Comparação do controle do inversor trifásico conectado à rede com filtro LCL considerando o amortecimento passivo e ativo

Distributed generation systems must fulfill standards specifications of current harmonics injected to the grid. In order to satisfy these grid requirements, passive filters are connected between inverter and grid. This work compares the characteristic response of the traditional inductive (L) filter with the inductive-capacitive-inductive (LCL) filter. It is shown that increasing the inductance L leads to a good ripple current suppression around the inverter switching frequency. The LCL filter provides better harmonic attenuation and reduces the filter size. The main drawback is the LCL filter impedance, which is characterized by a typical resonance peak, which must be damped to avoid instability. Passive or active techniques can be used to damp the LCL resonance. To address this issue, this dissertation presents a comparison of current control for PV grid-tied inverters with L filter and LCL filter and also discuss the use of active and passive damping for different regions of resonance frequency. From the mathematical models, a design methodology of the controllers was developed and the dynamic behavior of the system operating in closed loop was investigated. To validate the studies developed during this work, experimental results are presented using a three-phase 5kW experimental platform. The main components and their functions are discussed in this work. Experimental results are given to support the theoretical analysis and to illustrate the performance of grid-connected PV inverter system. It is shown that the resonant frequency of the system, and sampling frequency can be associated in order to calculate a critical frequency, below which is essential to perform the damping of the LCL filter. Also, the experimental results show that the active buffer per virtual resistor, although with a simple development, is effective to damp the resonance of the LCL filter and allow the system to operate stable within predetermined parameters.

Class-D audio amplifiers with negative feedback

There are many different designs for audio amplifiers. Class-D, or switching, amplifiers generate their output signal in the form of a high-frequency square wave of variable duty cycle (ratio of on time to off time). The square-wave nature of the output allows a particularly efficient output stage, with minimal losses. The output is ultimately filtered to remove components of the spectrum above the audio range. Mathematical models are derived here for a variety of related class-D amplifier designs that use negative feedback. These models use an asymptotic expansion in powers of a small parameter related to the ratio of typical audio frequencies to the switching frequency to develop a power series for the output component in the audio spectrum. These models confirm that there is a form of distortion intrinsic to such amplifier designs. The models also explain why two approaches used commercially succeed in largely eliminating this distortion; a new means of overcoming the intrinsic distortion is revealed by the analysis. Copyright (2006) Society for Industrial and Applied Mathematics

A path-based framework for analyzing large markov models

Reliability and dependability modeling can be employed during many stages of analysis of a computing system to gain insights into its critical behaviors. To provide useful results, realistic models of systems are often necessarily large and complex. Numerical analysis of these models presents a formidable challenge because the sizes of their state-space descriptions grow exponentially in proportion to the sizes of the models. On the other hand, simulation of the models requires analysis of many trajectories in order to compute statistically correct solutions. This dissertation presents a novel framework for performing both numerical analysis and simulation. The new numerical approach computes bounds on the solutions of transient measures in large continuous-time Markov chains (CTMCs). It extends existing path-based and uniformization-based methods by identifying sets of paths that are equivalent with respect to a reward measure and related to one another via a simple structural relationship. This relationship makes it possible for the approach to explore multiple paths at the same time,· thus significantly increasing the number of paths that can be explored in a given amount of time. Furthermore, the use of a structured representation for the state space and the direct computation of the desired reward measure (without ever storing the solution vector) allow it to analyze very large models using a very small amount of storage. Often, path-based techniques must compute many paths to obtain tight bounds. In addition to presenting the basic path-based approach, we also present algorithms for computing more paths and tighter bounds quickly. One resulting approach is based on the concept of path composition whereby precomputed subpaths are composed to compute the whole paths efficiently. Another approach is based on selecting important paths (among a set of many paths) for evaluation. Many path-based techniques suffer from having to evaluate many (unimportant) paths. Evaluating the important ones helps to compute tight bounds efficiently and quickly.

