Optimización de la densidad de energía en vigas de material compuesto (PRF) sometidas a flexión pura

Las necesidades energéticas actuales requieren el desarrollo de tecnologías eficaces y eficientes en producción, transporte y distribución de energía. Estas necesidades han impulsado nuevos desarrollos en el ámbito energético, entre los cuales se encuentran sistemas de almacenamiento de energía. El avance en ingeniería de materiales permite pensar en la posibilidad de almacenamiento mediante deformación elástica de vigas. Concretamente se parte de un concepto de mecanismo acumulador de energía basado en la deformación elástica de resortes espirales a torsión. Dichos resortes se pueden considerar como elementos vigas sometidos a flexión pura y grandes deflexiones. Esta Tesis de centra en el diseño y optimización de estos elementos con el fin de maximizar la densidad de energía que son capaces de absorber. El proceso de optimización comienza con la identificación del factor crítico del que depende dicho proceso, en este caso de trata de la densidad de energía. Dicho factor depende de la geometría de la sección resistente y del material empleado en su construcción. En los últimos años ha existido un gran desarrollo de los materiales compuestos de tipo polimérico reforzados con fibras (PRF). Estos materiales están sustituyendo gradualmente a otros materiales, como los metales, debido principalmente a su excelente relación entre propiedades mecánicas y peso. Por otro lado, analizando las posibles geometrías para la sección resistente, se observó que la más adecuada es una estructura tipo sándwich. Se implementa así un procedimiento de diseño de vigas sándwich sometidas a flexión pura, con las pieles fabricadas en materiales compuestos tipo PRF y un núcleo que debe garantizar el bajo peso de la estructura. Se desarrolla así un procedimiento sistemático que se puede particularizar dependiendo de los parámetros de entrada de la viga, y que tiene en cuenta y analiza la aparición de todos los posibles modos de fallo posibles. Así mismo se desarrollan una serie de mapas o ábacos de diseño que permiten seleccionar rápidamente las dimensiones preliminares de la viga. Finalmente se llevan a cabo ensayos que permiten, por un lado, validar el concepto del mecanismo acumulador de energía a través del ensayo de un muelle con sección monolítica, y por otro validar los distintos diseños de vigas sándwich propuestos y mostrar el incremento de la densidad de energía con respecto a la alternativa monolítica. Como líneas futuras de investigación se plantean la investigación en nuevos materiales, como la utilización de nanotubos de carbono, y la optimización del mecanismo de absorción de energía; optimizando el mecanismo de absorción a flexión pura e implementando sistemas que permitan acumular energía mediante la deformación elástica debida a esfuerzos de tracción-compresión. ABSTRACT Energy supply requires the development of effective and efficient technologies for the production, transport and distribution of energy. In recent years, many energy storage systems have been developed. Advances in the field of materials engineering has allowed the development of new concepts as the energy storage by elastic deformation of beams. Particularly, in this Thesis an energy storage device based on the elastic deformation of torsional springs has been studied. These springs can be considered as beam elements subjected to pure bending loads and large deflections. This Thesis is focused on the design and optimization of these beam elements in order to maximize its density of stored energy. The optimization process starts with the identification of the critical factors for the elastic energy storage: the density. This factor depends on the geometry of the cross section of the beam and the materials from which it is made. In the last 20 years, major advances in the field of composite materials have been made, particularly in the field of fiber reinforced polymers (FRP). This type of material is substituting gradually metallic materials to their excellent weight-mechanical properties ratio. In the other side, several possible geometries are analyzed for its use in the cross section of the beam; it was concluded that the best option, for maximum energy density, is using a sandwich beam. A design procedure for sandwich beams with skins made up with FRP composites and a light weight core is developed. This procedure can be particularized for different input parameters and it analyzes all the possible failure modes. Abacus and failure mode maps have been developed in order to simplify the design process. Finally several tested was made. Firstly, a prototype of the energy storage system which uses a monolithic composite beam was tested in order to validate the concept of the energy storage by elastic deformation. After that sandwich beam samples are built and tested, validating the design and showing the increase of energy density with respect to the monolithic beam. As futures research lines the following are proposed: research in new materials, as carbon nanotubes; and the optimization of the energy storage mechanism, that means optimizing the pure bending storage mechanism and developing new ones based on traction-compression mechanisms.

