980 resultados para Source wavelet estimation
Resumo:
The crossflow filtration process differs of the conventional filtration by presenting the circulation flow tangentially to the filtration surface. The conventional mathematical models used to represent the process have some limitations in relation to the identification and generalization of the system behaviour. In this paper, a system based on artificial neural networks is developed to overcome the problems usually found in the conventional mathematical models. More specifically, the developed system uses an artificial neural network that simulates the behaviour of the crossflow filtration process in a robust way. Imprecisions and uncertainties associated with the measurements made on the system are automatically incorporated in the neural approach. Simulation results are presented to justify the validity of the proposed approach. (C) 2007 Elsevier B.V. All rights reserved.
Resumo:
In this study, the innovation approach is used to estimate the measurement total error associated with power system state estimation. This is required because the power system equations are very much correlated with each other and as a consequence part of the measurements errors is masked. For that purpose an index, innovation index (II), which provides the quantity of new information a measurement contains is proposed. A critical measurement is the limit case of a measurement with low II, it has a zero II index and its error is totally masked. In other words, that measurement does not bring any innovation for the gross error test. Using the II of a measurement, the masked gross error by the state estimation is recovered; then the total gross error of that measurement is composed. Instead of the classical normalised measurement residual amplitude, the corresponding normalised composed measurement residual amplitude is used in the gross error detection and identification test, but with m degrees of freedom. The gross error processing turns out to be very simple to implement, requiring only few adaptations to the existing state estimation software. The IEEE-14 bus system is used to validate the proposed gross error detection and identification test.
Resumo:
The aim of this study is to quantify the mass transfer velocity using turbulence parameters from simultaneous measurements of oxygen concentration fields and velocity fields. The surface divergence model was considered in more detail, using data obtained for the lower range of beta (surface divergence). It is shown that the existing models that use the divergence concept furnish good predictions for the transfer velocity also for low values of beta, in the range of this study. Additionally, traditional conceptual models, such as the film model, the penetration-renewal model, and the large eddy model, were tested using the simultaneous information of concentration and velocity fields. It is shown that the film and the surface divergence models predicted the mass transfer velocity for all the range of the equipment Reynolds number used here. The velocity measurements showed viscosity effects close to the surface, which indicates that the surface was contaminated with some surfactant. Considering the results, this contamination can be considered slight for the mass transfer predictions. (C) 2009 American Institute of Chemical Engineers AIChE J, 56: 2005-2017; 2010
Resumo:
Ammonium nitrogen removal from a synthetic wastewater by nitrification and denitrification processes were performed in a sequencing batch biofilm reactor containing immobilized biomass on polyurethane foam with circulation of the liquid-phase. It was analyzed the effect of four external carbon sources (ethanol, acetate, carbon synthetic medium and methanol) acting as electron donors in the denitrifying process. The experiments were conducted with intermittent aeration and operated at 30+/-1 degrees C in 8-h cycles. The synthetic wastewater (100 mgCOD/L and 50 mgNH(4)(+)-N/L) was added batch-wise, while the external carbon sources were added fed-batch-wise during the periods where aeration was suspended. Ammonium nitrogen removal efficiencies obtained were 95.7, 94.3 and 97.5% for ethanol, acetate and carbon synthetic medium, respectively. As to nitrite, nitrate and ammonium nitrogen effluent concentrations, the results obtained were, respectively: 0.1, 5.7 and 1.4 mg/L for ethanol; 0.2, 4.1 and 1.8 mg/L for acetate and 0.2, 6.7 and 0.8 for carbon synthetic medium. On the other hand using methanol, even at low concentrations (50% of the stoichiometric value calculated for complete denitrification), resulted in increasing accumulation of nitrate and ammonium nitrogen in the effluent over time.