Estudo experimental do escoamento bifásico líquido gás em golfadas com leve mudança de direção

Gas-liquid two-phase flow is very common in industrial applications, especially in the oil and gas, chemical, and nuclear industries. As operating conditions change such as the flow rates of the phases, the pipe diameter and physical properties of the fluids, different configurations called flow patterns take place. In the case of oil production, the most frequent pattern found is slug flow, in which continuous liquid plugs (liquid slugs) and gas-dominated regions (elongated bubbles) alternate. Offshore scenarios where the pipe lies onto the seabed with slight changes of direction are extremely common. With those scenarios and issues in mind, this work presents an experimental study of two-phase gas-liquid slug flows in a duct with a slight change of direction, represented by a horizontal section followed by a downward sloping pipe stretch. The experiments were carried out at NUEM (Núcleo de Escoamentos Multifásicos UTFPR). The flow initiated and developed under controlled conditions and their characteristic parameters were measured with resistive sensors installed at four pipe sections. Two high-speed cameras were also used. With the measured results, it was evaluated the influence of a slight direction change on the slug flow structures and on the transition between slug flow and stratified flow in the downward section.

Simulação numérica do escoamento monofásico em uma bomba centrífuga radial

Centrifugal pumps are vastly used in many industrial applications. Knowledge of how these components behave in several circumstances is crucial for the development of more efficient and, therefore, less expensive pumping installations. The combination of multiple impellers, vaned diffusers and a volute might introduce several complex flow characteristics that largely deviate from regular inviscid pump flow theory. Computational Fluid Dynamics can be very helpful to extract information about which physical phenomena are involved in such flows. In this sense, this work performs a numerical study of the flow in a two-stage centrifugal pump (Imbil ITAP 65-330/2) with a vaned diffuser and a volute. The flow in the pump is modeled using the software Ansys CFX, by means of a multi-block, transient rotor-stator technique, with structured grids for all pump parts. The simulations were performed using water and a mixture of water and glycerin as work fluids. Several viscosities were considered, in a range between 87 and 720 cP. Comparisons between experimental data obtained by Amaral (2007) and numerical head curves showed a good agreement, with an average deviation of 6.8% for water. The behavior of velocity, pressure and turbulence kinetic energy fields was evaluated for several operational conditions. In general, the results obtained by this work achieved the proposed goals and are a significant contribution to the understanding of the flow studied.

Regional differences of outpatient physician supply as a theoretical economic and empirical generalized linear model

BACKGROUND: Regional differences in physician supply can be found in many health care systems, regardless of their organizational and financial structure. A theoretical model is developed for the physicians' decision on office allocation, covering demand-side factors and a consumption time function. METHODS: To test the propositions following the theoretical model, generalized linear models were estimated to explain differences in 412 German districts. Various factors found in the literature were included to control for physicians' regional preferences. RESULTS: Evidence in favor of the first three propositions of the theoretical model could be found. Specialists show a stronger association to higher populated districts than GPs. Although indicators for regional preferences are significantly correlated with physician density, their coefficients are not as high as population density. CONCLUSIONS: If regional disparities should be addressed by political actions, the focus should be to counteract those parameters representing physicians' preferences in over- and undersupplied regions.

Método para reconhecimento de vogais e extração de parâmetros acústicos para analises forenses

Forensic speaker comparison exams have complex characteristics, demanding a long time for manual analysis. A method for automatic recognition of vowels, providing feature extraction for acoustic analysis is proposed, aiming to contribute as a support tool in these exams. The proposal is based in formant measurements by LPC (Linear Predictive Coding), selectively by fundamental frequency detection, zero crossing rate, bandwidth and continuity, with the clustering being done by the k-means method. Experiments using samples from three different databases have shown promising results, in which the regions corresponding to five of the Brasilian Portuguese vowels were successfully located, providing visualization of a speaker’s vocal tract behavior, as well as the detection of segments corresponding to target vowels.

