Tm-afm nonlinear motion control with robustness analysis to parametric errors in the control signal determination

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Proposta para a estimativa da acurácia de redes geodésicas horizontais integrando análise de robustez e de covariância

The goal of this paper is to present a methodology for quality control of horizontal geodetic networks through robustness and covariance analysis. In the proposed methodology, the positional accuracy of each point is estimated by a possible bias in their position (based on robustness analysis), in addition to its own positional precision (uncertainty) (through covariance analysis), being a measure independently from the choice of the datum. Besides presenting the theoretical development of the method, its application is demonstrated in a numerical example. The results indicate that, in general, the greater the distance of an unknown point to the control(s) point(s) of the network, the greater is the propagation of random errors on this unknown point, and the smaller the number of redundant observations around a unknown point, the greater the influence of possible (undetected) non-random errors on this point.

Análise de robustez de estações da rede GNSS-SP

Currently, the need of reliable coordinates has been one of the main objectives of the scientific and practice community. Thus, the robustness analysis of a geodetic network, aims, at analyzing if the network is robust or not, based on the maximum undetectable errors. The network will be robust if the influence of these errors is small, otherwise it is weak, or not robust. This analysis is performed with the merger of two techniques, one which deals with the statistical analysis of reliability and the other one with the geometric strength analysis. The reliability analysis will provide the maximum error that cannot be detected by tests, after the adjustment. After finding these errors, the geometric strength analysis will determine the potential strain that the network will have, based on these errors. It is emphasized that the robustness analysis doesn't depend of the datum, reflecting only the geometry of the network and the accuracy of the observations (VANÌCEK et al., 2001). Therefore, this work aims at contributing to the scientific research on geodetic networks, checking the same, based on their geometry and observations.

Métrica para definição de pontos estáveis utilizando-se da Análise de Robustez no posicionamento por ponto preciso

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

An Intelligent System for Petroleum Well Drilling Cutting Analysis

Cutting analysis is a important and crucial task task to detect and prevent problems during the petroleum well drilling process. Several studies have been developed for drilling inspection, but none of them takes care about analysing the generated cutting at the vibrating shale shakers. Here we proposed a system to analyse the cutting's concentration at the vibrating shale shakers, which can indicate problems during the petroleum well drilling process, such that the collapse of the well borehole walls. Cutting's images are acquired and sent to the data analysis module, which has as the main goal to extract features and to classify frames according to one of three previously classes of cutting's volume. A collection of supervised classifiers were applied in order to allow comparisons about their accuracy and efficiency. We used the Optimum-Path Forest (OPF), Artificial Neural Network using Multi layer Perceptrons (ANN-MLP), Support Vector Machines (SVM) and a Bayesian Classifier (BC) for this task. The first one outperformed all the remaining classifiers. Recall that we are also the first to introduce the OPF classifier in this field of knowledge. Very good results show the robustness of the proposed system, which can be also integrated with other commonly system (Mud-Logging) in order to improve the last one's efficiency.

A Parameterization Technique for the Continuation Power Flow Developed from the Analysis of Power Flow Curves

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Rotor support stiffness estimation by sensitivity analysis

In the present work, a method for rotor support stiffness estimation via a model updating process using the sensitivity analysis is presented. This method consists in using the eigenvalues sensitivity analysis, relating to the rotor support stiffnesses variation to perform the adjustment of the model based on the minimization of the difference between eigenvalues of reference and eigenvalues obtained via mathematical model from previously adopted support bearing stiffness values. The mathematical model is developed by the finite element method and the method of adjustment should converge employing an iterative process. The performance and robustness of the method have been analyzed through a numerical example.

Integrated analysis of halogenated organic pollutants in sub-millilitre volumes of venous and umbilical cord blood sera

A rapid, robust and economical method for the analysis of persistent halogenated organic compounds in small volumes of human serum and umbilical cord blood is described. The pollutants studied cover a broad range of molecules of contemporary epidemiological and legislative concern, including polychlorobiphenyls (PCBs), polychlorobenzenes (CBs), hexachlorocyclohexanes (HCHs), DDTs, polychlorostyrenes (PCSs) and polybromodiphenyl ethers (PBDEs). Extraction and clean-up with n-hexane and concentrated sulphuric acid was followed with analysis by gas chromatography coupled to electron capture (GC-ECD) and GC coupled to negative ion chemical ionisation mass spectrometry (GC-NICI-MS). The advantages of this method rest in the broad range of analytes and its simplicity and robustness, while the use of concentrated sulphuric acid extraction/clean-up destroys viruses that may be present in the samples. Small volumes of reference serum between 50 and 1000 μL were extracted and the limits of detection/quantification and repeatability were determined. Recoveries of spiked compounds for the extraction of small volumes (≥300 μL) of the spiked reference serum were between 90% and 120%. The coefficients of variation of repeatability ranged from 0.1-14%, depending on the compound. Samples of 4-year-old serum and umbilical cord blood (n = 73 and 40, respectively) from a population inhabiting a village near a chloro-alkali plant were screened for the above-mentioned halogenated pollutants using this method and the results are briefly described. © 2010 Springer-Verlag.

