992 resultados para Order-parameter


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This paper aims to study evolution of increase, distribution and classification of pits in 310S austenitic stainless steels obtained in the state as-received and heat-treated under different exposure times in saline. This work applicability has been based on a technique development for morphologic characterization of localized corrosion associated with description aspects of shapes, size and population-specific parameters. Methodology has been consisted in the following steps: specimens preparation, corrosion tests via salt spray in different conditions, microstructural analysis, pits profiles analysis and images analysis, digital processing and image analysis in order to characterize the pits distribution, morphology and size. Results obtained in digital processing and profiles image analysis have been subjected to statistical analysis using median as parameter in the alloy as received and treated. The alloy as received displays the following morphology: hemispheric pits> transition region A> transition region B> irregular> conic. The pits amount in the treated alloy at each exposure time is: transition region B> hemispherical> transition region A> conic> irregular.

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The concentration of hydrogen peroxide is an important parameter in the azo dyes decoloration process through the utilization of advanced oxidizing processes, particularly by oxidizing via UV/H2O2. It is pointed out that, from a specific concentration, the hydrogen peroxide works as a hydroxyl radical self-consumer and thus a decrease of the system`s oxidizing power happens. The determination of the process critical point (maximum amount of hydrogen peroxide to be added) was performed through a ""thorough mapping"" or discretization of the target region, founded on the maximization of an objective function objective (constant of reaction kinetics of pseudo-first order). The discretization of the operational region occurred through a feedforward backpropagation neural model. The neural model obtained presented remarkable coefficient of correlation between real and predicted values for the absorbance variable, above 0.98. In the present work, the neural model had, as phenomenological basis the Acid Brown 75 dye decoloration process. The hydrogen peroxide addition critical point, represented by a value of mass relation (F) between the hydrogen peroxide mass and the dye mass, was established in the interval 50 < F < 60. (C) 2007 Elsevier B.V. All rights reserved.

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Xylitol enzymatic production can be an alternative to chemical and microbial processes, because of advantages like higher conversion efficiency. However, for an adequate conversion, it is necessary to investigate the effect of many parameters, such as buffer initial concentration, pH, temperature, agitation, etc. In this context, the objective of this work was to evaluate xylitol enzymatic production under different Tris buffer initial concentrations in order to determine the best condition for this parameter to begin the reaction. The best results were obtained when Tris buffer initial concentration was 0.22 M, reaching 0.31 g L(-1) h(-1) xylitol volumetric productivity with 99% xylose-xylitol conversion efficiency. Although the increase in buffer concentration allowed better pH maintenance, it hindered the catalysis. The results demonstrate that this bioreaction is greatly influenced by involved ions concentrations.

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This paper proposes a three-stage offline approach to detect, identify, and correct series and shunt branch parameter errors. In Stage 1 the branches suspected of having parameter errors are identified through an Identification Index (II). The II of a branch is the ratio between the number of measurements adjacent to that branch, whose normalized residuals are higher than a specified threshold value, and the total number of measurements adjacent to that branch. Using several measurement snapshots, in Stage 2 the suspicious parameters are estimated, in a simultaneous multiple-state-and-parameter estimation, via an augmented state and parameter estimator which increases the V - theta state vector for the inclusion of suspicious parameters. Stage 3 enables the validation of the estimation obtained in Stage 2, and is performed via a conventional weighted least squares estimator. Several simulation results (with IEEE bus systems) have demonstrated the reliability of the proposed approach to deal with single and multiple parameter errors in adjacent and non-adjacent branches, as well as in parallel transmission lines with series compensation. Finally the proposed approach is confirmed on tests performed on the Hydro-Quebec TransEnergie network.

