Universität Stuttgart
Permanent URI for this communityhttps://elib.uni-stuttgart.de/handle/11682/1
Browse
6 results
Search Results
Item Open Access Long-term lumped projections of groundwater balances in the face of limited data(Stuttgart : Eigenverlag des Instituts für Wasser- und Umweltsystemmodellierung der Universität Stuttgart, 2024) Ejaz, Fahad; Nowak, Wolfgang (Prof. Dr.-Ing.)Item Open Access Experimental multi-scale characterization using micro X-ray computed tomography(Stuttgart : Institute of Applied Mechanics, 2023) Ruf, Matthias; Steeb, Holger (Prof. Dr.-Ing.)The effective mechanical and hydro-mechanical behavior of porous media, granular solids, and related materials with complex morphologies is intimately linked to their internal microstructure on the pore/grain scale. For microstructural characterization, transmission micro X-Ray Computed Tomography (µXRCT) has emerged as a crucial three-dimensional (3D) imaging technique that can provide structural information from the micrometer to centimeter scale. Due to its non-destructive nature, it can be excellently combined with time-dependent investigations, either ex situ or in situ. In particular, the possibility of coupling mechanical or hydro-mechanical characterization with µXRCT-based 3D imaging in situ allows many physical phenomena to be studied in more detail and consequently understood more comprehensively. For example, the microstructure evolution can be observed under various controlled boundary conditions and linked to measured effective quantities. New insights and improved understanding can ultimately positively influence modeling approaches. In order to be able to perform such multi-scale studies, a modular, open, and versatile lab-based µXRCT system was developed within the scope of this work. It provides a spatial resolution of down to less than 10 µm. The developed system has an integrated universal testing machine that enables in situ compressive, tensile, and torsional studies as well as their combinations, parallel or sequential. Furthermore, hydro-mechanical coupled phenomena can be investigated using appropriate equipment, such as triaxial flow cells. Thanks to the open and modular concept, the developed system can be used in the future for a wide variety of multiphysics research questions and can be considered as an open experimental platform. Employing the established system, various multi-scale phenomena from different material classes are motivated and partly investigated in more detail within this work. For this purpose, classical experimental characterization methods are combined with µXRCT-based 3D imaging ex situ as well as in situ. Among others, 3D imaging is combined with ultrasound wave propagation measurements to investigate the influence of artificially generated crack networks in Carrara marble by different thermal treatment protocols. Load-sequence effects are demonstrated on an open-cell foam sample. An in situ workflow is shown to investigate the not-well-understood effective stiffness behavior of biphasic monodisperse granular packings of stiff and soft particles of different volume fractions at different stress states. The fracturing of a rock sample in a triaxial flow cell shows possibilities of application in the context of fracture mechanics. All resulting data sets, including metadata, are available via the Data Repository of the University of Stuttgart (DaRUS).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 The role of retardation, attachment and detachment processes during microbial coal-bed methane production after organic amendment(2020) Emmert, Simon; Davis, Katherine; Gerlach, Robin; Class, HolgerMicrobially enhanced coal-bed methane could allow for a more sustainable method of harvesting methane from un-mineable coaldbeds. The model presented here is based on a previously validated batch model; however, this model system is based on upflow reactor columns compared to previous experiments and now includes flow, transport and reactions of amendment as well as intermediate products. The model implements filtration and retardation effects, biofilm decay, and attachment and detachment processes of microbial cells due to shear stress. The model provides additional insights into processes that cannot be easily observed in experiments. This study improves the understanding of complex and strongly interacting processes involved in microbially enhanced coal-bed methane production and provides a powerful tool able to model the entire process of enhancing methane production and transport during microbial stimulation.Item Open Access Stochastic model comparison and refinement strategies for gas migration in the subsurface(Stuttgart : Eigenverlag des Instituts für Wasser- und Umweltsystemmodellierung der Universität Stuttgart, 2023) Banerjee, Ishani; Nowak, Wolfgang (Prof. Dr.