Made available in DSpace on 2014-12-17T14:55:42Z (GMT). No. of bitstreams: 1 LeandroLSL_DISSERT.pdf: 1890433 bytes, checksum: 540cbd4cf39fb3515249b7cecd6d0dcc (MD5) Previous issue date: 2010-03-19 / Conselho Nacional de Desenvolvimento Cient?fico e Tecnol?gico / 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 / Nos dias atuais, em que a concorr?ncia de mercado exige produtos de melhor qualidade e a busca constante pela redu??o de custos e pelo melhor aproveitamento das mat?rias-primas, a utiliza??o de estrat?gias de controle mais eficientes torna-se fundamental. Nas Unidades de Processamento de G?s Natural (UPGNs), assim como na maioria dos processos qu?micos, o controle de qualidade ? realizado a partir da composi??o de seus produtos. Entretanto, a an?lise de composi??es qu?micas, mesmo quando realizada por equipamentos como os cromat?grafos a g?s, apresenta longos intervalos de medi??o. Esse fato dificulta a elabora??o de estrat?gias de controle que proporcionem um melhor rendimento do processo. Geralmente, o principal produto econ?mico de uma UPGN ? o GLP (G?s Liquefeito de Petr?leo). Outros produtos comumente obtidos nessas unidades s?o a gasolina natural e o g?s residual. O GLP ? formado idealmente por propano e butano. Entretanto, na pr?tica, apresenta em sua composi??o contaminantes, tais como o etano e o pentano. Neste trabalho ? proposto um sistema de infer?ncia utilizando redes neurais para estimar as fra??es molares de etano e pentano no GLP e a fra??o molar de propano no g?s residual. O objetivo ? estimar essas vari?veis a cada minuto com uma ?nica rede neural de m?ltiplas camadas, permitindo a aplica??o de t?cnicas de controle inferencial visando a controlar a qualidade do GLP e reduzir a perda de propano no processo. No desenvolvimento deste trabalho, ? simulada no software HYSYS R uma UPGN formada por uma coluna de destila??o deetanizadora e outra debutanizadora. A infer?ncia ? realizada a partir das vari?veis de processo de alguns controladores PID presentes na instrumenta??o das colunas citadas. Com o intuito de reduzir a complexidade da rede neural de infer?ncia, ? utilizada a t?cnica estat?stica de an?lise de componentes principais (ACP) para diminuir o n?mero de entradas da rede. Tem-se, portanto, um sistema h?brido de infer?ncia. Tamb?m ? proposta neste trabalho, uma estrat?gia simples para a corre??o em tempo real do sistema de infer?ncia, tendo como base as medi??es dos poss?veis cromat?grafos de linha presentes no processo em estudo

Made available in DSpace on 2014-12-17T15:12:08Z (GMT). No. of bitstreams: 1 RenatoMJ.pdf: 302842 bytes, checksum: 740d121ea6f32e914bba6e0a61a27825 (MD5) Previous issue date: 2007-11-26 / Starting from the idea that the result of the Humean analysis of causal inferences must be applied coherently to the remaining part of his work, including its moral theory, the present master thesis aims at investigating whether Hume?s moral philosophy is essentially based on feeling, or whether this would not be rather essentially a consequence of our causal inferences in human actions and deliberations. The main idea consists in showing that our moral inferences, to the extent that they are for Hume empirical , depend on our belief in a connexion between something which has been previously observed and something which is not being observed ( but that it is expected to occur or to be observed in the future). Thus, this very belief must base our moral inferences concerning the actions and deliberations of the individuals. Therefore, must e o ipso induce us to associate actions and behaviors, as well as character and moral claims of men to certain moral feelings. Accordingly, the thesis is unfolded in three chapters. In the first chapter Hume?s theory of the perception is reported as essential part of the explanation or the principles that bind ideas in our mind and constitute our inferences. In the second chapter, the Humean analysis of causal inferences is presented and the way they contribute in the formation of our moral inferences is explained. In the third and last chapter, the formation of our moral inferences and the real contribution of the doctrine of freedom and necessity for the examination or our actions are analysed and discussed. / Partindo da id?ia de que o resultado da an?lise humeana das infer?ncias causais deve aplicar-se coerentemente ao restante de sua obra, incluindo sua teoria moral, a presente disserta??o objetiva investigar se a filosofia moral de Hume se fundamenta no sentimento, ou se isto n?o seria antes essencialmente uma conseq??ncia de nossas infer?ncias causais. A id?ia central consiste em mostrar que nossas infer?ncias morais, na medida em que para Hume s?o emp?ricas, dependem da nossa cren?a em uma conex?o entre o que foi anteriormente observado e algo que n?o ? observado ( mas espera-se ocorrer ou observar-se no futuro ). Assim, essa mesma cren?a fundamentaria nossas infer?ncias morais sobre as a??es dos indiv?duos, e conseq?entemente, nos levaria a associar determinados comportamentos, bem como o car?ter e as convic??es morais dos homens a certos sentimentos morais . A disserta??o desdobra-se em tr?s cap?tulos. No primeiro cap?tulo relata-se a teoria da percep??o e mostra-se que ela constitui parte essencial da explica??o das nossas infer?ncias . No segundo cap?tulo, trata-se da an?lise das infer?ncias causais e como contribuem na forma??o das nossas infer?ncias morais. No terceiro, a partir da an?lise anterior, investiga-se a forma??o de nossas infer?ncias morais e a real contribui??o da doutrina da necessidade e da liberdade para o exame de nossas a??es.