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A phase-only encryption/decryption scheme with the readout based on the zeroth-order phase-contrast technique (ZOPCT), without the use of a phase-changing plate on the Fourier plane of an optical system based on the 4f optical correlator, is proposed. The encryption of a gray-level image is achieved by multiplying the phase distribution obtained directly from the gray-level image by a random phase distribution. The robustness of the encoding is assured by the nonlinearity intrinsic to the proposed phase-contrast method and the random phase distribution used in the encryption process. The experimental system has been implemented with liquid-crystal spatial modulators to generate phase-encrypted masks and a decrypting key. The advantage of this method is the easy scheme to recover the gray-level information from the decrypted phase-only mask applying the ZOPCT. An analysis of this decryption method was performed against brute force attacks. (C) 2009 Society of Photo-Optical Instrumentation Engineers. [DOI: 10.1117/1.3223629]

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This paper presents a new approach, predictor-corrector modified barrier approach (PCMBA), to minimize the active losses in power system planning studies. In the PCMBA, the inequality constraints are transformed into equalities by introducing positive auxiliary variables. which are perturbed by the barrier parameter, and treated by the modified barrier method. The first-order necessary conditions of the Lagrangian function are solved by predictor-corrector Newton`s method. The perturbation of the auxiliary variables results in an expansion of the feasible set of the original problem, reaching the limits of the inequality constraints. The feasibility of the proposed approach is demonstrated using various IEEE test systems and a realistic power system of 2256-bus corresponding to the Brazilian South-Southeastern interconnected system. The results show that the utilization of the predictor-corrector method with the pure modified barrier approach accelerates the convergence of the problem in terms of the number of iterations and computational time. (C) 2008 Elsevier B.V. All rights reserved.

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The asymptotic behavior of a class of coupled second-order nonlinear dynamical systems is studied in this paper. Using very mild assumptions on the vector-field, conditions on the coupling parameters that guarantee synchronization are provided. The proposed result does not require solutions to be ultimately bounded in order to prove synchronization, therefore it can be used to study coupled systems that do not globally synchronize, including synchronization of unbounded solutions. In this case, estimates of the synchronization region are obtained. Synchronization of two-coupled nonlinear pendulums and two-coupled Duffing systems are studied to illustrate the application of the proposed theory.

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Sulfide-oxidizing autotrophic denitrification is an advantageous alternative over heterotrophic denitrification, and may have potential for nitrogen removal of low-strength wastewaters, such as anaerobically pre-treated domestic sewage. This study evaluated the fundamentals and kinetics of this process in batch reactors containing suspended and immobilized cells. Batch tests were performed for different NO(x)(-)/S(2-) ratios and using nitrate and nitrite as electron acceptors. Autotrophic denitrification was observed for both electron acceptors, and NO(x)(-)/S(2-) ratios defined whether sulfide oxidation was complete or not. Kinetic parameter values obtained for nitrate were higher than for nitrite as electron acceptor. Zero-order models were better adjusted to profiles obtained for suspended cell reactors, whereas first-order models were more adequate for immobilized cell reactors. However, in the latter, mass transfer physical phenomena had a significant effect on kinetics based on biochemical reactions. Results showed that sulfide-oxidizing autotrophic denitrification can be successfully established for low-strength wastewaters and have potential for nitrogen removal from anaerobically pre-treated domestic sewage.

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An investigation was performed on the effect of temperature and organic load on the stability and efficiency of a 1.8-L fluidized-bed anaerobic sequencing batch reactor (ASBR), containing granulated biomass. Assays were carried out employing superficial up How velocity of 7 m/h, total cycle length of 6 h and synthetic wastewater volume of 1.3 L per cycle. The fluidized-bed ASH was operated at 15, 20, 25 and 30 degrees C with influent organic matter concentrations of 500 and 1000 mgCOD/L The system showed stability under all conditions and presented filtered samples removal efficiency ranging from 79 to 86%. A first-order kinetic model could be fitted to the experimental values of the organic matter concentration profiles. The specific kinetic parameter values of this model ranged from 0.0435 to 0.2360 L/(gTVS h) at the implemented operation conditions. in addition, from the slope of an Arrhenius plot, the activation energy values were calculated to be 16,729 and 12,673 cal/mol for operation with 500 and 1000 mgCOD/L, respectively. These results show that treatment of synthetic wastewater. with concentration of 500 mgCOD/L, was more sensitive to temperature variations than treatment of the same residue with concentration of 1000 mgCOD/L. Comparing the activation energy value for operation at 500 mgCOD/L with the value obtained by Agibert et al. (S.A. Agibert, M.B. Moreira, S.M. Ratusznei, J.A.D. Rodrigues, M. Zaiat, E. Foresti. Influence of temperature on performance of an ASBBR with circulation applied to treatment of low-strength wastewater. journal of Applied Biochemistry and Biotechnology, 136 (2007) 193-206) in an ASBBR treating the same wastewater at the same concentration, the value obtained in the fluidized-bed ASBR showed to be superior, indicating that treatment of synthetic wastewater in a reactor containing granulated biomass was more sensitive to temperature variations than the treatment using immobilized biomass. (c) 2008 Elsevier B.V. All rights reserved.