The Spatial Convergence of Knowledge in Portugal

Human resources are an essential element in territorial development. When these are characterized by a high level of training, they also enhance a number of effects in fundamental areas of binomial territorial-social cohesion. In this respect, the existence of higher education institutions throughout the territory allows the spread of human resources’ qualification but, by itself, does not guarantee the retention of these resources in different regions. Thus, the objective of this paper is to undertake a spatial analysis of convergence of knowledge through studying the evolution of the percentage of population with higher education in the periods elapsed between the last three censuses in Portugal. Although that percentage has risen appreciably, the convergence is shown to be (very) insignificant.

The study of the impact of demand controlled ventilation in energy consumption of offices in Portuguese commercial buildings

Indoor Air 2016 - The 14th International Conference of Indoor Air Quality and Climate

Desenvolvimento de metodologia de análise de indicadores de sustentabilidade como ferramenta para tomada de decisão utilizando lógica fuzzy

Dissertação (Mestrado em Tecnologia Nuclear)

Previsão do índice bovespa por meio de redes neurais artificiais: uma análise comparada aos métodos tradicionais de séries de tempo

Forecast is the basis for making strategic, tactical and operational business decisions. In financial economics, several techniques have been used to predict the behavior of assets over the past decades.Thus, there are several methods to assist in the task of time series forecasting, however, conventional modeling techniques such as statistical models and those based on theoretical mathematical models have produced unsatisfactory predictions, increasing the number of studies in more advanced methods of prediction. Among these, the Artificial Neural Networks (ANN) are a relatively new and promising method for predicting business that shows a technique that has caused much interest in the financial environment and has been used successfully in a wide variety of financial modeling systems applications, in many cases proving its superiority over the statistical models ARIMA-GARCH. In this context, this study aimed to examine whether the ANNs are a more appropriate method for predicting the behavior of Indices in Capital Markets than the traditional methods of time series analysis. For this purpose we developed an quantitative study, from financial economic indices, and developed two models of RNA-type feedfoward supervised learning, whose structures consisted of 20 data in the input layer, 90 neurons in one hidden layer and one given as the output layer (Ibovespa). These models used backpropagation, an input activation function based on the tangent sigmoid and a linear output function. Since the aim of analyzing the adherence of the Method of Artificial Neural Networks to carry out predictions of the Ibovespa, we chose to perform this analysis by comparing results between this and Time Series Predictive Model GARCH, developing a GARCH model (1.1).Once applied both methods (ANN and GARCH) we conducted the results' analysis by comparing the results of the forecast with the historical data and by studying the forecast errors by the MSE, RMSE, MAE, Standard Deviation, the Theil's U and forecasting encompassing tests. It was found that the models developed by means of ANNs had lower MSE, RMSE and MAE than the GARCH (1,1) model and Theil U test indicated that the three models have smaller errors than those of a naïve forecast. Although the ANN based on returns have lower precision indicator values than those of ANN based on prices, the forecast encompassing test rejected the hypothesis that this model is better than that, indicating that the ANN models have a similar level of accuracy . It was concluded that for the data series studied the ANN models show a more appropriate Ibovespa forecasting than the traditional models of time series, represented by the GARCH model

Quantificação do ião cálcio nas uvas e vinhos brancos por espectroscopia de infravermelho

Com o objetivo de diminuir a incidência das leveduras encapsulas em alginato se aglomerarem na segunda fermentação em garrafa e reduzir custos associados à sua eliminação, pretendeu-se utilizar a metodologia NIR para determinar a quantidade de cálcio no vinho. Foram quantificados outros minerais para avaliar hipotéticos antagonismos iónicos. Observou-se também que este controlo de qualidade poderá ser efetuado no mosto. Atualmente este controlo é realizado por metodologias de análise de referência bastante morosas como EAA. Contudo a metodologia NIR demonstrou ser uma boa alternativa no controlo dos parâ-metros de qualidade na produção de vinho espumante, permitindo a diminuição do tempo de análise e de resíduos. No desenvolvimento dos modelos matemáticos para a calibração do NIR utilizaram-se 79 vinhos brancos e 60 amostras de mosto. Foram desenvolvidos 11 modelos de calibração onde o coeficiente de correlação foi, em aproximadamente 58% dos casos, maior que 0,99; ABSTRACT: In order to reduce the incidence of alginate beads aggregation during the second fermentation in the bottle and to reduce costs associated with their disposal, it was used the NIR technology to quantify calcium content in the wine. Other minerals were also quantified in order to evaluate possible ionic antagonisms. Quality control is usually done in the base wine but it can also be evaluated in the must. Currently this control was carried out by reference analysis methodologies generally rather slow as AAS. However NIR proved to be a good alternative technique in the control of quality parameters of wine production, allowing the reduction of the analysis time and waste. In order to develop mathematical models for the calibration of NIR it was used 79 white wine samples and 60 must samples. Eleven calibration models have been developed, where the correlation coeffi-cient was, in approximately 58% of cases, greater than 0,99.

