Adsorção de cobre e cromo utilizando fibra de sisal visando o tratamento da água produzida pela indústria petrolífera

Currently, the oil industry is the biggest cause of environmental pollution. The objective was to reduce the concentration of copper and chromium in the water produced by the oil industry. It was used as adsorbent natural sisal fiber Agave sp treated with nitric acid and sodium hydroxide. All vegetable fibers have physical and morphological properties that enablies the adsorption of pollutants. The basic composition of sisal is cellulose, hemicellulose and lignin. The features are typically found in the characterization of vegetable fibers, except the surface area that was practically zero. In the first stage of adsorption, it was evaluated the effect of temperature and time skeeking to optimize the execution of the factorial design. The results showed that the most feasible fiber was the one treated with acid in five hours (30°C). The second phase was a factorial design, using acid and five hours, this time was it determined in the first phase. The tests were conducted following the experimental design and the results were analyzed by statistical methods in order to optimize the main parameters that influence the process: pH, concentration (mol / L) and fiber mass/ metal solution volume. The volume / mass ratio factor showed significant interference in the adsorption process of chromium and copper. The results obtained after optimization showed that the highest percentages of extraction (98%) were obtained on the following operating conditions: pH: 5-6, Concentration: 100 ppm and mass/ volume: 1 gram of fiber/50mL solution. The results showed that the adsorption process was efficient to remove chromium and copper using sisal fibers, however, requiring further studies to optimize the process.

Previsão do índice bovespa por meio de redes neurais artificiais: uma análise comparada aos métodos tradicionais de séries de tempo

Forecast is the basis for making strategic, tactical and operational business decisions. In financial economics, several techniques have been used to predict the behavior of assets over the past decades.Thus, there are several methods to assist in the task of time series forecasting, however, conventional modeling techniques such as statistical models and those based on theoretical mathematical models have produced unsatisfactory predictions, increasing the number of studies in more advanced methods of prediction. Among these, the Artificial Neural Networks (ANN) are a relatively new and promising method for predicting business that shows a technique that has caused much interest in the financial environment and has been used successfully in a wide variety of financial modeling systems applications, in many cases proving its superiority over the statistical models ARIMA-GARCH. In this context, this study aimed to examine whether the ANNs are a more appropriate method for predicting the behavior of Indices in Capital Markets than the traditional methods of time series analysis. For this purpose we developed an quantitative study, from financial economic indices, and developed two models of RNA-type feedfoward supervised learning, whose structures consisted of 20 data in the input layer, 90 neurons in one hidden layer and one given as the output layer (Ibovespa). These models used backpropagation, an input activation function based on the tangent sigmoid and a linear output function. Since the aim of analyzing the adherence of the Method of Artificial Neural Networks to carry out predictions of the Ibovespa, we chose to perform this analysis by comparing results between this and Time Series Predictive Model GARCH, developing a GARCH model (1.1).Once applied both methods (ANN and GARCH) we conducted the results' analysis by comparing the results of the forecast with the historical data and by studying the forecast errors by the MSE, RMSE, MAE, Standard Deviation, the Theil's U and forecasting encompassing tests. It was found that the models developed by means of ANNs had lower MSE, RMSE and MAE than the GARCH (1,1) model and Theil U test indicated that the three models have smaller errors than those of a naïve forecast. Although the ANN based on returns have lower precision indicator values than those of ANN based on prices, the forecast encompassing test rejected the hypothesis that this model is better than that, indicating that the ANN models have a similar level of accuracy . It was concluded that for the data series studied the ANN models show a more appropriate Ibovespa forecasting than the traditional models of time series, represented by the GARCH model

