Tungsten permanent chemical modifier for fast estimation of Se contents in soil by graphite furnace atomic absorption spectrometry

A tungsten carbide coating on the integrated platform of a transversely heated graphite atomizer was used as a modifier for the direct determination of Se in soil extracts by graphite furnace atomic absorption spectrometry. Diethylenetriaminepentaacetic acid (0.0050 mol L-1) plus ammonium hydrogencarbonate (1.0 mol L-1) extracted predominantly available inorganic selenate from soil. The formation of a large amount of carbonaceous residue inside the atomizer was avoided with a first pyrolysis step at 600 degreesC assisted by air during 30 s. For 20 muL of soil extracts delivered to the atomizer and calibration by matrix matching, an analytical curve (10.0-100 mug of L-1) with good linear correlation (r = 0.999) between integrated absorbance and analyte concentration was established. The characteristic mass was similar to63 pg of Se, and the lifetime of the tube was similar to750 firings. The limit of detection was 1.6 mug L-1, and the relative standard deviations (n = 12) were typically <4% for a soil extract containing 50 mug of L-1. The accuracy of the determination of Se was checked for soil samples by means of addition/recovery tests. Recovery data of Se added to four enriched soil samples varied from 80 to 90% and indicated an accurate method.

Optical Behavior of Conjugated Pt-Containing Polymetallaynes Exposed to Gamma-Ray Radiation Doses

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Structural Changes of Conjugated Pt-Containing Polymetallaynes Exposed to Gamma Ray Radiation Doses

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Ionizing radiation induced degradation of poly (2-methoxy-5-(2 '-ethyl-hexyloxy)-1,4-phenylene vinylene) in solution

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

A neural network approach for robust nonlinear parameter estimation in presence of unknown-but-bounded errors

Systems based on artificial neural networks have high computational rates due to the use of a massive number of simple processing elements and the high degree of connectivity between these elements. This paper presents a novel approach to solve robust parameter estimation problem for nonlinear model with unknown-but-bounded errors and uncertainties. More specifically, a modified Hopfield network is developed and its internal parameters are computed using the valid-subspace technique. These parameters guarantee the network convergence to the equilibrium points. A solution for the robust estimation problem with unknown-but-bounded error corresponds to an equilibrium point of the network. Simulation results are presented as an illustration of the proposed approach. Copyright (C) 2000 IFAC.

Using neural networks for estimation of aquifer dynamical behavior

The systems of water distribution from groundwater wells can be monitored using the changes observed on its dynamical behavior. In this paper, artificial neural networks are used to estimate the depth of the dynamical water level of groundwater wells in relation to water flow, operation time and rest time. Simulation results are presented to demonstrate the validity of the proposed approach. These results have shown that artificial neural networks can be effectively used for the identification and estimation of parameters related to systems of water distribution.

Neural network based estimation of torque in induction motors for real-time applications

Induction motors are largely used in several industry sectors. The selection of an induction motor has still been inaccurate because in most of the cases the load behavior in its shaft is completely unknown. The proposal of this article is to use artificial neural networks for torque estimation with the purpose of best selecting the induction motors rather than conventional methods, which use classical identification techniques and mechanical load modeling. Since proposed approach estimates the torque behavior from the transient to the steady state, one of its main contributions is the potential to also be implemented in control schemes for real-time applications. Simulation results are also presented to validate the proposed approach.

A novel approach to robust parameter estimation using neurofuzzy systems

A novel approach for solving robust parameter estimation problems is presented for processes with unknown-but-bounded errors and uncertainties. An artificial neural network is developed to calculate a membership set for model parameters. Techniques of fuzzy logic control lead the network to its equilibrium points. Simulated examples are presented as an illustration of the proposed technique. The result represent a significant improvement over previously proposed methods. (C) 1999 IMACS/Elsevier B.V. B.V. All rights reserved.

