993 resultados para Particle tracking detectors


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The paper presents, in three parts, a new approach to improve the detection and tracking performance of a track-while-scan radar. Part 1 presents a review of the current status of the subject. Part 2 details the new approach. It shows how a priori information provided by the tracker can be used to improve detection. It also presents a new multitarget tracking algorithm. In the present Part, analytical derivations are presented for assessing, a priori, the performance of the TWS radar system. True track initiation, false track initiation, true track continuation and false track deletion characteristics have been studied. It indicates how the various thresholds can be chosen by the designer to optimise performance. Simulation results are also presented.

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he paper presents, in three parts, a new approach to improve the detection and tracking performance of a track-while-scan (TWS) radar. Part 1 presents a review of current status. In this part, Part 2, it is shown how the detection can be improved by utilising information from tracker. A new multitarget tracking algorithm, capable of tracking manoeuvring targets in clutter, is then presented. The algorithm is specifically tailored so that the solution to the combinatorial problem presented in a companion paper can be applied. The implementation aspects are discussed and a multiprocessor architecture identified to realise the full potential of the algorithm. Part 3 presents analytical derivations for quantitative assessment of the performance of the TWS radar system. It also shows how the performance can be optimised.

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Several orientation and tracking systems employed in parabolic-cylindrical concentrators for focusing the direct solar radiation on the absorber tubes are analyzed from the technical and economic points of view. Case one, where the incidence factor was a function of declination and hour angle, showed that the maximum variations of incident factor from morning to noon was 0.5 at zero angle of declination. Case two, where the incidence factor was a function of declination, hour angle and latitude, showed the maximum variation of the incidence factor to be 0.128, which occurred during noon at the latitude of 30 degrees, corresponding to a change of declination from 0 to 23.5 degrees. In case three, the incidence factor, a function of declination only, showed that the maximum variation of the incidence factor corresponding to the change in declination from 0 to 23.5 degree was 0.0758. It is concluded that system three is the most efficient from the technical and economic point of view.

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A novel solid-solution precursor method for the preparation of fine-particle cobaltites at low temperatures has been described. The precursors, hydrazinium metal hydrazine carboxylate hydrates, N2H5M1/3Co2/3(N2H3COO)3 · H2O, where M = Mg, Mn, Fe, Co, Ni, and Zn, decompose in air <250°C to yield corresponding metal cobaltites, MCo2O4. Formation of cobaltites has been confirmed by thermogravimetry (TG) weight loss, IR, and X-ray diffraction. Combustion of the precursor in air yields fine-particle cobaltites with surface areas in the range of 12–115 m2g−1 and particle sizes of 1–40 μm. Low decomposition temperatures of the precursors accompanied by the evolution of large amounts of gases appear to control the particle size of the cobaltites.

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The microstructure of a cast Al---Si alloy-graphite particle composite is examined using optical and analytical scanning electron microscopy. Specimens containing different percentages of graphite were machined by orthogonal planning with 25° and 45° rake angle tools at both 6.5 and 13.2 m min−1. The machining forces are reported and the chip-rake-face friction coefficients and shear flow stresses are calculated. It is shown that the reduction in machining forces with increasing graphite content is due mostly to a decrease in the shear flow stress rather than to lower chip-rake-face friction. Both the polished and the machined surfaces of the composite are rougher than those of the simple alloy, apparently owing to the greater porosity, the tearing out of graphite particles, or the opening of cracks at the graphite particles in the wake of the tool.

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Synthesis of fine particle α-alumina and related oxide materials such as MgAl2O4, CaAl2O4, Y3Al5O12 (YAG), Image , β′-alumina, LaAlO3 and ruby powder (Image ) has been achieved at low temperatures (500°C) by the combustion of corresponding metal nitrate-urea mixtures. Solid combustion products have been identified by their characteristic X-ray diffraction patterns. The fine particle nature of α-alumina and related oxide materials has been investigated using SEM, TEM, particle size analysis and surface area measurements.