Resumo:
Biological sulfate reduction was studied in a laboratory-scale anaerobic sequential batch reactor (14 L) containing mineral coal for biomass attachment. The reactor was fed industrial wastewater with increasingly high sulfate concentrations to establish its application limits. Special attention was paid to the use of butanol in the sulfate reduction that originated from melamine resin production. This product was used as the main organic amendment to support the biological process. The reactor was operated for 65 cycles (48 h each) at sulfate loading rates ranging from 2.2 to 23.8 g SO(4)(2-)/cycle, which corresponds to sulfate concentrations of 0.25, 0.5,1.0, 2.0 and 3.0 g SW(4)(2-)L(-1). The sulfate removal efficiency reached 99% at concentrations of 0.25, 0.5 and 1.0 g SO(4)(2-)L(-1). At higher sulfate concentrations (2.0 and 3.0 g SO(4)(2-)L(-1)), the sulfate conversion remained in the range of 71-95%. The results demonstrate the potential applicability of butanol as the carbon source for the biological treatment of sulfate in an anaerobic batch reactor. (C) 2011 Elsevier Ltd. All rights reserved.
Resumo:
This paper analyzes the influence of carbon source and inoculum origin on the dynamics of biomass adhesion to an inert support in anaerobic reactors fed with acid mine drainage. Formic acid, lactic acid and ethanol were used as carbon sources. Two different inocula were evaluated: one taken from an UASB reactor and other from the sediment of a uranium mine. The values of average colonization rates and the maximum biomass concentration (C(max)) were inversely proportional to the number of carbon atoms in each substrate. The highest C(max) value (0.35 g TVS g(-1) foam) was observed with formic acid and anaerobic sludge as inoculum. Maximum colonization rates (v(max)) were strongly influenced by the type of inoculum when ethanol and lactic acid were used. For both carbon sources, the use of mine sediment as inoculum resulted in a v(max) of 0.013 g TVS g(-1) foam day(-1), whereas 0.024 g TVS g(-1) foam day(-1) was achieved with anaerobic sludge. (C) 2011 Elsevier Ltd. All rights reserved.
Resumo:
Fault resistance is a critical component of electric power systems operation due to its stochastic nature. If not considered, this parameter may interfere in fault analysis studies. This paper presents an iterative fault analysis algorithm for unbalanced three-phase distribution systems that considers a fault resistance estimate. The proposed algorithm is composed by two sub-routines, namely the fault resistance and the bus impedance. The fault resistance sub-routine, based on local fault records, estimates the fault resistance. The bus impedance sub-routine, based on the previously estimated fault resistance, estimates the system voltages and currents. Numeric simulations on the IEEE 37-bus distribution system demonstrate the algorithm`s robustness and potential for offline applications, providing additional fault information to Distribution Operation Centers and enhancing the system restoration process. (C) 2011 Elsevier Ltd. All rights reserved.
Resumo:
This paper considers the optimal linear estimates recursion problem for discrete-time linear systems in its more general formulation. The system is allowed to be in descriptor form, rectangular, time-variant, and with the dynamical and measurement noises correlated. We propose a new expression for the filter recursive equations which presents an interesting simple and symmetric structure. Convergence of the associated Riccati recursion and stability properties of the steady-state filter are provided. (C) 2010 Elsevier Ltd. All rights reserved.
Resumo:
Power distribution automation and control are import-ant tools in the current restructured electricity markets. Unfortunately, due to its stochastic nature, distribution systems faults are hardly avoidable. This paper proposes a novel fault diagnosis scheme for power distribution systems, composed by three different processes: fault detection and classification, fault location, and fault section determination. The fault detection and classification technique is wavelet based. The fault-location technique is impedance based and uses local voltage and current fundamental phasors. The fault section determination method is artificial neural network based and uses the local current and voltage signals to estimate the faulted section. The proposed hybrid scheme was validated through Alternate Transient Program/Electromagentic Transients Program simulations and was implemented as embedded software. It is currently used as a fault diagnosis tool in a Southern Brazilian power distribution company.
