Universität Stuttgart
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Item Open Access Untersuchung der Antriebsstrangdynamik in Windenergieanlagen(2020) Horch, JoachimDiese Arbeit beschäftigt sich damit die Stabilität und Funktionstüchtigkeit des Antriebsstranges einer Windenergieanlage der Größenordnung 10 MW zu untersuchen. Hierfür erfolgt der Aufbau eines Computermodells einer 10-MW-Windenergieanlage mithilfe des Mehrkörpersimulationsprogrammes SIMPACK. Weiterhin wird eine Parameterstudie durchgeführt, welche über eine Matlab-induzierte SIMPACK-Simulation speziell ausgewählte Parameter des Antriebsstranges variiert, Simulationen durchführt und so den Einfluss bestimmter Parameter, sowie Parameterkombinationen, auf die Stabilität des Antriebsstranges prüft. Auf diese Weise sollen Stabilitätskriterien für einen Antriebsstrang dieser Größenordnung ermittelt werden. Es erfolgen sowohl statische, als auch dynamische Untersuchungen.Item Open Access A MATLAB toolbox for the Scintrex CG-5 gravimeter at GIS(2017) Gu, SiyunThis thesis is about a MATLAB toolbox for the Scintrex CG-5 gravimeter. The aim of this toolbox is to offer a basic data process for gravity measurement, which is compatible for most applications in geodesy. In particular, the toolbox covers: 1. data selection, 2. adjustment, 3. gravity gradient computation, 4. gravity visualization, 5. calibration factor estimation. A graphical user interface enables users without deeper programming knowledge to operate this toolbox and obtain the results like adjusted values or figures.Item Open Access Indefinite linear quadratic optimal control: periodic dissipativity and turnpike properties(2018) Berberich, JulianItem Open Access Monitoring inland surface water level from Sentinel-3 data(2019) Wang, BoInland surface water bodies (e.g. lakes and rivers) are very important to the nature and human society. To monitor the water level of inland water bodies, gauge stations were built since 19th century, but the amount of the stations is declining since the 1970s because of lack of maintenance. An accurate and continuous monitoring of lakes and rivers is available because of the satellite altimetry missions launched, e.g. Jason-2 and ENVISAT. These satellites can provide water level with proper spatial and temporal resolution. In the recent past, researchers have used different satellite mission observations to generate time series of inland water level in order for monitoring the water bodies. In this thesis, we use the new designed satellite mission Sentinel-3, which carries different sensors, to generate the water level time series of Dongting Lake and Poyang Lake in China. Initially, we combine the altimetry measurements with satellite images to determine virtual station. We choose Sentinel-3 Ku band data and on-board Ocean tracker to generate the water level time series. Afterwards, we apply different waveform retracking algorithms (5β-parameter and OCOG) to compare the results with on-board tracker. We also validate the results with the other database, then investigate the waveforms of each sampling date. The comparisons show the three tracking methods we used are capable to Quasi-Specular waveforms, and OCOG shows the best result to flat patch waveforms. Furthermore, some suggestions for improvements are also discussed in the last chapter.Item Open Access Characterizing storage-based drought using satellite gravimetry(2021) Saemian, PeymanDrought is a complex phenomenon leading to a wide range of socio-economic, environmental, and political problems. The storage-based drought which represents the persistent lack of water in different levels of the Total Water Storage (TWS) from deep groundwater to surface water plays a vital role in proactive drought management. Despite its necessity, TWS could not be monitored due to the lack of consistent measurements from regional to continental scale. Since its launch in 2002, the Gravity Recovery and Climate Experiment (grace) mission and its successor GRACE Follow-On have provided unique observations of the TWS change at the global scale. In this study, we have investigated characterizing the storage-based drought at the global scale using GRACE measurements. To this end, the Equivalent Water Height (EWH) has been retrieved from GRACE level 02 solutions. We have addressed the short record of GRACE observations in capturing the full hydroclimate variations. Based on our analysis, regions with a considerable direct human intervention like overexploitation of groundwater in the Middle East, regions that were affected by climate change like ice-melting over the Mackenzie river basin in Canada, or extreme precipitation events over the Ob river basin in the boreal regions are