82 resultados para Density-based Scanning Algorithm


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Platinum plays an important role in catalysis and electrochemistry, and it is known that the direct interaction of oxygen with Pt surfaces can lead to the formation of platinum oxides (PtO(x)), which can affect the reactivity. To contribute to the atomistic understanding of the atomic structure of PtO(x), we report a density functional theory study of the atomic structure of bulk PtO(x) (1 <= x <= 2). From our calculations, we identified a lowest-energy structure (GeS type, space group Pnma) for PtO, which is 0.181 eV lower in energy than the structure suggested by W. J. Moore and L. Pauling [J. Am. Chem. Soc. 63, 1392 (1941)] (PtS type). Furthermore, two atomic structures were identified for PtO(2), which are almost degenerate in energy with the lowest-energy structure reported so far for PtO(2) (CaCl(2) type). Based on our results and analysis, we suggest that Pt and O atoms tend to form octahedron motifs in PtO(x) even at lower O composition by the formation of Pt-Pt bonds.

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Southeastern Brazil has seen dramatic landscape modifications in recent decades, due to expansion of agriculture and urban areas; these changes have influenced the distribution and abundance of vertebrates. We developed predictive models of ecological and spatial distributions of capybaras (Hydrochoerus hydrochaeris) using ecological niche modeling. Most Occurrences of capybaras were in flat areas with water bodies Surrounded by sugarcane and pasture. More than 75% of the Piracicaba River basin was estimated as potentially habitable by capybara. The models had low omission error (2.3-3.4%), but higher commission error (91.0-98.5%); these ""model failures"" seem to be more related to local habitat characteristics than to spatial ones. The potential distribution of capybaras in the basin is associated with anthropogenic habitats, particularly with intensive land use for agriculture.

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The degree of homogeneity is normally assessed by the variability of the results of independent analyses of several (e.g., 15) normal-scale replicates. Large sample instrumental neutron activation analysis (LS-INAA) with a collimated Ge detector allows inspecting the degree of homogeneity of the initial batch material, using a kilogram-size sample. The test is based on the spatial distributions of induced radioactivity. Such test was applied to samples of Brazilian whole (green) coffee beans (Coffea arabica and Coffea canephora) of approximately I kg in the frame of development of a coffee reference material. Results indicated that the material do not contain significant element composition inhomogeneities between batches of approximately 30-50 g, masses typically forming the starting base of a reference material.

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In this work, the synthesis of Y(2)O(3) stabilized tetragonal zirconia polycrystals (Y-TZP)-alumina (Al(2)O(3)) powder mixture was performed by high-energy ball milling and the sintering behavior of this composite was investigated. In order to understand the phase transformations occurring during ball milling, samples were collected after different milling times, from 1 to 60 h. The milled powders were compacted by cold uniaxial pressing and sintered at 1400 and 1600 degrees C. Both powders and sintered samples were characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), energy dispersive spectrometry analysis (EDS) and mechanical properties. Fully dense samples were obtained after sintering at 1600 degrees C, while the samples sintered at 1400 degrees C presented a full density for powder mixtures milled for 30 and 60 h. Fracture toughness and Vickers hardnessvalues of the Y-T-ZP/Al(2)O(3) nanocomposite were improved due to dispersed Al(2)O(3) grains and reduced ZrO(2) grain size. Samples sintered at 1400 degrees C, based on powders milled for 60 h, presented high K(IC) and hardness values near to 8.0 Mpan(1/2) and 15 GPa, respectively (C) 2008 Elsevier B.V. All rights reserved

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The power transformer is a piece of electrical equipment that needs continuous monitoring and fast protection since it is very expensive and an essential element for a power system to perform effectively. The most common protection technique used is the percentage differential logic, which provides discrimination between an internal fault and different operating conditions. Unfortunately, there are some operating conditions of power transformers that can affect the protection behavior and the power system stability. This paper proposes the development of a new algorithm to improve the differential protection performance by using fuzzy logic and Clarke`s transform. An electrical power system was modeled using Alternative Transients Program (ATP) software to obtain the operational conditions and fault situations needed to test the algorithm developed. The results were compared to a commercial relay for validation, showing the advantages of the new method.

