Universität Stuttgart
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Item Open Access Heat transport from atmosphere through the subsurface to drinking‐water supply pipes(2023) Nissler, Elisabeth; Scherrer, Samuel; Class, Holger; Müller, Tanja; Hermannspan, Mark; Osmancevic, Esad; Haslauer, ClausDrinking‐water quality in supply pipe networks can be negatively affected by high temperatures during hot summer months due to detrimental bacteria encountering ideal conditions for growth. Thus, water suppliers are interested in estimating the temperature in their distribution networks. We investigate both experimentally and by numerical simulation the heat and water transport from ground surface into the subsurface, (i.e., above drinking‐water pipes). We consider the meteorological forcing functions by a sophisticated approach to model the boundary conditions for the heat balance at the soil-atmosphere interface. From August to December 2020, soil temperatures and soil moisture were measured dependent on soil type, land‐use cover, and weather data at a pilot site, constructed specifically for this purpose at the University of Stuttgart with polyethylene and cast‐iron pipes installed under typical in situ conditions. We included this interface condition at the atmosphere-subsurface boundary into an integrated non‐isothermal, variably saturated (Richards') the numerical simulator DuMux 3. This allowed, after calibration, to match measured soil temperatures with ±2°C accuracy. The land‐use cover influenced the soil temperature in 1.5 m more than the soil material used for back‐filling the trench above the pipe.Item Open Access High-resolution spatio-temporal measurements of the colmation phenomenon under laboratory conditions(Stuttgart : Eigenverlag des Instituts für Wasser- und Umweltsystemmodellierung der Universität Stuttgart, 2022) Mayar, Mohammad Assem; Wieprecht, Silke (Prof. Dr.-Ing.)The fine sediment infiltration and accumulation into the gravel bed of rivers, the so-called colmation phenomenon, is a pernicious process exacerbated by anthropogenic activities. Owing to the importance and complexity of this phenomenon, it has been widely studied over the last decades. Various devices and methods have been developed to assess this phenomenon, where most of them are destructive and sample-based, resulting in an alteration of the natural conditions. Therefore, non-intrusive techniques, which provide spatial and temporal details with a high-resolution, are required to discretize the mechanisms involved in the colmation process. To address these issues, investigations under laboratory conditions may simplify the complexity of nature and enable individual and exactly defined boundary conditions to be investigated. Therefore, this thesis aims at (i) developing a non-intrusive and undisturbed measurement method for the high-resolution spatio-temporal measurements of the sediment infiltration processes and the development of sediment accumulation in an artificial river bed under laboratory conditions, (ii) applying this method to certain experiments for the assessment of the effects of different boundary conditions on sediment infiltration, and (iii) investigating the colmation phenomenon (also known as clogging) of gravel beds. For this purpose, the gamma-ray attenuation method is used together with an artificial gravel bed arranged from the spheres with various diameters and placed in a laboratory flume. This new method works based on the gamma radiation that passes through the infiltrated sediments, water, and bed spheres, in which the gamma-ray attenuation is linked to the variations of the infiltrated sediments’ quantity. The main simplification of this approach is that gravel beds are represented by the combinations of different-sized spheres. This gives the opportunity to fully distinguish infiltrating sediments from the bed material, reduce the complexity of the natural environment, and allows for repetitive measurements of the same position with different boundary conditions. From the results of this study, first, the gamma-ray attenuation measurement method was optimized to resolve the inconsistencies in the measurements. Subsequently, the concept of the non-intrusive and undisturbed measurement is proved through box experiments. Additional reproducibility experiments in the laboratory flume, for a similar bed structure, showed only small deviations between two experiments with the same setup. Consequently, the established technique was used in a series of experiments to evaluate the effects of different supply rates, total supply masses, and sediment particle size boundary conditions on the sediment infiltration and colmation processes. Vertical profiles of the infiltrated sediment were quantified through high spatial resolution measurements. Furthermore, to evaluate the infiltrating sediment accumulation development, and the temporal variations of the infiltrated sediments, the vertical profile measurements were first repeated after a specific time-period to track interval-averaged variations in all positions of the vertical axis. Next, a specific position of the vertical axis was measured continuously during the entire experiment in a high temporal resolution. The measured vertical profiles illustrate the vertical distribution, colmation, and unimpeded percolation of the infiltrated sediments. The dynamic one-point measurement precisely identifies the three phases (the start of the pore-filling, the required time to fill the pore, and the final amount of infiltrated sediments including natural fluctuation during the ongoing experiments) of the sediment infiltration or the