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Year of publication
- 2019 (33) (remove)
Due to an increased need for hydro-electricity, water storage, and flood protection, it is assumed that a series of new dams will be built throughout the world. Comparing existing design methodologies for arch-type dams, model-based shape optimization can effectively reduce construction costs and leverage the properties of construction materials. To apply the means of shape optimization, suitable variables need to be chosen to formulate the objective function, which is the volume of the arch dam here. In order to increase the consistency with practical conditions, a great number of geometrical and behavioral constraints are included in the mathematical model. An optimization method, namely Genetic Algorithm is adopted which allows a global search.
Traditional optimization techniques are realized based on a deterministic approach, which means that the material properties and loading conditions are assumed to be fixed values. As a result, the real-world structures that are optimized by these approaches suffer from uncertainties that one needs to be aware of. Hence, in any optimization process for arch dams, it is nec- essary to find a methodology that is capable of considering the influences of uncertainties and generating a solution which is robust enough against the uncertainties.
The focus of this thesis is the formulation and the numerical method for the optimization of the arch dam under the uncertainties. The two main models, the probabilistic model, and non-probabilistic models are intro- duced and discussed. Classic procedures of probabilistic approaches un- der uncertainties, such as RDO (robust design optimization) and RBDO (reliability-based design optimization), are in general computationally ex- pensive and rely on estimates of the system’s response variance and fail- ure probabilities. Instead, the robust optimization (RO) method which is based on the non-probabilistic model, will not follow a full probabilistic approach but works with pre-defined confidence levels. This leads to a bi-level optimization program where the volume of the dam is optimized under the worst combination of the uncertain parameters. By this, robust and reliable designs are obtained and the result is independent of any as- sumptions on stochastic properties of the random variables in the model.
The optimization of an arch-type dam is realized here by a robust optimiza- tion method under load uncertainty, where hydraulic and thermal loads are considered. The load uncertainty is modeled as an ellipsoidal expression. Comparing with any traditional deterministic optimization (DO) method, which only concerns the minimum objective value and offers a solution candidate close to limit-states, the RO method provides a robust solution against uncertainties.
All the above mentioned methods are applied to the optimization of the arch dam to compare with the optimal design with DO methods. The re- sults are compared and analyzed to discuss the advantages and drawbacks of each method.
In order to reduce the computational cost, a ranking strategy and an ap- proximation model are further involved to do a preliminary screening. By means of these, the robust design can generate an improved arch dam structure which ensures both safety and serviceability during its lifetime.
The task-based view of web search implies that retrieval should take the user perspective into account. Going beyond merely retrieving the most relevant result set for the current query, the retrieval system should aim to surface results that are actually useful to the task that motivated the query.
This dissertation explores how retrieval systems can better understand and support their users’ tasks from three main angles: First, we study and quantify search engine user behavior during complex writing tasks, and how task success and behavior are associated in such settings. Second, we investigate search engine queries formulated as questions, and explore patterns in a large query log that may help search engines to better support this increasingly prevalent interaction pattern. Third, we propose a novel approach to reranking the search result lists produced by web search engines, taking into account retrieval axioms that formally specify properties of a good ranking.
Focusing on the neoliberal symbolic urban reconstruction of the Macedonian capital, known as “Skopje 2014”, the PhD work deals with urban space production through storytelling. Embracing the criticism put forward in the political, cultural and social debates that have spun around Skopje’s reconstruction, the artistic-based research sought to relate and analyze the symbolic narratives of “Skopje 2014” and the vernacular and civic narratives of Skopje and locate overlapping, divergent, complementary or conflictual aspects of their respective narrative structures. Informed by subjective citizens’ stories and experiences of the urban as well as binaural sonic observations of the city, the research findings were presented in the form of an interactive audio guided walk through the city. The thesis is organized in three chapters, preceded by an INTRODUCTION and followed by a CONCLUSION. CHAPTER ONE sets the theoretical context, presents the case study “Skopje 2014”, and discusses the research design. The audio guided walk is presented in CHAPTER TWO. Its content consists of five tracks, or subchapters, conceptualized and named as five different aspects of the city: THE MODERNIST CITY, THE FEMALE CITY, THE MEMORY CITY, THE POSTCOMMUNIST CITY and THE TOURIST CITY, according to the discourses related to these tracks. CHAPTER THREE, the EPILOGUE, is the final discussion of the research project, in which several meta-conclusions are drawn.
