425 resultados para Distillation.
Estudo térmico dos resíduos gerados da destilação atmosférica das misturas diesel/biodiesel de dendê
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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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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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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
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The main purpose of this work is to develop an environment that allows HYSYS R chemical process simulator communication with sensors and actuators from a Foundation Fieldbus industrial network. The environment is considered a hybrid resource since it has a real portion (industrial network) and a simulated one (process) with all measurement and control signals also real. It is possible to reproduce different industrial process dynamics without being required any physical network modification, enabling simulation of some situations that exist in a real industrial environment. This feature testifies the environment flexibility. In this work, a distillation column is simulated through HYSYS R with all its variables measured and controlled by Foundation Fieldbus devices
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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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Given the growing environmental crisis caused by degradation, mainly due to the use of polluting energy sources, increasing the growing use of renewable energies worldwide, with emphasis on solar energy, an abundant supply and available to everyone, which can be harnessed in several ways: electricity generation; dehydration of food; heating, disinfection and distillation and cooking. The latter has as its primary feature the viability of clean, renewable energy for society, combating ecological damage caused by large-scale use of firewood for cooking foods, use in tropical countries with high solar radiation, and has funding NGOs throughout the world with the goal of achieving low-income population. The proposed project consists of a solar cooker for concentration, working from the reflection of sunlight by a hub that they converge to a focal point at the bottom of the pot, getting lots of heat. The solar cooker under study consists of two elliptical reflecting parabolas made from the recycling of scrap TV antenna, having 0.29 m² of surface area for each antenna, which were covered by multiple mirrors of 2 mm thick and mounted on a metal structure, with correction for the mobility of the apparent movement of the sun. This structure was built with the recycling of scrap metal, possessing a relatively low cost compared with other solar cookers, around US$ 50.00. This cost becomes negligible, since that will involve a great benefit to not have fuel costs for each meal, unlike the use of gas or firewood for cooking food. The tests show that the cooker has reached the maximum temperature of 740 ° C, for boiling water in an average time of 28 minutes, cooking various types of foods such as potatoes, rice and pasta in an average time of 45 minutes and still going as a solar oven, making pizza baking and meat. These cooking times do not differ much from the cooking times on a gas stove, it becomes the solar cooker as a good consumer acceptance, and furthermore not to deliver the same gases that can poison the food as with the wood stove. Proves the viability of using the stove to cook or bake in two daily meals for a family, still presenting a position to improve his performance with the addition of new materials, equipment and techniques
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The production of petroleum is frequently accomplished with great volumes of water, that it is carried of the underground with the oil. It is a challenge of the present century the development of technologies that allow the use of waste water for purposes that consume great amounts of water and don't demand as rigid as the one of the drinking water requirements. The solar distillation has been configuring as an alternative of clean technology for desalination of brine and saline. Besides causing the minimum possible damage to the environment, it takes advantage of an abundant and free energy source: the solar energy. That study aims to develop a Solar Distillator for treatment of the produced water of the oil wells, to obtain an efluent to use in agriculture and vapor generation. The methodology for collection, conservation and analysis of the physical-chemical parameters obeyed the norms in APHA (1995). The sampling was of the composed type. Experiments were accomplished in the solar distillation pilot and simulation in thermostatic bathing. The operation was in batch system and for periods of 4, 6 and 12 h. The developed Distillator is of the type simple effect of two waters. It was still tested two inclination angles for covering; 20º and 45º. The Distillator presented minimum of 2,85 L/m2d revenues and maximum of 7,14 L/m2d. The removals of salts were great than 98%. The removal of TOC in the simulation was great than 90%. In agreement with the data of energy and mass balance, it was verified that the developed solar Distillator presented compatible revenues with those found in literature for similar types. It can be inferred that the obtained distilled water assists to the requirements CONAMA in almost all the points and could be used for irrigation of cultures such as cotton and mamona. As the distilled water has characteristics of fresh water it can be used in the generation of vapor
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Natural gas, although basically composed by light hydrocarbons, also presents in its composition gaseous contaminants such as CO2 (carbon dioxide) and H2S (hydrogen sulfide). Hydrogen sulfide, which commonly occurs in oil and gas exploration and production activities, besides being among the gases that are responsible by the acid rain and greenhouse effect, can also cause serious harm to health, leading even to death, and damages to oil and natural gas pipelines. Therefore, the removal of hydrogen sulfide will significantly reduce operational costs and will result in oil with best quality to be sent to refinery, thereby resulting in economical, environmental, and social benefits. These factors highlight the need for the development and improvement of hydrogen sulfide sequestrating agents to be used in the oil industry. Nowadays there are several procedures for hydrogen sulfide removal from natural gas used by the petroleum industry. However, they produce derivatives of amines that are harmful to the distillation towers, form