885 resultados para Modelagem de dados
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Retaining walls design involves factors such as plastification, loading and unloading, pre-stressing, excessive displacements and earth and water thrust. Furthermore, the interaction between the retained soil and the structure is rather complex and hard to predict. Despite the advances in numerical simulation techniques and monitoring of forces and displacements with field instrumentation, design projects are still based on classical methods, whose simplifying assumptions may overestimate structural elements of the retaining wall. This dissertation involves a three-dimensional numerical study on the behavior of a retaining wall using the finite element method (FEM). The retaining wall structure is a contiguous bored pile wall with tie-back anchors. The numerical results were compared to data obtained from field instrumentation. The influence of the position of one or two layers of anchors and the effects of the construction of a slab bounded at the top of the retaining wall was evaluated. Furthermore, this study aimed at investigating the phenomenon of arching in the soil behind the wall. Arching was evaluated by analyzing the effects of pile spacing on horizontal stresses and displacements. Parametric analysis with one layers of anchors showed that the smallest horizontal displacements of the structure were achieved for between 0.3 and 0.5 times the excavation depth. Parametric analyses with two anchor layers showed that the smallest horizontal displacements were achieve for anchors positioned in depths of 0.4H and 0.7H. The construction of a slab at the top of the retaining wall decreased the horizontal displacements by 0.14% times the excavation depth as compared to analyses without the slab. With regard to the arching , analyzes showed an optimal range of spacing between the faces of the piles between 0.4 and 0.6 times the diameter of the pile
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES
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Primary processing of natural gas platforms as Mexilhão Field (PMXL-1 ) in the Santos Basin, where monoethylene glycol (MEG) has been used to inhibit the formation of hydrates, present operational problems caused by salt scale in the recovery unit of MEG. Bibliographic search and data analysis of salt solubility in mixed solvents, namely water and MEG, indicate that experimental reports are available to a relatively restricted number of ionic species present in the produced water, such as NaCl and KCl. The aim of this study was to develop a method for calculating of salt solubilities in mixed solvent mixtures, in explantion, NaCl or KCl in aqueous mixtures of MEG. The method of calculating extend the Pitzer model, with the approach Lorimer, for aqueous systems containing a salt and another solvent (MEG). Python language in the Integrated Development Environment (IDE) Eclipse was used in the creation of the computational applications. The results indicate the feasibility of the proposed calculation method for a systematic series of salt (NaCl or KCl) solubility data in aqueous mixtures of MEG at various temperatures. Moreover, the application of the developed tool in Python has proven to be suitable for parameter estimation and simulation purposes
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Conselho Nacional de Desenvolvimento Científico e Tecnológico - CNPq
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Actually, Brazil is one of the larger fruit producer worldwide, with most of its production being consumed in nature way or either as juice or pulp. It is important to highlig ht in the fruit productive chain there are a lot lose due mainly to climate reasons, as well as storage, transportation, season, market, etc. It is known that in the pulp and fruit processing industy a yield of 50% (in mass) is usually obtained, with the other part discarded as waste. However, since most this waste has a high nutrient content it can be used to generate added - value products. In this case, drying plays an important role as an alternative process in order to improve these wastes generated by the fruit industry. However, despite the advantage of using this technique in order to improve such wastes, issues as a higher power demand as well as the thermal efficiency limitation should be addressed. Therefore, the control of the main variables in t his drying process is quite important in order to obtain operational conditions to produce a final product with the target specification as well as with a lower power cost. M athematical models can be applied to this process as a tool in order to optimize t he best conditions. The main aim of this work was to evaluate the drying behaviour of a guava industrial pulp waste using a batch system with a convective - tray dryer both experimentally and using mathematical modeling. In the experimental study , the dryin g carried out using a group of trays as well as the power consume were assayed as response to the effects of operational conditions (temperature, drying air flow rate and solid mass). Obtained results allowed observing the most significant variables in the process. On the other hand, the phenomenological mathematical model was validated and allowed to follow the moisture profile as well as the temperature in the solid and gas phases in every tray. Simulation results showed the most favorable procedure to o btain the minimum processing time as well as the lower power demand.
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In this work it were developed synthetic and theoretical studies for clerodane-type diterpenes obtained from Croton cajucara Benth which represents one of the most important medicinal plant of the Brazil amazon region. Specifically, the majoritary biocompound 19-nor-clerodane trans-dehydrocrotonin (t-DCTN) isolated from the bark of this Croton, was used as target molecule. Semi-synthetic derivatives were obtained from t-DCTN by using the followed synthetic procedures: 1) catalytic reduction with H2, 2) reduction using NaBH4 and 3) reduction using NaBH4/CeCl3. The semi-synthetic 19-nor-furan-clerodane alcohol-type derivatives were denominated such as t-CTN, tCTN-OL, t-CTN-OL, t-DCTN-OL, t-DCTN-OL, being all of them characterized by NMR. The furan-clerodane alcohol derivatives t-CTN-OL and tCTN-OL were obtained form the semi-synthetic t-CTN, which can be isolated from the bark of C. cajucara. A theoretical protocol (DFT/B3LYP) involving the prevision of geometric and magnetic properties such as bond length and angles, as well as chemical shifts and coupling constants, were developed for the target t-DCTN in which was correlated NMR theoretical data with structural data, with satisfactory correlation with NMR experimental data (coefficients ranging from 0.97 and 0.99) and X-ray diffraction data. This theoretical methodology was also validated for all semi-synthetic derivatives described in this work. In addition, topological data from the Quantum Theory of Atoms in Molecules (QTAIM) showed the presence of H-H and (C)O--H(C) intramolecular stabilized interactions types for t-DCTN e t-CTN, contributing to the understanding of the different reactivity of this clerodanes in the presence of NaBH4.