Made available in DSpace on 2014-12-17T14:55:19Z (GMT). No. of bitstreams: 1 JoseMAJ_TESE.pdf: 3560157 bytes, checksum: 2f20316c7b980a74bdb7b82e97e3bb43 (MD5) Previous issue date: 2014-03-24 / Conselho Nacional de Desenvolvimento Cient?fico e Tecnol?gico / In last decades, neural networks have been established as a major tool for the identification of nonlinear systems. Among the various types of networks used in identification, one that can be highlighted is the wavelet neural network (WNN). This network combines the characteristics of wavelet multiresolution theory with learning ability and generalization of neural networks usually, providing more accurate models than those ones obtained by traditional networks. An extension of WNN networks is to combine the neuro-fuzzy ANFIS (Adaptive Network Based Fuzzy Inference System) structure with wavelets, leading to generate the Fuzzy Wavelet Neural Network - FWNN structure. This network is very similar to ANFIS networks, with the difference that traditional polynomials present in consequent of this network are replaced by WNN networks. This paper proposes the identification of nonlinear dynamical systems from a network FWNN modified. In the proposed structure, functions only wavelets are used in the consequent. Thus, it is possible to obtain a simplification of the structure, reducing the number of adjustable parameters of the network. To evaluate the performance of network FWNN with this modification, an analysis of network performance is made, verifying advantages, disadvantages and cost effectiveness when compared to other existing FWNN structures in literature. The evaluations are carried out via the identification of two simulated systems traditionally found in the literature and a real nonlinear system, consisting of a nonlinear multi section tank. Finally, the network is used to infer values of temperature and humidity inside of a neonatal incubator. The execution of such analyzes is based on various criteria, like: mean squared error, number of training epochs, number of adjustable parameters, the variation of the mean square error, among others. The results found show the generalization ability of the modified structure, despite the simplification performed / Nas ?ltimas d?cadas, as redes neurais t?m se estabelecido como uma das principais ferramentas para a identifica??o de sistemas n?o lineares. Entre os diversos tipos de redes utilizadas em identifica??o, uma que se pode destacar ? a rede neural wavelet (ou Wavelet Neural Network - WNN). Esta rede combina as caracter?sticas de multirresolu??o da teoria wavelet com a capacidade de aprendizado e generaliza??o das redes neurais, podendo fornecer modelos mais exatos do que os obtidos pelas redes tradicionais. Uma evolu??o das redes WNN consiste em combinar a estrutura neuro-fuzzyANFIS (Adaptive Network Based Fuzzy Inference System) com estas redes, gerando-se a estrutura Fuzzy Wavelet Neural Network - FWNN. Essa rede ? muito similar ?s redes ANFIS, com a diferen?a de que os tradicionais polin?mios presentes nos consequentes desta rede s?o substitu?dos por redes WNN. O presente trabalho prop?e uma rede FWNN modificada para a identifica??o de sistemas din?micos n?o lineares. Nessa estrutura, somente fun??es waveletss?o utilizadas nos consequentes. Desta forma, ? poss?vel obter uma simplifica??o da estrutura com rela??o a outras estruturas descritas na literatura, diminuindo o n?mero de par?metros ajust?veis da rede. Para avaliar o desempenho da rede FWNN com essa modifica??o, ? realizada uma an?lise das caracter?sticas da rede, verificando-se as vantagens, desvantagens e o custo-benef?cio quando comparada com outras estruturas FWNNs. As avalia??es s?o realizadas a partir da identifica??o de dois sistemas simulados tradicionalmente encontrados na literatura e um sistema real n?o linear, consistindo de um tanque de multisse??es e n?o linear. Por fim, a rede foi utilizada para inferir valores de temperatura e umidade no interior de uma incubadora neonatal. A execu??o dessa an?lise baseia-se em v?rios crit?rios, tais como: erro m?dio quadr?tico, n?mero de ?pocas de treinamento, n?mero de par?metros ajust?veis, vari?ncia do erro m?dio quadr?tico, entre outros. Os resultados encontrados evidenciam a capacidade de generaliza??o da estrutura modificada, apesar da simplifica??o realizada