Controle preditivo neural aplicado à processos petroquímicos

A pesquisa tem como objetivo desenvolver uma estrutura de controle preditivo neural, com o intuito de controlar um processo de pH, caracterizado por ser um sistema SISO (Single Input - Single Output). O controle de pH é um processo de grande importância na indústria petroquímica, onde se deseja manter constante o nível de acidez de um produto ou neutralizar o afluente de uma planta de tratamento de fluidos. O processo de controle de pH exige robustez do sistema de controle, pois este processo pode ter ganho estático e dinâmica nãolineares. O controlador preditivo neural envolve duas outras teorias para o seu desenvolvimento, a primeira referente ao controle preditivo e a outra a redes neurais artificiais (RNA s). Este controlador pode ser dividido em dois blocos, um responsável pela identificação e outro pelo o cálculo do sinal de controle. Para realizar a identificação neural é utilizada uma RNA com arquitetura feedforward multicamadas com aprendizagem baseada na metodologia da Propagação Retroativa do Erro (Error Back Propagation). A partir de dados de entrada e saída da planta é iniciado o treinamento offline da rede. Dessa forma, os pesos sinápticos são ajustados e a rede está apta para representar o sistema com a máxima precisão possível. O modelo neural gerado é usado para predizer as saídas futuras do sistema, com isso o otimizador calcula uma série de ações de controle, através da minimização de uma função objetivo quadrática, fazendo com que a saída do processo siga um sinal de referência desejado. Foram desenvolvidos dois aplicativos, ambos na plataforma Builder C++, o primeiro realiza a identificação, via redes neurais e o segundo é responsável pelo controle do processo. As ferramentas aqui implementadas e aplicadas são genéricas, ambas permitem a aplicação da estrutura de controle a qualquer novo processo

Potencial larvicida de extratos de plantas regionais no controle de larvas de Aedes aegypti

Dengue, amongst the virus illnesses one can get by vectorial transmission, is the one that causes more impact in the morbidity and mortality of world s population. The resistance to the insecticides has caused difficulties to control of vector insect (Aedes aegypti) and has stimulated a search for vegetables with larvicidal activity. The biodiversity of Caatinga is barely known and it is potential of use even less. Some plants of this biome are commercialized in free fairs northeast of Brazil, because of its phytotherapics properties. The vegetables in this study had been selected by means of a questionnaire applied between grass salesmen and natives of the Serido region from Rio Grande do Norte state; culicids eggs had been acquired with traps and placed in container with water for the larva birth. Thirty larvae had been used in each group (a group control and five experimental groups), with four repetitions four times. The vegetables had been submitted to the processes of decoction, infusion and maceration in the standard concentration of 100g of the vegetable of study in 1l of H2O and analyzed after ½, 1, 2, 4, 8, 12, 24 and 48 hours for verification of the average lethal dose (LD50) from the groups with thirty larva. The LD50 was analyzed in different concentrations (50g/l, 100g/l, 150g/l, 200g/l e 300g/l) of Aspidosperma pyrifolium Mart. 48 extracts of rind, leaf and stem of the seven vegetal species: Aspidosperma pyrifolium Mart., Mimosa verrucosa Benth, Mimosa hostilis (Mart.) Benth., Myracrodruon urundeuva Allemão, Ximenia americana L, Bumelia sartorum Mart Zizyphus joazeiro Mart, had been analyzed. The extracts proceeding from the three methods were submitted to the freezedrying, to evaluate and to quantify substances extracted in each process. The results had shown that Aspidosperma pyrifolium Mart. and Myracrodruon urundeuva Allemão are the species that are more distinguished as larvicidal after 24 hours of experiment, in all used processes of extraction in the assays. The Zizyphus joazeiro Mart species has not shown larvicidal activity in none of the assays. In relation to the extraction method, the decoction was the most efficient method in the mortality tax of the A. aegypti larvae

Controlador preditivo não linear aplicado ao controle de golfadas em processos de produção de petróleo

Slugging is a well-known slugging phenomenon in multiphase flow, which may cause problems such as vibration in pipeline and high liquid level in the separator. It can be classified according to the place of its occurrence. The most severe, known as slugging in the riser, occurs in the vertical pipe which feeds the platform. Also known as severe slugging, it is capable of causing severe pressure fluctuations in the flow of the process, excessive vibration, flooding in separator tanks, limited production, nonscheduled stop of production, among other negative aspects that motivated the production of this work . A feasible solution to deal with this problem would be to design an effective method for the removal or reduction of the system, a controller. According to the literature, a conventional PID controller did not produce good results due to the high degree of nonlinearity of the process, fueling the development of advanced control techniques. Among these, the model predictive controller (MPC), where the control action results from the solution of an optimization problem, it is robust, can incorporate physical and /or security constraints. The objective of this work is to apply a non-conventional non-linear model predictive control technique to severe slugging, where the amount of liquid mass in the riser is controlled by the production valve and, indirectly, the oscillation of flow and pressure is suppressed, while looking for environmental and economic benefits. The proposed strategy is based on the use of the model linear approximations and repeatedly solving of a quadratic optimization problem, providing solutions that improve at each iteration. In the event where the convergence of this algorithm is satisfied, the predicted values of the process variables are the same as to those obtained by the original nonlinear model, ensuring that the constraints are satisfied for them along the prediction horizon. A mathematical model recently published in the literature, capable of representing characteristics of severe slugging in a real oil well, is used both for simulation and for the project of the proposed controller, whose performance is compared to a linear MPC