Metodología para la asignación de vehículos de una flota a rutas preestablecidas

En general, la distribución de una flota de vehículos que recorre rutas fijas no se realiza completamente en base a criterios objetivos, primando otros aspectos más difícilmente cuantificables. El análisis apropiado debería tener en consideración la variabilidad existente entre las diferentes rutas dentro de una misma ciudad para así determinar qué tecnología es la que mejor se adapta a las características de cada itinerario. Este trabajo presenta una metodología para optimizar la asignación de una flota de vehículos a sus rutas, consiguiendo reducir el consumo y las emisiones contaminantes. El método propuesto está organizado según el siguiente procedimiento: - Registro de las características cinemáticas de los vehículos que recorren un conjunto representativo de rutas. - Agrupamiento de las líneas en conglomerados de líneas similares empleando un algoritmo jerárquico que optimice el índice de semejanza entre rutas obtenido mediante contraste de hipótesis de las variables representativas. - Generación de un ciclo cinemático específico para cada conglomerado. - Tipificación de variables macroscópicas que faciliten la clasificación de las restantes líneas utilizando una red neuronal entrenada con la información recopilada en las rutas medidas. - Conocimiento de las características de la flota disponible. - Disponibilidad de un modelo que estime, según la tecnología del vehículo, el consumo y las emisiones asociados a las variables cinemáticas de los ciclos. - Desarrollo de un algoritmo de reasignación de vehículos que optimice una función objetivo dependiente de las emisiones. En el proceso de optimización de la flota se plantean dos escenarios de gran trascendencia en la evaluación ambiental, consistentes en minimizar la emisión de dióxido de carbono y su impacto como gas de efecto invernadero (GEI), y alternativamente, la producción de nitróxidos, por su influencia en la lluvia ácida y en la formación de ozono troposférico en núcleos urbanos. Además, en ambos supuestos se introducen en el problema restricciones adicionales para evitar que las emisiones de las restantes sustancias superen los valores estipulados según la organización de la flota actualmente realizada por el operador. La metodología ha sido aplicada en 160 líneas de autobús de la EMT de Madrid, conociéndose los datos cinemáticos de 25 rutas. Los resultados indican que, en ambos supuestos, es factible obtener una redistribución de la flota que consiga reducir significativamente la mayoría de las sustancias contaminantes, evitando que, en contraprestación, aumente la emisión de cualquier otro contaminante. ABSTRACT In general, the distribution of a fleet of vehicles that travel fixed routes is not usually implemented on the basis of objective criteria, thus prioritizing on other features that are more difficult to quantify. The appropriate analysis should consider the existing variability amongst the different routes within the city in order to determine which technology adapts better to the peculiarities of each itinerary. This study proposes a methodology to optimize the allocation of a fleet of vehicles to the routes in order to reduce fuel consumption and pollutant emissions. The suggested method is structured in accordance with the following procedure: - Recording of the kinematic characteristics of the vehicles that travel a representative set of routes. - Grouping of the lines in clusters of similar routes by utilizing a hierarchical algorithm that optimizes the similarity index between routes, which has been previously obtained by means of hypothesis contrast based on a set of representative variables. - Construction of a specific kinematic cycle to represent each cluster of routes. - Designation of macroscopic variables that allow the classification of the remaining lines using a neural network trained with the information gathered from a sample of routes. - Identification and comprehension of the operational characteristics of the existing fleet. - Availability of a model that evaluates, in accordance with the technology of the vehicle, the fuel consumption and the emissions related with the kinematic variables of the cycles. - Development of an algorithm for the relocation of the vehicle fleet by optimizing an objective function which relies on the values of the pollutant emissions. Two scenarios having great relevance in environmental evaluation are assessed during the optimization process of the fleet, these consisting in minimizing carbon dioxide emissions due to its impact as greenhouse gas (GHG), and alternatively, the production of nitroxides for their influence on acid rain and in the formation of tropospheric ozone in urban areas. Furthermore, additional restrictions are introduced in both assumptions in order to prevent that emission levels for the remaining substances exceed the stipulated values for the actual fleet organization implemented by the system operator. The methodology has been applied in 160 bus lines of the EMT of Madrid, for which kinematic information is known for a sample consisting of 25 routes. The results show that, in both circumstances, it is feasible to obtain a redistribution of the fleet that significantly reduces the emissions for the majority of the pollutant substances, while preventing an alternative increase in the emission level of any other contaminant.