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An investigation has been performed on the effect of liquid phase recirculation velocity and increasing influent concentration on the stability and efficiency of an anaerobic sequencing batch reactor (ASBR) containing granular biomass. The reactor treated 1.3 L synthetic wastewater at 30 degrees C in 6 h cycles. Initially the effect of recirculation velocity was investigated employing velocities of 5, 7 and 10 m/h and influent concentration of 500 mg COD/L. At these velocities, filtered sample organic matter removal efficiencies were 83, 85 and 84%, respectively. A first order kinetic model could also be fitted to the experimental organic matter concentration profiles. The kinetic parameter values of this model were 1.35, 2.36 and 1.00 h(-1) at the recirculation velocities of 5, 7 and 10 m/h, respectively. The recirculation velocity of 7 m/h was found to be the best operating strategy and this value was maintained while the influent concentration was altered in order to verify system efficiency and stability at increasing organic load. Influent concentration of 1000 mg COD/L resulted in filtered sample organic matter removal efficiency of 80%, and a first order kinetic parameter value of 1.14 h(-1), whereas the concentration of 1500 mg COD/L resulted in an efficiency of 82% and a kinetic parameter value of 1.31 h(-1). (C) 2007 Elsevier B.V. All rights reserved.

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This paper presents results on a verification test of a Direct Numerical Simulation code of mixed high-order of accuracy using the method of manufactured solutions (MMS). This test is based on the formulation of an analytical solution for the Navier-Stokes equations modified by the addition of a source term. The present numerical code was aimed at simulating the temporal evolution of instability waves in a plane Poiseuille flow. The governing equations were solved in a vorticity-velocity formulation for a two-dimensional incompressible flow. The code employed two different numerical schemes. One used mixed high-order compact and non-compact finite-differences from fourth-order to sixth-order of accuracy. The other scheme used spectral methods instead of finite-difference methods for the streamwise direction, which was periodic. In the present test, particular attention was paid to the boundary conditions of the physical problem of interest. Indeed, the verification procedure using MMS can be more demanding than the often used comparison with Linear Stability Theory. That is particularly because in the latter test no attention is paid to the nonlinear terms. For the present verification test, it was possible to manufacture an analytical solution that reproduced some aspects of an instability wave in a nonlinear stage. Although the results of the verification by MMS for this mixed-order numerical scheme had to be interpreted with care, the test was very useful as it gave confidence that the code was free of programming errors. Copyright (C) 2009 John Wiley & Sons, Ltd.

