"A Low Noise Amplifier (LNA) is an important building block in the RF receiver chain. Typically the LNA should provide acceptable gain and high linearity while maintaining low noise and power consumption. To optimize these conflicting goals the so-called Cascode topology is widely used in industry. Here the gain cell is comprised of two transistors, one in common-source and the other in common gate configuration. Cascode has a number of competitive advantages over other topologies such as high output impedance that shields the input device from voltage variations at the output, good reverse isolation resulting in improved stability, and acceptable input matching. Moreover, the topology features excellent frequency characteristics. Unfortunately, a Cascode design is expensive to deploy in RF systems and it requires more careful tuning and matching. Since the design relies on many circuit components, optimization methods are generally difficult to implement and often inaccurate in their predictions. To overcome these problems, this thesis proposes a modeling environment within the Advanced Design Systems (ADS) simulator that utilized DC and RF measurements in an effort to characterize each transistor separately. The model creates an easy-to-apply design approach capable of predicting the most important circuit components of the Cascode topology. The validity of the method is tested in ADS with a realistic p-HEMT library device. The comparison between model prediction and the realistic device involves both standard transistor parameters and high-frequency parasitic effects. "

No / Achieving an environmentally friendly fuel with respect to minimum sulfur compounds has recently became a significant issue for petroleum refining industries. This paper focuses on investigating oxidative desulfurization (ODS) process for removal of sulfur compounds found in light gas oil (LGO) in a batch reactor (at different reaction temperatures and batch time) using a novel nano-catalyst based on 4% iron oxide (Fe2O3) as an active component. Precipitation and Impregnation methods are used to prepare the nano-gamma alumina (γ-alumina) and to generate the new synthetic homemade nanocatalyst. A mathematical model is formulated for the ODS process to estimate the optimal kinetic parameters within gPROMS package. An excellent consistency with the experimental data of all runs with error less than 5% have obtained. The optimization results display that the new nanocatalyst prepared here is effective in removing more than 97% of the sulfur compounds from LGO resulting in a cleaner fuel. / The authors thank Petroleum Research and Development Center, The Iraqi Ministry of Oil /Baghdad, IRAQ for its financial support.

Orientador: Lucio Tunes Dos Santos / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Mecanica e Instituto de Geociências / Made available in DSpace on 2018-08-11T01:05:43Z (GMT). No. of bitstreams: 1 Grosfeld_Valeria_D.pdf: 2985169 bytes, checksum: 82ddf2042ee5ce573f870e3deebfa469 (MD5) Previous issue date: 2007 / Resumo: Neste trabalho estudamos os coeficientes de reflexão RPP e RPS para ondas elásticas. Introduzimos uma nova aproximação tipo impedância para o coeficiente RPS, baseados no êxito deste tipo de aproximações para o RPP na região de ângulos críticos e pós-críticos. Apesar de não ter-se mostrado tão eficiente quanto a aproximação tipo impedância de reflexão para RPP na região de interesse, se comparamos nossa aproximação com algumas já existentes, o comportamento é um pouco melhor que as aproximações precedentes. Esta análise foi feita mediante uma nova metodología, baseada em curvas de desempenho de algoritmos. Também mostramos que aproximando o coeficiente de reflexão RPP por uma aproximação tipo impedância é possível obter um indicador da presença de hidrocarbonetos sem necessidade de inverter os dados. Por outro lado discutimos como, com algumas hipóteses adicionais, se podem estimar alguns parâmetros elásticos das rochas diretamente dos dados. Por último, analisamos o efeito de parte do processamento sísmico na obtenção de nossas estimações em dados sintéticos / Abstract: In this work we are concerned with the reflection coefficients RPP and RPS for elastic waves. Based on the success of an impedance type approximation for the coefficient RPP in the critical region, we introduce a new approximation for the coefficient RPS. Although the new approximation was not so good as for the previous in the RPP case, comparing our approach with the existing ones we found that its behaviour is a little better than the preceding approaches. This comparison was made using a new methodology based on performace profile curves. Moreover, we show that, using the impedance type approximation for the reflection coeficient RPP , it is possible to get an indicator that reacts to the presence of hydrocarbons without the necessity of the invert the data. We also demostrate that under suitable conditions some elastic parameters of the rocks can be estimated directly from the data. Finally, we analyse the effect of seismic processing in order to obtain our estimate in synthetic data / Doutorado / Reservatórios e Gestão / Doutor em Ciências e Engenharia de Petróleo

