51 resultados para Extractive distillation

em Universidade Federal do Rio Grande do Norte(UFRN)


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Anhydrous ethanol is used in chemical, pharmaceutical and fuel industries. However, current processes for obtaining it involve high cost, high energy demand and use of toxic and pollutant solvents. This problem occurs due to the formation of an azeotropic mixture of ethanol + water, which does not allow the complete separation by conventional methods such as simple distillation. As an alternative to currently used processes, this study proposes the use of ionic liquids as solvents in extractive distillation. These are organic salts which are liquids at low temperatures (under 373,15 K). They exhibit characteristics such as low volatility (almost zero/ low vapor ), thermal stability and low corrosiveness, which make them interesting for applications such as catalysts and as entrainers. In this work, experimental data for the vapor pressure of pure ethanol and water in the pressure range of 20 to 101 kPa were obtained as well as for vapor-liquid equilibrium (VLE) of the system ethanol + water at atmospheric pressure; and equilibrium data of ethanol + water + 2-HDEAA (2- hydroxydiethanolamine acetate) at strategic points in the diagram. The device used for these experiments was the Fischer ebulliometer, together with density measurements to determine phase compositions. The experimental data were consistent with literature data and presented thermodynamic consistency, thus the methodology was properly validated. The results were favorable, with the increase of ethanol concentration in the vapor phase, but the increase was not shown to be pronounced. The predictive model COSMO-SAC (COnductor-like Screening MOdels Segment Activity Coefficient) proposed by Lin & Sandler (2002) was studied for calculations to predict vapor-liquid equilibrium of systems ethanol + water + ionic liquids at atmospheric pressure. This is an alternative for predicting phase equilibrium, especially for substances of recent interest, such as ionic liquids. This is so because no experimental data nor any parameters of functional groups (as in the UNIFAC method) are needed

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LOPES, Jose Soares Batista et al. Application of multivariable control using artificial neural networks in a debutanizer distillation column.In: INTERNATIONAL CONGRESS OF MECHANICAL ENGINEERING - COBEM, 19, 5-9 nov. 2007, Brasilia. Anais... Brasilia, 2007

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LOPES, Jose Soares Batista et al. Application of multivariable control using artificial neural networks in a debutanizer distillation column.In: INTERNATIONAL CONGRESS OF MECHANICAL ENGINEERING - COBEM, 19, 5-9 nov. 2007, Brasilia. Anais... Brasilia, 2007

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This work is an ethnographic research with collectors women of Mangaba in the village of Ponta Negra in Natal - RN. This Women also known as Mangabeira's women reproduce a practice learned with their ancestors, collecting this fruit in the coastal tablelands forests and latter commercializing it in the local markets. This research uses the methodology of oral history and visual anthropology with presentation of collected images on board. It is intended to emphasize the botanical and environmental aspects of the Mangabeira plant, its ecosystem, territorial, economic and historical aspects of it, also the knowledge of this extractive practice of our immaterial culture.

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With the new discoveries of oil and gas, the exploration of fields in various geological basins, imports of other oils and the development of alternative fuels, more and more research labs have evaluated and characterized new types of petroleum and derivatives. Therefore the investment in new techniques and equipment in the samples analysis to determine their physical and chemical properties, their composition, possible contaminants, especification of products, among others, have multiplied in last years, so development of techniques for rapid and efficient characterization is extremely important for a better economic recovery of oil. Based on this context, this work has two main objectives. The first one is to characterize the oil by thermogravimetry coupled with mass spectrometry (TG-MS), and correlate these results with from other types of characterizations data previously informed. The second is to use the technique to develop a methodology to obtain the curve of evaluation of hydrogen sulfide gas in oil. Thus, four samples were analyzed by TG-MS, and X-ray fluorescence spectrometry (XRF). TG results can be used to indicate the nature of oil, its tendency in coke formation, temperatures of distillation and cracking, and other features. It was observed in MS evaluations the behavior of oil main compounds with temperature, the points where the volatilized certain fractions and the evaluation gas analysis of sulfide hydrogen that is compared with the evaluation curve obtained by Petrobras with another methodology