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The power loss reduction in distribution systems (DSs) is a nonlinear and multiobjective problem. Service restoration in DSs is even computationally hard since it additionally requires a solution in real-time. Both DS problems are computationally complex. For large-scale networks, the usual problem formulation has thousands of constraint equations. The node-depth encoding (NDE) enables a modeling of DSs problems that eliminates several constraint equations from the usual formulation, making the problem solution simpler. On the other hand, a multiobjective evolutionary algorithm (EA) based on subpopulation tables adequately models several objectives and constraints, enabling a better exploration of the search space. The combination of the multiobjective EA with NDE (MEAN) results in the proposed approach for solving DSs problems for large-scale networks. Simulation results have shown the MEAN is able to find adequate restoration plans for a real DS with 3860 buses and 632 switches in a running time of 0.68 s. Moreover, the MEAN has shown a sublinear running time in function of the system size. Tests with networks ranging from 632 to 5166 switches indicate that the MEAN can find network configurations corresponding to a power loss reduction of 27.64% for very large networks requiring relatively low running time.

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This research presents a method for frequency estimation in power systems using an adaptive filter based on the Least Mean Square Algorithm (LMS). In order to analyze a power system, three-phase voltages were converted into a complex signal applying the alpha beta-transform and the results were used in an adaptive filtering algorithm. Although the use of the complex LMS algorithm is described in the literature, this paper deals with some practical aspects of the algorithm implementation. In order to reduce computing time, a coefficient generator was implemented. For the algorithm validation, a computing simulation of a power system was carried Out using the ATP software. Many different situations were Simulated for the performance analysis of the proposed methodology. The results were compared to a commercial relay for validation, showing the advantages of the new method. (C) 2009 Elsevier Ltd. All rights reserved.

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A technique for improving the performance of an OSNR monitor based on a polarisation nulling method with the downhill simplex algorithm is demonstrated. Establishing a compromise between accuracy and acquisition time, the monitor has been calibrated to 0.72 dB/390 ms and 0.98 dB/320 ms, over a range of nearly 21 dB. As far as is known, these are the best values achieved with such an OSNR monitoring method.

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This work presents the study and development of a combined fault location scheme for three-terminal transmission lines using wavelet transforms (WTs). The methodology is based on the low- and high-frequency components of the transient signals originated from fault situations registered in the terminals of a system. By processing these signals and using the WT, it is possible to determine the time of travelling waves of voltages and/or currents from the fault point to the terminals, as well as estimate the fundamental frequency components. A new approach presents a reliable and accurate fault location scheme combining some different solutions. The main idea is to have a decision routine in order to select which method should be used in each situation presented to the algorithm. The combined algorithm was tested for different fault conditions by simulations using the ATP (Alternative Transients Program) software. The results obtained are promising and demonstrate a highly satisfactory degree of accuracy and reliability of the proposed method.

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The main objective of this paper is to relieve the power system engineers from the burden of the complex and time-consuming process of power system stabilizer (PSS) tuning. To achieve this goal, the paper proposes an automatic process for computerized tuning of PSSs, which is based on an iterative process that uses a linear matrix inequality (LMI) solver to find the PSS parameters. It is shown in the paper that PSS tuning can be written as a search problem over a non-convex feasible set. The proposed algorithm solves this feasibility problem using an iterative LMI approach and a suitable initial condition, corresponding to a PSS designed for nominal operating conditions only (which is a quite simple task, since the required phase compensation is uniquely defined). Some knowledge about the PSS tuning is also incorporated in the algorithm through the specification of bounds defining the allowable PSS parameters. The application of the proposed algorithm to a benchmark test system and the nonlinear simulation of the resulting closed-loop models demonstrate the efficiency of this algorithm. (C) 2009 Elsevier Ltd. All rights reserved.

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Voltage and current waveforms of a distribution or transmission power system are not pure sinusoids. There are distortions in these waveforms that can be represented as a combination of the fundamental frequency, harmonics and high frequency transients. This paper presents a novel approach to identifying harmonics in power system distorted waveforms. The proposed method is based on Genetic Algorithms, which is an optimization technique inspired by genetics and natural evolution. GOOAL, a specially designed intelligent algorithm for optimization problems, was successfully implemented and tested. Two kinds of representations concerning chromosomes are utilized: binary and real. The results show that the proposed method is more precise than the traditional Fourier Transform, especially considering the real representation of the chromosomes.

