106 resultados para modelagem probabilística


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The fluorescent proteins are an essential tool in many fields of biology, since they allow us to watch the development of structures and dynamic processes of cells in living tissue, with the aid of fluorescence microscopy. Optogenectics is another technique that is currently widely used in Neuroscience. In general, this technique allows to activate/deactivate neurons with the radiation of certain wavelengths on the cells that have ion channels sensitive to light, at the same time that can be used with fluorescent proteins. This dissertation has two main objectives. Initially, we study the interaction of light radiation and mice brain tissue to be applied in optogenetic experiments. In this step, we model absorption and scattering effects using mice brain tissue characteristics and Kubelka-Munk theory, for specific wavelengths, as a function of light penetration depth (distance) within the tissue. Furthermore, we model temperature variations using the finite element method to solve Pennes’ bioheat equation, with the aid of COMSOL Multiphysics Modeling Software 4.4, where we simulate protocols of light stimulation tipically used in optogenetics. Subsequently, we develop some computational algorithms to reduce the exposure of neuron cells to the light radiation necessary for the visualization of their emitted fluorescence. At this stage, we describe the image processing techniques developed to be used in fluorescence microscopy to reduce the exposure of the brain samples to continuous light, which is responsible for fluorochrome excitation. The developed techniques are able to track, in real time, a region of interest (ROI) and replace the fluorescence emitted by the cells by a virtual mask, as a result of the overlay of the tracked ROI and the fluorescence information previously stored, preserving cell location, independently of the time exposure to fluorescent light. In summary, this dissertation intends to investigate and describe the effects of light radiation in brain tissue, within the context of Optogenetics, in addition to providing a computational tool to be used in fluorescence microscopy experiments to reduce image bleaching and photodamage due to the intense exposure of fluorescent cells to light radiation.

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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.

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This work consists basically in the elaboration of an Artificial Neural Network (ANN) in order to model the composites materials’ behavior when submitted to fatigue loadings. The proposal is to develop and present a mixed model, which associate an analytical equation (Adam Equation) to the structure of the ANN. Given that the composites often shows a similar behavior when subject to float loadings, this equation aims to establish a pre-defined comparison pattern for a generic material, so that the ANN fit the behavior of another composite material to that pattern. In this way, the ANN did not need to fully learn the behavior of a determined material, because the Adam Equation would do the big part of the job. This model was used in two different network architectures, modular and perceptron, with the aim of analyze it efficiency in distinct structures. Beyond the different architectures, it was analyzed the answers generated from two sets of different data – with three and two SN curves. This model was also compared to the specialized literature results, which use a conventional structure of ANN. The results consist in analyze and compare some characteristics like generalization capacity, robustness and the Goodman Diagrams, developed by the networks.

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The fracturing in carbonate rocks has been attracting increasingly attention due to new oil discoveries in carbonate reservoirs. This study investigates how the fractures (faults and joints) behave when subjected to different stress fields and how their behavior may be associated with the generation of karst and consequently to increased secondary porosity in these rocks. In this study I used satellite imagery and unmanned aerial vehicle UAV images and field data to identify and map faults and joints in a carbonate outcrop, which I consider a good analogue of carbonate reservoir. The outcrop comprises rocks of the Jandaíra Formation, Potiguar Basin. Field data were modeled using the TECTOS software, which uses finite element analysis for 2D fracture modeling. I identified three sets of fractures were identified: NS, EW and NW-SE. They correspond to faults that reactivate joint sets. The Ratio of Failure by Stress (RFS) represents stress concentration and how close the rock is to failure and reach the Mohr-Coulomb envelopment. The results indicate that the tectonic stresses are concentrated in preferred structural zones, which are ideal places for carbonate dissolution. Dissolution was observed along sedimentary bedding and fractures throughout the outcrop. However, I observed that the highest values of RFS occur in fracture intersections and terminations. These are site of karst concentration. I finally suggest that there is a relationship between stress concentration and location of karst dissolution in carbonate rocks.