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In this study, was used a very promising technique called of pyrolysis, which can be used for obtaining products with higher added value. From oils and residues, since the contribution of heavier oils and residues has intensified to the world refining industry, due to the growing demand for fuel, for example, liquid hydrocarbons in the range of gasoline and diesel. The catalytic pyrolysis of vacuum residues was performed with the use of a mesoporous material belonging the M41S family, which was discovered in the early 90s by researchers Mobil Oil Corporation, allowing new perspectives in the field of catalysis. One of the most important members of this family is the MCM-41, which has a hexagonal arrangement of mesopores with pore diameters between 2 and 10 nm and a high specific surface area, making it very promising for use as a catalyst in petroleum refining for catalytic cracking, and their mesopores facilitate the access of large hydrocarbon molecules. The addition of aluminum in the structure of MCM-41 increases the acidity of the material, making it more positive for application in the petrochemical industry. The mesoporous material of the type Al-MCM41 (ratio Si / Al = 50) was synthesized by hydrothermal method starting from the silica gel, NaOH and distilled water added to the gel pseudobohemita synthesis. Driver was used as structural CTMABr. Removal of organic driver (CTMABr) was observed by TG / DTG and FTIR, but this material was characterized by XRD, which was observed the formation of the main peaks characteristic of mesoporous materials. The analysis of adsorption / desorption of nitrogen this material textural parameters were determined. The vacuum residues (VR's) that are products of the bottom of the vacuum distillation tower used in this study are different from oil fields (regions of Ceará and Rio de Janeiro). Previously characterized by various techniques such as FTIR, viscosity, density, SARA, elemental analysis and thermogravimetry, which was performed by thermal and catalytic degradation of vacuum residues. The effect of AlMCM-41 was satisfactory, since promoted a decrease in certain ranges of temperature required in the process of conversion of hydrocarbons, but also promoted a decrease in energy required in the process. Thus enabling lower costs related to energy expenditure from degradation during processing of the waste

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The objective of the thermal recovery is to heat the resevoir and the oil in it to increase its recovery. In the Potiguar river basin there are located several heavy oil reservoirs whose primary recovery energy provides us with a little oil flow, which makes these reservoirs great candidates for application of a method of recovery advanced of the oil, especially the thermal. The steam injection can occur on a cyclical or continuous manner. The continuous steam injection occurs through injection wells, which in its vicinity form a zone of steam that expands itself, having as a consequence the displace of the oil with viscosity and mobility improved towards the producing wells. Another possible mechanism of displacement of oil in reservoirs subjected to continuous injection of steam is the distillation of oil by steam, which at high temperatures; their lighter fractions can be vaporized by changing the composition of the oil produced, of the oil residual or to shatter in the amount of oil produced. In this context, this paper aims to study the influence of compositional models in the continuous injection of steam through in the analysis of some parameters such as flow injection steam and temperature of injection. Were made various leading comparative analysis taking the various models of fluid, varying from a good elementary, with 03 pseudocomponents to a modeling of fluids with increasing numbers of pseudocomponents. A commercial numerical simulator was used for the study from a homogeneous reservoir model with similar features to those found in northeastern Brazil. Some conclusions as the increasing of the simulation time with increasing number of pseudocomponents, the significant influence of flow injection on cumulative production of oil and little influence of the number of pseudocomponents in the flows and cumulative production of oil were found

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The worldwide concern regarding the use of sustainable energy and preserving the environment are determining factors in the search for resources and alternative sources of energy and therefore fuel less aggressive nature. In response to these difficulties Biodiesel has emerged as a good solution because it is produced from renewable sources, produces burns cleaner and is easily reproducible. This work was synthesized with biodiesel oil, sunflower via homogeneous catalysis in the presence of KOH, with and without the use of BHT and subsequently added to the blends BX (a proportion of biodiesel X = 5, 10, 15 and 20 %). Atmospheric distillation of the analysis, performed in blends with and without BHT were collected residue generated by each sample and performed a study heat from the thermogravimetric analysis at a heating rate of 10 °C*min-1, nitrogen atmosphere and heating to 600 °C. According to the specifications of Resolution N 7/2008 for biodiesel, it was found that the synthesized material was in accordance with the specifications. For blends showed that the samples are in accordance with the Resolution of ANP N 42/2009. From the TG / DTG curves of the samples of biodiesel, blends and waste can be seen that these show a single loss of thermal decomposition concerning constituents present in each sample. The blends without BHT with ratios of 5%, 10% and 15% biodiesel showed a lower amount of waste (1,07%; 1,09% e 1,10%) to mineral diesel (1,15%). Therefore, it is concluded that the addition of biodiesel with diesel mineral can improve some physico-chemical parameters, but also, depending on the added amount, decreasing the amount of waste generated. This fact is of great importance because the carbonaceous residue can cause problems in mechanical equipment and parts for vehicles, causing more frequent maintenance, and this is not desirable