Designer-driven 3D buildings generated using variable neighborhood search

This paper presents a mechanism to generate virtual buildings considering designer constraints and guidelines. This mechanism is implemented as a pipeline of different Variable Neighborhood Search (VNS) optimization processes in which several subproblems are tackled (1) rooms locations, (2) connectivity graph, and (3) element placement. The core VNS algorithm includes some variants to improve its performance, such as, for example constraint handling and biased operator selection. The optimization process uses a toolkit of construction primitives implemented as "smart objects" providing basic elements such as rooms, doors, staircases and other connectors. The paper also shows experimental results of the application of different designer constraints to a wide range of buildings from small houses to a large castle with several underground levels.

Uso de circuitos equivalentes y teoría de filtros para el diseño de superficies selectivas en frecuencia

Frequency selective surfaces (FSS) and reflect/trasmitarrays are mostly designed on the basis ot optimization using an electromagnetic simulator. That is a time consuming method and some decisions have to be taken using simply intuition. The use of equivalent circuits of the scatterers selected for the design allows the substitution of the intuition and most part of the optimization process by the application of the classic rules of filter design. This communication presents all the steps necessary to obtain the equivalent circuit of different square scatterers in a periodic lattice and to implement the desired FSS frequency behaviour calculating the number of layers and the dimensions of the periodic cells. Several examples are included to evaluate the results.

Compatibilidad del principio de óptimo de Bellman con los métodos secuenciales de optimización de redes de tuberías

En el proceso de cálculo de redes de tuberías se maneja un conjunto de variables con unas características muy peculiares, ya que son discretas y estandarizadas. Por lo tanto su evolución se produce por escalones (la presión nominal, el diámetro y el costo de los tubos). Por otro lado la presión de diseño de la red es una función directa de la presión de cabecera. En el proceso de optimización mediante programación dinámica la presión de cabecera se va reduciendo gradualmente en cada secuencia del proceso, haciendo que evolucione a la par la presión de diseño, lo que genera a su vez saltos discriminados en la presión nominal de los tramos, y con ello en su costo y en su gradiente de cambio. En esta tesis doctoral se analiza si estos cambios discriminados que se producen en el gradiente de cambio de algunos tramos en el curso de una secuencia, ocasionados por la evolución de la presión de cabecera de la red, generan interferencias que alteran el proceso secuencial de la programación dinámica. La modificación del gradiente de cambio durante el transcurso de una secuencia se conoce con el nombre de mutación, la cual puede ser activa cuando involucra a un tramo optimo modificando las condiciones de la transacción o pasiva si no crea afección alguna. En el análisis realizado se distingue entre la mutación del gradiente de cambio de los tramos óptimos (que puede generarse exclusivamente en el conjunto de los trayectos que los albergan), y entre los efectos que el cambio de timbraje produce en el resto de los tramos de la red (incluso los situados aguas abajo de los nudos con holgura de presión nula) sobre el mecanismo iterativo, estudiando la compatibilidad de este fenómeno con el principio de óptimo de Bellman. En el proceso de investigación llevado a cabo se destaca la fortaleza que da al proceso secuencial del método Granados el hecho de que el gradiente de cambio siempre sea creciente en el avance hacia el óptimo, es decir que el costo marginal de la reducción de las pérdidas de carga de la red que se consigue en una iteración siempre sea más caro que el de la iteración precedente. Asimismo, en el estudio realizado se revisan los condicionantes impuestos al proceso de optimización, incluyendo algunos que hasta ahora no se han tenido en cuenta en los estudios de investigación, pero que están totalmente integrados en la ingeniería práctica, como es la disposición telescópica de las redes (reordenación de los diámetros de mayor a menor de cabeza a cola de la red), y la disposición de un único diámetro por tramo, en lugar de que estén compartidos por dos diámetros contiguos (con sus salvedades en caso de tramos de gran longitud, o en otras situaciones muy específicas). Finalmente se incluye un capítulo con las conclusiones, aportaciones y recomendaciones, las cuales se consideran de gran utilidad para la ingeniería práctica, entre las que se destaca la perfección del método secuencial, la escasa transcendencia de las mutaciones del gradiente de cambio y la forma en que pueden obviarse, la inocuidad de las mutaciones pasivas y el cumplimiento del principio de Bellman en todo el proceso de optimización. The sizing process of a water distribution network is based on several variables, being some of them special, as they are discrete and their values are standardized: pipe pressure rating, pipe diameter and pipe cost. On another note, the sizing process is directly related with the pressure at the network head. Given that during the optimization by means of the Granados’ Method (based on dynamic programming) the pressure at the network head is being gradually reduced, a jump from one pipe pressure rating to another may arise during the sequential process, leading to changes on the pipe cost and on the gradient change (unitary cost for reducing the head losses). This chain of changes may, in turn, affect the sequential process diverting it from an optimal policies path. This thesis analyses how the abovementioned alterations could influence the results of the dynamic programming algorithm, that is to say the compatibility with the Bellman’s Principle of Optimality, which states that the sequence has to follow a route of optimal policies, and that past decisions should not influence the remaining ones. The modification of the gradient change is known as mutation. Mutations are active when they affect the optimal link (the one which was selected to be changed during iteration) or passive when they do not alter the selection of the optimal link. The thesis analysed the potential mutations processes along the network, both on the optimal paths and also on the rest of the network, and its influence on the final results. Moreover, the investigation analysed the practical restrictions of the sizing process that are fully integrated in the applied engineering, but not always taken into account by the optimization tools. As the telescopic distribution of the diameters (i.e. larger diameters are placed at the network head) and the use of a unique diameter per link (with the exception of very large links, where two consecutive diameters may be placed). Conclusions regarding robustness of the dynamic programming algorithm are given. The sequence of the Granados Method is quite robust and it has been shown capable to auto-correct the mutations that could arise during the optimization process, and to achieve an optimal distribution even when the Bellman’s Principle of Optimality is not fully accomplished. The fact that the gradient change is always increasing during the optimization (that is to say, the marginal cost of reducing head losses is always increasing), provides robustness to the algorithm, as looping are avoided in the optimization sequence. Additionally, insight into the causes of the mutation process is provided and practical rules to avoid it are given, improving the current definition and utilization of the Granados’ Method.