Die Gase Sauerstoff und Stickstoff werden für eine Vielzahl an technischen, industriellen, biologischen und medizinischen Einsatzzwecken benötigt. So liegen Anwendungsgebiete dieser Gase neben der klassischen metallverarbeitenden und der chemischen Industrie bei Sauerstoff vor allem in der Medizin, Verbrennungs- und Kläranlagenoptimierung sowie der Fischzucht und bei Stickstoff als Schutz- beziehungsweise Inertgas in der Kunststoffindustrie, der Luft- und Raumfahrt sowie dem Brandschutz.
Die Bereitstellung der Gase Sauerstoff und Stickstoff wird nahezu ausschließlich durch die Abtrennung aus der Umgebungsluft realisiert, welche aus ca. 78 Vol.-% Stickstoff, 21 Vol.-% Sauerstoff und 1 Vol.-% Spurengasen (Ar, CO2, Ne, He, ...) besteht. Am Markt etablierte Verfahren der Luftzerlegung sind das Linde-, das PSA- (pressure swing adsorption/Druckwechseladsorption) oder verschiedene Membran-Verfahren. Hierdurch werden die benötigten Gase entweder direkt vor Ort beim Verbraucher erzeugt (PSA- und Polymer-Membranverfahren: geringe Reinheiten) oder zentral in großen Anlagen hergestellt (Linde-Verfahren: hohe Reinheiten) und anschließend zum Verbraucher in Form von Flaschen- oder Tankgasen geliefert (Tansportkosten).
Für kleinere Verbraucher mit hohen Ansprüchen an die Reinheit des benötigten Sauerstoffs beziehungsweise Stickstoffs ergibt sich nur die Möglichkeit, die Gase als kostenintensive Transportgase zentraler Gaseversorger zu beziehen und sich somit in eine Abhängigkeit (Lieferverträge, Flaschen-/Tankmieten, ...) zu diesen zu begeben sowie eine eigene Lagerhaltung für die benötigten Gase (Mehraufwand, Lagerkosten, Platzbedarf) zu betreiben.
Ziel dieser Arbeit ist es, keramische Material-Systeme auf Basis chemischer Hochtemperatur-Reaktionen als Reaktive Oxidkeramiken zu entwickeln und diese hinsichtlich eines möglichen Einsatzes für die Sauerstoffseparation in neuartigen Luftzerlegungsanlagen zu untersuchen.
Derartige Anlagen sollen in ihrem Prinzip an die regenerative Sauerstoffseparation angelehnt sein und in ihren Reaktoren die Reaktiven Oxidkeramiken als Festbett-Material abwechselnd mit Luft be- und Vakuum oder O2-armen Atmosphären entladen.
Die Verwendung Reaktiver Oxidkeramiken, welche im Vergleich zu den bisherigen Materialien höhere Sauerstoffaustauschmengen und -raten bei gleichzeitig hoher Lebensdauer und Korrosionsbeständigkeit sowie relativ einfacher Handhabe aufweisen würden, soll ein Schritt in Richtung einer effizienten alternativen Luftzerlegungstechnologie sein.
Mit den Reaktiven Oxidkeramiken in einer Luftzerlegungsanlage sollte es im besten Fall möglich sein, in kleinen Anlagen sehr reinen Sauerstoff und zugleich sauerstofffreies Inertgas zu erzeugen sowie eine Sauerstoffan- oder -abreicherung von Luft, Prozess- oder Abgasen zu generieren.
Somit besäße eine solche, auf Reaktiven Oxidkeramiken basierende Technologie sehr weit gefächerte Einsatzgebiete und demzufolge ein enormes wirtschaftliches Potential.