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The growing world demand for energy supplied by fossil fuels, a major contributor to the emission of pollutants into the atmosphere and causing environmental problems, has been encouraging governments and international organizations to reflect and encourage the use of alternative renewable sources. Among these new possibilities deserves attention biodiesel, fuel cleaner and easy to reproduce. The study of new technologies involving that source is necessary. From this context, the paper aims at analyzing the thermal stability by thermogravimetric analysis, of the waste generated from atmospheric distillation of mixtures with ratios of 5, 10, 15 and 20% palm biodiesel in diesel with and without addition of BHT antioxidant. It was synthesized biodiesel through palm oil, via homogeneous catalysis in the presence of KOH, with and without the use of BHT and subsequently added to the diesel common indoor type (S1800) from a gas station BR. The diesel was already added with 5% biodiesel, and thus the proportions used for these blends were subtracted from the existing ratio in diesel fuel, resulting in the following proportions palm oil biodiesel: 0% (B5), 5% (B10), 10 % (B15) and 15% (B20). From atmospheric distillation analysis, performed in mixtures with and without BHT were collected residue generated by each sample and performed a thermal study from the thermogravimetric analysis at a heating rate of 10 °C.min-1, nitrogen atmosphere and heating to 600 ° C. According to the specifications of Resolution No. 7/2008 for biodiesel, it was found that the material was synthesized in accordance with the specifications. For mixtures, it was noted that the samples were in accordance with the ANP Resolution No. 42/2009. Given the TG / DTG curves of the samples of waste mixtures with and without BHT antioxidant was able to observe that they showed a single stage of thermal decomposition attributed to decomposition of heavy hydrocarbons and esters and other heavier constituents of the waste sample weighed. The thermal behavior of residues from atmospheric distillation of mixtures of diesel / biodiesel is very important to understand how this affects the proper functioning of the engine. A large amount of waste can generate a high content of particulate material, coke formation and carbonaceous deposits in engine valves, compromising their performance

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This work aims to obtain a low-cost virtual sensor to estimate the quality of LPG. For the acquisition of data from a distillation tower, software HYSYS ® was used to simulate chemical processes. These data will be used for training and validation of an Artificial Neural Network (ANN). This network will aim to estimate from available simulated variables such as temperature, pressure and discharge flow of a distillation tower, the mole fraction of pentane present in LPG. Thus, allowing a better control of product quality

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The increasing in the consumption of plant medicine by parts of the population generated a bigger need for studies. Drug substitutions, changes and adulterations at the production techniques are common places at plant-originated drugs trade, leading governmental departments of drug control round the world to adopt many analytical practices to medicinal plants. However, agronomic and technological issues cause characteristics and chemical composition variation at the drug, problem to be solved by the subject researchers. The present work aims to obtain a spray dried extract from a extractive solution obtained from Psidium guajava L. leaves based in book references that stress the intermediate dosage forms advantages. It also tries to validate useful methodologies for the quality control for both raw material and its derivates. Using eight sets of the spray dried extract (with Eudragit®, Aerosil ® e Avicel PH101 ® as drying adjuvants), the study proposes analytical methods using techniques commonly performed to plant medicines and its intermediate forms. As results, a viable spray-dried extract was obtained from a standartized extract solution. Among the studied adjuvants, the combination Aerosil ® with Eudragit ® showed the drying outcome, rheology, humidity and tannin content values that best fitted the demands of the Brazilian Pharmacopaea