Optimización del consumo de combustible de un vehículo dependiendo de las condiciones de la carretera

El consumo de combustible en un automóvil es una característica que se intenta mejorar continuamente debido a los precios del carburante y a la creciente conciencia medioambiental. Esta tesis doctoral plantea un algoritmo de optimización del consumo que tiene en cuenta las especificaciones técnicas del vehículo, el perfil de orografía de la carretera y el tráfico presente en ella. El algoritmo de optimización calcula el perfil de velocidad óptima que debe seguir el vehículo para completar un recorrido empleando un tiempo de viaje especificado. El cálculo del perfil de velocidad óptima considera los valores de pendiente de la carretera así como también las condiciones de tráfico vehicular de la franja horaria en que se realiza el recorrido. El algoritmo de optimización reacciona ante condiciones de tráfico cambiantes y adapta continuamente el perfil óptimo de velocidad para que el vehículo llegue al destino cumpliendo el horario de llegada establecido. La optimización de consumo es aplicada en vehículos convencionales de motor de combustión interna y en vehículos híbridos tipo serie. Los datos de consumo utilizados por el algoritmo de optimización se obtienen mediante la simulación de modelos cuasi-estáticos de los vehículos. La técnica de minimización empleada por el algoritmo es la Programación Dinámica. El algoritmo divide la optimización del consumo en dos partes claramente diferenciadas y aplica la Programación Dinámica sobre cada una de ellas. La primera parte corresponde a la optimización del consumo del vehículo en función de las condiciones de tráfico. Esta optimización calcula un perfil de velocidad promedio que evita, cuando es posible, las retenciones de tráfico. El tiempo de viaje perdido durante una retención de tráfico debe recuperarse a través de un aumento posterior de la velocidad promedio que incrementaría el consumo del vehículo. La segunda parte de la optimización es la encargada del cálculo de la velocidad óptima en función de la orografía y del tiempo de viaje disponible. Dado que el consumo de combustible del vehículo se incrementa cuando disminuye el tiempo disponible para finalizar un recorrido, esta optimización utiliza factores de ponderación para modular la influencia que tiene cada una de estas dos variables en el proceso de minimización. Aunque los factores de ponderación y la orografía de la carretera condicionan el nivel de ahorro de la optimización, los perfiles de velocidad óptima calculados logran ahorros de consumo respecto de un perfil de velocidad constante que obtiene el mismo tiempo de recorrido. Las simulaciones indican que el ahorro de combustible del vehículo convencional puede lograr hasta un 8.9% mientras que el ahorro de energía eléctrica del vehículo híbrido serie un 2.8%. El algoritmo fusiona la optimización en función de las condiciones del tráfico y la optimización en función de la orografía durante el cálculo en tiempo real del perfil óptimo de velocidad. La optimización conjunta se logra cuando el perfil de velocidad promedio resultante de la optimización en función de las condiciones de tráfico define los valores de los factores de ponderación de la optimización en función de la orografía. Aunque el nivel de ahorro de la optimización conjunta depende de las condiciones de tráfico, de la orografía, del tiempo de recorrido y de las características propias del vehículo, las simulaciones indican ahorros de consumo superiores al 6% en ambas clases de vehículo respecto a optimizaciones que no logran evitar retenciones de tráfico en la carretera. ABSTRACT Fuel consumption of cars is a feature that is continuously being improved due to the fuel price and an increasing environmental awareness. This doctoral dissertation describes an optimization algorithm to decrease the fuel consumption taking into account the technical specifications of the vehicle, the terrain profile of the road and the traffic conditions of the trip. The algorithm calculates the optimal speed profile that completes a trip having a specified travel time. This calculation considers the road slope and the expected traffic conditions during the trip. The optimization algorithm is also able to react to changing traffic conditions and tunes the optimal speed profile to reach the destination within the specified arrival time. The optimization is applied on a conventional vehicle and also on a Series Hybrid Electric vehicle (SHEV). The fuel consumption optimization algorithm uses data obtained from quasi-static simulations. The algorithm is based on Dynamic Programming and divides the fuel consumption optimization problem into two parts. The first part of the optimization process reduces the fuel consumption according to foreseeable traffic conditions. It calculates an average speed profile that tries to avoid, if possible, the traffic jams on the road. Traffic jams that delay drivers result in higher vehicle speed to make up for lost time. A higher speed of the vehicle within an already defined time scheme increases fuel consumption. The second part of the optimization process is in charge of calculating the optimal speed profile according to the road slope and the remaining travel time. The optimization tunes the fuel consumption and travel time relevancies by using two penalty factors. Although the optimization results depend on the road slope and the travel time, the optimal speed profile produces improvements of 8.9% on the fuel consumption of the conventional car and of 2.8% on the spent energy of the hybrid vehicle when compared with a constant speed profile. The two parts of the optimization process are combined during the Real-Time execution of the algorithm. The average speed profile calculated by the optimization according to the traffic conditions provides values for the two penalty factors utilized by the second part of the optimization process. Although the savings depend on the road slope, traffic conditions, vehicle features, and the remaining travel time, simulations show that this joint optimization process can improve the energy consumption of the two vehicles types by more than 6%.