Made available in DSpace on 2014-12-17T14:56:12Z (GMT). No. of bitstreams: 1 DaniloCS_DISSERT.pdf: 3897603 bytes, checksum: cd98fa05a1dee36b5186c50e95b2f03b (MD5) Previous issue date: 2013-02-01 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior / Operating industrial processes is becoming more complex each day, and one of the factors that contribute to this growth in complexity is the integration of new technologies and smart solutions employed in the industry, such as the decision support systems. In this regard, this dissertation aims to develop a decision support system based on an computational tool called expert system. The main goal is to turn operation more reliable and secure while maximizing the amount of relevant information to each situation by using an expert system based on rules designed for a particular area of expertise. For the modeling of such rules has been proposed a high-level environment, which allows the creation and manipulation of rules in an easier way through visual programming. Despite its wide range of possible applications, this dissertation focuses only in the context of real-time filtering of alarms during the operation, properly validated in a case study based on a real scenario occurred in an industrial plant of an oil and gas refinery / A opera??o de processos industriais vem se tornando mais complexa ao longo dos anos, e um dos elementos que possibilitam este aumento de complexidade ? a integra??o de novas tecnologias e solu??es inteligentes empregadas no setor, como ? o caso dos sistemas de apoio ? decis?o. Neste sentido, esta disserta??o visa o desenvolvimento de um sistema de aux?lio ? opera??o baseado em uma ferramenta computacional chamada de sistema especialista. O objetivo principal ? tornar a opera??o mais confi?vel e segura ao maximizar a quantidade de informa??es relevantes a cada situa??o atrav?s da utiliza??o de um sistema especialista baseado em regras pr?-moldadas para uma determinada ?rea de conhecimento. Para a modelagem de tais regras foi proposto um ambiente de alto-n?vel, que permite a cria??o e manipula??o de regras de forma facilitada atrav?s de programa??o visual. A despeito de sua ampla gama de poss?veis aplica??es, esta disserta??o tem como foco o contexto de filtragem em tempo real de alarmes durante a opera??o, devidamente validada em um estudo de caso baseado em um cen?rio real ocorrido em uma planta industrial de uma refinaria de petr?leo e g?s