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The fracturing in carbonate rocks has been attracting increasingly attention due to new oil discoveries in carbonate reservoirs. This study investigates how the fractures (faults and joints) behave when subjected to different stress fields and how their behavior may be associated with the generation of karst and consequently to increased secondary porosity in these rocks. In this study I used satellite imagery and unmanned aerial vehicle UAV images and field data to identify and map faults and joints in a carbonate outcrop, which I consider a good analogue of carbonate reservoir. The outcrop comprises rocks of the Jandaíra Formation, Potiguar Basin. Field data were modeled using the TECTOS software, which uses finite element analysis for 2D fracture modeling. I identified three sets of fractures were identified: NS, EW and NW-SE. They correspond to faults that reactivate joint sets. The Ratio of Failure by Stress (RFS) represents stress concentration and how close the rock is to failure and reach the Mohr-Coulomb envelopment. The results indicate that the tectonic stresses are concentrated in preferred structural zones, which are ideal places for carbonate dissolution. Dissolution was observed along sedimentary bedding and fractures throughout the outcrop. However, I observed that the highest values of RFS occur in fracture intersections and terminations. These are site of karst concentration. I finally suggest that there is a relationship between stress concentration and location of karst dissolution in carbonate rocks.

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In this master thesis, we propose a multiscale mathematical and computational model for electrokinetic phenomena in porous media electrically charged. We consider a porous medium rigid and incompressible saturated by an electrolyte solution containing four monovalent ionic solutes completely diluted in the aqueous solvent. Initially we developed the modeling electrical double layer how objective to compute the electrical potential, surface density of electrical charges and considering two chemical reactions, we propose a 2-pK model for calculating the chemical adsorption occurring in the domain of electrical double layer. Having the nanoscopic model, we deduce a model in the microscale, where the electrochemical adsorption of ions, protonation/ deprotonation reactions and zeta potential obtained in the nanoscale, are incorporated through the conditions of interface uid/solid of the Stokes problem and transportation of ions, modeled by equations of Nernst-Planck. Using the homogenization technique of periodic structures, we develop a model in macroscopic scale with respective cells problems for the e ective macroscopic parameters of equations. Finally, we propose several numerical simulations of the multiscale model for uid ow and transport of reactive ionic solute in a saturated aqueous solution of kaolinite. Using nanoscopic model we propose some numerical simulations of electrochemical adsorption phenomena in the electrical double layer. Making use of the nite element method discretize the macroscopic model and propose some numerical simulations in basic and acid system aiming to quantify the transport of ionic solutes in porous media electrically charged.

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In this master thesis, we propose a multiscale mathematical and computational model for electrokinetic phenomena in porous media electrically charged. We consider a porous medium rigid and incompressible saturated by an electrolyte solution containing four monovalent ionic solutes completely diluted in the aqueous solvent. Initially we developed the modeling electrical double layer how objective to compute the electrical potential, surface density of electrical charges and considering two chemical reactions, we propose a 2-pK model for calculating the chemical adsorption occurring in the domain of electrical double layer. Having the nanoscopic model, we deduce a model in the microscale, where the electrochemical adsorption of ions, protonation/ deprotonation reactions and zeta potential obtained in the nanoscale, are incorporated through the conditions of interface uid/solid of the Stokes problem and transportation of ions, modeled by equations of Nernst-Planck. Using the homogenization technique of periodic structures, we develop a model in macroscopic scale with respective cells problems for the e ective macroscopic parameters of equations. Finally, we propose several numerical simulations of the multiscale model for uid ow and transport of reactive ionic solute in a saturated aqueous solution of kaolinite. Using nanoscopic model we propose some numerical simulations of electrochemical adsorption phenomena in the electrical double layer. Making use of the nite element method discretize the macroscopic model and propose some numerical simulations in basic and acid system aiming to quantify the transport of ionic solutes in porous media electrically charged.

