947 resultados para Direct integration method
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Direct expressions for the design of a lead-lag continuous compensator using the root locus method and the procedure described in the 1970 and 1990 books by Ogata are presented. These results are useful in the Ogata design method because they avoid the geometrical determination of poles and zeros, making it easier to create a computer-based design.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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The problem of power system stability including the effects of a flexible alternating current transmission system (FACTS) is approached. First, the controlled series compensation is considered in the machine against infinite bar system and its effects are taken into account by means of construction of a Lyapunov function (LF). This simple system is helpful in order to understand the form the device affects dynamic and transient performance of the power system. After, the multimachine case is considered and it is shown that the single-machine results apply to multimachine systems. An energy-form Lyapunov function is derived for the power system including the FACTS device and it is used to analyse damping and synchronizing effects due to the FACTS device in single-machine as well as in multimachine power systems. © 2005 Elsevier Ltd. All rights reserved.
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The retention phase is initiated after orthodontic treatment completion to prevent orthodontic relapse. There are several techniques, direct and indirect, available for placing bonded lingual retainers, but none of them is considered as a standard clinical protocol. The best choice should be the association of simplicity and efficiency. This article presents a practical method sequence for fixation of the lingual retainer before direct bonding. © 2009 Elsevier Ltd and the Japanese Orthodontic Society.
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In conservation agriculture, mainly under direct seeding, maintaining the vegetation ground cover is essential, since this serves as a reservoir of nutrients which are slowly released to plants by microorganisms. Some authors have sought to study increases in the amount of straw in the soil, in addition to slowing down the process of decomposition, with hormesis being one of the techniques used. This technique states that all chemical substances are both poisonous and nonpoisonous, with only the dosage determining whether they are lethal or not. This study aimed to evaluate the dry weight and agronomic characteristics of a crop of black oat subjected to hormesis. The experimental design was of randomised blocks, with 12 treatments and 4 replications, giving a total of 48 experimental lots. The treatments were: Haloxyfop-R Methyl Ester at dosages of 0.625, 1.25 and 2.50 g ha(-1); Glyphosate at dosages of 12.50, 25.00 and 50.00 g ha-1; 2,4-D dimethylamine salt at dosages of 100.00, 200.00 and 300.00 g ha(-1); Alterbane at a dosage of 500.00 g ha(-1); Salicylic acid at a dose of 100 g ha(-1); and a control. It was concluded that for the subdosages under test, the herbicides 2,4-D at medium dosage and Verdict at low dosage were shown to be the best treatments for conserving straw as ground cover under direct seeding.
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The aim of this work was to perform a systematic study of the parameters that can influence the composition, morphology, and catalytic activity of PtSn/C nanoparticles and compare two different methods of nanocatalyst preparation, namely microwave-assisted heating (MW) and thermal decomposition of polymeric precursors (DPP). An investigation of the effects of the reducing and stabilizing agents on the catalytic activity and morphology of Pt75Sn25/C catalysts prepared by microwave-assisted heating was undertaken for optimization purposes. The effect of short-chain alcohols such as ethanol, ethylene glycol, and propylene glycol as reducing agents was evaluated, and the use of sodium acetate and citric acid as stabilizing agents for the MW procedure was examined. Catalysts obtained from propylene glycol displayed higher catalytic activity compared with catalysts prepared in ethylene glycol. Introduction of sodium acetate enhanced the catalytic activity, but this beneficial effect was observed until a critical acetate concentration was reached. Optimization of the MW synthesis allowed for the preparation of highly dispersed catalysts with average sizes lying between 2.0 and 5.0 nm. Comparison of the best catalyst prepared by MW with a catalyst of similar composition prepared by the polymeric precursors method showed that the catalytic activity of the material can be improved when a proper condition for catalyst preparation is achieved. (C) 2012 Elsevier B.V. All rights reserved.
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Over the years the Differential Quadrature (DQ) method has distinguished because of its high accuracy, straightforward implementation and general ap- plication to a variety of problems. There has been an increase in this topic by several researchers who experienced significant development in the last years. DQ is essentially a generalization of the popular Gaussian Quadrature (GQ) used for numerical integration functions. GQ approximates a finite in- tegral as a weighted sum of integrand values at selected points in a problem domain whereas DQ approximate the derivatives of a smooth function at a point as a weighted sum of function values at selected nodes. A direct appli- cation of this elegant methodology is to solve ordinary and partial differential equations. Furthermore in recent years the DQ formulation has been gener- alized in the weighting coefficients computations to let the approach to be more flexible and accurate. As a result it has been indicated as Generalized Differential Quadrature (GDQ) method. However the applicability of GDQ in its original form is still limited. It has been proven to fail for problems with strong material discontinuities as well as problems involving singularities and irregularities. On the other hand the very well-known Finite Element (FE) method could overcome these issues because it subdivides the computational domain into a certain number of elements in which the solution is calculated. Recently, some researchers have been studying a numerical technique which could use the advantages of the GDQ method and the advantages of FE method. This methodology has got different names among each research group, it will be indicated here as Generalized Differential Quadrature Finite Element Method (GDQFEM).