Opciones reales en la gerencia de proyectos

Teniendo en cuenta el escaso conocimiento y utilización de las opciones reales a la hora de realizar la evaluación financiera de un proyecto, se evidencia una oportunidad de elaborar un estado del arte de esta metodología con el fin de comparar las ventajas y las desventajas respecto a los métodos tradicionales más utilizados -- Para el desarrollo de la investigación se recurrió a información secundaria dentro de las bases de datos de la universidad EAFIT y su biblioteca, donde se encontraron artículos y material académico que arrojaron datos significativos que contribuyeron al cumplimiento de los objetivos -- Dentro de los resultados se encentra que el VPN y la TIR son las metodologías más comunes para la evaluación de proyectos en gran medida por su sencilla aplicación -- Por otro lado, las opciones reales son poco utilizadas por desconocimiento y por la aparente complejidad de su aplicación -- La mayor desventaja que presentan las metodologías tradicionales es que son estáticas, rígidas, orientadas al corto plazo y no manejan eficazmente la incertidumbre, mientras que las opciones reales tienen en cuenta la flexibilidad estratégica incorporada en un proyecto

Energy norm a-posteriori error estimation for hp-adaptive discontinuous Galerkin methods for elliptic problems in three dimensions

We develop the energy norm a-posteriori error estimation for hp-version discontinuous Galerkin (DG) discretizations of elliptic boundary-value problems on 1-irregularly, isotropically refined affine hexahedral meshes in three dimensions. We derive a reliable and efficient indicator for the errors measured in terms of the natural energy norm. The ratio of the efficiency and reliability constants is independent of the local mesh sizes and weakly depending on the polynomial degrees. In our analysis we make use of an hp-version averaging operator in three dimensions, which we explicitly construct and analyze. We use our error indicator in an hp-adaptive refinement algorithm and illustrate its practical performance in a series of numerical examples. Our numerical results indicate that exponential rates of convergence are achieved for problems with smooth solutions, as well as for problems with isotropic corner singularities.

Aplicação de Sistema de Informações Geográficas na análise espacial de doenças do milho no Brasil.

This study presents an application of the geographical information system technology on plant disease involving a multidisciplinary teamwork of geoprocessing and physiopathology specialists. The spatial analysis tools in a GIS were used to evaluate the spatial distribution of two diseases of maize in Brazil: polysora rusl caused by Puccinia polysora and tropical rust caused by Physopella zeae. A database of cIimate variables (mean temperature. relative humidity. and leaf wetness duration) of cIimatological normal from 1961-1990 was obtained and then related it to a mathematical model of disease development (polysora rust) and to the cIimate intervals (tropical rust) in order to obtain the maps. The choice of the model or the favorable climate interval is the important chalIenge of the method because the difficulty of adequacy to the spatial and temporal scales for the specific application. The major incidence of both disease occurred in almost alI the North region from January to June. although this region has traditionalIy a low production of maize. Considering the biggest producers regions. for both the diseases, favorable areas are located in part of Mato Grosso, Tocanlins. Minas Gerais; Mato Grosso do Sul. and coastal areas of São Paulo, Paraná, and Santa Catarina. varying among the dilferent months from January to June. The method allowed making an adequate distinction of the states and the months considered.