Síntese e caracterização de pigmentos nanométricos encapsulados pelos métodos dos precursores poliméricos, hidrotermal de microondas e co-precipitação associado à química sol-gel convencional

The demand for materials with high consistency obtained at relatively low temperatures has been leveraging the search for chemical processes substituents of the conventional ceramic method. This paper aims to obtain nanosized pigments encapsulated (core-shell) the basis of TiO2 doped with transition metals (Fe, Co, Ni, Al) through three (3) methods of synthesis: polymeric precursors (Pechini); hydrothermal microwave, and co-precipitation associated with the sol-gel chemistry. The study was motivated by the simplicity, speed and low power consumption characteristic of these methods. Systems costs are affordable because they allow achieving good control of microstructure, combined with high purity, controlled stoichiometric phases and allowing to obtain particles of nanometer size. The physical, chemical, morphological, structural and optical properties of the materials obtained were analyzed using different techniques for materials characterization. The powder pigments were tested in discoloration and degradation using a photoreactor through the solution of Remazol yellow dye gold (NNI), such as filtration, resulting in a separation of solution and the filter pigments available for further UV-Vis measurements . Different calcination temperatures taken after obtaining the post, the different methods were: 400 º C and 1000 º C. Using a fixed concentration of 10% (Fe, Al, Ni, Co) mass relative to the mass of titanium technologically and economically enabling the study. By transmission electron microscopy (TEM) technique was possible to analyze and confirm the structural formation nanosized particles of encapsulated pigment, TiO2 having the diameter of 20 nm to 100 nm, and thickness of coated layer of Fe, Ni and Co between 2 nm and 10 nm. The method of synthesis more efficient has been studied in the work co-precipitation associated with sol-gel chemistry, in which the best results were achieved without the need for the obtainment of powders the calcination process

Gráfico de controle modificado para processos com estruturas complexas de autocorrelação

This work proposes a modified control chart incorporating concepts of time series analysis. Specifically, we considerer Gaussian mixed transition distribution (GMTD) models. The GMTD models are a more general class than the autorregressive (AR) family, in the sense that the autocorrelated processes may present flat stretches, bursts or outliers. In this scenario traditional Shewhart charts are no longer appropriate tools to monitoring such processes. Therefore, Vasilopoulos and Stamboulis (1978) proposed a modified version of those charts, considering proper control limits based on autocorrelated processes. In order to evaluate the efficiency of the proposed technique a comparison with a traditional Shewhart chart (which ignores the autocorrelation structure of the process), a AR(1) Shewhart control chart and a GMTD Shewhart control chart was made. An analytical expression for the process variance, as well as control limits were developed for a particular GMTD model. The ARL was used as a criteria to measure the efficiency of control charts. The comparison was made based on a series generated according to a GMTD model. The results point to the direction that the modified Shewhart GMTD charts have a better performance than the AR(1) Shewhart and the traditional Shewhart.

Previsão do índice bovespa por meio de redes neurais artificiais: uma análise comparada aos métodos tradicionais de séries de tempo