An intelligent system to detect drilling problems through drilled cuttings return analysis

Cuttings return analysis is an important tool to detect and prevent problems during the petroleum well drilling process. Several measurements and tools have been developed for drilling problems detection, including mud logging, PWD and downhole torque information. Cuttings flow meters were developed in the past to provide information regarding cuttings return at the shale shakers. Their use, however, significantly impact the operation including rig space issues, interferences in geological analysis besides, additional personel required. This article proposes a non intrusive system to analyze the cuttings concentration at the shale shakers, which can indicate problems during drilling process, such as landslide, the collapse of the well borehole walls. Cuttings images are acquired by a high definition camera installed above the shakers and sent to a computer coupled with a data analysis system which aims the quantification and closure of a cuttings material balance in the well surface system domain. No additional people at the rigsite are required to operate the system. Modern Artificial intelligence techniques are used for pattern recognition and data analysis. Techniques include the Optimum-Path Forest (OPF), Artificial Neural Network using Multilayer Perceptrons (ANN-MLP), Support Vector Machines (SVM) and a Bayesian Classifier (BC). Field test results conducted on offshore floating vessels are presented. Results show the robustness of the proposed system, which can be also integrated with other data to improve the efficiency of drilling problems detection. Copyright 2010, IADC/SPE Drilling Conference and Exhibition.

Experimental analysis and adherence test of the electromagnetic zero-sequence blocking model

This paper reveals new contributions to the analysis and development of mitigating harmonic distortion devices. Considering the variety of sequential distribution of harmonic current, in the use of passive filters, one can point out the electromagnetic blocking device, which have received particular attention due to its robustness and low cost of installation. In this context, aiming the evaluation of the reliability of the results obtained through mathematical modeling, experimental tests are carried out using a low-power prototype, highlighting particular aspects related to its function as a zero-sequence harmonic blocking. © 2011 IEEE.

Multivariate curve resolution analysis applied to time-resolved synchrotron X-ray Absorption Spectroscopy monitoring of the activation of copper alumina catalyst

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Artificial Immune Systems Applied to the Analysis of Structural Integrity of a Building

This paper presents the application of artificial immune systems for analysis of the structural integrity of a building. Inspired by a biological process, it uses the negative selection algorithm to perform the identification and characterization of structural failure. This paper presents the application of artificial immune systems for analysis of the structural integrity of a building. Inspired by a biological process, it uses the negative selection algorithm to perform the identification and characterization of structural failure. This methodology can assist professionals in the inspection of mechanical and civil structures, to identify and characterize flaws, in order to perform preventative maintenance to ensure the integrity of the structure and decision-making. In order to evaluate the methodology was made modeling a two-story building and several situations were simulated (base-line condition and improper conditions), yielding a database of signs, which were used as input data for the negative selection algorithm. The results obtained by the present method efficiency, robustness and accuracy.

Analysis of Structural Integrity Using an ARTMAP-Fuzzy Artificial Neural Network

This paper presents the application of artificial neural networks in the analysis of the structural integrity of a building. The main objective is to apply an artificial neural network based on adaptive resonance theory, called ARTMAP-Fuzzy neural network and apply it to the identification and characterization of structural failure. This methodology can help professionals in the inspection of structures, to identify and characterize flaws in order to conduct preventative maintenance to ensure the integrity of the structure and decision-making. In order to validate the methodology was modeled a building of two walk, and from this model were simulated various situations (base-line condition and improper conditions), resulting in a database of signs, which were used as input data for ARTMAP-Fuzzy network. The results show efficiency, robustness and accuracy.

Reintroducing the red-billed curassow in Brazil: Population viability analysis points to potential success

Reintroduction can be enhanced by data from long-term post-release monitoring, which allows for modeling opportunities such as population viability analysis (PVA). PVA-relevant data were gathered via long-term monitoring of reintroduced red-billed curassows at the Guapiacu Ecological Reserve (REGUA), located in Rio de Janeiro, Brazil, over 25 months. In the present article, we (1) assess the robustness of the reintroduction plan, (2) evaluate the viability of the current reintroduced population, and (3) examine mitigation options to increase the viability of this population. VORTEX indicates that the initial plan, fully implemented, was likely to establish a viable population at REGUA. The current population is unviable; the best mitigation strategies are to eliminate hunting altogether, or at least reduce it by half, and to supplement ten immature pairs in 2015. A positive long-term outcome at REGUA is still possible; we encourage the Brazilian government and private stakeholders to consider population supplementation, both to achieve success at REGUA and to improve the evidence base for future reintroductions. (C) 2014 Associacao Brasileira de Ciencia Ecologica e Conservacao. Published by Elsevier Editora Ltda.

Validation of high-performance liquid chromatographic method for analysis of fluconazole in microemulsions and liquid crystals

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