Applying fuzzy logic systems in the estimation of crossflow filtration processes

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 behavior. In this paper, a system based on fuzzy logic systems is developed to overcome the problems usually found in the conventional mathematical models. Imprecisions and uncertainties associated with the measurements made on the system are automatically incorporated in the fuzzy approach. Simulation results are presented to justify the validity of the proposed approach.

Designing a modified Hopfield network to solve an Economic Dispatch problem with nonlinear cost function

Economic Dispatch (ED) problems have recently been solved by artificial neural networks approaches. In most of these dispatch models, the cost function must be linear or quadratic. Therefore, functions that have several minimum points represent a problem to the simulation since these approaches have not accepted nonlinear cost function. Another drawback pointed out in the literature is that some of these neural approaches fail to converge efficiently towards feasible equilibrium points. This paper discusses the application of a modified Hopfield architecture for solving ED problems defined by nonlinear cost function. The internal parameters of the neural network adopted here are computed using the valid-subspace technique, which guarantees convergence to equilibrium points that represent a solution for the ED problem. Simulation results and a comparative analysis involving a 3-bus test system are presented to illustrate efficiency of the proposed approach.

Mapping lightning processes using fuzzy inference system

This paper describes a novel approach for mapping lightning processes using fuzzy logic. The core regarding lightning process is to identify and to model those uncertain information on mathematical principles. In fact, the lightning process involves several nonlinear features that our current mathematical tools would not be able to model. The estimation process has been carried out using a fuzzy system based on Sugeno's architecture. Simulation results confirm that proposed approach can be efficiently used in these types of problem.

Nonlinear optimization using a modified Hopfield model

Systems based on artificial neural networks have high computational rates due to the use of a massive number of simple processing elements. Neural networks with feedback connections provide a computing model capable of solving a rich class of optimization problems. In this paper, a modified Hopfield network is developed for solving constrained nonlinear optimization problems. The internal parameters of the network are obtained using the valid-subspace technique. Simulated examples are presented as an illustration of the proposed approach.

Speciation analysis of Sn(II) and Sn(IV) using baker's yeast and inductively coupled plasma optical emission spectrometry

The use of Saccharomyces cerevisiae as a substrate to selectively retain Sn(II) and Sn(IV) has been investigated. Several factors affecting the retention of the analytes by yeast, such as pH, amount of biomass, temperature and time of contact were evaluated. Based on this study, a method for determination of Sn(II) and Sn(IV) combining inductively coupled plasma optical emission spectrometry (ICP OES) and solid phase extraction using Saccharomyces cerevisiae is proposed. The procedure consists of the selective retention of Sn(IV) by yeast at pH = 2.0 while Sn(II) remains in solution. Determination of tin in the solid phase was easily carried out by submitting a slurry of the yeast (0.5 g/40 mL) directly to ICP OES. The precision of the extraction procedure was characterized by an RSD lower than 4%. The detection limits of tin (3 sigma) in the solid phase and the liquid phase were 1.1 and 0.7 mu g L-1, respectively. The proposed approach was evaluated for determination of Sn(II) and Sn(IV) in spiked river water and real samples of industrial waste water (untreated and treated). For all samples, recoveries of spiked Sn(II) and Sn(IV) were between 85 and 112%.

Determination of Cd(II) and Cd-metallothioneins in biological extracts using baker's yeast and inductively coupled plasma optical emission spectrometry

The use of Saccharomyces cerevisiae as a sorbent material to separate Cd(II) and Cd-metallothionein complex (Cd-MT) has been explored. Solid-liquid phase extractions were carried out in batch mode and the main parameters of the process (pH, temperature, time of incubation, amount of biomass and analyte) were evaluated. Under optimized conditions, the yeast quantitatively retain (94 +/- 5%) the Cd(II) while 97 +/- 2% of the Cd-MT remain in the supernatant. on base of the findings of this study, a simple method is proposed to determine Cd(II) and Cd-MT in cytosols extracted from mouse kidney and crab hepatopancreas. Inductively coupled plasma optical emission spectrometry was used to quantify the analytes in solid and liquid phase. Determination of Cd in the solid phase was carried out by introducing a slurry of the yeast (0.0625 g/10 mL) directly to the inductively coupled plasma optical emission spectrometer. Mixed standards solutions, which also have been submitted to the extraction procedure, were used to quantify the analytes in the samples. Thus, matrix effects due to nebulization of the slurry were overcame. Limits of detection (3 sigma) for Cd(II) and Cd-MT were 1.5 and 1.2 mu g L-1, respectively. Relative standard deviations of signals were 4.2% for measurements in the slurry of solid phase and 2.1% for measurements in the liquid phase. Recoveries of the analytes in cytosol samples were between 76 and 114%. The concentrations of Cd(II) (2.4 +/- 0.5 mu g L-1) and Cd-MT (3.0 +/- 0.5 mu g L-1) found by using the proposed approach were close to those found by tangential-flow ultrafiltration technique (2.6 +/- 0.7 mu g L-1 for Cd(II) and 3.7 +/- 1.7 mu g L-1 for Cd-MT).