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Advanced Oxidation Processes (AOP) are techniques involving the formation of hydroxyl radical (HO•) with high organic matter oxidation rate. These processes application in industry have been increasing due to their capacity of degrading recalcitrant substances that cannot be completely removed by traditional processes of effluent treatment. In the present work, phenol degrading by photo-Fenton process based on addition of H2O2, Fe2+ and luminous radiation was studied. An experimental design was developed to analyze the effect of phenol, H2O2 and Fe2+ concentration on the fraction of total organic carbon (TOC) degraded. The experiments were performed in a batch photochemical parabolic reactor with 1.5 L of capacity. Samples of the reactional medium were collected at different reaction times and analyzed in a TOC measurement instrument from Shimadzu (TOC-VWP). The results showed a negative effect of phenol concentration and a positive effect of the two other variables in the TOC degraded fraction. A statistical analysis of the experimental design showed that the hydrogen peroxide concentration was the most influent variable in the TOC degraded fraction at 45 minutes and generated a model with R² = 0.82, which predicted the experimental data with low precision. The Visual Basic for Application (VBA) tool was used to generate a neural networks model and a photochemical database. The aforementioned model presented R² = 0.96 and precisely predicted the response data used for testing. The results found indicate the possible application of the developed tool for industry, mainly for its simplicity, low cost and easy access to the program.

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Advanced Oxidation Processes (AOP) are techniques involving the formation of hydroxyl radical (HO•) with high organic matter oxidation rate. These processes application in industry have been increasing due to their capacity of degrading recalcitrant substances that cannot be completely removed by traditional processes of effluent treatment. In the present work, phenol degrading by photo-Fenton process based on addition of H2O2, Fe2+ and luminous radiation was studied. An experimental design was developed to analyze the effect of phenol, H2O2 and Fe2+ concentration on the fraction of total organic carbon (TOC) degraded. The experiments were performed in a batch photochemical parabolic reactor with 1.5 L of capacity. Samples of the reactional medium were collected at different reaction times and analyzed in a TOC measurement instrument from Shimadzu (TOC-VWP). The results showed a negative effect of phenol concentration and a positive effect of the two other variables in the TOC degraded fraction. A statistical analysis of the experimental design showed that the hydrogen peroxide concentration was the most influent variable in the TOC degraded fraction at 45 minutes and generated a model with R² = 0.82, which predicted the experimental data with low precision. The Visual Basic for Application (VBA) tool was used to generate a neural networks model and a photochemical database. The aforementioned model presented R² = 0.96 and precisely predicted the response data used for testing. The results found indicate the possible application of the developed tool for industry, mainly for its simplicity, low cost and easy access to the program.

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LINS, Filipe C. A. et al. Modelagem dinâmica e simulação computacional de poços de petróleo verticais e direcionais com elevação por bombeio mecânico. In: CONGRESSO BRASILEIRO DE PESQUISA E DESENVOLVIMENTO EM PETRÓLEO E GÁS, 5. 2009, Fortaleza, CE. Anais... Fortaleza: CBPDPetro, 2009.

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Deep bed filtration occurs in several industrial and environmental processes like water filtration and soil contamination. In petroleum industry, deep bed filtration occurs near to injection wells during water injection, causing injectivity reduction. It also takes place during well drilling, sand production control, produced water disposal in aquifers, etc. The particle capture in porous media can be caused by different physical mechanisms (size exclusion, electrical forces, bridging, gravity, etc). A statistical model for filtration in porous media is proposed and analytical solutions for suspended and retained particles are derived. The model, which incorporates particle retention probability, is compared with the classical deep bed filtration model allowing a physical interpretation of the filtration coefficients. Comparison of the obtained analytical solutions for the proposed model with the classical model solutions allows concluding that the larger the particle capture probability, the larger the discrepancy between the proposed and the classical models

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Waterflooding is a technique largely applied in the oil industry. The injected water displaces oil to the producer wells and avoid reservoir pressure decline. However, suspended particles in the injected water may cause plugging of pore throats causing formation damage (permeability reduction) and injectivity decline during waterflooding. When injectivity decline occurs it is necessary to increase the injection pressure in order to maintain water flow injection. Therefore, a reliable prediction of injectivity decline is essential in waterflooding projects. In this dissertation, a simulator based on the traditional porous medium filtration model (including deep bed filtration and external filter cake formation) was developed and applied to predict injectivity decline in perforated wells (this prediction was made from history data). Experimental modeling and injectivity decline in open-hole wells is also discussed. The injectivity of modeling showed good agreement with field data, which can be used to support plan stimulation injection wells

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This work aims presenting the development of a model and computer simulation of a sucker rod pumping system. This system take into account the well geometry, the flow through the tubing, the dynamic behavior of the rod string and the use of a induction motor model. The rod string were modeled using concentrated parameters, allowing the use of ordinary differential equations systems to simulate it s behavior