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The purpose of this paper is to propose a multiobjective optimization approach for solving the manufacturing cell formation problem, explicitly considering the performance of this said manufacturing system. Cells are formed so as to simultaneously minimize three conflicting objectives, namely, the level of the work-in-process, the intercell moves and the total machinery investment. A genetic algorithm performs a search in the design space, in order to approximate to the Pareto optimal set. The values of the objectives for each candidate solution in a population are assigned by running a discrete-event simulation, in which the model is automatically generated according to the number of machines and their distribution among cells implied by a particular solution. The potential of this approach is evaluated via its application to an illustrative example, and a case from the relevant literature. The obtained results are analyzed and reviewed. Therefore, it is concluded that this approach is capable of generating a set of alternative manufacturing cell configurations considering the optimization of multiple performance measures, greatly improving the decision making process involved in planning and designing cellular systems. (C) 2010 Elsevier Ltd. All rights reserved.

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Modal filters may be obtained by a properly designed weighted sum of the output signals of an array of sensors distributed on the host structure. Although several research groups have been interested in techniques for designing and implementing modal filters based on a given array of sensors, the effect of the array topology on the effectiveness of the modal filter has received much less attention. In particular, it is known that some parameters, such as size, shape and location of a sensor, are very important in determining the observability of a vibration mode. Hence, this paper presents a methodology for the topological optimization of an array of sensors in order to maximize the effectiveness of a set of selected modal filters. This is done using a genetic algorithm optimization technique for the selection of 12 piezoceramic sensors from an array of 36 piezoceramic sensors regularly distributed on an aluminum plate, which maximize the filtering performance, over a given frequency range, of a set of modal filters, each one aiming to isolate one of the first vibration modes. The vectors of the weighting coefficients for each modal filter are evaluated using QR decomposition of the complex frequency response function matrix. Results show that the array topology is not very important for lower frequencies but it greatly affects the filter effectiveness for higher frequencies. Therefore, it is possible to improve the effectiveness and frequency range of a set of modal filters by optimizing the topology of an array of sensors. Indeed, using 12 properly located piezoceramic sensors bonded on an aluminum plate it is shown that the frequency range of a set of modal filters may be enlarged by 25-50%.

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The general flowshop scheduling problem is a production problem where a set of n jobs have to be processed with identical flow pattern on in machines. In permutation flowshops the sequence of jobs is the same on all machines. A significant research effort has been devoted for sequencing jobs in a flowshop minimizing the makespan. This paper describes the application of a Constructive Genetic Algorithm (CGA) to makespan minimization on flowshop scheduling. The CGA was proposed recently as an alternative to traditional GA approaches, particularly, for evaluating schemata directly. The population initially formed only by schemata, evolves controlled by recombination to a population of well-adapted structures (schemata instantiation). The CGA implemented is based on the NEH classic heuristic and a local search heuristic used to define the fitness functions. The parameters of the CGA are calibrated using a Design of Experiments (DOE) approach. The computational results are compared against some other successful algorithms from the literature on Taillard`s well-known standard benchmark. The computational experience shows that this innovative CGA approach provides competitive results for flowshop scheduling; problems. (C) 2007 Elsevier Ltd. All rights reserved.

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The aim of this work is to verify the possibility to correlating specific gravity and wood hardness parallel and perpendicular to the grain. The purpose is to offer one more tool to help in the decision about wood species choice for use in floors and sleepers. To reach this intent, we considered the results of standard tests (NBR 7190:1997, Timber Structures Design, Annex B, Brazilian Association of Technical Standards) to determine hardness parallel and normal to the grain in fourteen tropical high density wood species (over 850 kg/m(3), at 12% moisture content). For each species twelve determinations were made, based on the material obtained at Sao Carlos and its regional wood market. Statistical analysis led to some expressions to describe the cited properties relationships, with a determination coefficient about 0.8.