more sensitive to the length of ewh time series. Due to the crucial need for a long (at least 30 years) record of EWH, we have extended GRACE observations back to 1980 using an ensemble of models. The extended dataset has been developed using a pixel-wise selection of best-performed models among global hydrological models, land surface models, and atmospheric reanalysis models. The extended dataset has been used in the study for drought characterization over the grac period. The proposed Storage-based Drought Index (SDI) successfully captured the documented drought events globally in terms of intensity and spatio-temporal distribution. Moreover, the analysis of SDI over the five classes of drought from D0 as abnormally dry to D4 as exceptional drought showed that most regions have suffered at least once from the storage-based drought over the GRACE period (2002–2016). Besides, the map of exceptional drought frequency highlights regions with significant groundwater extraction like California, the Middle East, and north of India and regions with exceptional shifts in the precipitation and temperature pattern and intensity like Amazon in South America and China. Finally, our comparison of SDI with three most widely used drought indices namely the Standardized Precipitation Index (SPI), the Standardized Precipitation Evapotranspiration Index (SPEI), and the Palmer Drought Severity Index (PDSI) reveals that despite their high correlation over climate-driven regions, these indices failed to characterize anthropogenic drought events, especially over regions with considerable groundwater withdraws. The study allows for a more informative storage-based drought with a more robust climatology as the reference, thus enabling a more realistic risk assessment.Item Open Access Reconstruction of μXRCT data sets using the ASTRA toolbox(2020) Voland, PaulItem Open Access Assessment of altimetric river water level time series densification methods(2018) Xia, ZhugeNowadays, collecting and analysing water level time series recorded by gauging stations or by satellite altimetry is crucial for the geodetic and environmental purposes, such as modelling ocean circulation and monitoring climate change. Since the 1970s, a large number of gauging stations has been removed. This has made altimetry increasing more important. However, data collected by individual altimetric satellites are limited, i.e., the temporal resolution is limited to the repeat cycle of satellites, and the spatial resolution is constrained to the distribution of virtual stations. In order to overcome these limitations, methods have been developed to combine all available altimetric satellite missions along a river to construct a new densified time series. This is referred to as densification. To our knowledge, there are only two proven densification methods applied to the river for now. The first is a hydraulic statistic densification method developed by Tourian et al. (2016). The other is the kriging densification method published by Boergens et al. (2017). However, each of them is realized under different circumstances, which makes them incomparable with each other. In this work, we implement the two densification methods and apply them under similar conditions. The various densified water level time series are compared and analysed both visually and statistically. Results reveal different characteristics of the two densification methods.Item Open Access Identifiability and sensitivity analysis of heterogeneous cell population models(2013) Zeng, ShenIn this thesis, we introduce novel concepts to the modeling and analysis of heterogeneous cell populations. Heterogeneous cell populations can be interpreted as large populations of structurally identical cells with heterogeneous parameters and initial conditions. They appear in biological systems such as tissues of higher organisms or colonies of microorganisms. A well-known approach for the modeling of heterogeneous cell populations is the so called density-based approach, in which the state of a heterogeneous cell population is given by the probability density of the cell states. The evolution of the probability densities is in this approach given in terms of a partial differential equation. We extend this approach via a measure theoretical consideration, which exploits the probabilistic nature of the problem. The result of this novel ansatz is a framework in which the evolution of densities is described by operators. One of the key tasks in the analysis of heterogeneous cell population models is parameter estimation. For heterogeneous cell populations we want to estimate the probability density of parameters and initial conditions. However, to be able to perform parameter