Spacecraft's attitude prediction: solar radiation torque and the Earth's shadow

A semi-analytical approach is proposed to study the rotational motion of an artificial satellite, under the influence of torque due to the solar radiation pressure, and taking into account the influence of Earth's shadow. Using Andoyer variables the equations for the rotational motion are presented in extended Hamiltonian form. In order to get a solution for the state variables close to an actual motion, the considered model for the shadow function takes into account physical and geometric factors and three specific regions: shadow, penumbra and full light. A mapping for the shadow function is proposed and a semi-analytical process is applied. When the satellite is totally illuminated or it is inside the penumbra, a known analytical solution is used to compute the satellite's attitude. A numerical simulation shows, when the penumbra region is included, the attenuation of the rotational motion during the transition from the shadow to the illuminate region and vice versa. (c) 2005 Published by Elsevier Ltd on behalf of COSPAR.

Stratified Sampling Applied to Estimation of the Volumetric Fraction of Alumina in Cast Metal Matrix Composites

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Unscented Kalman Filter Applied to the Spacecraft Attitude Estimation with Euler Angles

The aim of this work is to test an algorithm to estimate, in real time, the attitude of an artificial satellite using real data supplied by attitude sensors that are on board of the CBERS-2 satellite (China Brazil Earth Resources Satellite). The real-time estimator used in this work for attitude determination is the Unscented Kalman Filter. This filter is a new alternative to the extended Kalman filter usually applied to the estimation and control problems of attitude and orbit. This algorithm is capable of carrying out estimation of the states of nonlinear systems, without the necessity of linearization of the nonlinear functions present in the model. This estimation is possible due to a transformation that generates a set of vectors that, suffering a nonlinear transformation, preserves the same mean and covariance of the random variables before the transformation. The performance will be evaluated and analyzed through the comparison between the Unscented Kalman filter and the extended Kalman filter results, by using real onboard data.

Fault section estimation in electric power systems using an optimization immune algorithm

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Levenberg-Marquardt application to two-phase nonlinear parameter estimation for finned-tube coil evaporators

A procedure for calculation of refrigerant mass flow rate is implemented in the distributed numerical model to simulate the flow in finned-tube coil dry-expansion evaporators, usually found in refrigeration and air-conditioning systems. Two-phase refrigerant flow inside the tubes is assumed to be one-dimensional, unsteady, and homogeneous. In themodel the effects of refrigerant pressure drop and the moisture condensation from the air flowing over the external surface of the tubes are considered. The results obtained are the distributions of refrigerant velocity, temperature and void fraction, tube-wall temperature, air temperature, and absolute humidity. The finite volume method is used to discretize the governing equations. Additionally, given the operation conditions and the geometric parameters, the model allows the calculation of the refrigerant mass flow rate. The value of mass flow rate is computed using the process of parameter estimation with the minimization method of Levenberg-Marquardt minimization. In order to validate the developed model, the obtained results using HFC-134a as a refrigerant are compared with available data from the literature.

Reduction of crotoxin-induced neuromuscular blockade by gamma radiation

A comparative study between crotoxin and gamma irradiated crotoxin was performed on the indirectly evoked twitches and tetani of sciatic nerve-extensor digitorum longus muscle of rats. Crotoxin (3 to 14 mu g/ml) decreased the amplitude of twitches and induced a slight tetanic fade, and irradiated crotoxin did not significantly affect either twitch amplitude or tetanic tension. Since gamma radiation reduced the neurotoxicity of crotoxin it may be useful for the production of anticrotalic serum. (C) 1998 Elsevier B.V. Ltd. All rights reserved.

Quantitative estimation of Br, Cl, K and Na in sample blood by NAA

Neutron activation analysis, using Au as flux monitor, was applied to determine the concentrations of Br, Cl, K and Na in blood of healthy male and female blood donors, selected from blood banks and hematological laboratories from different regions of Brazil. The aims of this study were to collect more reference values of the Brazilian population as well as to perform hematological investigations. The advantages as well as the limitations of using this nuclear procedure are discussed.