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Al-Si-graphite particle composite alloy pistons containing different percentages of about 80 μm uncoated graphite particles were successfully cast by foundry techniques. Tests with a 5 hp single-cylinder diesel engine show that Al-Si-graphite particle composite pistons can withstand an endurance test of 500 h without any apparent deterioration and do not seize during the running-in period. The use of the Al-Si-3% graphite particle composite piston also results in (a) up to 3% reduction in the specific fuel consumption, (b) considerable reduction in the wear of all four piston rings, (c) a reduction in piston wear, (d) a 9% reduction in the frictional horsepower losses of the engine as determined by the motoring test and (e) a slight increase in the exhaust gas temperature. These reductions (a)–(d) appear to be due to increased lubrication from the graphite particles which are smeared on the bearing surface, the higher damping capacity of the composite pistons and the reduced coefficient of thermal expansion of the composite pistons. Preliminary results indicate that aluminum-graphite particle composite alloy is a promising material for automotive pistons.

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Electrical properties of deep defects induced in n-silicon by -particles of about 10 MeV energy at a dose of 1014 and 1015 cm-2 are studied by DLTS. The levels at Ec -0.18 eV, Ec -0.26 eV, and Ec -0.48 eV are identified as A center, V2 (=/-) and V2 (-/0) on the basis of activation energy, electron capture cross section, and annealing behavior. Two other irradiation related levels at Ec -0.28 eV and Ec -0.51 eV could not be related to any known center.

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The optimum conditions for producing cast aluminium alloy-mica particle composites, by stirring mica particles (40 to 120 mgrm) in molten aluminium alloys (above their liquidus temperatures), followed by casting in permanent moulds, are described. Addition of magnesium either as pieces along with mica particles on the surface of the melts or as a previously added alloying element was found to be necessary to disperse appreciable quantities (1.5 to 2 wt.%) of mica particles in the melts and retain them as uniform dispersions in castings under the conditions of present investigation. These castings can be remelted and degassed with nitrogen at least once with the retention of about 80% mica particles in the castings. Electron probe micro-analysis of these cast composites showed that magnesium added to the surface of the melt along with mica has a tendency to segregate around the mica particles, apparently improving the dispersability for mica particles in liquid aluminium alloys. The mechanical properties of the aluminium alloy-mica particle composite decrease with an increase in mica content, however, even at 2.2% the composite has a tensile strength of 14.22 kg mm–2 with 1.1% elongation, a compression strength of 42.61 kg mm–2, and an impact strength of 0.30 kgm cm–2. The properties are adequate for certain bearing applications, and the aluminium-mica composite bearings were found to run under boundary lubrication, semi-dry and dry friction conditions whereas the matrix alloy (without mica) bearings seized or showed stick slip under the same conditions.

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The spreadability of SAE-30 oil on Al-12 Si base (LM-13) alloy containing dispersed graphite particles about 50 μm average size in its matrix is found to be greater than on either LM-13 with no graphite or brass. It is also found that the spreadability on LM-13 base alloys increase with increasing volume of graphite dispersion in the matrix of these alloys. Further increases in the spreadability of oil on machined LM-13-graphite particle composite test surfaces occur if these are rubbed initially against control discs of either LM-13 or grey cast iron. The formation of a triboinduced graphite-rich layer, confirmed by esca, appears to be responsible for the improved oil spreadability on the rubbed test surfaces of LM-13 base alloys as compared to the as-machined test surfaces prior to rubbing. The triboinduced layer of graphite is apparently responsible for the observed reduction in the friction, wear and seizing tendency of triboelements made from aluminium alloy-graphite particle composites.