Forecast is the basis for making strategic, tactical and operational business decisions. In financial economics, several techniques have been used to predict the behavior of assets over the past decades.Thus, there are several methods to assist in the task of time series forecasting, however, conventional modeling techniques such as statistical models and those based on theoretical mathematical models have produced unsatisfactory predictions, increasing the number of studies in more advanced methods of prediction. Among these, the Artificial Neural Networks (ANN) are a relatively new and promising method for predicting business that shows a technique that has caused much interest in the financial environment and has been used successfully in a wide variety of financial modeling systems applications, in many cases proving its superiority over the statistical models ARIMA-GARCH. In this context, this study aimed to examine whether the ANNs are a more appropriate method for predicting the behavior of Indices in Capital Markets than the traditional methods of time series analysis. For this purpose we developed an quantitative study, from financial economic indices, and developed two models of RNA-type feedfoward supervised learning, whose structures consisted of 20 data in the input layer, 90 neurons in one hidden layer and one given as the output layer (Ibovespa). These models used backpropagation, an input activation function based on the tangent sigmoid and a linear output function. Since the aim of analyzing the adherence of the Method of Artificial Neural Networks to carry out predictions of the Ibovespa, we chose to perform this analysis by comparing results between this and Time Series Predictive Model GARCH, developing a GARCH model (1.1).Once applied both methods (ANN and GARCH) we conducted the results' analysis by comparing the results of the forecast with the historical data and by studying the forecast errors by the MSE, RMSE, MAE, Standard Deviation, the Theil's U and forecasting encompassing tests. It was found that the models developed by means of ANNs had lower MSE, RMSE and MAE than the GARCH (1,1) model and Theil U test indicated that the three models have smaller errors than those of a naïve forecast. Although the ANN based on returns have lower precision indicator values than those of ANN based on prices, the forecast encompassing test rejected the hypothesis that this model is better than that, indicating that the ANN models have a similar level of accuracy . It was concluded that for the data series studied the ANN models show a more appropriate Ibovespa forecasting than the traditional models of time series, represented by the GARCH model

Controle preditivo neural aplicado à processos petroquímicos

A pesquisa tem como objetivo desenvolver uma estrutura de controle preditivo neural, com o intuito de controlar um processo de pH, caracterizado por ser um sistema SISO (Single Input - Single Output). O controle de pH é um processo de grande importância na indústria petroquímica, onde se deseja manter constante o nível de acidez de um produto ou neutralizar o afluente de uma planta de tratamento de fluidos. O processo de controle de pH exige robustez do sistema de controle, pois este processo pode ter ganho estático e dinâmica nãolineares. O controlador preditivo neural envolve duas outras teorias para o seu desenvolvimento, a primeira referente ao controle preditivo e a outra a redes neurais artificiais (RNA s). Este controlador pode ser dividido em dois blocos, um responsável pela identificação e outro pelo o cálculo do sinal de controle. Para realizar a identificação neural é utilizada uma RNA com arquitetura feedforward multicamadas com aprendizagem baseada na metodologia da Propagação Retroativa do Erro (Error Back Propagation). A partir de dados de entrada e saída da planta é iniciado o treinamento offline da rede. Dessa forma, os pesos sinápticos são ajustados e a rede está apta para representar o sistema com a máxima precisão possível. O modelo neural gerado é usado para predizer as saídas futuras do sistema, com isso o otimizador calcula uma série de ações de controle, através da minimização de uma função objetivo quadrática, fazendo com que a saída do processo siga um sinal de referência desejado. Foram desenvolvidos dois aplicativos, ambos na plataforma Builder C++, o primeiro realiza a identificação, via redes neurais e o segundo é responsável pelo controle do processo. As ferramentas aqui implementadas e aplicadas são genéricas, ambas permitem a aplicação da estrutura de controle a qualquer novo processo

Potencial larvicida de extratos de plantas regionais no controle de larvas de Aedes Aegypti (Diptera:Culicidae)

Dengue, amongst the virus illnesses one can get by vectorial transmission, is the one that causes more impact in the morbidity and mortality of world s population. The resistance to the insecticides has caused difficulties to control of vector insect (Aedes aegypti) and has stimulated a search for vegetables with larvicidal activity. The biodiversity of Caatinga is barely known and it is potential of use even less. Some plants of this biome are commercialized in free fairs northeast of Brazil, because of its phytotherapics properties. The vegetables in this study had been selected by means of a questionnaire applied between grass salesmen and natives of the Serido region from Rio Grande do Norte state; culicids eggs had been acquired with traps and placed in container with water for the larva birth. Thirty larvae had been used in each group (a group control and five experimental groups), with four repetitions four times. The vegetables had been submitted to the processes of decoction, infusion and maceration in the standard concentration of 100g of the vegetable of study in 1l of H2O and analyzed after ½, 1, 2, 4, 8, 12, 24 and 48 hours for verification of the average lethal dose (LD50) from the groups with thirty larva. The LD50 was analyzed in different concentrations (50g/l, 100g/l, 150g/l, 200g/l e 300g/l) of Aspidosperma pyrifolium Mart. 48 extracts of rind, leaf and stem of the seven vegetal species: Aspidosperma pyrifolium Mart., Mimosa verrucosa Benth, Mimosa hostilis (Mart.) Benth., Myracrodruon urundeuva Allemão, Ximenia americana L, Bumelia sartorum Mart Zizyphus joazeiro Mart, had been analyzed. The extracts proceeding from the three methods were submitted to the freezedrying, to evaluate and to quantify substances extracted in each process. The results had shown that Aspidosperma pyrifolium Mart. and Myracrodruon urundeuva Allemão are the species that are more distinguished as larvicidal after 24 hours of experiment, in all used processes of extraction in the assays. The Zizyphus joazeiro Mart species has not shown larvicidal activity in none of the assays. In relation to the extraction method, the decoction was the most efficient method in the mortality tax of the A. aegypti larvae