Turbomachinery plays an important role in many cases of energy generation or conversion. Therefore, turbomachinery is a promising approaching point for optimization in order to increase the efficiency of energy use. In recent years, the use of automated optimization strategies in combination with numerical simulation has become increasingly popular in many fields of engineering. The complex interactions between fluid and solid mechanics encountered in turbomachines on the one hand and the high computational expense needed to calculate the performance on the other hand, have, however, prevented a widespread use of these techniques in this field of engineering. The objective of this work was the development of a strategy for efficient metamodel based optimization of centrifugal compressor impellers. In this context, the main focus is the reduction of the required numerical expense. The central idea followed in this research was the incorporation of preliminary information acquired from low-fidelity computation methods and empirical correlations into the sampling process to identify promising regions of the parameter space. This information was then used to concentrate the numerically expensive high-fidelity computations of the fluid dynamic and structure mechanic performance of the impeller in these regions while still maintaining a good coverage of the whole parameter space. The development of the optimization strategy can be divided into three main tasks. Firstly, the available preliminary information had to be researched and rated. This research identified loss models based on one dimensional flow physics and empirical correlations as the best suited method to predict the aerodynamic performance. The loss models were calibrated using available performance data to obtain a high prediction quality. As no sufficiently exact models for the prediction of the mechanical loading of the impellercould be identified, a metamodel based on finite element computations was chosen for this estimation. The second task was the development of a sampling method which concentrates samples in regions of the parameter space where high quality designs are predicted by the preliminary information while maintaining a good overall coverage. As available methods like rejection sampling or Markov-chain Monte-Carlo methods did not meet the requirements in terms of sample distribution and input correlation, a new multi-fidelity sampling method called “Filtered Sampling“has been developed. The last task was the development of an automated computational workflow. This workflow encompasses geometry parametrization, geometry generation, grid generation and computation of the aerodynamic performance and the structure mechanic loading. Special emphasis was put into the development of a geometry parametrization strategy based on fluid mechanic considerations to prevent the generation of physically inexpedient designs. Finally, the optimization strategy, which utilizes the previously developed tools, was successfully employed to carry out three optimization tasks. The efficiency of the method was proven by the first and second testcase where an existing compressor design was optimized by the presented method. The results were comparable to optimizations which did not take preliminary information into account, while the required computational expense cloud be halved. In the third testcase, the method was applied to generate a new impeller design. In contrast to the previous examples, this optimization featuredlargervariationsoftheimpellerdesigns. Therefore, theapplicability of the method to parameter spaces with significantly varying designs could be proven, too.
Railway systems are highly competitive compared with other means of transportation because of their distinct advantages in speed, convenience and safety. Therefore, the demand for railway transportation is increasing around the world. Constructing railway tracks and related engineering structures in areas with loose or soft cohesive subgrade usually leads to problems, such as excessive settlement, deformation and instability. Several remedies have been proposed to avoid or reduce such problems, including the replacement of soft soil and the construction of piles or stone columns.
This thesis aims to expand the geotechnical knowledge of how to improve subgrade ballasted railway tracks, using stone columns and numerical modeling for the railway infrastructure. Three aspects are considered: i) railway track dynamics modeling and validation by field measurements, ii) modeling and parametric studies on stone columns, and iii) studies on the linear and non-linear behavior of stone columns under the dynamic load of trains.
The first step of this research was to develop a reliable numerical model of a railway track. The finite element method in a time domain was used for either a 2D plane strain or 3D analysis. Individual methods for modeling a train load in 2D and 3D were implemented and are discussed in this thesis. The developed loading method was validated with three different railway tracks using obtained vibration measurements. Later, these numerical models were used to analyze the influence of stone column length and train speed in the stress field.
The performance of the treated ground depends on various parameters, such as the strength of stone columns, spacing, length and diameter of the columns. Therefore, the second step was devoted to a parameter study of stone columns as a unit cell with an axisymmetric condition. The results showed that even short stone columns were effective for settlement reduction, and area of replacement was the main influential parameter in their performance.
The third part of this thesis focuses on a hypothetical railway-track response to the passage of various train speeds and the influence of stone-column length. The stress-strain response of subgrade is analyzed under either an elastic–perfectly plastic or advanced constitutive model. The non-linear soil response in the finite element method and the impact of train speed and stone column length on railway tracks are also evaluated. Moreover, the reductions of induced vibration – in both a horizontal and a vertical direction – after improvement are investigated.
Großsiedlungen sind nicht nur ein Erbe der Moderne, sondern seit über drei Jahrzehnten Gegenstand der Stadterneuerung. Dieses Buch erörtert, was eine heute „normale“ Großsiedlung stadtplanerisch benötigt und welche stadtentwicklungs- als auch wohnungspolitisch gesteuerten Ressourcen in einer integrierten Planungssteuerung gebündelt werden sollten. Dabei wird das grundsätzliche Planungsinstrument des Quartiersmanagements aktualisiert – über den Gegenstand Großsiedlungen hinaus.
Matrix-free voxel-based finite element method for materials with heterogeneous microstructures
(2019)
Modern image detection techniques such as micro computer tomography
(μCT), magnetic resonance imaging (MRI) and scanning electron microscopy (SEM) provide us with high resolution images of the microstructure of materials in a non-invasive and convenient way. They form the basis for the geometrical models of high-resolution analysis, so called image-based analysis.
However especially in 3D, discretizations of these models reach easily the size of 100 Mill. degrees of freedoms and require extensive hardware resources in terms of main memory and computing power to solve the numerical model. Consequently, the focus of this work is to combine and adapt numerical solution methods to reduce the memory demand first and then the computation time and therewith enable an execution of the image-based analysis on modern computer desktops. Hence, the numerical model is a straightforward grid discretization of the voxel-based (pixels with a third dimension) geometry which omits the boundary detection algorithms and allows reduced storage of the finite element data structure and a matrix-free solution algorithm.
