884 resultados para Online flow theory
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This paper describes the automation of a fully electrochemical system for preconcentration, cleanup, separation and detection, comprising the hyphenation of a thin layer electrochemical flow cell with CE coupled with contactless conductivity detection (CE-C(4)D). Traces of heavy metal ions were extracted from the pulsed-flowing sample and accumulated on a glassy carbon working electrode by electroreduction for some minutes. Anodic stripping of the accumulated metals was synchronized with hydrodynamic injection into the capillary. The effect of the angle of the slant polished tip of the CE capillary and its orientation against the working electrode in the electrochemical preconcentration (EPC) flow cell and of the accumulation time were studied, aiming at maximum CE-C(4)D signal enhancement. After 6 min of EPC, enhancement factors close to 50 times were obtained for thallium, lead, cadmium and copper ions, and about 16 for zinc ions. Limits of detection below 25 nmol/L were estimated for all target analytes but zinc. A second separation dimension was added to the CE separation capabilities by staircase scanning of the potentiostatic deposition and/or stripping potentials of metal ions, as implemented with the EPC-CE-C(4)D flow system. A matrix exchange between the deposition and stripping steps, highly valuable for sample cleanup, can be straightforwardly programmed with the multi-pumping flow management system. The automated simultaneous determination of the traces of five accumulable heavy metals together with four non-accumulated alkaline and alkaline earth metals in a single run was demonstrated, to highlight the potentiality of the system.
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The purpose of this presentation is to offer a deeper understanding of adult learning and provide tips on how to effectively teach in the online environment. The presenter will compare and contrast two learning theories: andragogy and pedagogy. Furthermore, the roles of the online instructor and e-learner will be outlined. An open discussion at the end of the presentation will allow participants to make implications as to which learning theory is more effective for online learning.
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A dislocation model, accurately describing the uniaxial plastic stress-strain behavior of dual phase (DP) steels, is proposed and the impact of martensite content and ferrite grain size in four commercially produced DP steels is analyzed. It is assumed that the plastic deformation process is localized to the ferrite. This is taken into account by introducing a non-homogeneity parameter, f(e), that specifies the volume fraction of ferrite taking active part in the plastic deformation process. It is found that the larger the martensite content the smaller the initial volume fraction of active ferrite which yields a higher initial deformation hardening rate. This explains the high energy absorbing capacity of DP steels with high volume fractions of martensite. Further, the effect of ferrite grain size strengthening in DP steels is important. The flow stress grain size sensitivity for DP steels is observed to be 7 times larger than that for single phase ferrite.
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This paper uses Shannon's information theory to give a quantitative definition of information flow in systems that transform inputs to outputs. For deterministic systems, the definition is shown to specialise to a simpler form when the information source and the known inputs jointly determine the inputs. For this special case, the definition is related to the classical security condition of non-interference and an equivalence is established between non-interference and independence of random variables. Quantitative information flow for deterministic systems is then presented in relational form. With this presentation, it is shown how relational parametricity can be used to derive upper and lower bounds on information flows through families of functions defined in the second order lambda calculus.
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Oxygen-deficient TiO2 films with enhanced visible and near-infrared optical absorption have been deposited by reactive sputtering using a planar diode radio frequency magnetron configuration. It is observed that the increase in the absorption coefficient is more effective when the O-2 gas supply is periodically interrupted rather than by a decrease of the partial O-2 gas pressure in the deposition plasma. The optical absorption coefficient at 1.5 eV increases from about 1 x 10(2) cm(-1) to more than 4 x 10(3) cm(-1) as a result of the gas flow discontinuity. A red-shift of similar to 0.24 eV in the optical absorption edge is also observed. High resolution transmission electron microscopy with composition analysis shows that the films present a dense columnar morphology, with estimated mean column width of 40nm. Moreover, the interruptions of the O-2 gas flow do not produce detectable variations in the film composition along its growing direction. X-ray diffraction and micro-Raman experiments indicate the presence of the TiO2 anatase, rutile, and brookite phases. The anatase phase is dominant, with a slight increment of the rutile and brookite phases in films deposited under discontinued O-2 gas flow. The increase of optical absorption in the visible and near-infrared regions has been attributed to a high density of defects in the TiO2 films, which is consistent with density functional theory calculations that place oxygen-related vacancy states in the upper third of the optical bandgap. The electronic structure calculation results, along with the adopted deposition method and experimental data, have been used to propose a mechanism to explain the formation of the observed oxygen-related defects in TiO2 thin films. The observed increase in sub-bandgap absorption and the modeling of the corresponding changes in the electronic structure are potentially useful concerning the optimization of efficiency of the photocatalytic activity and the magnetic doping of TiO2 films. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.4724334]
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This work presents the application of a multiobjective evolutionary algorithm (MOEA) for optimal power flow (OPF) solution. The OPF is modeled as a constrained nonlinear optimization problem, non-convex of large-scale, with continuous and discrete variables. The violated inequality constraints are treated as objective function of the problem. This strategy allows attending the physical and operational restrictions without compromise the quality of the found solutions. The developed MOEA is based on the theory of Pareto and employs a diversity-preserving mechanism to overcome the premature convergence of algorithm and local optimal solutions. Fuzzy set theory is employed to extract the best compromises of the Pareto set. Results for the IEEE-30, RTS-96 and IEEE-354 test systems are presents to validate the efficiency of proposed model and solution technique.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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In the limit of small values of the aspect ratio parameter (or wave steepness) which measures the amplitude of a surface wave in units of its wave-length, a model equation is derived from the Euler system in infinite depth (deep water) without potential flow assumption. The resulting equation is shown to sustain periodic waves which on the one side tend to the proper linear limit at small amplitudes, on the other side possess a threshold amplitude where wave crest peaking is achieved. An explicit expression of the crest angle at wave breaking is found in terms of the wave velocity. By numerical simulations, stable soliton-like solutions (experiencing elastic interactions) propagate in a given velocities range on the edge of which they tend to the peakon solution. (c) 2005 Elsevier B.V. All rights reserved.