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Screening of wastewater effluents from municipal and industrial wastewater treatment plants with biotests showed that the treated wastewater effluents possess only minor acute toxic properties towards whole organisms (e.g. bacteria, algae, daphnia), if any. In vitro tests (sub-mitochondrial membranes and fish hepatocytes) were generally more susceptible to the effluents. Most of the effluents indicated the presence of hormonally active compounds, as the production of vitellogenin, an egg yolk precursor protein, was induced in fish hepatocytes exposed to wastewater. In addition, indications of slight genotoxic potential was found in one effluent concentrate with a recombinant bacteria test. Reverse electron transport (RET) of mitochondrial membranes was used as a model test to conduct effluent assessment followed by toxicant characterisations and identifications. Using a modified U.S. EPA Toxicity Identification Evaluation Phase I scheme and additional case-specific methods, the main compound in a pulp and paper mill effluent causing RET inhibition was characterised to be an organic, relatively hydrophilic high molecular weight (HMW) compound. The toxicant could be verified as HMW lignin by structural analyses using nuclear magnetic resonance. In the confirmation step commercial and in-house extracted lignin products were used. The possible toxicity related structures were characterised by statistical analysis of the chemical breakdown structures of laboratory-scale pulping and bleaching effluents and the toxicities of these effluents. Finally, the biological degradation of the identified toxicant and other wastewater constituents was evaluated using bioassays in combination with chemical analyses. Biological methods have not been used routinely in establishing effluent discharge limits in Finland. However, the biological effects observed in this study could not have been predicted using only routine physical and chemical effluent monitoring parameters. Therefore chemical parameters cannot be considered to be sufficient in controlling effluent discharges especially in case of unknown, possibly bioaccumulative, compounds that may be present in small concentrations and may cause chronic effects.

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There is an increased interest on the use of UAVs for environmental research such as tracking bush fires, volcanic eruptions, chemical accidents or pollution sources. The aim of this paper is to describe the theory and results of a bio-inspired plume tracking algorithm. A method for generating sparse plumes in a virtual environment was also developed. Results indicated the ability of the algorithms to track plumes in 2D and 3D. The system has been tested with hardware in the loop (HIL) simulations and in flight using a CO2 gas sensor mounted to a multi-rotor UAV. The UAV is controlled by the plume tracking algorithm running on the ground control station (GCS).

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ALICE (A Large Ion Collider Experiment) is an experiment at CERN (European Organization for Nuclear Research), where a heavy-ion detector is dedicated to exploit the unique physics potential of nucleus-nucleus interactions at LHC (Large Hadron Collider) energies. In a part of that project, 716 so-called type V4 modules were assembles in Detector Laboratory of Helsinki Institute of Physics during the years 2004 - 2006. Altogether over a million detector strips has made this project the most massive particle detector project in the science history of Finland. One ALICE SSD module consists of a double-sided silicon sensor, two hybrids containing 12 HAL25 front end readout chips and some passive components, such has resistors and capacitors. The components are connected together by TAB (Tape Automated Bonding) microcables. The components of the modules were tested in every assembly phase with comparable electrical tests to ensure the reliable functioning of the detectors and to plot the possible problems. The components were accepted or rejected by the limits confirmed by ALICE collaboration. This study is concentrating on the test results of framed chips, hybrids and modules. The total yield of the framed chips is 90.8%, hybrids 96.1% and modules 86.2%. The individual test results have been investigated in the light of the known error sources that appeared during the project. After solving the problems appearing during the learning-curve of the project, the material problems, such as defected chip cables and sensors, seemed to induce the most of the assembly rejections. The problems were typically seen in tests as too many individual channel failures. Instead, the bonding failures rarely caused the rejections of any component. One sensor type among three different sensor manufacturers has proven to have lower quality than the others. The sensors of this manufacturer are very noisy and their depletion voltage are usually outside of the specification given to the manufacturers. Reaching 95% assembling yield during the module production demonstrates that the assembly process has been highly successful.

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In this paper, we examine approaches to estimate a Bayesian mixture model at both single and multiple time points for a sample of actual and simulated aerosol particle size distribution (PSD) data. For estimation of a mixture model at a single time point, we use Reversible Jump Markov Chain Monte Carlo (RJMCMC) to estimate mixture model parameters including the number of components which is assumed to be unknown. We compare the results of this approach to a commonly used estimation method in the aerosol physics literature. As PSD data is often measured over time, often at small time intervals, we also examine the use of an informative prior for estimation of the mixture parameters which takes into account the correlated nature of the parameters. The Bayesian mixture model offers a promising approach, providing advantages both in estimation and inference.