Elastografia em imagens de ultrassom utilizando elementos de contorno.

Este trabalho apresenta uma nova metodologia para elastografia virtual em imagens simuladas de ultrassom utilizando métodos numéricos e métodos de visão computacional. O objetivo é estimar o módulo de elasticidade de diferentes tecidos tendo como entrada duas imagens da mesma seção transversal obtidas em instantes de tempo e pressões aplicadas diferentes. Esta metodologia consiste em calcular um campo de deslocamento das imagens com um método de fluxo óptico e aplicar um método iterativo para estimar os módulos de elasticidade (análise inversa) utilizando métodos numéricos. Para o cálculo dos deslocamentos, duas formulações são utilizadas para fluxo óptico: Lucas-Kanade e Brox. A análise inversa é realizada utilizando duas técnicas numéricas distintas: o Método dos Elementos Finitos (MEF) e o Método dos Elementos de Contorno (MEC), sendo ambos implementados em Unidades de Processamento Gráfico de uso geral, GpGPUs ( \"General Purpose Graphics Units\" ). Considerando uma quantidade qualquer de materiais a serem determinados, para a implementação do Método dos Elementos de Contorno é empregada a técnica de sub-regiões para acoplar as matrizes de diferentes estruturas identificadas na imagem. O processo de otimização utilizado para determinar as constantes elásticas é realizado de forma semi-analítica utilizando cálculo por variáveis complexas. A metodologia é testada em três etapas distintas, com simulações sem ruído, simulações com adição de ruído branco gaussiano e phantoms matemáticos utilizando rastreamento de ruído speckle. Os resultados das simulações apontam o uso do MEF como mais preciso, porém computacionalmente mais caro, enquanto o MEC apresenta erros toleráveis e maior velocidade no tempo de processamento.

Modelo de otimização multiobjetivo aplicado ao projeto de concepção de submarinos convencionais.

