58 resultados para Fluxo de calor sensível


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In this work, we present our understanding about the article of Aksoy [1], which uses Markov chains to model the flow of intermittent rivers. Then, we executed an application of his model in order to generate data for intermittent streamflows, based on a data set of Brazilian streams. After that, we build a hidden Markov model as a proposed new approach to the problem of simulation of such flows. We used the Gamma distribution to simulate the increases and decreases in river flows, along with a two-state Markov chain. The motivation for us to use a hidden Markov model comes from the possibility of obtaining the same information that the Aksoy’s model provides, but using a single tool capable of treating the problem as a whole, and not through multiple independent processes

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The solution of partial differential equation of seepage problems is difficult to find analytically, especially for situations that involve great complexity. To overcome this problem, software based on finite differences and finite elements are usually used. This work presents the use of a finite element software, the GEO5, to solve the seepage problem at a dam of very complex section, the dam Eng. Armando Ribeiro Gonçalves, which at the end of its construction suffered rupture of the upstream slope at the central dam and then went through a process of reconstruction and auscultation. The analyses were performed for the operating condition of the reservoir, with an established flow. A numerical model was developed based on the level readings of the reservoir water and their piezometric readings as a proposal for the evaluation and future behavior prediction of the dam on established flow conditions. The use of constitutive models with the aid of computer systems is reflected in a way to predict future risk situations so they can be prevented

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In this work we have investigated some aspects of the two-dimensional flow of a viscous Newtonian fluid through a disordered porous medium modeled by a random fractal system similar to the Sierpinski carpet. This fractal is formed by obstacles of various sizes, whose distribution function follows a power law. They are randomly disposed in a rectangular channel. The velocity field and other details of fluid dynamics are obtained by solving numerically of the Navier-Stokes and continuity equations at the pore level, where occurs actually the flow of fluids in porous media. The results of numerical simulations allowed us to analyze the distribution of shear stresses developed in the solid-fluid interfaces, and find algebraic relations between the viscous forces or of friction with the geometric parameters of the model, including its fractal dimension. Based on the numerical results, we proposed scaling relations involving the relevant parameters of the phenomenon, allowing quantifying the fractions of these forces with respect to size classes of obstacles. Finally, it was also possible to make inferences about the fluctuations in the form of the distribution of viscous stresses developed on the surface of obstacles.

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Registration of point clouds captured by depth sensors is an important task in 3D reconstruction applications based on computer vision. In many applications with strict performance requirements, the registration should be executed not only with precision, but also in the same frequency as data is acquired by the sensor. This thesis proposes theuse of the pyramidal sparse optical flow algorithm to incrementally register point clouds captured by RGB-D sensors (e.g. Microsoft Kinect) in real time. The accumulated errorinherent to the process is posteriorly minimized by utilizing a marker and pose graph optimization. Experimental results gathered by processing several RGB-D datasets validatethe system proposed by this thesis in visual odometry and simultaneous localization and mapping (SLAM) applications.

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The process mapping is an important tool in the management of organizations, allowing better levels of productivity, quality and reciprocity concerning the implementation and decision-making. It benefits in a clear way the process organization and assures the manager a macro vision of the system. In this sense, the objective of this study is to describe the mapping process as it occurs in the Januario Cicco Maternity School–MEJC. The bibliographic and descriptive research included interviews, observations and researches in many databases. The study analyzed the limiting points of the detected flow trying to find a better comprehension of the flow of patients in the maternity in order to offer the gestors the information necessary to improve the quality of the assistance as well as a general view of the flow of patients and any change detected there. As a result, we believe that the process mapping may become a relevant factor to the organizational management of MEJC, in view that it is an element that can contribute to ease up the management of information studied, considering that the perfect change of information inside a complex system will produce improvements in all spheres of this institution.

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The expansion of cultivated areas with genetically modified crops (GM) is a worldwide phenomenon, stimulating regulatory authorities to implement strict procedures to monitor and verify the presence of GM varieties in agricultural crops. With the constant growing of plant cultivating areas all over the world, consumption of aflatoxin-contaminated food also increased. Aflatoxins correspond to a class of highly toxic contaminants found in agricultural products that can have harmful effects on human and animal health. Therefore, the safety and quality evaluation of agricultural products are important issues for consumers. Lateral flow tests (strip tests) is a promising method for the detection both proteins expressed in GM crops and aflatoxins-contaminated food samples. The advantages of this technique include its simplicity, rapidity and cost-effective when compared to the conventional methods. In this study, two novel and sensitive strip tests assay were developed for the identification of: (i) Cry1Ac and Cry8Ka5 proteins expressed in GM cotton crops and; (ii) aflatoxins from agricultural products. The first strip test was developed using a sandwhich format, while the second one was developed using a competitive format. Gold colloidal nanoparticles were used as detector reagent when coated with monoclonal antibodies. An anti-species specific antibody was sprayed at the nitrocellulose membrane to be used as a control line. To validate the first strip test, GM (Bollgard I® e Planta 50- EMBRAPA) and non-GM cotton leaf (Cooker 312) were used. The results showed that the strip containing antibodies for the identification of Cry1Ac and Cry8Ka5 proteins was capable of correctly distinguishing between GM samples (positive result) and non-GM samples (negative result), in a high sensitivity manner. To validate the second strip test, artificially contaminated soybean with Aspergillus flavus (aflatoxin-producing fungus) was employed. Food samples, such as milk and soybean, were also evaluated for the presence of aflatoxins. The strip test was capable to distinguish between samples with and without aflatoxins samples, at a sensitivity concentration of 0,5 μg/Kg. Therefore, these results suggest that the strip tests developed in this study can be a potential tool as a rapid and cost-effective method for detection of insect resistant GM crops expressing Cry1Ac and Cry8Ka5 and aflatoxins from food samples.