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This work addresses issues related to analysis and development of multivariable predictive controllers based on bilinear multi-models. Linear Generalized Predictive Control (GPC) monovariable and multivariable is shown, and highlighted its properties, key features and applications in industry. Bilinear GPC, the basis for the development of this thesis, is presented by the time-step quasilinearization approach. Some results are presented using this controller in order to show its best performance when compared to linear GPC, since the bilinear models represent better the dynamics of certain processes. Time-step quasilinearization, due to the fact that it is an approximation, causes a prediction error, which limits the performance of this controller when prediction horizon increases. Due to its prediction error, Bilinear GPC with iterative compensation is shown in order to minimize this error, seeking a better performance than the classic Bilinear GPC. Results of iterative compensation algorithm are shown. The use of multi-model is discussed in this thesis, in order to correct the deficiency of controllers based on single model, when they are applied in cases with large operation ranges. Methods of measuring the distance between models, also called metrics, are the main contribution of this thesis. Several application results in simulated distillation columns, which are close enough to actual behaviour of them, are made, and the results have shown satisfactory

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Artificial Intelligence techniques are applied to improve performance of a simulated oil distillation system. The chosen system was a debutanizer column. At this process, the feed, which comes to the column, is segmented by heating. The lightest components become steams, by forming the LPG (Liquefied Petroleum Gas). The others components, C5+, continue liquid. In the composition of the LPG, ideally, we have only propane and butanes, but, in practice, there are contaminants, for example, pentanes. The objective of this work is to control pentane amount in LPG, by means of intelligent set points (SP s) determination for PID controllers that are present in original instrumentation (regulatory control) of the column. A fuzzy system will be responsible for adjusting the SP's, driven by the comparison between the molar fraction of the pentane present in the output of the plant (LPG) and the desired amount. However, the molar fraction of pentane is difficult to measure on-line, due to constraints such as: long intervals of measurement, high reliability and low cost. Therefore, an inference system was used, based on a multilayer neural network, to infer the pentane molar fraction through secondary variables of the column. Finally, the results shown that the proposed control system were able to control the value of pentane molar fraction under different operational situations

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The need to implement a software architecture that promotes the development of a SCADA supervisory system for monitoring industrial processes simulated with the flexibility of adding intelligent modules and devices such as CLP, according to the specifications of the problem, it was the motivation for this work. In the present study, we developed an intelligent supervisory system on a simulation of a distillation column modeled with Unisim. Furthermore, OLE Automation was used as communication between the supervisory and simulation software, which, with the use of the database, promoted an architecture both scalable and easy to maintain. Moreover, intelligent modules have been developed for preprocessing, data characteristics extraction, and variables inference. These modules were fundamentally based on the Encog software

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Nowadays, where the market competition requires products with better quality and a constant search for cost savings and a better use of raw materials, the research for more efficient control strategies becomes vital. In Natural Gas Processin Units (NGPUs), as in the most chemical processes, the quality control is accomplished through their products composition. However, the chemical composition analysis has a long measurement time, even when performed by instruments such as gas chromatographs. This fact hinders the development of control strategies to provide a better process yield. The natural gas processing is one of the most important activities in the petroleum industry. The main economic product of a NGPU is the liquefied petroleum gas (LPG). The LPG is ideally composed by propane and butane, however, in practice, its composition has some contaminants, such as ethane and pentane. In this work is proposed an inferential system using neural networks to estimate the ethane and pentane mole fractions in LPG and the propane mole fraction in residual gas. The goal is to provide the values of these estimated variables in every minute using a single multilayer neural network, making it possibly to apply inferential control techniques in order to monitor the LPG quality and to reduce the propane loss in the process. To develop this work a NGPU was simulated in HYSYS R software, composed by two distillation collumns: deethanizer and debutanizer. The inference is performed through the process variables of the PID controllers present in the instrumentation of these columns. To reduce the complexity of the inferential neural network is used the statistical technique of principal component analysis to decrease the number of network inputs, thus forming a hybrid inferential system. It is also proposed in this work a simple strategy to correct the inferential system in real-time, based on measurements of the chromatographs which may exist in process under study