Este trabalho apresenta um modelo de otimização multiobjetivo aplicado ao projeto de concepção de submarinos convencionais (i.e. de propulsão dieselelétrica). Um modelo de síntese que permite a estimativa de pesos, volume, velocidade, carga elétrica e outras características de interesse para a o projeto de concepção é formulado. O modelo de síntese é integrado a um modelo de otimização multiobjetivo baseado em algoritmos genéticos (especificamente, o algoritmo NSGA II). A otimização multiobjetivo consiste na maximização da efetividade militar do submarino e na minimização de seu custo. A efetividade militar do submarino é representada por uma Medida Geral de Efetividade (OMOE) estabelecida por meio do Processo Analítico Hierárquico (AHP). O Custo Básico de Construção (BCC) do submarino é estimado a partir dos seus grupos de peso. Ao fim do processo de otimização, é estabelecida uma Fronteira de Pareto composta por soluções não dominadas. Uma dessas soluções é selecionada para refinamento preliminar e os resultados são discutidos. Subsidiariamente, esta dissertação apresenta discussão sucinta sobre aspectos históricos e operativos relacionados a submarinos, bem como sobre sua metodologia de projeto. Alguns conceitos de Arquitetura Naval, aplicada ao projeto dessas embarcações, são também abordados.

Extração, determinação da composição fenólica e avaliação do potencial de desativação de espécies reativas de oxigênio e da atividade anti-inflamatória de resíduos de amendoim, pimenta-rosa e pimenta-do-reino

O setor agroindustrial tem se expandido muito nos últimos anos, levando o país a um aumento na geração de resíduos agroindustriais, sendo que a maior parte deles ainda é descartada no meio ambiente, sem tratamento adequado, ou utilizada na alimentação animal, destinos que a priori, não geram ganhos econômicos para a agroindústria além de representarem gargalos logísticos e ambientais na sua disposição. Nesse sentido, o presente trabalho teve como objetivos otimizar o processo de extração de compostos bioativos, avaliar in vitro as atividades antioxidante, por meio da desativação de espécies reativas de oxigênio, e anti-inflamatória, bem como determinar a composição fenólica dos resíduos agroindustriais a saber: película de amendoim (Arachis hypogaea) (cultivares IAC886 e IAC505), pimenta-rosa (Schinus terebinthifolius Raddi) e pimenta-do-reino (Piper Nigrum L). O processo de otimização da extração de compostos antioxidantes foi realizado utilizando dois processos de extração, extração convencional e subcrítica, em delineamento composto central rotacional, utilizando como variáveis a temperatura e tempo e a pressão e temperatura, respectivamente, com os solventes etanol 80%, água e propilenoglicol 80%. Durante o processo de otimização a atividade antioxidante foi avaliada pelo método de sequestro do radical ABTS. Os melhores resultados foram obtidos para a extração convencional com os solventes etanol 80%, água e propilenoglicol 80%. A película de amendoim (IAC505) apresentou as maiores atividades antioxidantes (1.396,67, 580,44 e 859,89 μmol.g-1 em equivalentes de trolox, para os solventes etanol 80%, água e propilenoglicol 80%, respectivamente). A partir dos resultados obtidos para os solventes testados, utilizando a extração convencional, foram feitas outras análises de atividade antioxidante considerando o tempo e temperatura ideal de extração. Foram realizadas análises de avaliação da capacidade de redução de Folin-Ciocalteau e potencial de desativação dos radicais livres sintéticos (DPPH e ABTS) e espécies reativas de oxigênio (radicais peroxila, superóxido e ácido hipocloroso). O solvente de extração que apresentou melhores resultados em todos os ensaios foi o etanol 80%, sendo, portanto o solvente utilizado nas análises subsequentes. A partir da definição do melhor sistema extrator foram realizadas análises da composição fenólica, por meio das técnicas de cromatografia líquida de alta eficiência em modo analítico (HPLC-RP), cromatografia gasosa acoplada com espectrometria de massas (GC-MS), e avaliação in vitro da atividade anti-inflamatória. Foram identificados nos resíduos estudados procianidinas B1 e B2, ácido p-cumárico, miricetina, ácido ferúlico, ácido siríngico, ácido sinápico, epicatequina e catequina. A pimenta-do-reino diminui significativamente os níveis de TNF-α e nitritos, reduzindo assim o processo inflamatório gerado. Os resultados obtidos neste trabalho demonstram que estes resíduos agroindústrias possuem grande potencial biológico, podendo assim ser melhores aproveitados tanto pela indústria de alimentos quanto pela indústria farmacêutica.