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The expansion of cultivated areas with genetically modified crops (GM) is a worldwide phenomenon, stimulating regulatory authorities to implement strict procedures to monitor and verify the presence of GM varieties in agricultural crops. With the constant growing of plant cultivating areas all over the world, consumption of aflatoxin-contaminated food also increased. Aflatoxins correspond to a class of highly toxic contaminants found in agricultural products that can have harmful effects on human and animal health. Therefore, the safety and quality evaluation of agricultural products are important issues for consumers. Lateral flow tests (strip tests) is a promising method for the detection both proteins expressed in GM crops and aflatoxins-contaminated food samples. The advantages of this technique include its simplicity, rapidity and cost-effective when compared to the conventional methods. In this study, two novel and sensitive strip tests assay were developed for the identification of: (i) Cry1Ac and Cry8Ka5 proteins expressed in GM cotton crops and; (ii) aflatoxins from agricultural products. The first strip test was developed using a sandwhich format, while the second one was developed using a competitive format. Gold colloidal nanoparticles were used as detector reagent when coated with monoclonal antibodies. An anti-species specific antibody was sprayed at the nitrocellulose membrane to be used as a control line. To validate the first strip test, GM (Bollgard I® e Planta 50- EMBRAPA) and non-GM cotton leaf (Cooker 312) were used. The results showed that the strip containing antibodies for the identification of Cry1Ac and Cry8Ka5 proteins was capable of correctly distinguishing between GM samples (positive result) and non-GM samples (negative result), in a high sensitivity manner. To validate the second strip test, artificially contaminated soybean with Aspergillus flavus (aflatoxin-producing fungus) was employed. Food samples, such as milk and soybean, were also evaluated for the presence of aflatoxins. The strip test was capable to distinguish between samples with and without aflatoxins samples, at a sensitivity concentration of 0,5 μg/Kg. Therefore, these results suggest that the strip tests developed in this study can be a potential tool as a rapid and cost-effective method for detection of insect resistant GM crops expressing Cry1Ac and Cry8Ka5 and aflatoxins from food samples.

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Until the early 90s, the simulation of fluid flow in oil reservoir basically used the numerical technique of finite differences. Since then, there was a big development in simulation technology based on streamlines, so that nowadays it is being used in several cases and it can represent the physical mechanisms that influence the fluid flow, such as compressibility, capillarity and gravitational segregation. Streamline-based flow simulation is a tool that can help enough in waterflood project management, because it provides important information not available through traditional simulation of finite differences and shows, in a direct way, the influence between injector well and producer well. This work presents the application of a methodology published in literature for optimizing water injection projects in modeling of a Brazilian Potiguar Basin reservoir that has a large number of wells. This methodology considers changes of injection well rates over time, based on information available through streamline simulation. This methodology reduces injection rates in wells of lower efficiency and increases injection rates in more efficient wells. In the proposed model, the methodology was effective. The optimized alternatives presented higher oil recovery associated with a lower water injection volume. This shows better efficiency and, consequently, reduction in costs. Considering the wide use of the water injection in oil fields, the positive outcome of the modeling is important, because it shows a case study of increasing of oil recovery achieved simply through better distribution of water injection rates

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The oil companies in the area in general are looking for new technologies that can increase the recovery factor of oil contained in reservoirs. These investments are mainly aimed at reducing the costs of projects which are high. Steam injection is one of these special methods of recovery in which steam is injected into the reservoir in order to reduce the viscosity of the oil and make it more mobile. The process assisted gravity drainage steam (SAGD) using steam injection in its mechanism, as well as two parallel horizontal wells. In this process steam is injected through the horizontal injection well, then a vapor chamber is formed by heating the oil in the reservoir and, by the action of gravitational forces, this oil is drained down to where the production well. This study aims to analyze the influence of pressure drop and heat along the injection well in the SAGD process. Numerical simulations were performed using the thermal simulator STARS of CMG (Computer Modeling Group). The parameters studied were the thermal conductivity of the formation, the flow of steam injection, the inner diameter of the column, the steam quality and temperature. A factorial design was used to verify the influence of the parameters studied in the recovery factor. We also analyzed different injection flow rates for the model with pressure drop and no pressure drop, as well as different maximum flow rates of oil production. Finally, we performed an economic analysis of the two models in order to check the profitability of the projects studied. The results showed that the pressure drop in injection well have a significant influence on the SAGD process.

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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.