This paper presents 3-D face modeling with head pose and depth information estimated from a 2-D query face image. Many recent approaches to 3-D face modeling are based on a 3-D morphable model that separately encodes the shape and texture in a parameterized model. The model parameters are often obtained by applying statistical analysis to a set of scanned 3-D faces. Such approaches tend to depend on the number and quality of scanned 3-D faces, which are difficult to obtain and computationally intensive. To overcome the limitations of 3-D morphable models, several modeling techniques from 2-D images have been proposed. We propose a novel framework for depth estimation from a single 2-D image with an arbitrary pose. The proposed scheme uses a set of facial features in a query face image and a reference 3-D face model to estimate the head pose angles of the face. The depth information of the subject at each feature point is represented by the depth information of the reference 3-D face model multiplied by a vector of scale factors. We use the positions of a set of facial feature points on the query 2-D image to deform the reference face dense model into a person specific 3-D face by minimizing an objective function. The objective function is defined as the feature disparity between the facial features in the face image and the corresponding 3-D facial features on the rotated reference model projected onto 2-D space. The pose and depth parameters are iteratively refined until stopping criteria are reached. The proposed method requires only a face image of arbitrary pose for the reconstruction of the corresponding 3-D face dense model with texture. Experiment results with USF Human-ID and Pointing'04 databases show that the proposed approach is effective to estimate depth and head pose information with a single 2-D image. / Electrical and Computer Engineering

Yes / In this work, the performance of oxidative desulfurization (ODS) of dibenzothiophene (DBT) in light gas oil (LGO) is evaluated with a homemade manganese oxide (MnO2/γ-Al2O3) catalyst. The catalyst is prepared by Incipient Wetness Impregnation (IWI) method with air under moderate operating conditions. The effect of different reaction parameters such as reaction temperature, liquid hour space velocity and initial concentration of DBT are also investigated experimentally. Developing a detailed and a validated trickle bed reactor (TBR) process model that can be employed for design and optimization of the ODS process, it is important to develop kinetic models for the relevant reactions with high accuracy. Best kinetic model for the ODS process taking into account hydrodynamic factors (mainly, catalyst effectiveness factor, catalyst wetting efficiency and internal diffusion) and the physical properties affecting the oxidation process is developed utilizing data from pilot plant experiments. An optimization technique based upon the minimization of the sum of the squared error between the experimental and predicted composition of oxidation process is used to determine the best parameters of the kinetic models. The predicted product conversion showed very good agreement with the experimental data for a wide range of the operating condition with absolute average errors less than 5%.

Yes / In this paper, oxidative desulfurization (ODS) process is studied for the purpose of removing the sulfur components from light gas oil (LGO) via experimentation and process modeling. A recently developed (by the authors) copper and nickel oxide based composite nano-catalyst is used in the process. The ODS experiments are conducted in a batch reactor and air is used as an oxidizer under moderate operation conditions. Determination of the kinetic parameters with high accuracy is necessary of the related chemical reactions to develop a helpful model for the ODS operation giving a perfect design of the reactor and process with high confidence. High conversion of 92% LGO was obtained under a reaction temperature of 413 K and reaction time of 90 min for synthesized Cu Ni /HY nano-catalyst. Here model based optimization technique incorporating experimental data is used to estimate such parameters. Two approaches (linear and non-linear) are utilized to estimate the best kinematic parameters with an absolute error of less than 5% between the predicted and the experimental results. An environmentally friendly fuel is regarded the main goal of this study, therefore the optimization process is then employed utilizing the validated model of the prepared composite nano-catalyst to get the optimal operating conditions achieving maximum conversion of such process. The results show that the process is effective in removing more than 99% of the sulfur from the LGO resulting in a cleaner fuel.

Yes / Batch oxidative desulfurization (ODS) process is investigated here for the removal sulfur compound from light naphtha using homemade new nano-catalyst. The catalyst is made of manganese dioxide supported on zeolite nanoparticles which shows an excellent catalytic performance with good impregnation, high activity, good pore size distribution and larger surface area. Different reaction temperature, time and initial sulfur concentration are used to have a deeper insight of the process. The experimental results reveal that the conversion of sulfur compound is increased by increasing the initial sulfur concentration, the reaction temperature and batch time. A mathematical model of the process is developed and validated using the experimental data within gPROMS software with high accuracy. The validated model (errors less than 5% between experimental and predicted results) is then utilized to obtain the optimal operation conditions of the process giving maximum conversion of sulfur (higher than 99%) resulting in an environmentally friendly fuel.