Eleição nas escolas: uma análise do impacto do diretor eleito sobre o desempenho educacional no Estado da Bahia

In Brazil, the selection of school principals is set in a decentralized manner by each state and city, such that processes may vary with time for a specific locality. In the state of Bahia, school principals were appointed by a higher political hierarchy until 2008, when schools under state administration started selecting principals by elections. The main goal of this work is to evaluate whether changing this specific rule affected students proficiency levels. This is achieved by using a panel data and difference-in-differences approachs that compares state schools (treatment group) to city schools (control group) that did not face a selection rule change and thus kept having their principals politically appointed. The databases used are Prova Brasil 2007, 2009 and 2011, the first one prior and the other two former to the policy change. Our results suggest that students attending schools with principals that are selected and elected have slightly lower mean proficiency levels both in mathematics and in portuguese exams than those attending schools with appointed principals. This result, according to the literature, could be related to perverse effects of selecting school administrators by vote, such as corporatism, clientelism and politicization of the school environment

Reconfiguração dinâmica de estratégias distribuídas em dispositivos foundation fieldbus para a otimização de processos na indústria do petróleo

The petrochemical industry has as objective obtain, from crude oil, some products with a higher commercial value and a bigger industrial utility for energy purposes. These industrial processes are complex, commonly operating with large production volume and in restricted operation conditions. The operation control in optimized and stable conditions is important to keep obtained products quality and the industrial plant safety. Currently, industrial network has been attained evidence when there is a need to make the process control in a distributed way. The Foundation Fieldbus protocol for industrial network, for its interoperability feature and its user interface organized in simple configuration blocks, has great notoriety among industrial automation network group. This present work puts together some benefits brought by industrial network technology to petrochemical industrial processes inherent complexity. For this, a dynamic reconfiguration system for intelligent strategies (artificial neural networks, for example) based on the protocol user application layer is proposed which might allow different applications use in a particular process, without operators intervention and with necessary guarantees for the proper plant functioning

Estimação e compensação de não linearidades inerentes aos atuadores dos processos industriais

The oscillations presents in control loops can cause damages in petrochemical industry. Canceling, or even preventing such oscillations, would save up to large amount of dollars. Studies have identified that one of the causes of these oscillations are the nonlinearities present on industrial process actuators. This study has the objective to develop a methodology for removal of the harmful effects of nonlinearities. Will be proposed an parameter estimation method to Hammerstein model, whose nonlinearity is represented by dead-zone or backlash. The estimated parameters will be used to construct inverse models of compensation. A simulated level system was used as a test platform. The valve that controls inflow has a nonlinearity. Results and describing function analysis show an improvement on system response

Desenvolvimento de sistemas embarcados para redes de sensores e atuadores sem fio aplicadas em unidades de elevação de petróleo do tipo Plunger-Lift

The Wireless Sensor Networks (WSN) methods applied to the lifting of oil present as an area with growing demand technical and scientific in view of the optimizations that can be carried forward with existing processes. This dissertation has as main objective to present the development of embedded systems dedicated to a wireless sensor network based on IEEE 802.15.4, which applies the ZigBee protocol, between sensors, actuators and the PLC (Programmable Logic Controller), aiming to solve the present problems in the deployment and maintenance of the physical communication of current elevation oil units based on the method Plunger-Lift. Embedded systems developed for this application will be responsible for acquiring information from sensors and control actuators of the devices present at the well, and also, using the Modbus protocol to make this network becomes transparent to the PLC responsible for controlling the production and delivery information for supervisory SISAL

Financiamento e gasto público em saúde: o caso do Rio Grande do Norte

Conselho Nacional de Desenvolvimento Científico e Tecnológico