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Injectivity decline, which can be caused by particle retention, generally occurs during water injection or reinjection in oil fields. Several mechanisms, including straining, are responsible for particle retention and pore blocking causing formation damage and injectivity decline. Predicting formation damage and injectivity decline is essential in waterflooding projects. The Classic Model (CM), which incorporates filtration coefficients and formation damage functions, has been widely used to predict injectivity decline. However, various authors have reported significant discrepancies between Classical Model and experimental results, motivating the development of deep bed filtration models considering multiple particle retention mechanisms (Santos & Barros, 2010; SBM). In this dissertation, inverse problem solution was studied and a software for experimental data treatment was developed. Finally, experimental data were fitted using both the CM and SBM. The results showed that, depending on the formation damage function, the predictions for injectivity decline using CM and SBM models can be significantly different

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A legislação ambiental e os principais agentes que se relacionam com a empresa se constituem em fatores exógenos que não podem ser negligenciados ao formular-se e avaliar-se a política ambiental corporativa. As influências exógenas e seus efeitos sobre a gestão ambiental e o gerenciamento de projetos de exploração e produção (E&P) e, por essa via, sobre o desempenho ambiental, foram objetos de estudo desta tese. Embora o desempenho ambiental seja um assunto relevante, a pesquisa sobre esse tema ainda é escassa. Tal carência desponta ainda mais acentuada quando se aborda o desempenho ambiental de projetos na indústria de petróleo e gás. O principal objetivo deste estudo foi avaliar a relação entre a legislação ambiental vigente, as ações de órgãos reguladores, fornecedores, empresas terceirizadas e comunidades locais e o desempenho ambiental dos projetos de E&P na indústria de petróleo e gás e, também, analisar os efeitos do sistema de gestão ambiental e o gerenciamento dos projetos sobre tal desempenho. Na fase abdutiva, foi conduzido um estudo de caso com abordagem qualitativa em uma grande empresa brasileira do setor de petróleo e gás, na fase dedutiva, foi realizada uma pesquisa survey explanatória de corte transversal com abordagem quantitativa, incluindo 113 projetos de E&P de cinco unidades executoras da empresa. Foi formulado um modelo conceitual, com cinco construtos e sete hipóteses de pesquisa, representativo dos efeitos de fatores externos sobre o desempenho ambiental dos projetos de E&P. Os dados foram tratados aplicando a Análise Fatorial Exploratória e a Modelagem de Equações Estruturais com aplicação dos softwares IBM® SPSS® Statistics 20.0 e IBM® SPSS® Amos 18.0. O modelo de equações estruturais foi reespecificado e estimado utilizando o método de Máxima Verossimilhança e o procedimento bootstrap com 2000 reamostragens, até alcançar adequados valores dos índices de ajustamento. O modelo mostrou boa aderência às evidências empíricas, representando uma teoria explicativa dos fatores que influenciam o desempenho ambiental dos projetos de E&P na empresa estudada. As estatísticas descritivas apontaram adequado desempenho dos projetos de E&P com relação aos efluentes descartados, volume de água reutilizada, redução de resíduos e práticas de reciclagem. Identificou-se que projetos de maior porte alcançam melhor desempenho ambiental em relação aos de menor tamanho. Não foram achadas diferenças significativas entre os desempenhos de projetos executados por unidades operacionais distintas. Os resultados da modelagem indicaram que nem a legislação ambiental, nem os agentes externos exercem influência significativa sobre a sistemática da gestão dos projetos de E&P. Os agentes externos atuam sobre a gestão ambiental da empresa exercitando capacidades colaborativas, obstrutivas e propositivas. A legislação ambiental é percebida como entrave ao desenvolvimento dos projetos ao longo de seu ciclo de vida, principalmente, pelas deficiências dos órgãos ambientais. Identificou-se que o sistema de gestão ambiental influencia diretamente o Programa de Desenvolvimento e Execução de Projetos de E&P, que, por sua vez, provoca efeitos diretos e indiretos sobre o desempenho ambiental. Finalmente, comprovou-se que o Sistema de Gestão Ambiental da empresa é determinante para o desempenho ambiental dos projetos de E&P, tanto pelos seus efeitos diretos, como pelos indiretos, estes últimos mediados pela sistemática de gestão dos projetos de E&P