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The aim of this work is to present various aspects of numerical simulation of particle and radiation transport for industrial and environmental protection applications, to enable the analysis of complex physical processes in a fast, reliable, and efficient way. In the first part we deal with speed-up of numerical simulation of neutron transport for nuclear reactor core analysis. The convergence properties of the source iteration scheme of the Method of Characteristics applied to be heterogeneous structured geometries has been enhanced by means of Boundary Projection Acceleration, enabling the study of 2D and 3D geometries with transport theory without spatial homogenization. The computational performances have been verified with the C5G7 2D and 3D benchmarks, showing a sensible reduction of iterations and CPU time. The second part is devoted to the study of temperature-dependent elastic scattering of neutrons for heavy isotopes near to the thermal zone. A numerical computation of the Doppler convolution of the elastic scattering kernel based on the gas model is presented, for a general energy dependent cross section and scattering law in the center of mass system. The range of integration has been optimized employing a numerical cutoff, allowing a faster numerical evaluation of the convolution integral. Legendre moments of the transfer kernel are subsequently obtained by direct quadrature and a numerical analysis of the convergence is presented. In the third part we focus our attention to remote sensing applications of radiative transfer employed to investigate the Earth's cryosphere. The photon transport equation is applied to simulate reflectivity of glaciers varying the age of the layer of snow or ice, its thickness, the presence or not other underlying layers, the degree of dust included in the snow, creating a framework able to decipher spectral signals collected by orbiting detectors.
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There is a need by engine manufactures for computationally efficient and accurate predictive combustion modeling tools for integration in engine simulation software for the assessment of combustion system hardware designs and early development of engine calibrations. This thesis discusses the process for the development and validation of a combustion modeling tool for Gasoline Direct Injected Spark Ignited Engine with variable valve timing, lift and duration valvetrain hardware from experimental data. Data was correlated and regressed from accepted methods for calculating the turbulent flow and flame propagation characteristics for an internal combustion engine. A non-linear regression modeling method was utilized to develop a combustion model to determine the fuel mass burn rate at multiple points during the combustion process. The computational fluid dynamic software Converge ©, was used to simulate and correlate the 3-D combustion system, port and piston geometry to the turbulent flow development within the cylinder to properly predict the experimental data turbulent flow parameters through the intake, compression and expansion processes. The engine simulation software GT-Power © is then used to determine the 1-D flow characteristics of the engine hardware being tested to correlate the regressed combustion modeling tool to experimental data to determine accuracy. The results of the combustion modeling tool show accurate trends capturing the combustion sensitivities to turbulent flow, thermodynamic and internal residual effects with changes in intake and exhaust valve timing, lift and duration.
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The tremendous application potential of nanosized materials stays in sharp contrast to a growing number of critical reports of their potential toxicity. Applications of in vitro methods to assess nanoparticles are severely limited through difficulties in exposing cells of the respiratory tract directly to airborne engineered nanoparticles. We present a completely new approach to expose lung cells to particles generated in situ by flame spray synthesis. Cerium oxide nanoparticles from a single run were produced and simultaneously exposed to the surface of cultured lung cells inside a glovebox. Separately collected samples were used to measure hydrodynamic particle size distribution, shape, and agglomerate morphology. Cell viability was not impaired by the conditions of the glovebox exposure. The tightness of the lung cell monolayer, the mean total lamellar body volume, and the generation of oxidative DNA damage revealed a dose-dependent cellular response to the airborne engineered nanoparticles. The direct combination of production and exposure allows studying particle toxicity in a simple and reproducible way under environmental conditions.
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Integrating evidence from different imaging modalities is important to overcome specific limitations of any given imaging method, such as insensitivity of the EEG to unsynchronized neural events, or the lack of fMRI sensitivity to events of low metabolic demand. Processes that are visible in one modality may be related in a nontrivial way to other processes visible in another modality and insight may only be obtained by integrating both methods through a common analysis. For example, brain activity at rest seems to be at least partly determined by an interaction of cortical rhythms (visible to EEG but not to fMRI) with sub-cortical activity (visible to fMRI, but usually not to EEG without averaging). A combination of EEG and fMRI data during rest may thus be more informative than the sum of two separate analyses in both modalities. Integration is also an important source of converging evidence about specific aspects and general principles of neural functions and their dysfunctions in certain pathologies. This is because not only electrical, but also energetic, biochemical, hemodynamic and metabolic processes characterize neural states and functions, and because brain structure provides crucial constraints upon neural functions. Focusing on multimodal integration of functional data should not distract from the privileged status of the electric field as the primary direct, noninvasive real-time measure of neural transmission. The preceding chapters illustrate how electrical neuroimaging has turned scalp EEG into an imaging modality which directly captures the full temporal dynamics of neural activity in the brain.