possible clogging. As a limitation, the gamma-ray attenuation system’s current configuration only works in artificial gravel beds because of the given density difference between infiltrated sediments and the artificial bed structure. Intense radiations that pass through the natural bed's thickness are capable of detecting a significant amount of infiltrated sediments. However, small amounts of infiltrated sediments will create only a minimal shift in attenuation, which might be confused with the statistical error. In addition, the legal restriction against using radioactive material in the natural environment is another reason for not applying it in the field. Furthermore, the gamma-ray attenuation method cannot resolve the sediment distribution in the measurement horizon and provides an integrative result for each measurement position. In addition, if a mixture of silt, clay, and sand is supplied to the experiment, the gamma-ray attenuation system will produce a bulk result of all the infiltrated materials. To conclude, despite the limitations mentioned above, the gamma-ray attenuation method offers a unique opportunity for the non-intrusive and undisturbed measurements of the sediment infiltration or the special case of colmation, with a high spatio-temporal resolution. This method has the potential to quantify the investigated processes on a millimetric spatial scale, if the measurement time is not a constraint, or vice versa, in a high temporal resolution (seconds) for a specific position, if spatial scale is not important. Moreover, the gamma-ray attenuation approach can simultaneously measure the longitudinal distribution of the sedimentological processes, if multiple instruments or a single device with several radiation-emitting-holes is in operation. Last, but not least, rather than the spheres, artificial gravel beds could be made of any substance with a composition significantly different from the infiltrating sediments, and the boundary conditions of the experiments can be improved in order to attain conditions close to nature. Finally, the gamma-ray attenuation method can be integrated with advanced flow measurement instruments such as Particle Image Velocimetry (PIV) and other high-resolution endoscopic devices to track the behavior of fine sediment infiltration and its clogging process in the porous gravel beds as it occurs in nature.Item Open Access Magnetic resonance imaging of water content and flow processes in natural soils by pulse sequences with ultrashort detection(2021) Haber-Pohlmeier, Sabina; Caterina, David; Blümich, Bernhard; Pohlmeier, AndreasMagnetic resonance imaging is a valuable tool for three-dimensional mapping of soil water processes due to its sensitivity to the substance of interest: water. Since conventional gradient- or spin-echo based pulse sequences do not detect rapidly relaxing fractions of water in natural porous media with transverse relaxation times in the millisecond range, pulse sequences with ultrafast detection open a way out. In this work, we compare a spin-echo multislice pulse sequence with ultrashort (UTE) and zero-TE (ZTE) sequences for their suitability to map water content and its changes in 3D in natural soil materials. Longitudinal and transverse relaxation times were found in the ranges around 80 ms and 1 to 50 ms, respectively, so that the spin echo sequence misses larger fractions of water. In contrast, ZTE and UTE could detect all water, if the excitation and detection bandwidths were set sufficiently broad. More precisely, with ZTE we could map water contents down to 0.1 cm3/cm3. Finally, we employed ZTE to monitor the development of film flow in a natural soil core with high temporal resolution. This opens the route for further quantitative imaging of soil water processes.Item Open Access Porosity and permeability alterations in processes of biomineralization in porous media - microfluidic investigations and their interpretation(Stuttgart : Eigenverlag des Instituts für Wasser- und Umweltsystemmodellierung der Universität Stuttgart, 2022) Weinhardt, Felix; Class, Holger (apl. Prof. Dr.-Ing)Motivation: Biomineralization refers to microbially induced processes resulting in mineral formations. In addition to complex biomineral structures frequently formed by marine organisms, like corals or mussels, microbial activities may also indirectly induce mineralization. A famous example is the formation of stromatolites, which result from biofilm activities that locally alter the chemical and physical properties of the environment in favor of carbonate precipitation. Recently, biomineralization gained attention as an engineering application. Especially with the background of global warming and the objective to reduce CO2 emissions, biomineralization offers an innovative and sustainable alternative to the usage of conventional Portland cement, whose production currently contributes significantly to global CO2 emissions. The most widely used method of biomineralization in engineering applications, is ureolytic calcium carbonate precipitation, which relies on the hydrolysis of urea and the subsequent precipitation of calcium carbonate. The hydrolysis of urea at moderate temperatures is relatively slow and therefore needs to be catalyzed by the enzyme urease to be practical for applications. Urease can be extracted from plants, for example from ground jack beans, and the process is consequently referred to as enzyme-induced calcium carbonate precipitation (ECIP). Another method is microbially induced calcium carbonate precipitation (MICP), which uses ureolytic bacteria that produce the enzyme in situ. EICP and MICP applications allow