estimation, one always needs specific identifiability properties of a system. We formulate for the first time the concept of structural identifiability of a heterogeneous cell population model. It is revealed that this concept is closely related to observability of the corresponding single cell model. The connection between both concepts is studied and illuminated in a concrete example. The second emphasis of this thesis is the implementation of sensitivity analysis to the class of heterogeneous cell population models. Here we study sensitivity with respect to variations or misspecifications in the probability density of parameters and initial conditions.Item Open Access Validierung eines gekoppelten Simulationsmodells schwimmender Windkraftanlagen mit Hilfe von Modellversuchen(2016) Koch, ChristianFür die Konzeptionierung und Konstruktion schwimmender Windenergiesysteme müssen die Belastungen des Gesamtsystems, die aus kombinierten Wind- und Wellenkräften resultieren, genau untersucht und bestimmt werden. Nur bei genauer Kenntnis dieser Belastungen können effiziente, sichere und wirtschaftliche Gesamtkonzepte entwickelt werden. Für eine zuverlässige Bestimmung der kombinierten Wind- und Wellen- sowie Ankerleinenlasten können validierte Simulationsmodelle eingesetzt werden. Um eine Validierung von Simulationsprogrammen vornehmen zu können, muss auf definierte Lastfälle mit realen Datensätzen zurückgegriffen werden. Im INNWIND.EU Projekt wurde für die Validierung bestehender Simulationscodes eine froudeskalierte, auf der „OC4-DeepCwind“ Halbtaucherplattform basierende, schwimmende 10MW Windenergieanlage mit Rotorblättern mit niedriger Reynoldszahl unter verschiedenen definierten Belastungsfällen in einem kombinierten Wind- und Wellentank in Nantes (Frankreich) untersucht. Im Rahmen dieser Arbeit wird ausgehend von den in in Frankreich erhobenen Daten des INNWIND.EU Projekts ein vollständig gekoppeltes Simulationsmodell, auf einem bestehenden SIMPACK Mehrkörpersimulationsmodell aufgebaut und validiert. Für die Modellierung der Ankerleinenkräfte wurde dabei erstmalig das von NREL entwickelte Ankerleinensimulationsprogramm MAP++ eingesetzt. Die Modellierung der Aerodynamik erfolgte mittels AeroDyn unter Verwendung der Blattelementimpulsmethode. Für die Modellierung der Hydrodynamik wurde HydroDyn mit einer vorgeschalteten AQWA Berechnung zur Bestimmung der hydrodynamischen Koeffizienten eingesetzt. Im Rahmen der Untersuchung wurde eine Vielzahl verschiedener Lastfälle, angefangen von Einschwingversuchen, Versuchen mit reiner Wellen- oder reiner Windbelastung sowie mit kombinierter Wind- und Wellenbelastung simuliert und untersucht. Für die kombinierten Belastungsfälle wurden auch Extrembelastungstests untersucht und die Simulationsergebnisse mit den Messdaten verglichen. Vor allem für große Wellenhöhen zeigten sich dabei gute Übereinstimmungen zwischen Simulation und Messung.Item Open Access The optimal regularization and its application in extreme learning machine for regression analysis and multi-class classification(2018) Qian, KunExtreme Learning Machine (ELM) proposed by Huang et al. (2006) is a newly developed single layer feed-forward neural network (SLFN). It is attractive for its high training efficiency and satisfactory performance, especially when dealing with a large amount of data, which are often in high-dimensional space. However, current ELM cannot solve the over-fitting problem among other several problems. While minimizing residuals of output errors for the training data, it tends to generate an over-fitting model, whose generalization ability is relatively weak. Even if the model fits the training data perfectly, it performs unsatisfactory for the testing data. In training process, we aim to minimize residuals of output errors of training data. It tends to generate an over-fitting model, which has poor generalization ability. The model maybe fit the training data perfectly, but performs badly in testing data. Furthermore, in order to improve accuracy, the traditional way is increasing the number of hidden-layer neurons, but excessive hidden-layer neurons result in an ill-posed normal matrix and a model which is over sensitive to the change of the training data. In such case, the performance of ELM is significantly affected by the outliers in the training data. In order to overcome these problems, we apply the regularization to the original ELM. In this study, the A-optimal design regularization is performed to improve the generalization ability and stability of ELM. The performance of ELM with the A-optimal design regularization will be evaluated through two main applications, respectively, regression analysis and satellite image multi-class classification.