O processo de estimação de estado em sistemas elétricos de potência está sujeito a três tipos de erros: erros nas medidas analógicas (erros grosseiros); erros devido a informações erradas quanto aos estados de chaves e/ou disjuntores (erros topológicos) e erros causados por informações erradas de algum parâmetro do sistema (erros de parâmetros). É drástico o efeito de erros de parâmetros, para o processo de estimação de estado, normalmente intolerável, sendo, entretanto, menos evidente que os erros grosseiros e topológicos. Aproveitando o fato de que certas medidas não sofrem mudanças significativas de valor, durante um determinado intervalo de tempo, propõe-se uma metodologia para estimação de estado e parâmetros de linhas de transmissão. Na metodologia proposta, que se baseia nas equações normais, o vetor de estado convencional é aumentado para a inclusão dos parâmetros a serem estimados. Este vetor de estado aumentado é então estimado através de uma grande quantidade de medidas, obtidas em diversas amostras, durante um intervalo de tempo em que as variáveis de estado do sistema não tenham sofrido alterações significativas de valor. Esta situação ocorre tipicamente à noite, fora dos horários de pico. Propõe-se também uma metodologia para análise de observabilidade para o estimador proposto. Para comprovar a eficiência das metodologias propostas, vários testes foram realizados, utilizando os sistemas de 6, 14 e 30 barras do IEEE. / The process of power system state estimation is subjected to three types of errors: errors in analogical measurements (gross errors), incorrect information about the status of switching devices (topology errors) and incorrect information about the model of the systems equipment (parameter errors). The effects of parameter errors on the process of power system state estimation are drastic and less evident to detect than gross and topology errors. Taking advantage of the fact that a certain fraction of the measurements varies over a small range in a certain period of time, a methodology to estimative transmission line parameters and state based on normal equations has been proposed. In such methodology, which is based on normal equations, the traditional state vector is expanded to include the parameters to be estimated. This augmented state vector is estimated through a large collection of measurements, recorded within several snapshots of the power system, during which the actual system state varies over a small range. This situation typically occurs during the night off-peak periods. An observability analysis methodology is also proposed for the presented estimator. To prove the efficiency of the methodologies, several tests were made using the systems of 6, 14 and 30 buses from IEEE.