for producing various construction materials, stabilizing soils, or creating hydraulic barriers in the subsurface. The latter can be used, for example, to remediate leakages at the top layer of gas storage reservoirs, or to contain contaminant plumes in aquifers. Especially when remediating leakages in the subsurface, the most crucial parameter to be controlled is its intrinsic permeability. A valuable tool for predicting and planning field applications is the use of numerical simulation at the scale of representative elementary volumes (REV). For that, the considered domain is subdivided into several REV’s, which do not resolve the pore space in detail, but represent it by averaged parameters, such as the porosity and permeability. The porosity describes the ratio of the pore space to the considered bulk volume, and the permeability quantifies the ease of fluid flow through a porous medium. A change in porosity generally also affects permeability. Therefore, for REV-scale simulations, constitutive relationships are utilized to describe permeability as a function of porosity. There are several porosity-permeability relationships in the literature, such as the Kozeny-Carman relationship, Verma-Pruess, or simple power-law relationships. These constitutive relationships can describe individual states but usually do not include the underlying processes. Different boundary conditions during biomineralization may influence the course of porosity-permeability relationships. However, these relationships have not yet been adequately addressed. Pore-scale simulations are, in principle, very well suited to investigate pore space changes and their effects on permeability systematically. However, these simulations also rely on simplifications and assumptions. Therefore, it is essential to conduct experimental studies to investigate the complex processes during calcium carbonate precipitation in detail at the pore scale. Recent studies have shown that microfluidic methods are particularly suitable for this purpose. However, previous microfluidic studies have not explicitly addressed the impact of biomineralization on hydraulic effects. Therefore, this work aims to identify relevant phenomena at the pore scale to conclude on the REV-scale parameters, porosity and permeability, and their relationship. Contributions: This work comprises three publications. First, a suitable microfluidic setup and workflow were developed in Weinhardt et al. [2021a] to study pore space changes and the associated hydraulic effects reliably. This paper illustrated the benefits and insights of combining optical microscopy and micro X-ray computed tomography (micro XRCT) with hydraulic measurements in microfluidic chips. The elaborated workflow allowed for quantitative analysis of the evolution of calcium carbonate precipitates in terms of their size, shape, and spatial distribution. At the same time, their influence on differential pressure could be observed as a measure of flow resistance. Consequently, porosity and permeability changes could be determined. Along with this paper, we published two data sets [Weinhardt et al., 2021b, Vahid Dastjerdi et al., 2021] and set the basis for two other publications. In the second publication [von Wolff et al., 2021], the simulation results of a pore-scale numerical model, developed by Lars von Wolff, were compared to the experimental data of the first paper [Weinhardt et al., 2021b]. We observed a good agreement between the experimental data and the model results. The numerical studies complemented the experimental observations in allowing for accurate analysis of crystal growth as a function of local velocity profiles. In particular, we observed that crystal aggregates tend to grow toward the upstream side, where the supply of reaction products is higher than on the downstream side. Crystal growth during biomineralization under continuous inflow is thus strongly dependent on the locally varying velocities in a porous medium. In the third publication [Weinhardt et al., 2022a], we conducted further microfluidic experiments based on the experimental setup and workflow of the first contribution and published another data set [Weinhardt et al., 2022b]. We used microfluidic cells with a different, more realistic pore structure and investigated the influence of different injection strategies. We found that the development of preferential flow paths during EICP application may depend on the given boundary conditions. Constant inflow rates can lead to the development of preferential flow paths and keep them open. Gradually reduced inflow rates can mitigate this effect. In addition, we concluded that the coexistence of multiple calcium carbonate polymorphs and their transformations could influence the temporal evolution of porosity-permeability relationships.Item Open Access Investigations on functional relationships between cohesive sediment erosion and sediment characteristics(Stuttgart : Eigenverlag des Instituts für Wasser- und Umweltsystemmodellierung der Universität Stuttgart, 2021) Beckers, Felix; Wieprecht, Silke (Prof. Dr.