An implicit BEM formulation to model strong discontinuities in solids

A boundary element method (BEM) formulation to predict the behavior of solids exhibiting displacement (strong) discontinuity is presented. In this formulation, the effects of the displacement jump of a discontinuity interface embedded in an internal cell are reproduced by an equivalent strain field over the cell. To compute the stresses, this equivalent strain field is assumed as the inelastic part of the total strain. As a consequence, the non-linear BEM integral equations that result from the proposed approach are similar to those of the implicit BEM based on initial strains. Since discontinuity interfaces can be introduced inside the cell independently on the cell boundaries, the proposed BEM formulation, combined with a tracking scheme to trace the discontinuity path during the analysis, allows for arbitrary discontinuity propagation using a fixed mesh. A simple technique to track the crack path is outlined. This technique is based on the construction of a polygonal line formed by segments inside the cells, in which the assumed failure criterion is reached. Two experimental concrete fracture tests were analyzed to assess the performance of the proposed formulation.

Load torque estimation in induction motors using artificial neural networks

The induction motors are largely used in several industry sectors. The dimensioning 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 paper is to use artificial neural networks as tool for dimensioning of induction motors rather than conventional methods, which use classical identification techniques and mechanical load modeling. Simulation results are also presented to validate the proposed approach.

Automatic absolute orientation of scanned aerial photographs

Image orientation is a basic problem in Digital Photogrammetry. While interior and relative orientations were succesfully automated, the same can not be said about absolute orientation. This process can be automated by using an approach based on relational matching and a heuristic that uses the analytical relation between straight features in the object space and its homologous in the image space. A build-in self-diagnosis is also used in this method, that is based on the implementation of data snooping statistic test in the process of spatial resection, using the Iterated Extended Kalman Filtering (IEKF). The aim of this paper is to present the basic principles of the proposed approach and results based on real data.

Use of diffusive gradients in thin films and tangential flow ultrafiltration for fractionation of Al(III) and Cu(II) in organic-rich river waters

Diffusive gradients in thin films (DGT) and tangential-flow ultrafiltration (TF-UF) were combined for fractionation of Al and Cu in river water containing high content of dissolved organic carbon. A procedure based on ultrafiltration data is proposed to determine diffusion coefficients of the analytes in water samples and model solutions containing both free metal (M) and complex (metal - humic substance). Aiming to evaluate the accuracy of the proposed approach, the DGT results were compared with those from a protocol for determination of labile Al and Cu based on solid phase extraction (SPE). Good agreement between data from DGT and SPE were attained for model solutions. For analysis of real organic-rich water samples, differences between DGT and SPE measurements were consistent with the time-scales of the techniques. The concentration of labile Al determined by DGT were lower than the total dissolved concentrations (determined by inductively coupled plasma mass spectrometry) and exceeded the ultrafiltered concentration, indicating that inorganic Al species (species small enough to pass through 1 kDa membrane) were minor species as compared with Al organic complexes. For both Al and Cu, there were species not measured by DGT as they are not sufficiently labile. (C) 2007 Elsevier B.V. All rights reserved.

Strategy to detect ground control in digital images

The identification of ground control on photographs or images is usually carried out by a human operator, who uses his natural skills to make interpretations. In Digital Photogrammetry, which uses techniques of digital image processing extraction of ground control can be automated by using an approach based on relational matching and a heuristic that uses the analytical relation between straight features of object space and its homologous in the image space. A build-in self-diagnosis is also used in this method. It is based on implementation of data snooping statistic test in the process of spatial resection using the Iterated Extended Kalman Filtering (IEKF). The aim of this paper is to present the basic principles of the proposed approach and results based on real data.

Lagrangian heuristic for a class of the generalized assignment problems

A Lagrangian based heuristic is proposed for many-to-many assignment problems taking into account capacity limits for task and agents. A modified Lagrangian bound studied earlier by the authors is presented and a greedy heuristic is then applied to get a feasible Lagrangian-based solution. The latter is also used to speed up the subgradient scheme to solve the modified Lagrangian dual problem. A numerical study is presented to demonstrate the efficiency of the proposed approach. (C) 2010 Elsevier Ltd. All rights reserved.

Location and contract pricing of distributed generation using a genetic algorithm

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Accountability in Smart Microgrids Based on Conservative Power Theory

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.

Paper-based diffusive gradients in thin films technique coupled to energy dispersive X-ray fluorescence spectrometry for the determination of labile Mn, Co, Ni, Cu, Zn and Pb in river water

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