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The dynamic scale theory and fractal concepts are employed in the characterization of surface morphological properties of layer-by-layer (LBL) films from poly(o-methoxyaniline) (POMA) alternated with poly(vinyl sulfonic acid) (PVS). The fractal dimensions are found to depend on the procedures to fabricate the POMA/PVS multilayers, particularly with regard to the drying procedures. LBL films obtained via drying in ambient air show a more homogeneous surface, compared to films dried under vacuum or a flow of nitrogen, due to a uniform rearrangement of polymer molecules during solvent evaporation.
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Smart microgrids offer a new challenging domain for power theories and metering techniques because they include a variety of intermittent power sources which positively impact on power flow and distribution losses but may cause voltage asymmetry and frequency variation. In smart microgrids, the voltage distortion and asymmetry in presence of poly-phase nonlinear loads can be also greater than in usual distribution lines fed by the utility, thus affecting measurement accuracy and possibly causing tripping of protections. In such a context, a reconsideration of power theories is required since they form the basis for supply and load characterization. A revision of revenue metering techniques is also suggested to ensure a correct penalization of the loads for their responsibility in generating reactive power, voltage asymmetry, and distortion. This paper shows that the conservative power theory provides a suitable background to cope with smart grids characterization and metering needs. Simulation and experimental results show the properties of the proposed approach.
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This paper presents a viscous three-dimensional simulations coupling Euler and boundary layer codes for calculating flows over arbitrary surfaces. The governing equations are written in a general non orthogonal coordinate system. The Levy-Lees transformation generalized to three-dimensional flows is utilized. The inviscid properties are obtained from the Euler equations using the Beam and Warming implicit approximate factorization scheme. The resulting equations are discretized and approximated by a two-point fmitedifference numerical scheme. The code developed is validated and applied to the simulation of the flowfield over aerospace vehicle configurations. The results present good correlation with the available data.
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A new approach to solving the Optimal Power Flow problem is described, making use of some recent findings, especially in the area of primal-dual methods for complex programming. In this approach, equality constraints are handled by Newton's method inequality constraints for voltage and transformer taps by the logarithmic barrier method and the other inequality constraints by the augmented Lagrangian method. Numerical test results are presented, showing the effective performance of this algorithm. © 2001 IEEE.
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The prediction of the traffic behavior could help to make decision about the routing process, as well as enables gains on effectiveness and productivity on the physical distribution. This need motivated the search for technological improvements in the Routing performance in metropolitan areas. The purpose of this paper is to present computational evidences that Artificial Neural Network ANN could be use to predict the traffic behavior in a metropolitan area such So Paulo (around 16 million inhabitants). The proposed methodology involves the application of Rough-Fuzzy Sets to define inference morphology for insertion of the behavior of Dynamic Routing into a structured rule basis, without human expert aid. The dynamics of the traffic parameters are described through membership functions. Rough Sets Theory identifies the attributes that are important, and suggest Fuzzy relations to be inserted on a Rough Neuro Fuzzy Network (RNFN) type Multilayer Perceptron (MLP) and type Radial Basis Function (RBF), in order to get an optimal surface response. To measure the performance of the proposed RNFN, the responses of the unreduced rule basis are compared with the reduced rule one. The results show that by making use of the Feature Reduction through RNFN, it is possible to reduce the need for human expert in the construction of the Fuzzy inference mechanism in such flow process like traffic breakdown. © 2011 IEEE.
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Experiments of biomass combustion were performed to determine whether specimen size, tray inclination, or combustion air flow rate was the factor that most affects the emission of carbon dioxide, carbon monoxide, and methane. The chosen biomass was Eucalyptus citriodora, a very abundant species in Brazil, utilized in many industrial applications, including combustion for energy generation. Analyses by gas chromatograph and specific online instruments were used to determine the concentrations of the main emitted gases, and the following figures were found for the emission factors: 1400 ± 101 g kg-1 of CO2, 50 ± 13 g kg-1 of CO, and 3.2 ± 0.5 g kg-1 of CH4, which agree with values published in the literature for biomass from the Amazon rainforest. Statistical analysis of the experiments determined that specimen size most significantly affected the emission of gases, especially CO2 and CO. •Statistical analysis to determine effects on emission factors.•CO2, CO, CH4 emission factors determined for combustion of Eucalyptus.•Laboratory results agreed with data for Amazonian biomass combustion in field tests.•Combustion behavior under flaming and smoldering was analyzed. © 2013 Elsevier Ltd.