-Ing.)Item Open Access A surrogate-assisted uncertainty-aware Bayesian validation framework and its application to coupling free flow and porous-medium flow(2023) Mohammadi, Farid; Eggenweiler, Elissa; Flemisch, Bernd; Oladyshkin, Sergey; Rybak, Iryna; Schneider, Martin; Weishaupt, KilianExisting model validation studies in geoscience often disregard or partly account for uncertainties in observations, model choices, and input parameters. In this work, we develop a statistical framework that incorporates a probabilistic modeling technique using a fully Bayesian approach to perform a quantitative uncertainty-aware validation. A Bayesian perspective on a validation task yields an optimal bias-variance trade-off against the reference data. It provides an integrative metric for model validation that incorporates parameter and conceptual uncertainty. Additionally, a surrogate modeling technique, namely Bayesian Sparse Polynomial Chaos Expansion, is employed to accelerate the computationally demanding Bayesian calibration and validation. We apply this validation framework to perform a comparative evaluation of models for coupling a free flow with a porous-medium flow. The correct choice of interface conditions and proper model parameters for such coupled flow systems is crucial for physically consistent modeling and accurate numerical simulations of applications. We develop a benchmark scenario that uses the Stokes equations to describe the free flow and considers different models for the porous-medium compartment and the coupling at the fluid-porous interface. These models include a porous-medium model using Darcy’s law at the representative elementary volume scale with classical or generalized interface conditions and a pore-network model with its related coupling approach. We study the coupled flow problems’ behaviors considering a benchmark case, where a pore-scale resolved model provides the reference solution. With the suggested framework, we perform sensitivity analysis, quantify the parametric uncertainties, demonstrate each model’s predictive capabilities, and make a probabilistic model comparison.Item Open Access A surrogate-assisted Bayesian framework for uncertainty-aware validation benchmarks(Stuttgart : Eigenverlag des Instituts für Wasser- und Umweltsystemmodellierung der Universität Stuttgart, 2023) Mohammadi, Farid; Flemisch, Bernd (apl. Prof. Dr. rer. nat.)Over the last century, computational modeling in geoscience, especially in porous media research, has witnessed tremendous improvement. After decades of development, the state-of-the-art simulators can now solve coupled partial differential equations governing the complex subsurface multiphase flow system within a practically large spatial and temporal domain. Given the importance of computational modeling, quality assessment of these models in light of the purpose of a given simulation is of paramount importance to engineering designers and managers, public officials, and those affected by the decisions based on the predictions. Users and developers of computational simulations deal with a challenging question: How should confidence in modeling and simulation be critically assessed? Validation is one of the primary methods for building and quantifying confidence in modeling and simulation. It investigates the degree to which a model accurately represents reality from the perspective of the intended application of the model. Usually, this comparison between model outputs and experimental data constitutes plotting the model results against data on the same axes to provide a visual assessment of agreement or lack thereof. While comparisons between model and data are at the heart of any validation procedure, there are several concerns with such naive comparisons. First, these comparisons tend to provide qualitative rather than quantitative assessments and are clearly insufficient as a basis for making decisions regarding model validity. Second, naive comparisons often disregard or only partly account for existing uncertainties in the experimental observations or the model input parameters. Third, such comparisons can not reveal whether the model is appropriate for the intended purposes, as they mainly focus on the agreement in the observable quantities. These pitfalls give rise to the need for an uncertainty-aware framework that includes a validation metric. This metric shall provide a measure for comparison of the system response quantities of an experiment with the ones from a computational model while accounting for uncertainties in both in a rigorous way. To address this need, we developed a statistical framework incorporating a probabilistic modeling technique using a fully Bayesian approach. The dissertation aims to help modelers perform uncertainty aware model validation benchmarks. A two-stage Bayesian multi-model framework is discussed for modeling tasks where a set of models are at hand. To make this framework applicable for computationally demanding models, it is extended to a surrogate-assisted framework, keeping the computational costs at a reasonable level. Moreover, correction factors were introduced to compensate for the surrogate error in the Bayesian hypothesis testing and Bayesian model selection, as using surrogate representations instead of the full-fidelity computational models introduces additional errors to the validation metrics. In this dissertation, I show how the Bayesian formalism could be materialized by employing the concept of polynomial chaos expansion to achieve more accurate surrogates with a sparse representation and account for the uncertainty in the surrogate’s predictions. I also highlight how such surrogate models could be constructed with as few simulations as the computational budget allows. To this end, sequential adaptive sampling strategies are discussed, in which one attempts to augment the initial design iteratively. By doing so, informative regions in the parameter space are adequately explored. These regions are more likely to provide valuable information on the behavior of the original model responses. Using a sequential sampling strategy avoids the waste of computational resources, as opposed to the so-called one-shot designs. A