Modelagem e simulação da solubilização da parafina em tubos circulares e em regime laminar

O óleo produzido nos novos campos de petróleo está cada vez mais parafínico e viscoso, com isso, à medida que o óleo é escoado, parafinas são depositadas sobre as paredes internas do tubo, e ao longo do tempo, tendem a reduzir drasticamente a área transversal ao escoamento. Visando estudar o processo de solubilização da parafina em dutos, esse trabalho objetiva desenvolver modelos matemáticos que represente o processo, com base nos fenômenos envolvidos no mesmo tais como transferência de massa, transferência de energia e equilíbrio sólido-líquido, implementando-os em um ambiente de desenvolvimento VBA (Visual Basic) for Excel ®. O presente trabalho foi realizado em quatro etapas: i) modelagem dos fenômenos de transferência de calor e massa, ii) modelagem da rotina dos coeficientes de atividade através do modelo UNIFAC e modelagem do sistema de equilíbrio sólido-líquido; iii) modelagem matemática do processo de solubilização e cálculo da espessura da parafina ao longo do tempo; iv) implementação dos modelos em um ambiente de desenvolvimento VBA for Excel® e criação de um simulador com uma interface gráfica, para simular o processo de solubilização da parafina depositada em dutos e sua otimização. O simulador conseguiu produzir soluções bastante adequadas, mantendo continuidade das equações diferenciáveis do balanço de energia e de massa, com uma interpretação física viável, sem a presença de dissipação de oscilações nos perfis de temperatura e massa. Além disso, esse simulador visa permitir a simulação nas diversas condições de escoamento, bem como compreender a importância das variáveis (vazão, temperatura de entrada, temperatura externa, cadeia carbônica do solvente). Através dos resultados foram possíveis verificar os perfis de temperatura, fração molar e o de solubilização

Estudo da organização funcional do sistema circadiano por meio de ferramentas computacionais e matemáticas

Circadian rhythms are variations in physiological processes that help living beings to adapt to environmental cycles. These rhythms are generated and are synchronized to the dark light cycle through the suprachiasmatic nucleus. The integrity of circadian rhythmicity has great implication on human health. Currently it is known that disturbances in circadian rhythms are related to some problems of today such as obesity, propensity for certain types of cancer and mental disorders for example. The circadian rhythmicity can be studied through experiments with animal models and in humans directly. In this work we use computational models to gather experimental results from the literature and explain the results of our laboratory. Another focus of this study was to analyze data rhythms of activity and rest obtained experimentally. Here we made a review on the use of variables used to analyze these data and finally propose an update on how to calculate these variables. Our models were able to reproduce the main experimental results in the literature and provided explanations for the results of experiments performed in our laboratory. The new variables used to analyze the rhythm of activity and rest in humans were more efficient to describe the fragmentation and synchronization of this rhythm. Therefore, the work contributed improving existing tools for the study of circadian rhythms in mammals

Sinalização cromática da condição reprodutiva de fêmeas de segui comum (Callithrix jacchus)

As social animals, primates use different sensory modalities (acoustic, chemical, tactile and visual) to convey information about social and sexual status to conspecifics. Among these modalities, visual signals are widely used, especially color signals, since primates are the mammalian group that displays the greatest variety of colors in their skin and fur. Studies with Old World primate species suggest that hormonal variations are related to variations in the colors of individual faces and genitals. Therefore, chromatic cues can be used by conspecifics to identify the reproductive condition of an individual. To date, studies with the same approach are unknown for New World species. However, behavioral and physiological studies suggest that different New World primate species seem to perceive reproductive conditions such as the timing of female conception and gestation. Thus, in this study, our aim was to: i) identify whether there are chromatic cues on the skin of female common marmosets, (Callithrix jacchus) that indicate their reproductive condition; ii) define whether this chromatic variation can be perceived by all visual phenotypes known in this species; iii) identify if these chromatic cues can be perceived under different light intensity levels (dim, intermediate and high). For this, we selected 13 female common marmosets in four distinct reproductive conditions: pregnant female preceding parturition, postpartum mothers, noncycling and cycling females. The coloration of the skin in genital and thigh areas in females was measured using a spectrophotometer. Using mathematical models of visual perception, we calculated the values of quantum catch for each photoreceptor type known in this species, the visual opponency channels and color contrast between those body spots. Our results indicate the occurance of chromatic variations in the genital area during the weeks that precede and follow parturition, forming a U-pattern of variation perceptible to males and females in natural conditions of low and high luminosity. Furthermore, we observed distinct color patterns in the genital skin of pregnant and cycling females that indicate their reproductive conditions. Finally, we present evidence of color contrast in noncycling females that is higher than that of pregnant ones. This study suggests that there is a chromatic xii variation in the genital skin of females that can be perceived by conspecifics and that may be related to hormonal changes typical of pregnancy and the ovarian cycle