This in turn reduce the effort of almost all applied grid-based solution techniques and results in memory efficient and numerically stable algorithms for the microstructural models. Two variants of the matrix-free algorithm are presented. The efficient iterative solution method of conjugate gradients is used with matrix-free applicable preconditioners such as the Jacobi and the especially suited multigrid method. The jagged material boundaries of the voxel-based mesh are smoothed through embedded boundary elements which contain different material information at the integration point and are integrated sub-cell wise though without additional boundary detection. The efficiency of the matrix-free methods can be retained.
This thesis addresses an adaptive higher-order method based on a Geometry Independent Field approximatTion(GIFT) of polynomial/rationals plines over hierarchical T-meshes(PHT/RHT-splines).
In isogeometric analysis, basis functions used for constructing geometric models in computer-aided design(CAD) are also employed to discretize the partial differential equations(PDEs) for numerical analysis. Non-uniform rational B-Splines(NURBS) are the most commonly used basis functions in CAD. However, they may not be ideal for numerical analysis where local refinement is required.
The alternative method GIFT deploys different splines for geometry and numerical analysis. NURBS are utilized for the geometry representation, while for the field solution, PHT/RHT-splines are used. PHT-splines not only inherit the useful properties of B-splines and NURBS, but also possess the capabilities of local refinement and hierarchical structure. The smooth basis function properties of PHT-splines make them suitable for analysis purposes. While most problems considered in isogeometric analysis can be solved efficiently when the solution is smooth, many non-trivial problems have rough solutions. For example, this can be caused by the presence of re-entrant corners in the domain. For such problems, a tensor-product basis (as in the case of NURBS) is less suitable for resolving the singularities that appear since refinement propagates throughout the computational domain. Hierarchical bases and local refinement (as in the case of PHT-splines) allow for a more efficient way to resolve these singularities by adding more degrees of freedom where they are necessary. In order to drive the adaptive refinement, an efficient recovery-based error estimator is proposed in this thesis. The estimator produces a recovery solution which is a more accurate approximation than the computed numerical solution. Several two- and three-dimensional numerical investigations with PHT-splines of higher order and continuity prove that the proposed method is capable of obtaining results with higher accuracy, better convergence, fewer degrees of freedom and less computational cost than NURBS for smooth solution problems. The adaptive GIFT method utilizing PHT-splines with the recovery-based error estimator is used for solutions with discontinuities or singularities where adaptive local refinement in particular domains of interest achieves higher accuracy with fewer degrees of freedom. This method also proves that it can handle complicated multi-patch domains for two- and three-dimensional problems outperforming uniform refinement in terms of degrees of freedom and computational cost.
Modern immersive telepresence systems enable people at different locations to meet in virtual environments using realistic three-dimensional representations of their bodies. For the realization of such a three-dimensional version of a video conferencing system, each user is continuously recorded in 3D. These 3D recordings are exchanged over the network between remote sites. At each site, the remote recordings of the users, referred to as 3D video avatars, are seamlessly integrated into a shared virtual scenery and displayed in stereoscopic 3D for each user from his or her perspective.
This thesis reports on algorithmic and technical contributions to modern immersive telepresence systems and presents the design, implementation and evaluation of the first immersive group-to-group telepresence system in which each user is represented as realistic life-size 3D video avatar. The system enabled two remote user groups to meet and collaborate in a consistent shared virtual environment. The system relied on novel methods for the precise calibration and registration of color- and depth- sensors (RGBD) into the coordinate system of the application as well as an advanced distributed processing pipeline that reconstructs realistic 3D video avatars in real-time. During the course of this thesis, the calibration of 3D capturing systems was greatly improved. While the first development focused on precisely calibrating individual RGBD-sensors, the second stage presents a new method for calibrating and registering multiple color and depth sensors at a very high precision throughout a large 3D capturing volume. This method was further refined by a novel automatic optimization process that significantly speeds up the manual operation and yields similarly high accuracy. A core benefit of the new calibration method is its high runtime efficiency by directly mapping from raw depth sensor measurements into an application coordinate system and to the coordinates of its associated color sensor. As a result, the calibration method is an efficient solution in terms of precision and applicability in virtual reality and immersive telepresence applications. In addition to the core contributions, the results of two case studies which address 3D reconstruction and data streaming lead to the final conclusion of this thesis and to directions of future work in the rapidly advancing field of immersive telepresence research.