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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).
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.
[{ReN(PMe2Ph)3}{ReO3N}]2 – Structural Evidence for the Nitridotrioxorhenate(VII) Anion, [ReO3N]2−
(2005)
Verformungsbasierter seismischer Nachweis von Mauerwerksbauten mit der Kapazitätsspektrum-Methode
(2005)
Formeln statt Zahlen : Referenzwerte Formeln zur energetischen Bewertung von Produktionsanlagen
(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.
The ClearPET™ project: Development of a 2nd generation high-performance small animal PET scanner
(2005)
Second generation high-performance PET scanners, called ClearPET™1, have been developed by working groups of the Crystal Clear Collaboration (CCC). High sensitivity and high spatial resolution for the ClearPET camera is achieved by using a phoswich arrangement combining two different types of lutetium-based scintillator materials: LSO from CTI and LuYAP:Ce from the CCC (ISTC project). In a first ClearPET prototype, phoswich arrangements of 8×8 crystals of 2×2×10 mm3 are coupled to multi-channel photomultiplier tubes (Hamamatsu R7600). A unit of four PMTs arranged in-line represents one of 20 sectors of the ring design. The opening diameter of the ring is 120 mm, the axial detector length is 110 mm.The PMT pulses are digitized by free-running ADCs and digital data processing determines the gamma energy, the phoswich layer and even the exact pulse starting time, which is subsequently used for coincidence detection. The gantry allows rotation of the detector modules around the field of view.
Preliminary data shows a correct identification of the crystal layer about (98±1)%. Typically the energy resolution is (23.3±0.5)% for the luyap layer and (15.4±0.4)% for the lso layer. early studies showed the timing resolution of 2 ns FWHM and 4.8 ns FWTM. the intrinsic spatial resolution ranges from 1.37 mm to 1.61 mm full-width of half-maximum (FWHM) with a mean of 1.48 mm FWHM. further improvements in image and energy resolution are expected when the system geometry is fully modeled.
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.