Especificação do tipo intervalar parametrizado em CASL

The interval datatype applications in several areas is important to construct a interval type reusable, i.e., a interval constructor can be applied to any datatype and get intervals this datatype. Since the interval is, of certain form, a set of elements limited for two bounds, left and right, with a order notions, then it s reasonable that interval constructor enclose datatypes with partial order. On the order hand, what we want is work with interval of any datatype like this we work with this datatype then. it s important to guarantee the properties of the datatype when maps to interval of this datatype. Thus, the interval constructor get a theory to parametrized interval type, i.e., a interval with generics parameters (for example rational, real, complex). Sometimes, the interval application in some algebras doesn t guarantee the mainutenance of their properties, for example, when we use interval of real, that satisfies the field properties, it doesn t guarantee the distributivity propertie. A form to surpass this problem Santiago introduced the local equality theory that weakened the notion of strong equality, and thus, allowing some properties are local keeped, what can be discard before. The interval arithmetic generalization aim to apply the interval constructor on ordered algebras weakened for local equality with the purpose of the keep their properties. How the intervals are important in applications with continuous data, it s interesting specify that theory using a specification language that supply a system development using intervals of form disciplined, trustworth and safe. Currently, the algebraic specification language, based in math models, have been use to that intention often. We choose CASL (Common Algebraic Specification Language) among others languages because CASL has several characteristics excellent to parametrized interval type, such as, provide parcialiy and parametrization

Métodos estatísticos recursivos aplicados ao problema de estimação de vazão de gás em plantas de Plunger-lift

This work has as main objective to find mathematical models based on linear parametric estimation techniques applied to the problem of calculating the grow of gas in oil wells. In particular we focus on achieving grow models applied to the case of wells that produce by plunger-lift technique on oil rigs, in which case, there are high peaks in the grow values that hinder their direct measurement by instruments. For this, we have developed estimators based on recursive least squares and make an analysis of statistical measures such as autocorrelation, cross-correlation, variogram and the cumulative periodogram, which are calculated recursively as data are obtained in real time from the plant in operation; the values obtained for these measures tell us how accurate the used model is and how it can be changed to better fit the measured values. The models have been tested in a pilot plant which emulates the process gas production in oil wells

Modelagem matemática e experimental da perda de injetividade em poços canhoneados

Water injection in oil reservoirs is a recovery technique widely used for oil recovery. However, the injected water contains suspended particles that can be trapped, causing formation damage and injectivity decline. In such cases, it is necessary to stimulate the damaged formation looking forward to restore the injectivity of the injection wells. Injectivity decline causes a major negative impact to the economy of oil production, which is why, it is important to foresee the injectivity behavior for a good waterflooding management project. Mathematical models for injectivity losses allow studying the effect of the injected water quality, also the well and formation characteristics. Therefore, a mathematical model of injectivity losses for perforated injection wells was developed. The scientific novelty of this work relates to the modeling and prediction of injectivity decline in perforated injection wells, considering deep filtration and the formation of external cake in spheroidal perforations. The classic modeling for deep filtration was rewritten using spheroidal coordinates. The solution to the concentration of suspended particles was obtained analytically and the concentration of the retained particles, which cause formation damage, was solved numerically. The acquisition of the solution to impedance assumed a constant injection rate and the modified Darcy´s Law, defined as being the inverse of the normalized injectivity by the inverse of the initial injectivity. Finally, classic linear flow injectivity tests were performed within Berea sandstone samples, and within perforated samples. The parameters of the model, filtration and formation damage coefficients, obtained from the data, were used to verify the proposed modeling. The simulations showed a good fit to the experimental data, it was observed that the ratio between the particle size and pore has a large influence on the behavior of injectivity decline.

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

Análise comparativa entre simuladores de linha de fluxo e diferenças finitas para um reservatório de petróleo submetido a injeção de água

Water injection is the most widely used method for supplementary recovery in many oil fields due to various reasons, like the fact that water is an effective displacing agent of low viscosity oils, the water injection projects are relatively simple to establish and the water availability at a relatively low cost. For design of water injection projects is necessary to do reservoir studies in order to define the various parameters needed to increase the effectiveness of the method. For this kind of study can be used several mathematical models classified into two general categories: analytical or numerical. The present work aims to do a comparative analysis between the results presented by flow lines simulator and conventional finite differences simulator; both types of simulators are based on numerical methods designed to model light oil reservoirs subjected to water injection. Therefore, it was defined two reservoir models: the first one was a heterogeneous model whose petrophysical properties vary along the reservoir and the other one was created using average petrophysical properties obtained from the first model. Comparisons were done considering that the results of these two models were always in the same operational conditions. Then some rock and fluid parameters have been changed in both models and again the results were compared. From the factorial design, that was done to study the sensitivity analysis of reservoir parameters, a few cases were chosen to study the role of water injection rate and the vertical position of wells perforations in production forecast. It was observed that the results from the two simulators are quite similar in most of the cases; differences were found only in those cases where there was an increase in gas solubility ratio of the model. Thus, it was concluded that in flow simulation of reservoirs analogous of those now studied, mainly when the gas solubility ratio is low, the conventional finite differences simulator may be replaced by flow lines simulator the production forecast is compatible but the computational processing time is lower.