791 resultados para Modelagem conceitual
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Dissertação (mestrado)—Universidade de Brasília, Faculdade UnB Gama, Faculdade de Tecnologia, Programa de Pós-graduação em Integridade de Materiais da Engenharia, 2016.
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Dissertação (mestrado)—Universidade de Brasília, Instituto de Geociências, 2015.
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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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Dissertação (mestrado)—Universidade de Brasília, Faculdade de Tecnologia, Departamento de Engenharia Mecânica, 2016.
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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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Dissertação (mestrado)—Universidade de Brasília, Faculdade de Tecnologia, Departamento de Engenharia Mecânica, 2016.
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Dissertação (mestrado)—Universidade de Brasília, Faculdade de Direito, Programa de Pós-Graduação em Direito, 2016.
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Discrepancies between classical model predictions and experimental data for deep bed filtration have been reported by various authors. In order to understand these discrepancies, an analytic continuum model for deep bed filtration is proposed. In this model, a filter coefficient is attributed to each distinct retention mechanism (straining, diffusion, gravity interception, etc.). It was shown that these coefficients generally cannot be merged into an effective filter coefficient, as considered in the classical model. Furthermore, the derived analytic solutions for the proposed model were applied for fitting experimental data, and a very good agreement between experimental data and proposed model predictions were obtained. Comparison of the obtained results with empirical correlations allowed identifying the dominant retention mechanisms. In addition, it was shown that the larger the ratio of particle to pore sizes, the more intensive the straining mechanism and the larger the discrepancies between experimental data and classical model predictions. The classical model and proposed model were compared via statistical analysis. The obtained p values allow concluding that the proposed model should be preferred especially when straining plays an important role. In addition, deep bed filtration with finite retention capacity was studied. This work also involves the study of filtration of particles through porous media with a finite capacity of filtration. It was observed, in this case, that is necessary to consider changes in the boundary conditions through time evolution. It was obtained a solution for such a model using different functions of filtration coefficients. Besides that, it was shown how to build a solution for any filtration coefficient. It was seen that, even considering the same filtration coefficient, the classic model and the one here propposed, show different predictions for the concentration of particles retained in the porous media and for the suspended particles at the exit of the media
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Tese (doutorado)—Universidade de Brasília, Instituto de Geociências, Pós-Graduação em Geociências Aplicadas, 2016.
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Apresentamos um modelo que estima o fator de bioconcentracão (BCF) de pesticidas em batatas supondo que o pesticida na solução do solo é absorvido pela batata por difusão passiva,seguindo a segunda lei de Fick.Os pesticidas do modelo são compostos orgânicos não-iônicos, tradicionalmente utilizados no cultivo de batatas que degradam no solo de acordo com uma equação cinética de primeira ordem. Este trabalho apresenta uma expressão que relaciona o BCF com a taxa de eliminação do pesticida pela batata, com a taxa de acumulação do pesticida na batata, com a taxa de crescimento da batata, e com a taxa de degradação do pesticida no solo. O BCF foi estimado supondo-se estado de equilíbrio estacionário do quociente entre a concentração do pesticida na batata e a concentração do pesticida na solução do solo. O modelo foi construído baseado no trabalho de Trapp et al. (2007), [Diffusion of PAH in Potato and Carrrot Slices and Applications for a Potato Model] no qual é apresentada uma expressão para calcular a difusividade de substâncias orgânicas persistentes em batatas. A modelagem consistiu em adicionar ao modelo de Trapp et al. (2007) a hipótese de que o pesticida degrada no solo. O valor do BCF sugere um conjunto de pesticidas que devem ser prioritariamente monitorados em cultivos de batatas. Foi estimado o BCF dos pesticidas methamidophos, cymoxanil, carbofuran, aldicarb, metalaxyl, fenamiphos, carbaryl, triazophos, tebuconazole, propiconazole, chlorothalonil e cypermethrin.
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Propriedades físico-químicas de herbicidas e propriedades fisiológicas de plantas foram utilizadas para apresentar um modelo que simula a bioconcentracão e calcula o fator de bioconcentração de herbicidas em plantas. A modelagem supõe que o herbicida na solução do solo é absorvido pela planta no processo de transpiração da solução do solo. Utilizamos o modelo para estimar o fator de bioconcentração dos herbicidas 2,4-D, acetochlor, ametryn, atrazine, clomazone, diuron, hexazinone, imazapyr, metribuzin, pendimethalin, picloram, simazine, sulfentrazone, tebuthiuron e trifluralin em cana-deaçúcar. A modelagem sugere que existe uma correlação negativa entre o fator de bioconcentração e o coeficiente de sorção de herbicidas no carbono orgânico do solo.
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2015
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Este trabalho teve como objetivo estimar a quantidade de biomassa seca em plantios de Eucalyptus no estado de Minas Gerais, a partir de resultados de 244 parcelas de inventário florestal, considerando variações de qualidade do sítio, área basal e idade entre 2 e 8 anos. Foi estabelecida a classificação de sítio, com ajuste de equação utilizando os dados de idade e altura dominante. A biomassa total por hectare foi calculada multiplicando-se o volume por hectare pela densidade da madeira de Eucalyptus grandis e por um fator de expansão de biomassa. Avaliando-se a correlação entre biomassa total por hectare e variáveis ambientais e dendrométricas, verificou-se que a área basal e o índice de sítio foram as duas variáveis do povoamento de correlação mais alta, 0,93 e 0,64, respectivamente. Doze modelos foram ajustados para representar a quantidade de biomassa total por hectare tendo como variáveis independentes a área basal, o índice de sítio e a idade, bem como combinações entre estas. O modelo que apresentou melhor ajuste e precisão foi: Bs = exp[−6,7518 + 0,9567 × ln(G) + 0,0388 × ln?(G) + 4,0732 × ln(IS) − 0,4799 × ln?(IS)] × 1,0020, com R²ajustado de 0,955 e Syx% de 5,29%, e indicou valores de estoque de biomassa entre 39,7 e 174,9 Mg.ha-1, para área basal entre 8,9 e 27,9 m2.ha-1. A aplicação do modelo ajustado, com as variáveis índice de sitio e área basal por hectare, pode estimar de maneira prática e precisa a biomassa total por hectare, por utilizar variáveis de simples obtenção e por ter sido gerada a partir de um conjunto de dados com pouca variabilidade atribuída ao material genético.