A bactéria Zymomonas mobilis atraiu considerável interesse nas últimas décadas devido ao seu metabolismo único e eficientes características fermentativas na produção de etanol a partir de açúcares simples. No entanto, apesar das aparentes vantagens na conversão e taxas específicas quando comparada com as leveduras, estas ainda dominam o mercado produtivo de etanol. Dentre os diversos modelos encontrados na literatura para representar o processo fermentativo de glicose através de Z. mobilis, o modelo proposto por Jöbses et al. (1986) aparenta ser bem estruturado e ideal para a criação de estratégias de controle e otimização de processos fermentativos com este microrganismo, viabilizando sua utilização em escala industrial. Fermentações de Z. mobilis em regime contínuo apresentam comportamento oscilatório para baixas taxas de diluição, fenômeno este comprovado experimentalmente. Experimentos laboratoriais foram utilizados para a estimação de parâmetros do modelo de Jöbses, através da técnica de minimização da derivada do erro da função objetivo. O novo modelo ajustado apresenta dinâmica equivalente ao modelo original de Jöbses, fato este comprovado através da construção dos diagramas de bifurcação. Os diagramas de fase dos modelos apresentam algumas diferenças estruturais entre si, entretanto, a ocorrência de multiplicidade de estados estacionários em baixos valores de taxa de diluição está presente em todos. Em bioprocessos, a obtenção de informações sobre o sistema é um tanto complexa, devido a estes meios serem muito suscetíveis a distúrbios, contaminações, além de que medidas de concentrações são relativamente dispendiosas, associadas com um alto tempo morto, o que impossibilita, muitas vezes, a implementação de sistemas de controle eficientes. Para contribuir com a resolução deste problema foi desenvolvida uma nova inferência das variáveis de estado através da informação de consumo de hidróxido de sódio, utilizado no controle de pH do meio. Inferidores de variáveis de estado que utilizam a variação no consumo de hidróxido de sódio foram ajustados e apresentaram resultados promissores, mostrando a viabilidade do desenvolvimento de metodologias para este tipo de análise, tornando a caracterização de sistemas fermentativos mais rápida e acessível, não apenas em nível acadêmico, que a desenvolvida atualmente, principalmente devido ao baixo custo associado, e a dinâmica rápida deste tipo de sensor. / The bacterium Zymomonas mobilis has attracted considerable interest in recent decades due to their unique metabolism and efficient characteristics in the production of ethanol by simple sugars. However, despite the apparent advantages in the conversion and specific rates, when compared with yeast, there is no industrial-scale fermentations with these bacteria. Among the various models found in literature to represent glucose fermentation with Z. mobilis, the model proposed by Jöbses et al. (1986) appears to be well structured and ideal for the creation of control strategies and optimization methods for increase productions. Fermentation in continuous mode with this organism exhibit oscillatory behavior at low dilution rates, phenomenon showed or demonstrated by experiments performed on laboratory scale. A laboratorial experiment also was used for estimation of new parameters group of Jöbses models, using the technique of minimization of error derivative for objective function. The new adjusted model set presents dynamics similar to the original model, fact confirmed by bifurcation analyses of both models. The diagram for these models show structural differences, but both presents steady states multiplicity and Hopf bifurcations. The obtained of fermentation characteristics is very complex, due to these reactive means being very susceptible to disturbances, contamination, among others, and concentrations measures are relatively expensive and whit a high dead time associated, which often prevents the implementation of control tools. The proposed inference of state variables by consumption rate of hydroxide sodium, used for maintenance pH medium, was tested and confirmed. Virtual sensors using the information of consumption rate of hydroxide were adjusted and have shown promising results, demonstrating the feasibility of developing methods of analysis based on this methodology, making the characterization of fermentative systems faster and cheaper them currently developed, mainly due to low cost associated, and the dynamics of this fast type of sensor.

Orthogonal Frequency Division Multiplexing (OFDM) techniques have been used in many wireless communication systems to improve the system capacity and achieve high data-rate. It possesses good spectral efficiency and robustness against interferences. The OFDM system has been adopted in many communication standards, such as the 802.11a/g standards for the high-speed WLAN, HIPERLAN2, and IEEE 802.16 standard, and meanwhile, it is also employed in the European DAB and DVB systems. To avoid the inter-block interference (IBI), usually, in the transmitter of OFDM systems the redundancy with sufficient length is introduced, it allows us to overcome the IBI problem, due to highly dispersive channel. Many redundancy insertion methods have been proposed in the literatures, there are cyclic prefix (CP), zero padding (ZP) and the pseudorandom postfix (PRP). Under such system we have still to know the correct channel state information for equalizing the noisy block signal. Especially, in time-varying channel, the incorrect channel state information may introduce serious inter-symbol interference (ISI), if the channel estimation could not perform correctly. In this thesis, the PRP-OFDM system is considered. According to the PRP-OFDM scheme, the redundancy with pseudorandom postfix (PRP) approach is employed to make semi-blind channel estimation with order-one statistics of the received signal. But these statistic characteristics may not be available under time-varying channel. Hence, in this thesis, we propose a modified PRP-OFDM system with assistant training sequences, which is equipped with minimum mean-square-error equalizer and utilize Kalman filter algorithm to implement time-varying channel estimation. To do so, we first model time-varying channel estimation problem with a dynamic system, and adopt the Kalman filter algorithm to estimate the true channel coefficients. Unfortunately, since most parameters in dynamic system are random and could not to be known in advance. We need to apply effective estimation schemes to estimate the statistics of true parameters for implementing the Kalman filter algorithm. When the channel state information is known, MMSE equalizer follows to suppress the inter-symbol interference (ISI). Moreover, after making decision the binary data can be used to re-modulate PRP-OFDM symbol and to be re-used in Kalman filter to obtain more accurate CSI to improve the effectiveness of the equalizer. Via computer simulations, we verify that desired performance in terms of bit error rate (BER), can be achieved compared with the CP-OFDM systems.