Made available in DSpace on 2014-12-17T14:56:12Z (GMT). No. of bitstreams: 1 VictorLCMS_DISSERT.pdf: 2392559 bytes, checksum: f4276b98c00bcaaa7742d7ced860b2b7 (MD5) Previous issue date: 2013-04-19 / Conselho Nacional de Desenvolvimento Cient?fico e Tecnol?gico / A serious problem that affects an oil refinery s processing units is the deposition of solid particles or the fouling on the equipments. These residues are naturally present on the oil or are by-products of chemical reactions during its transport. A fouled heat exchanger loses its capacity to adequately heat the oil, needing to be shut down periodically for cleaning. Previous knowledge of the best period to shut down the exchanger may improve the energetic and production efficiency of the plant. In this work we develop a system to predict the fouling on a heat exchanger from the Potiguar Clara Camar?o Refinery, based on data collected in a partnership with Petrobras. Recurrent Neural Networks are used to predict the heat exchanger s flow in future time. This variable is the main indicator of fouling, because its value decreases gradually as the deposits on the tubes reduce their diameter. The prediction could be used to tell when the flow will have decreased under an acceptable value, indicating when the exchanger shutdown for cleaning will be needed / Um s?rio problema que afeta unidades de refino de petr?leo ? a deposi??o e incrusta??o de s?lidos nos equipamentos. Esses res?duos est?o naturalmente presentes no petr?leo ou s?o produtos de rea??es qu?micas durante o seu transporte. Um permutador de calor, quando sujo, perde sua capacidade de aquecer adequadamente o petr?leo, precisando, periodicamente, ser retirado de opera??o, para que possa ser realizada uma limpeza. Informa??es pr?vias do melhor per?odo para realizar as paradas podem melhorar a efici?ncia energ?tica e de produ??o da planta. Esse trabalho desenvolveu um sistema de predi??o da incrusta??o em um permutador da Refinaria Potiguar Clara Camar?o, com base em dados coletados em parceria com a Petrobras. Foram utilizadas redes neurais recorrentes que preveem a vaz?o no permutador em instantes futuros. Essa vari?vel ? o principal indicador da incrusta??o, pois seu valor diminui gradualmente ? medida que os dep?sitos nas paredes dos tubos reduzem seu di?metro. A predi??o pode ser usada para dizer quando a vaz?o ter? ca?do abaixo de um valor satisfat?rio, indicando quando ser? necess?rio retirar o equipamento de opera??o

Cílem této práce je poskytnout snadný způsob, jak rozšířit analyzační nástroj o rozhraní splňující standard OSLC. Takové rozhraní umožňuje jednoduchou integraci nástrojů s jinými nástroji nebo systémy, umožňuje jejich vzdálené použití skrze webové služby a umožňuje je jednoduše propojit s databází pro databázové dotazy a pro perzistentní uložení dat. Toto je dosaženo návrhem a implementací OSLC adaptéru pomocí sady nástrojů Eclipse Lyo. Adaptér používá jako rozhraní doménu OSLC Automation a je dostatečně univerzální na to, aby skrze toto rozhraní pokryl funkcionalitu většiny analyzačních nástrojů za pomocí jejich stávajících rozhraní na příkazové řádce. Tato práce poskytuje úvod k OSLC, Eclipse Lyo a souvisejícím konceptům. Dále tato práce definuje požadavky a odlišnosti různých analyzačních nástrojů a diskutuje návrh adaptéru a faktory, které ovlivnily návrhová rozhodnutí. A nakonec prezentuje implementovaný adaptér a jeho vyhodnocení pomocí automatizované testovací sady a pomocí experimentů s řadou analyzačních nástrojů. Nejvýznamnější ukazatel hodnocení vytvořeného adaptéru je to, že už teď je používán v praxi pro přidání OSLC rozhraní k nástrojům ANaConDA, Perun, Spectra (všechny tři vyvíjené na VeriFIT) a HiLiTE (Honeywell).

Nástroj Atomer je statický analyzátor založený na myšlence, že pokud jsou některé sekvence funkcí vícevláknového programu prováděny v některých bězích pod zámky, je pravděpodobně zamýšleno, že mají být vždy provedeny atomicky. Analyzátor Atomer se tudíž snaží takové sekvence hledat a poté zjišťovat, pro které z nich může být v některých jiných bězích programu porušena atomicita. Autor této diplomové práce ve své bakalářské práci navrhl a implementoval první verzi nástroje Atomer jako zásuvný modul aplikačního rámce Facebook Infer. V této diplomové práci je navržena nová a výrazně vylepšená verze analyzátoru Atomer. Cílem vylepšení je zvýšení jak škálovatelnosti, tak přesnosti. Kromě toho byla přidána podpora pro několik původně nepodporovaných programovacích vlastností (včetně např. možnosti analyzovat programy napsané v jazycích C++ a Java nebo podpory pro reentrantní zámky nebo stráže zámků, tzv. "lock guards"). Prostřednictvím řady experimentů (včetně experimentů s reálnými programy a reálnými chybami) se ukázalo, že nová verze nástroje Atomer je skutečně mnohem obecnější, přesnější a lépe škáluje.

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