Guidelines for the design of efficient sono-microreactors

Possible drawbacks of microreactors are inefficient reactant mixing and the clogging of microchannels when solid-forming reactions are carried out or solid (catalysts) suspensions are used. Ultrasonic irradiation has been successfully implemented for solving these problems in microreactor configurations ranging from capillaries immersed in ultrasonic baths to devices with miniaturized piezoelectric transducers. Moving forward in process intensification and sustainable development, the acoustic energy implementation requires a strategy to optimize the microreactor from an ultrasound viewpoint during its design. In this work, we present a simple analytical model that can be used as a guide to achieving a proper acoustic design of stacked microreactors. An example of this methodology was demonstrated through finite element analysis and it was compared with an experimental study found in the literature.

A comprehensive portfolio construction under stochastic environment

Prior research has established that idiosyncratic volatility of the securities prices exhibits a positive trend. This trend and other factors have made the merits of investment diversification and portfolio construction more compelling. ^ A new optimization technique, a greedy algorithm, is proposed to optimize the weights of assets in a portfolio. The main benefits of using this algorithm are to: (a) increase the efficiency of the portfolio optimization process, (b) implement large-scale optimizations, and (c) improve the resulting optimal weights. In addition, the technique utilizes a novel approach in the construction of a time-varying covariance matrix. This involves the application of a modified integrated dynamic conditional correlation GARCH (IDCC - GARCH) model to account for the dynamics of the conditional covariance matrices that are employed. ^ The stochastic aspects of the expected return of the securities are integrated into the technique through Monte Carlo simulations. Instead of representing the expected returns as deterministic values, they are assigned simulated values based on their historical measures. The time-series of the securities are fitted into a probability distribution that matches the time-series characteristics using the Anderson-Darling goodness-of-fit criterion. Simulated and actual data sets are used to further generalize the results. Employing the S&P500 securities as the base, 2000 simulated data sets are created using Monte Carlo simulation. In addition, the Russell 1000 securities are used to generate 50 sample data sets. ^ The results indicate an increase in risk-return performance. Choosing the Value-at-Risk (VaR) as the criterion and the Crystal Ball portfolio optimizer, a commercial product currently available on the market, as the comparison for benchmarking, the new greedy technique clearly outperforms others using a sample of the S&P500 and the Russell 1000 securities. The resulting improvements in performance are consistent among five securities selection methods (maximum, minimum, random, absolute minimum, and absolute maximum) and three covariance structures (unconditional, orthogonal GARCH, and integrated dynamic conditional GARCH). ^

Hybrid power system intelligent operation and protection involving distributed architectures and pulsed loads

Efficient and reliable techniques for power delivery and utilization are needed to account for the increased penetration of renewable energy sources in electric power systems. Such methods are also required for current and future demands of plug-in electric vehicles and high-power electronic loads. Distributed control and optimal power network architectures will lead to viable solutions to the energy management issue with high level of reliability and security. This dissertation is aimed at developing and verifying new techniques for distributed control by deploying DC microgrids, involving distributed renewable generation and energy storage, through the operating AC power system. To achieve the findings of this dissertation, an energy system architecture was developed involving AC and DC networks, both with distributed generations and demands. The various components of the DC microgrid were designed and built including DC-DC converters, voltage source inverters (VSI) and AC-DC rectifiers featuring novel designs developed by the candidate. New control techniques were developed and implemented to maximize the operating range of the power conditioning units used for integrating renewable energy into the DC bus. The control and operation of the DC microgrids in the hybrid AC/DC system involve intelligent energy management. Real-time energy management algorithms were developed and experimentally verified. These algorithms are based on intelligent decision-making elements along with an optimization process. This was aimed at enhancing the overall performance of the power system and mitigating the effect of heavy non-linear loads with variable intensity and duration. The developed algorithms were also used for managing the charging/discharging process of plug-in electric vehicle emulators. The protection of the proposed hybrid AC/DC power system was studied. Fault analysis and protection scheme and coordination, in addition to ideas on how to retrofit currently available protection concepts and devices for AC systems in a DC network, were presented. A study was also conducted on the effect of changing the distribution architecture and distributing the storage assets on the various zones of the network on the system's dynamic security and stability. A practical shipboard power system was studied as an example of a hybrid AC/DC power system involving pulsed loads. Generally, the proposed hybrid AC/DC power system, besides most of the ideas, controls and algorithms presented in this dissertation, were experimentally verified at the Smart Grid Testbed, Energy Systems Research Laboratory. All the developments in this dissertation were experimentally verified at the Smart Grid Testbed.