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The practicability of estimating directional wave spectra based on a vessel`s 1st order response has been recently addressed by several researchers. Different alternatives regarding statistical inference methods and possible drawbacks that could arise from their application have been extensively discussed, with an apparent preference for estimations based on Bayesian inference algorithms. Most of the results on this matter, however, rely exclusively on numerical simulations or at best on few and sparse full-scale measurements, comprising a questionable basis for validation purposes. This paper discusses several issues that have recently been debated regarding the advantages of Bayesian inference and different alternatives for its implementation. Among those are the definition of the best set of input motions, the number of parameters required for guaranteeing smoothness of the spectrum in frequency and direction and how to determine their optimum values. These subjects are addressed in the light of an extensive experimental campaign performed with a small-scale model of an FPSO platform (VLCC hull), which was conducted in an ocean basin in Brazil. Tests involved long and short crested seas with variable levels of directional spreading and also bimodal conditions. The calibration spectra measured in the tank by means of an array of wave probes configured the paradigm for estimations. Results showed that a wide range of sea conditions could be estimated with good precision, even those with somewhat low peak periods. Some possible drawbacks that have been pointed out in previous works concerning the viability of employing large vessels for such a task are then refuted. Also, it is shown that a second parameter for smoothing the spectrum in frequency may indeed increase the accuracy in some situations, although the criterion usually proposed for estimating the optimum values (ABIC) demands large computational effort and does not seem adequate for practical on-board systems, which require expeditious estimations. (C) 2009 Elsevier Ltd. All rights reserved.

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In this paper, 2 different approaches for estimating the directional wave spectrum based on a vessel`s 1st-order motions are discussed, and their predictions are compared to those provided by a wave buoy. The real-scale data were obtained in an extensive monitoring campaign based on an FPSO unit operating at Campos Basin, Brazil. Data included vessel motions, heading and tank loadings. Wave field information was obtained by means of a heave-pitch-roll buoy installed in the vicinity of the unit. `two of the methods most widely used for this kind of analysis are considered, one based on Bayesian statistical inference, the other consisting of a parametrical representation of the wave spectrum. The performance of both methods is compared, and their sensitivity to input parameters is discussed. This analysis complements a set of previous validations based on numerical and towing-tank results and allows for a preliminary evaluation of reliability when applying the methodology at full scale.

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The objective of this paper is to develop and validate a mechanistic model for the degradation of phenol by the Fenton process. Experiments were performed in semi-batch operation, in which phenol, catechol and hydroquinone concentrations were measured. Using the methodology described in Pontes and Pinto [R.F.F. Pontes, J.M. Pinto, Analysis of integrated kinetic and flow models for anaerobic digesters, Chemical Engineering journal 122 (1-2) (2006) 65-80], a stoichiometric model was first developed, with 53 reactions and 26 compounds, followed by the corresponding kinetic model. Sensitivity analysis was performed to determine the most influential kinetic parameters of the model that were estimated with the obtained experimental results. The adjusted model was used to analyze the impact of the initial concentration and flow rate of reactants on the efficiency of the Fenton process to degrade phenol. Moreover, the model was applied to evaluate the treatment cost of wastewater contaminated with phenol in order to meet environmental standards. (C) 2009 Elsevier B.V. All rights reserved.

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Modern Integrated Circuit (IC) design is characterized by a strong trend of Intellectual Property (IP) core integration into complex system-on-chip (SOC) architectures. These cores require thorough verification of their functionality to avoid erroneous behavior in the final device. Formal verification methods are capable of detecting any design bug. However, due to state explosion, their use remains limited to small circuits. Alternatively, simulation-based verification can explore hardware descriptions of any size, although the corresponding stimulus generation, as well as functional coverage definition, must be carefully planned to guarantee its efficacy. In general, static input space optimization methodologies have shown better efficiency and results than, for instance, Coverage Directed Verification (CDV) techniques, although they act on different facets of the monitored system and are not exclusive. This work presents a constrained-random simulation-based functional verification methodology where, on the basis of the Parameter Domains (PD) formalism, irrelevant and invalid test case scenarios are removed from the input space. To this purpose, a tool to automatically generate PD-based stimuli sources was developed. Additionally, we have developed a second tool to generate functional coverage models that fit exactly to the PD-based input space. Both the input stimuli and coverage model enhancements, resulted in a notable testbench efficiency increase, if compared to testbenches with traditional stimulation and coverage scenarios: 22% simulation time reduction when generating stimuli with our PD-based stimuli sources (still with a conventional coverage model), and 56% simulation time reduction when combining our stimuli sources with their corresponding, automatically generated, coverage models.