nodes and reaches, this tool enhances the reliability of time-series analysis. This framework improves surface water change detection, reduces computational complexity, and refines water occurrence assessments under diverse hydroclimatic conditions. The workflow automates the entire process, allowing users to select lakes interactively via a geospatial interface or upload coordinate lists for batch processing. Key steps include (1) downloading images, (2) defining the search area, (3) normalization, (4) generating a water occurrence map, (5) defining constant water and land masks, (6) residual analysis, (7) deriving and applying thresholds, (8) generating time series plots, and (9) correlation analysis. Advanced filtering methods, such as threshold-based classification and residual analysis, refine water occurrence measurements, while an adaptive thresholding approach using the Cumulative Distribution Function (CDF) enhances water body delineation accuracy. To evaluate the reliability of the extracted data, the resulting surface area time series are compared against altimetry-derived water height records using correlation analysis. The analysis revealed clear seasonal and interannual variations in lake water areas, aligning well with natural hydrological patterns. Many lakes showed strong positive correlations between satellite-derived surface area and altimetry-based water levels, validating the method’s effectiveness. However, weaker correlations in some cases were attributed to issues like cloud cover, sensor limitations, and complex hydrodynamics. The study emphasized that a fixed threshold is insufficient for all systems, whereas the corrected method provided more reliable results across diverse conditions. Although river analysis showed varied hydraulic responses, the tool proved useful for monitoring floods, seasonal changes, and long-term water trends, especially with proper calibration. By providing an automated, scalable, and accurate tool for water body monitoring, this thesis contributes to advancing hydrological analysis using remote sensing and geospatial processing techniques. The developed tool can aid in climate studies, water resource management, and flood risk assessment, offering a valuable framework for long-term surface water monitoring.