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After a short introduction of a new nonconforming linear finite element on quadrilaterals recently developed by Park, we derive a dual weighted residual-based a posteriori error estimator (in the sense of Becker and Rannacher) for this finite element. By computing a corresponding dual solution we estimate the error with respect to a given target error functional. The reliability and efficiency of this estimator is analyzed in several numerical experiments.
The ClearPET® scanners developed by the Crystal Clear Collaboration use multichannel PMTs as photodetectors with scintillator pixels coupled individually to each channel. In order to localize an event each channel anode is connected to a comparator that triggers when the anode signal exceeds a common predefined threshold. Two major difficulties here are crosstalk of light and the gain nonuniformity of the PMT channels. Crosstalk can generate false triggering in channels adjacent to the actual event. On the one hand this can be suppressed by sufficiently increasing the threshold, but on the other hand a threshold too high can already prevent valid events on the lower gain channels from being detected. Finally, both effects restrict the dynamic range of pulse heights that can be processed. The requirements to the dynamic range are not low as the ClearPET® scanners detect the depth of interaction by phoswich pixels consisting of LSO and Lu0.7Y0.3AP, two scintillators with different light yields. We will present a model to estimate the achievable dynamic range and show solutions to increase it.
Erforderliche Einspanntiefe von Stahlstützen in Betonfundamenten / Kindmann, Rolf ; Laumann, Jörg
(2005)
Ermittlung von Eigenwerten und Eigenformen für Stäbe und Stabwerke / Kindmann, Rolf ; Laumann, Jörg
(2005)
Flow visualization by means of PIV of an artificial aortic heart valve fixed into a mock aorta
(2005)
Formeln statt Zahlen : Referenzwerte Formeln zur energetischen Bewertung von Produktionsanlagen
(2005)
Geotechnik
(2005)
Low-thrust space propulsion systems enable flexible high-energy deep space missions, but the design and optimization of the interplanetary transfer trajectory is usually difficult. It involves much experience and expert knowledge because the convergence behavior of traditional local trajectory optimization methods depends strongly on an adequate initial guess. Within this extended abstract, evolutionary neurocontrol, a method that fuses artificial neural networks and evolutionary algorithms, is proposed as a smart global method for low-thrust trajectory optimization. It does not require an initial guess. The implementation of evolutionary neurocontrol is detailed and its performance is shown for an exemplary mission.
Heerlen: Broken Glass
(2005)
This study has been performed to design the combination of the new ClearPET (ClearPET is a trademark of the Crystal Clear Collaboration), a small animal positron emission tomography (PET) system, with a micro-computed tomography (microCT) scanner. The properties of different microCT systems have been determined by simulations based on GEANT4. We will demonstrate the influence of the detector material and the X-ray spectrum on the obtained contrast. Four different detector materials (selenium, cadmium zinc telluride, cesium iodide and gadolinium oxysulfide) and two X-ray spectra (a molybdenum and a tungsten source) have been considered. The spectra have also been modified by aluminum filters of varying thickness. The contrast between different tissue types (water, air, brain, bone and fat) has been simulated by using a suitable phantom. The results indicate the possibility to improve the image contrast in microCT by an optimized combination of the X-ray source and detector material.
Mikrokleben
(2005)
Miniaturised reference electrodes for field-effect sensors compatible to silicon chip technology
(2005)
Mit Logik die Welt begreifen
(2005)
Multiple Near-Earth Asteroid Rendezvous and Sample Return Using First Generation Solar Sailcraft
(2005)
Numerik-Algorithmen : Verfahren, Beispiele, Anwendungen. - 9., vollst. überarb. und erw. Aufl.
(2005)
Searching optimal interplanetary trajectories for low-thrust spacecraft is usually a difficult and time-consuming task that involves much experience and expert knowledge in astrodynamics and optimal control theory. This is because the convergence behavior of traditional local optimizers, which are based on numerical optimal control methods, depends on an adequate initial guess, which is often hard to find, especially for very-low-thrust trajectories that necessitate many revolutions around the sun. The obtained solutions are typically close to the initial guess that is rarely close to the (unknown) global optimum. Within this paper, trajectory optimization problems are attacked from the perspective of artificial intelligence and machine learning. Inspired by natural archetypes, a smart global method for low-thrust trajectory optimization is proposed that fuses artificial neural networks and evolutionary algorithms into so-called evolutionary neurocontrollers. This novel method runs without an initial guess and does not require the attendance of an expert in astrodynamics and optimal control theory. This paper details how evolutionary neurocontrol works and how it could be implemented. The performance of the method is assessed for three different interplanetary missions with a thrust to mass ratio <0.15mN/kg (solar sail and nuclear electric).