Physics-based modeling of power system components for the evaluation of low-frequency radiated electromagnetic fields

The low-frequency electromagnetic compatibility (EMC) is an increasingly important aspect in the design of practical systems to ensure the functional safety and reliability of complex products. The opportunities for using numerical techniques to predict and analyze system's EMC are therefore of considerable interest in many industries. As the first phase of study, a proper model, including all the details of the component, was required. Therefore, the advances in EMC modeling were studied with classifying analytical and numerical models. The selected model was finite element (FE) modeling, coupled with the distributed network method, to generate the model of the converter's components and obtain the frequency behavioral model of the converter. The method has the ability to reveal the behavior of parasitic elements and higher resonances, which have critical impacts in studying EMI problems. For the EMC and signature studies of the machine drives, the equivalent source modeling was studied. Considering the details of the multi-machine environment, including actual models, some innovation in equivalent source modeling was performed to decrease the simulation time dramatically. Several models were designed in this study and the voltage current cube model and wire model have the best result. The GA-based PSO method is used as the optimization process. Superposition and suppression of the fields in coupling the components were also studied and verified. The simulation time of the equivalent model is 80-100 times lower than the detailed model. All tests were verified experimentally. As the application of EMC and signature study, the fault diagnosis and condition monitoring of an induction motor drive was developed using radiated fields. In addition to experimental tests, the 3DFE analysis was coupled with circuit-based software to implement the incipient fault cases. The identification was implemented using ANN for seventy various faulty cases. The simulation results were verified experimentally. Finally, the identification of the types of power components were implemented. The results show that it is possible to identify the type of components, as well as the faulty components, by comparing the amplitudes of their stray field harmonics. The identification using the stray fields is nondestructive and can be used for the setups that cannot go offline and be dismantled

Desenvolvimento da célula base de microestruturas periódicas de compósitos sob otimização topológica

This thesis develops a new technique for composite microstructures projects by the Topology Optimization process, in order to maximize rigidity, making use of Deformation Energy Method and using a refining scheme h-adaptative to obtain a better defining the topological contours of the microstructure. This is done by distributing materials optimally in a region of pre-established project named as Cell Base. In this paper, the Finite Element Method is used to describe the field and for government equation solution. The mesh is refined iteratively refining so that the Finite Element Mesh is made on all the elements which represent solid materials, and all empty elements containing at least one node in a solid material region. The Finite Element Method chosen for the model is the linear triangular three nodes. As for the resolution of the nonlinear programming problem with constraints we were used Augmented Lagrangian method, and a minimization algorithm based on the direction of the Quasi-Newton type and Armijo-Wolfe conditions assisting in the lowering process. The Cell Base that represents the composite is found from the equivalence between a fictional material and a preescribe material, distributed optimally in the project area. The use of the strain energy method is justified for providing a lower computational cost due to a simpler formulation than traditional homogenization method. The results are presented prescription with change, in displacement with change, in volume restriction and from various initial values of relative densities.

Estratificação de solos em camadas horizontais utilizando evolução diferencial

This work's objective is the development of a methodology to represent an unknown soil through a stratified horizontal multilayer soil model, from which the engineer may carry out eletrical grounding projects with high precision. The methodology uses the experimental electrical apparent resistivity curve, obtained through measurements on the ground, using a 4-wire earth ground resistance tester kit, along with calculations involving the measured resistance. This curve is then compared with the theoretical electrical apparent resistivity curve, obtained through calculations over a horizontally strati ed soil, whose parameters are conjectured. This soil model parameters, such as the number of layers, in addition to the resistivity and the thickness of each layer, are optimized by Differential Evolution method, with enhanced performance through parallel computing, in order to both apparent resistivity curves get close enough, and it is possible to represent the unknown soil through the multilayer horizontal soil model fitted with optimized parameters. In order to assist the Differential Evolution method, in case of a stagnation during an arbitrary amount of generations, an optimization process unstuck methodology is proposed, to expand the search space and test new combinations, allowing the algorithm to nd a better solution and/or leave the local minima. It is further proposed an error improvement methodology, in order to smooth the error peaks between the apparent resistivity curves, by giving opportunities for other more uniform solutions to excel, in order to improve the whole algorithm precision, minimizing the maximum error. Methodologies to verify the polynomial approximation of the soil characteristic function and the theoretical apparent resistivity calculations are also proposed by including middle points among the approximated ones in the verification. Finally, a statistical evaluation prodecure is presented, in order to enable the classication of soil samples. The soil stratification methodology is used in a control group, formed by horizontally stratified soils. By using statistical inference, one may calculate the amount of soils that, within an error margin, does not follow the horizontal multilayer model.