insoluble precipitates that cause pipe clogging and produce wastes of high environmental impact. Therefore, the obtaining of a stable system, in inorganic or organic reaction media, that is able to remove hydrogen sulfide without forming by-products that affect the quality and costs of natural gas processing, transport and distribution is of great importance. In this context, the evaluation of the kinetics of H2S removal is a valuable procedure for the treatment of natural gas and disposal of the byproducts generated by the process. This evaluation was made in an absorption column packed with Raschig ring, where natural gas with H2S passes through a stagnant solution, being the contaminant absorbed by it. The content of H2S in natural gas in column output was monitored by an H2S analyzer. The comparison between the obtained curves and the study of the involved reactions have not only allowed to determine the efficiency and mass transfer controlling step of the involved processes but also make possible to effect a more detailed kinetic study and evaluate the commercial potential of each reagent
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The oil industry, experiencing a great economic and environmental impact, has increasingly invested in researches aiming a more satisfactory treatment of its largest effluent, i.e., produced water. These are mostly discarded at sea, without reuse and after a basic treatment. Such effluent contains a range of organic compounds with high toxicity and are difficult to remove, such as polycyclic aromatic hydrocarbons, salts, heavy metals, etc.. The main objective of this work was to study the solar distillation of produced water pre-treated to remove salts and other contaminants trough of a hybrid system with a pre-heater. This developed apparatus was called solar system, which consists of a solar heater and a conventional distillation solar still. The first device consisted of a water tank, a solar flat plate collector and a thermal reservoir. The solar distillator is of simple effect, with 1m2 of flat area and 20° of inclination. This dissertation was divided in five steps: measurements in the solar system, i.e. temperatures and distillate flow rate and weather data; modeling and simulation of the system; study of vapor-liquid equilibrium of the synthetic wastewater by the aqueous solution of p-xylene; physical and chemical analyses of samples of the feed, distillate and residue, as well as climatology pertinent variables of Natal-RN. The solar system was tested separately, with the supply water, aqueous NaCl and synthetic oil produced water. Temperature measurements were taken every minute of the thermal reservoir, water tank and distillator (liquid and vapor phases). Data of solar radiation and rainfall were obtained from INPE (National Institute for Space Research). The solar pre-heater demonstrated to be effective for the liquid systems tested. The reservoir fluid had an average temperature of 58°C, which enabled the feed to be pre-heated in the distillator. The temperature profile in the solar distillator showed a similar behavior to daily solar radiation, with temperatures near 70°C. The distillation had an average yield of 2.4 L /day, i.e., an efficiency of 27.2%. Mathematical modeling aided the identification of the most important variables and parameters in the solar system. The study of the vapor-liquid equilibrium from Total Organic Carbon (TOC) analysis indicated heteroazeotropia and the vapor phase resulted more concentrated in p-xylene. The physical-chemical analysis of pH, conductivity, Total Dissolved Solids (TDS), chlorides, cations (including heavy metals) and anions, the effluent distillate showed satisfactory results, which presents a potential for reuse. The climatological study indicates the region of Natal-RN as favorable to the operation of solar systems, but the use of auxiliary heating during periods of higher rainfall and cloud cover is also recommended
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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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In the present work are established initially the fundamental relationships of thermodynamics that govern the equilibrium between phases, the models used for the description of the behavior non ideal of the liquid and vapor phases in conditions of low pressures. This work seeks the determination of vapor-liquid equilibrium (VLE) data for a series of multicomponents mixtures of saturated aliphatic hydrocarbons, prepared synthetically starting from substances with analytical degree and the development of a new dynamic cell with circulation of the vapor phase. The apparatus and experimental procedures developed are described and applied for the determination of VLE data. VLE isobarics data were obtained through a Fischer s ebulliometer of circulation of both phases, for the systems pentane + dodecane, heptane + dodecane and decane + dodecane. Using the two new dynamic cells especially projected, of easy operation and low cost, with circulation of the vapor phase, data for the systems heptane + decane + dodecane, acetone + water, tween 20 + dodecane, phenol + water and distillation curves of a gasoline without addictive were measured. Compositions of the equilibrium phases were found by densimetry, chromatography, and total organic carbon analyzer. Calibration curves of density versus composition were prepared from synthetic mixtures and the behavior excess volumes were evaluated. The VLE data obtained experimentally for the hydrocarbon and aqueous systems were submitted to the test of thermodynamic consistency, as well as the obtained from the literature data for another binary systems, mainly in the bank DDB (Dortmund Data Bank), where the Gibbs-Duhem equation is used obtaining a satisfactory data base. The results of the thermodynamic consistency tests for the binary and ternary systems were evaluated in terms of deviations for applications such as model development. Later, those groups of data (tested and approved) were used in the KijPoly program for the determination of the binary kij parameters of the cubic equations of state original Peng-Robinson and with the expanded alpha function. These obtained parameters can be applied for simulation of the reservoirs petroleum conditions and of the several distillation processes found in the petrochemistry industry, through simulators. The two designed dynamic cells used equipments of national technology for the determination of VLE data were well succeed, demonstrating efficiency and low cost. Multicomponents systems, mixtures of components of different molecular weights and also diluted solutions may be studied in these developed VLE cells