series of benchmark studies are conducted to investigate the predictive capabilities of different sparsity and sequential adaptive sampling methods. Moreover, I introduce BayesValidRox, an open-source, object-oriented Python package that provides an automated workflow for surrogate-based sensitivity analysis, Bayesian calibration, and validation of computational models with a modular structure. The uncertainty-aware validation framework was applied to a range of cases in the field of subsurface hydro-system modeling, mainly to flow and transport in porous media, such as flow simulation models in fractured porous media, coupling free flow and porous medium flow, and microbially induced calcite precipitation. However, this validation framework can be transferred to other disciplines in which models are used for prediction.Item Open Access Quantification of drainable water storage volumes on landmasses and in river networks based on GRACE and river runoff using a cascaded storage approach - first application on the Amazon(2020) Riegger, JohannesThe combined use of GRACE mass anomalies and observed river discharge for the first time allows us to quantify the water storage volumes drainable by gravity on global scales. Modelling of catchment and river network storages in a cascade with different dynamics reveals the time lag between total mass and runoff is caused by a non-zero river network storage. This allows catchment and river network storage volumes to be distinguished and is thus of great importance for water resources management.Item Open Access Learning groundwater contaminant diffusion‐sorption processes with a finite volume neural network(2022) Praditia, Timothy; Karlbauer, Matthias; Otte, Sebastian; Oladyshkin, Sergey; Butz, Martin V.; Nowak, WolfgangImproved understanding of complex hydrosystem processes is key to advance water resources research. Nevertheless, the conventional way of modeling these processes suffers from a high conceptual uncertainty, due to almost ubiquitous simplifying assumptions used in model parameterizations/closures. Machine learning (ML) models are considered as a potential alternative, but their generalization abilities remain limited. For example, they normally fail to predict accurately across different boundary conditions. Moreover, as a black box, they do not add to our process understanding or to discover improved parameterizations/closures. To tackle this issue, we propose the hybrid modeling framework FINN (finite volume neural network). It merges existing numerical methods for partial differential equations (PDEs) with the learning abilities of artificial neural networks (ANNs). FINN is applied on discrete control volumes and learns components of the investigated system equations, such as numerical stencils, model parameters, and arbitrary closure/constitutive relations. Consequently, FINN yields highly interpretable results. We demonstrate FINN's potential on a diffusion‐sorption problem in clay. Results on numerically generated data show that FINN outperforms other ML models when tested under modified boundary conditions, and that it can successfully differentiate between the usual, known sorption isotherms. Moreover, we also equip FINN with uncertainty quantification methods to lay open the total uncertainty of scientific learning, and then apply it to a laboratory experiment. The results show that FINN performs better than calibrated PDE‐based models as it is able to flexibly learn and model sorption isotherms without being restricted to choose among available parametric models.Item Open Access Obstacles, interfacial forms, and turbulence : a numerical analysis of soil-water evaporation across different interfaces(2020) Coltman, Edward; Lipp, Melanie; Vescovini, Andrea; Helmig, RainerExchange processes between a turbulent free flow and a porous media flow are sensitive to the flow dynamics in both flow regimes, as well as to the interface that separates them. Resolving these complex exchange processes across irregular interfaces is key in understanding many natural and engineered systems. With soil-water evaporation as the natural application of interest, the coupled behavior and exchange between flow regimes are investigated numerically, considering a turbulent free flow as well as interfacial forms and obstacles. Interfacial forms and obstacles will alter the flow conditions at the interface, creating flow structures that either enhance or reduce exchange rates based on their velocity conditions and their mixing with the main flow. To evaluate how these interfacial forms change the exchange rates, interfacial conditions are isolated and investigated numerically. First, different flow speeds are compared for a flat surface. Second, a porous obstacle of varied height is introduced at the interface, and the effects the flow structures that develop have on the interface are analyzed. The flow parameters of this obstacle are then varied and the interfacial exchange rates investigated. Next, to evaluate the interaction of flow structures between obstacles, a second obstacle is introduced, separated by a varied distance. Finally, the shape of these obstacles is modified to create different wave forms. Each of these interfacial forms and obstacles is shown to create different flow structures adjacent to the surface which alter the mass, momentum, and energy conditions at the interface. These changes will enhance the exchange rate in locations where higher velocity gradients and more mixing with the main flow develop, but will reduce the exchange rate in locations where low velocity gradients and limited mixing with the main flow occur.