Resumo:
This work presents an analysis of the wavelet-Galerkin method for one-dimensional elastoplastic-damage problems. Time-stepping algorithm for non-linear dynamics is presented. Numerical treatment of the constitutive models is developed by the use of return-mapping algorithm. For spacial discretization we can use wavelet-Galerkin method instead of standard finite element method. This approach allows to locate singularities. The discrete formulation developed can be applied to the simulation of one-dimensional problems for elastic-plastic-damage models. (C) 2007 Elsevier Inc. All rights reserved.
Resumo:
This paper presents a new methodology to estimate unbalanced harmonic distortions in a power system, based on measurements of a limited number of given sites. The algorithm utilizes evolutionary strategies (ES), a development branch of evolutionary algorithms. The problem solving algorithm herein proposed makes use of data from various power quality meters, which can either be synchronized by high technology GPS devices or by using information from a fundamental frequency load flow, what makes the overall power quality monitoring system much less costly. The ES based harmonic estimation model is applied to a 14 bus network to compare its performance to a conventional Monte Carlo approach. It is also applied to a 50 bus subtransmission network in order to compare the three-phase and single-phase approaches as well as the robustness of the proposed method. (C) 2010 Elsevier B.V. All rights reserved.
Resumo:
This paper presents a new methodology to estimate harmonic distortions in a power system, based on measurements of a limited number of given sites. The algorithm utilizes evolutionary strategies (ES), a development branch of evolutionary algorithms. The main advantage in using such a technique relies upon its modeling facilities as well as its potential to solve fairly complex problems. The problem-solving algorithm herein proposed makes use of data from various power-quality (PQ) meters, which can either be synchronized by high technology global positioning system devices or by using information from a fundamental frequency load flow. This second approach makes the overall PQ monitoring system much less costly. The algorithm is applied to an IEEE test network, for which sensitivity analysis is performed to determine how the parameters of the ES can be selected so that the algorithm performs in an effective way. Case studies show fairly promising results and the robustness of the proposed method.
Resumo:
A laboratory scale activated sludge sequencing batch reactor was operated in order to obtain total removal of influent ammonia (200; 300 and 500 mg NH(3)-N.L(-1)) with sustained nitrite accumulation at the end of the aerobic stages with phenol (1,000 mg C(6)H(5)OH.L(-1)) as the carbon source for denitrifying microorganisms during the anoxic stages. Ammonia removal above 95% and ratios of (NO(2)(-)-N / (NO(2)(-)-N + NO(3)(-)-N)) ranging from 89 to 99% were obtained by controlling the dissolved oxygen concentration (1.0 mg O(2).L(-1)) and the pH value of 8.3 during the aerobic stages. Phenol proved to be an adequate source of carbon for nitrogen removal via nitrite with continuous feeding throughout part of the anoxic stage. Nitrite concentrations greater than 70.0 mg NO(2)(-)-N.L(-1) inhibited the biological denitritation process.
Resumo:
This work examines the effect of weld strength mismatch on fracture toughness measurements defined by J and CTOD fracture parameters using single edge notch bend (SE(B)) specimens. A central objective of the present study is to enlarge on previous developments of J and CTOD estimation procedures for welded bend specimens based upon plastic eta factors (eta) and plastic rotational factors (r (p) ). Very detailed non-linear finite element analyses for plane-strain models of standard SE(B) fracture specimens with a notch located at the center of square groove welds and in the heat affected zone provide the evolution of load with increased crack mouth opening displacement required for the estimation procedure. One key result emerging from the analyses is that levels of weld strength mismatch within the range +/- 20% mismatch do not affect significantly J and CTOD estimation expressions applicable to homogeneous materials, particularly for deeply cracked fracture specimens with relatively large weld grooves. The present study provides additional understanding on the effect of weld strength mismatch on J and CTOD toughness measurements while, at the same time, adding a fairly extensive body of results to determine parameters J and CTOD for different materials using bend specimens with varying geometries and mismatch levels.
Resumo:
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.