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Projector-based displays have been evolving tremendously in the last decade. Reduced costs and increasing capabilities have let to a widespread use for home entertainment and scientific visualization. The rapid development is continuing - techniques that allow seamless projection onto complex everyday environments such as textured walls, window curtains or bookshelfs have recently been proposed. Although cameras enable a completely automatic calibration of the systems, all previously described techniques rely on a precise mapping between projector and camera pixels. Global illumination effects such as reflections, refractions, scattering, dispersion etc. are completely ignored since only direct illumination is taken into account. We propose a novel method that applies the light transport matrix for performing an image-based radiometric compensation which accounts for all possible lighting effects. For practical application the matrix is decomposed into clusters of mutually influencing projector and camera pixels. The compensation is modeled as a linear equation system that can be solved separately for each cluster. For interactive compensation rates this model is adapted to enable an efficient implementation on programmable graphics hardware. Applying the light transport matrix's pseudo-inverse allows to separate the compensation into a computational expensive preprocessing step (computing the pseudo-inverse) and an on-line matrix-vector multiplication. The generalized mathematical foundation for radiometric compensation with projector-camera systems is validated with several experiments. We show that it is possible to project corrected imagery onto complex surfaces such as an inter-reflecting statuette and glass. The overall sharpness of defocused projections is increased as well. Using the proposed optimization for GPUs, real-time framerates are achieved.
In displacement oriented methods of structural mechanics may static and dynamic equilibrium conditions lead to large coupled nonlinear systems of equations. In many cases they are solved iteratively utilizing derivatives of Newton's method. Alternatively, the equations may be expressed in terms of the Karush-Kuhn-Tucker conditions of an optimization problem and, therefore, may be solved using methods of mathematical programming. To begin with, the work deals with the fundamentals of the formulation as optimization problem. In particular, the requirements of material nonlinearity and contact situations are analyzed. Proximately, an algorithm is implemented which utilizes the usually sparse structure of the Hessian matrix, whereby particularly the convergence behaviour is analyzed and adjusted. The implementation was tested using examples from statics and dynamics of large systems. The results are verified considering the accuracy comparing alternative solutions (e.g. explicit methods). The potential areas of application is shown and the efficiency of the method is evaluated.
Die Entstehung des Baugrundes ist geprägt durch die Genese und von anthropogenen Einflüssen. In der Arbeit werden auf der Grundlage isotroper Betrachtungen im Halbraum Prognosen für unbeprobte Bereiche eines linienförmigen Bauwerkes erstellt. Aufbauend auf dem bekannten Algorithmus der Geostatistik werden Berechnungen mit deterministischen Eingangsgrößen durchgeführt. Diese sind in einem Datensatz zusammengefasst und gehen ohne Unterteilung bzw. Bildung von (Homogen)Bereichen in die Schätzungen ein. Zur Anwendung kam dabei die an der Professur Grundbau der Bauhaus-Universität Weimar entwickelte Software GeoStat. Nach der Variogrammanalyse folgten geostatistische Berechnungen mit dem Ordinary und dem Universal Kriging. Der genutzte Datensatz unterlag dabei mehrfachen Modifikationen, um Unterschiede in der Ergebnisbildung beobachten zu können. Die Krigingschätzungen wurden für subjektiv ausgewählte Beprobungspunkte erstellt, die mit Referenzprofilen verglichen werden konnten. Im Ergebnis traten für alle durchgeführten Simulationen erhebliche Abweichungen der berechneten Werte zu den Referenzprofilen auf. Die Verwendung von Datensätzen ohne eine vorherige Bearbeitung und Unterteilung in Homogenbereiche erweist sich als nicht ratsam. Vielmehr ist es notwendig kompliziertere Krigingvarianten einzusetzen bzw. die benutzten Methoden mit anderen Verfahren zu kombinieren.
Renewable energy use is on the rise and these alternative resources of energy can help combat with the climate change. Around 80% of the world's electricity comes from coal and petroleum however, the renewables are the fastest growing source of energy in the world. Solar, wind, hydro, geothermal and biogas are the most common forms of renewable energy. Among them, wind energy is emerging as a reliable and large-scaled source of power production. The recent research and confidence in the performance has led to the construction of more and bigger wind turbines around the world. As wind turbines are getting bigger, a concern regarding their safety is also in discussion. Wind turbines are expensive machinery to construct and the enormous capital investment is one of the main reasons, why many countries are unable to adopt to the wind energy. Generally, a reliable wind turbine will result in better performance and assist in minimizing the cost of operation. If a wind turbine fails, it's a loss of investment and can be harmful for the surrounding habitat. This thesis aims towards estimating the reliability of an offshore wind turbine. A model of Jacket type offshore wind turbine is prepared by using finite element software package ABAQUS and is compared with the structural failure criteria of the wind turbine tower. UQLab, which is a general uncertainty quantification framework developed at ETH Zürich, is used for the reliability analysis. Several probabilistic methods are included in the framework of UQLab, which include Monte Carlo, First Order Reliability Analysis and Adaptive Kriging Monte Carlo simulation. This reliability study is performed only for the structural failure of the wind turbine but it can be extended to many other forms of failures e.g. reliability for power production, or reliability for different component failures etc. It's a useful tool that can be utilized to estimate the reliability of future wind turbines, that could result in more safer and better performance of wind turbines.