-Ing.)Gas migration in the subsurface, a multiphase flow in a porous-medium system, is a problem of environmental concern and is also relevant for subsurface gas storage in the context of the energy transition. It is essential to know and understand the flow paths of these gases in the subsurface for efficient monitoring, remediation or storage operations. On the one hand, laboratory gas-injection experiments help gain insights into the involved processes of these systems. On the other hand, numerical models help test the mechanisms observed and inferred from the experiments and then make useful predictions for real-world engineering applications. Both continuum and stochastic modelling techniques are used to simulate multiphase flow in porous media. In this thesis, I use a stochastic discrete growth model: the macroscopic Invasion Percolation (IP) model. IP models have the advantages of simplicity and computational inexpensiveness over complex continuum models. Local pore-scale changes dominantly affect the flow processes of gas flow in water-saturated porous media. IP models are especially favourable for these multi-scale systems because using continuum models to simulate them can be extremely computationally difficult. Despite offering a computationally inexpensive way to simulate multiphase flow in porous media, only very few studies have compared their IP model results to actual laboratory experimental image data. One reason might be the fact that IP models lack a notion of experimental time but only have an integer counter for simulation steps that imply a time order. The few existing experiments-to-model comparison studies have used perceptual similarity or spatial moments as comparison measures. On the one hand, perceptual comparison between the model and experimental images is tedious and non-objective. On the other hand, comparing spatial moments of the model and experimental images can lead to misleading results because of the loss of information from the data. In this thesis, an objective and quantitative comparison method is developed and tested that overcomes the limitations of these traditional approaches. The first step involves volume-based time-matching between real-time experimental data and IP-model outputs. This is followed by using the (Diffused) Jaccard coefficient to evaluate the quality of the fit. The fit between the images from the models and experiments can be checked across various scales by varying the extent of blurring in the images. Numerical model predictions for sparsely known systems (like the gas flow systems) suffer from high conceptual uncertainties. In literature, numerous versions of IP models, differing in their underlying hypotheses, have been used for simulating gas flow in porous media. Besides, the gas-injection experiments belong to continuous, transitional, or discontinuous gas flow regimes, depending on the gas flow rate and the porous medium's nature. Literature suggests that IP models are well suited for the discontinuous gas flow regime; other flow regimes have not been explored. Using the abovementioned method, in this thesis, four macroscopic IP model versions are compared against data from nine gas-injection experiments in transitional and continuous gas flow regimes. This model inter-comparison helps assess the potential of these models in these unexplored regimes and identify the sources of model conceptual uncertainties. Alternatively, with a focus on parameter uncertainty, Bayesian Model Selection is a standard statistical procedure for systematically and objectively comparing different model hypotheses by computing the Bayesian Model Evidence (BME) against test data. BME is the likelihood of a model producing the observed data, given the prior distribution of its parameters. Computing BME can be challenging: exact analytical solutions require strong assumptions; mathematical approximations (information criteria) are often strongly biased; assumption-free numerical methods (like Monte Carlo) are computationally impossible for large data sets. In this thesis, a BME-computation method is developed to use BME as a ranking criterion for such infeasible scenarios: The \emph{Method of Forced Probabilities} for extensive data sets and Markov-Chain models. In this method, the direction of evaluation is swapped: instead of comparing thousands of model runs on random model realizations with the observed data, the model is forced to reproduce the data in each time step, and the individual probabilities of the model following these exact transitions are recorded. This is a fast, accurate and exact method for calculating BME for IP models which exhibit the Markov chain property and for complete "atomic" data. The analysis results obtained using the methods and tools developed in this thesis help identify the strengths and weaknesses of the investigated IP model concepts. This further aids model development and refinement efforts for predicting gas migration in the subsurface. Also, the gained insights foster improved experimental methods. These tools and methods are not limited to gas flow systems in porous media but can be extended to any system involving raster outputs.Item Open Access Developing and calibrating a numerical model for microbially enhanced coal-bed methane production(Stuttgart : Eigenverlag des Instituts für Wasser- und Umweltsystemmodellierung der Universität Stuttgart, 2021) Emmert, Simon; Class, Holger (apl. Prof. Dr.-Ing.)Experimental investigations demonstrate the potential of microbially enhanced coal-bed methane (MECBM) production on the lab scale. However, no in-depth mathematical and conceptual model including all sub-processes is reported in literature so far. With this study, we develop and present a conceptual food-web, included into a numerical model, that is calibrated and validated using batch experiments. The model is extended to model flow and transport features, test hypotheses, and compare against column experiments. Additionally, a sensitivity analysis of the model parameters as well as a preliminary study regarding operator-splitting techniques for the MECBM model are presented.