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Nowadays, most of the hydrocarbon reserves in the world are in the form of heavy oil, ultra - heavy or bitumen. For the extraction and production of this resource is required to implement new technologies. One of the promising processes for the recovery of this oil is the Expanding Solvent Steam Assisted Gravity Drainage (ES-SAGD) which uses two parallel horizontal wells, where the injection well is situated vertically above the production well. The completion of the process occurs upon injection of a hydrocarbon additive at low concentration in conjunction with steam. The steam adds heat to reduce the viscosity of the oil and solvent aids in reducing the interfacial tension between oil/ solvent. The main force acting in this process is the gravitational and the heat transfer takes place by conduction, convection and latent heat of steam. In this study was used the discretized wellbore model, where the well is discretized in the same way that the reservoir and each section of the well treated as a block of grid, with interblock connection with the reservoir. This study aims to analyze the influence of the pressure drop and heat along the injection well in the ES-SAGD process. The model used for the study is a homogeneous reservoir, semi synthetic with characteristics of the Brazilian Northeast and numerical simulations were performed using the STARS thermal simulator from CMG (Computer Modelling Group). The operational parameters analyzed were: percentage of solvent injected, the flow of steam injection, vertical distance between the wells and steam quality. All of them were significant in oil recovery factor positively influencing this. The results showed that, for all cases analyzed, the model considers the pressure drop has cumulative production of oil below its respective model that disregards such loss. This difference is more pronounced the lower the value of the flow of steam injection

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The demand for alternative sources of energy drives the technological development so that many fuels and energy conversion processes before judged as inadequate or even non-viable, are now competing fuels and so-called traditional processes. Thus, biomass plays an important role and is considered one of the sources of renewable energy most important of our planet. Biomass accounts for 29.2% of all renewable energy sources. The share of biomass energy from Brazil in the OIE is 13.6%, well above the world average of participation. Various types of pyrolysis processes have been studied in recent years, highlighting the process of fast pyrolysis of biomass to obtain bio-oil. The continuous fast pyrolysis, the most investigated and improved are the fluidized bed and ablative, but is being studied and developed other types in order to obtain Bio-oil a better quality, higher productivity, lower energy consumption, increased stability and process reliability and lower production cost. The stability of the product bio-oil is fundamental to designing consumer devices such as burners, engines and turbines. This study was motivated to produce Bio-oil, through the conversion of plant biomass or the use of its industrial and agricultural waste, presenting an alternative proposal for thermochemical pyrolysis process, taking advantage of particle dynamics in the rotating bed that favors the right gas-solid contact and heat transfer and mass. The pyrolyser designed to operate in a continuous process, a feeder containing two stages, a divisive system of biomass integrated with a tab of coal fines and a system of condensing steam pyrolytic. The prototype has been tested with sawdust, using a complete experimental design on two levels to investigate the sensitivity of factors: the process temperature, gas flow drag and spin speed compared to the mass yield of bio-oil. The best result was obtained in the condition of 570 oC, 25 Hz and 200 cm3/min, temperature being the parameter of greatest significance. The mass balance of the elementary stages presented in the order of 20% and 37% liquid pyrolytic carbon. We determined the properties of liquid and solid products of pyrolysis as density, viscosity, pH, PCI, and the composition characterized by chemical analysis, revealing the composition and properties of a Bio-oil.

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The present study provides a methodology that gives a predictive character the computer simulations based on detailed models of the geometry of a porous medium. We using the software FLUENT to investigate the flow of a viscous Newtonian fluid through a random fractal medium which simplifies a two-dimensional disordered porous medium representing a petroleum reservoir. This fractal model is formed by obstacles of various sizes, whose size distribution function follows a power law where exponent is defined as the fractal dimension of fractionation Dff of the model characterizing the process of fragmentation these obstacles. They are randomly disposed in a rectangular channel. The modeling process incorporates modern concepts, scaling laws, to analyze the influence of heterogeneity found in the fields of the porosity and of the permeability in such a way as to characterize the medium in terms of their fractal properties. This procedure allows numerically analyze the measurements of permeability k and the drag coefficient Cd proposed relationships, like power law, for these properties on various modeling schemes. The purpose of this research is to study the variability provided by these heterogeneities where the velocity field and other details of viscous fluid dynamics are obtained by solving numerically the continuity and Navier-Stokes equations at pore level and observe how the fractal dimension of fractionation of the model can affect their hydrodynamic properties. This study were considered two classes of models, models with constant porosity, MPC, and models with varying porosity, MPV. The results have allowed us to find numerical relationship between the permeability, drag coefficient and the fractal dimension of fractionation of the medium. Based on these numerical results we have proposed scaling relations and algebraic expressions involving the relevant parameters of the phenomenon. In this study analytical equations were determined for Dff depending on the geometrical parameters of the models. We also found a relation between the permeability and the drag coefficient which is inversely proportional to one another. As for the difference in behavior it is most striking in the classes of models MPV. That is, the fact that the porosity vary in these models is an additional factor that plays a significant role in flow analysis. Finally, the results proved satisfactory and consistent, which demonstrates the effectiveness of the referred methodology for all applications analyzed in this study.