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No mercado de telecomunicações as transformações tecnológicas das últimas décadas aliaram-se a um cenário formado por empresas de alta tecnologia que caracterizam o setor de comunicações móveis pessoais em todo mundo. Neste contexto, as empresas deste setor preocupam-se cada vez mais com a competitividade, oferta de serviços, área de atendimento, demanda reprimida e a lealdade do cliente. Estudos de comportamento do consumidor pesquisam a satisfação e lealdade de clientes como fatores básicos para relações bem sucedidas e duradouras com as empresas. A complexidade das relações entre variáveis na avaliação da satisfação do cliente em comunicações móveis pode ser adequadamente pesquisada com a utilização de métodos estatísticos multivariados. Essa tese analisou as relações causais envolvendo os antecedentes e consequentes associados à satisfação do cliente, no segmento de comunicações móveis, bem como desenvolveu e validou um modelo comportamental do cliente no uso deste serviço, buscando explicar as relações entre os construtos envolvidos: satisfação, qualidade dos serviços, valor percebido, imagem da marca, lealdade e reclamação. Foi estabelecida uma ampla base teórica para avaliar a importância estratégica do modelo que relaciona a influência na satisfação do serviço com as percepções dos clientes e avaliada a precisão deste modelo, por meio de uma análise comparativa a utilização de três métodos de estimação dos seus parâmetros, MLE, GLS, e ULS, com o emprego de modelagem de equações estruturais. Foram feitas aplicações em análises de dados, sendo testada e avaliada empiricamente, a influência do gênero na satisfação do cliente deste setor, além de uma segmentação de mercado utilizando mapas auto-organizáveis e a correspondente validação deste processo, com modelagem de equações estruturais.Os resultados do estudo empírico produziram uma boa qualidade de ajustamento para o modelo teórico proposto, com evidências do estabelecimento de uma adequada capacidade explicativa e preditiva, destacando-se a relevância da relação causal entre a satisfação e lealdade, em consonância com diversos estudos realizados para os mercados de comunicações móveis.
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Intense precipitation events (IPE) have been causing great social and economic losses in the affected regions. In the Amazon, these events can have serious impacts, primarily for populations living on the margins of its countless rivers, because when water levels are elevated, floods and/or inundations are generally observed. Thus, the main objective of this research is to study IPE, through Extreme Value Theory (EVT), to estimate return periods of these events and identify regions of the Brazilian Amazon where IPE have the largest values. The study was performed using daily rainfall data of the hydrometeorological network managed by the National Water Agency (Agência Nacional de Água) and the Meteorological Data Bank for Education and Research (Banco de Dados Meteorológicos para Ensino e Pesquisa) of the National Institute of Meteorology (Instituto Nacional de Meteorologia), covering the period 1983-2012. First, homogeneous rainfall regions were determined through cluster analysis, using the hierarchical agglomerative Ward method. Then synthetic series to represent the homogeneous regions were created. Next EVT, was applied in these series, through Generalized Extreme Value (GEV) and the Generalized Pareto Distribution (GPD). The goodness of fit of these distributions were evaluated by the application of the Kolmogorov-Smirnov test, which compares the cumulated empirical distributions with the theoretical ones. Finally, the composition technique was used to characterize the prevailing atmospheric patterns for the occurrence of IPE. The results suggest that the Brazilian Amazon has six pluvial homogeneous regions. It is expected more severe IPE to occur in the south and in the Amazon coast. More intense rainfall events are expected during the rainy or transitions seasons of each sub-region, with total daily precipitation of 146.1, 143.1 and 109.4 mm (GEV) and 201.6, 209.5 and 152.4 mm (GPD), at least once year, in the south, in the coast and in the northwest of the Brazilian Amazon, respectively. For the south Amazonia, the composition analysis revealed that IPE are associated with the configuration and formation of the South Atlantic Convergence Zone. Along the coast, intense precipitation events are associated with mesoscale systems, such Squall Lines. In Northwest Amazonia IPE are apparently associated with the Intertropical Convergence Zone and/or local convection.
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This work aims at modeling power consumption at the nodes of a Wireless Sensor Network (WSN). For doing so, a finite state machine was implemented by means of SystemC-AMS and Stateflow modeling and simulation tools. In order to achieve this goal, communication data in a WSN were collected. Based on the collected data, a simulation environment for power consumption characterization, which aimed at describing the network operation, was developed. Other than performing power consumption simulation, this environment also takes into account a discharging model as to analyze the battery charge level at any given moment. Such analysis result in a graph illustrating the battery voltage variations as well as its state of charge (SOC). Finally, a case study of the WSN power consumption aims to analyze the acquisition mode and network data communication. With this analysis, it is possible make adjustments in node-sensors to reduce the total power consumption of the network.
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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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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.