Caracterização de atapulgita visando aplicação para reforço de materiais poloméricos

The clay mineral attapulgite is a group of hormitas, which has its structures formed by microchannels, which give superior technological properties classified the industrial clays, clays of this group has a very versatile range of applications, ranging from the drilling fluid for wells oil has applications in the pharmaceutical industry. Such properties can be improved by activating acid and / or thermal activation. The attapulgite when activated can improve by up to 5-8 times some of its properties. The clay was characterized by X-ray diffraction, fluorescence, thermogravimetric analysis, differential thermal analysis, scanning electron microscopy and transmission electron microscopy before and after chemical activation. It can be seen through the results the efficiency of chemical treatment, which modified the clay without damaging its structure, as well as production of polymer matrix composites with particles dispersed atapugita

Uma aplicação da apredizagem por reforço na otimização da produção em um campo de petróleo

The objective of reservoir engineering is to manage fields of oil production in order to maximize the production of hydrocarbons according to economic and physical restrictions. The deciding of a production strategy is a complex activity involving several variables in the process. Thus, a smart system, which assists in the optimization of the options for developing of the field, is very useful in day-to-day of reservoir engineers. This paper proposes the development of an intelligent system to aid decision making, regarding the optimization of strategies of production in oil fields. The intelligence of this system will be implemented through the use of the technique of reinforcement learning, which is presented as a powerful tool in problems of multi-stage decision. The proposed system will allow the specialist to obtain, in time, a great alternative (or near-optimal) for the development of an oil field known

Aprendizado por Reforço com Valores deInfluência em Sistemas Multi-Agente

We propose a new paradigm for collective learning in multi-agent systems (MAS) as a solution to the problem in which several agents acting over the same environment must learn how to perform tasks, simultaneously, based on feedbacks given by each one of the other agents. We introduce the proposed paradigm in the form of a reinforcement learning algorithm, nominating it as reinforcement learning with influence values. While learning by rewards, each agent evaluates the relation between the current state and/or action executed at this state (actual believe) together with the reward obtained after all agents that are interacting perform their actions. The reward is a result of the interference of others. The agent considers the opinions of all its colleagues in order to attempt to change the values of its states and/or actions. The idea is that the system, as a whole, must reach an equilibrium, where all agents get satisfied with the obtained results. This means that the values of the state/actions pairs match the reward obtained by each agent. This dynamical way of setting the values for states and/or actions makes this new reinforcement learning paradigm the first to include, naturally, the fact that the presence of other agents in the environment turns it a dynamical model. As a direct result, we implicitly include the internal state, the actions and the rewards obtained by all the other agents in the internal state of each agent. This makes our proposal the first complete solution to the conceptual problem that rises when applying reinforcement learning in multi-agent systems, which is caused by the difference existent between the environment and agent models. With basis on the proposed model, we create the IVQ-learning algorithm that is exhaustive tested in repetitive games with two, three and four agents and in stochastic games that need cooperation and in games that need collaboration. This algorithm shows to be a good option for obtaining solutions that guarantee convergence to the Nash optimum equilibrium in cooperative problems. Experiments performed clear shows that the proposed paradigm is theoretical and experimentally superior to the traditional approaches. Yet, with the creation of this new paradigm the set of reinforcement learning applications in MAS grows up. That is, besides the possibility of applying the algorithm in traditional learning problems in MAS, as for example coordination of tasks in multi-robot systems, it is possible to apply reinforcement learning in problems that are essentially collaborative

Uma implementação paralela híbrida para o problema do caixeiro viajante usando algoritmos genéticos, GRASP e aprendizagem por reforço

The metaheuristics techiniques are known to solve optimization problems classified as NP-complete and are successful in obtaining good quality solutions. They use non-deterministic approaches to generate solutions that are close to the optimal, without the guarantee of finding the global optimum. Motivated by the difficulties in the resolution of these problems, this work proposes the development of parallel hybrid methods using the reinforcement learning, the metaheuristics GRASP and Genetic Algorithms. With the use of these techniques, we aim to contribute to improved efficiency in obtaining efficient solutions. In this case, instead of using the Q-learning algorithm by reinforcement learning, just as a technique for generating the initial solutions of metaheuristics, we use it in a cooperative and competitive approach with the Genetic Algorithm and GRASP, in an parallel implementation. In this context, was possible to verify that the implementations in this study showed satisfactory results, in both strategies, that is, in cooperation and competition between them and the cooperation and competition between groups. In some instances were found the global optimum, in others theses implementations reach close to it. In this sense was an analyze of the performance for this proposed approach was done and it shows a good performance on the requeriments that prove the efficiency and speedup (gain in speed with the parallel processing) of the implementations performed

Uma contribuição à solução do problema dos k-servos usando aprendizagem por reforço

Neste trabalho é proposto um novo algoritmo online para o resolver o Problema dos k-Servos (PKS). O desempenho desta solução é comparado com o de outros algoritmos existentes na literatura, a saber, os algoritmos Harmonic e Work Function, que mostraram ser competitivos, tornando-os parâmetros de comparação significativos. Um algoritmo que apresente desempenho eficiente em relação aos mesmos tende a ser competitivo também, devendo, obviamente, se provar o referido fato. Tal prova, entretanto, foge aos objetivos do presente trabalho. O algoritmo apresentado para a solução do PKS é baseado em técnicas de aprendizagem por reforço. Para tanto, o problema foi modelado como um processo de decisão em múltiplas etapas, ao qual é aplicado o algoritmo Q-Learning, um dos métodos de solução mais populares para o estabelecimento de políticas ótimas neste tipo de problema de decisão. Entretanto, deve-se observar que a dimensão da estrutura de armazenamento utilizada pela aprendizagem por reforço para se obter a política ótima cresce em função do número de estados e de ações, que por sua vez é proporcional ao número n de nós e k de servos. Ao se analisar esse crescimento (matematicamente, ) percebe-se que o mesmo ocorre de maneira exponencial, limitando a aplicação do método a problemas de menor porte, onde o número de nós e de servos é reduzido. Este problema, denominado maldição da dimensionalidade, foi introduzido por Belmann e implica na impossibilidade de execução de um algoritmo para certas instâncias de um problema pelo esgotamento de recursos computacionais para obtenção de sua saída. De modo a evitar que a solução proposta, baseada exclusivamente na aprendizagem por reforço, seja restrita a aplicações de menor porte, propõe-se uma solução alternativa para problemas mais realistas, que envolvam um número maior de nós e de servos. Esta solução alternativa é hierarquizada e utiliza dois métodos de solução do PKS: a aprendizagem por reforço, aplicada a um número reduzido de nós obtidos a partir de um processo de agregação, e um método guloso, aplicado aos subconjuntos de nós resultantes do processo de agregação, onde o critério de escolha do agendamento dos servos é baseado na menor distância ao local de demanda

Classificação de padrões através de um comitê de máquinas aprimorado por aprendizagem por reforço

Reinforcement learning is a machine learning technique that, although finding a large number of applications, maybe is yet to reach its full potential. One of the inadequately tested possibilities is the use of reinforcement learning in combination with other methods for the solution of pattern classification problems. It is well documented in the literature the problems that support vector machine ensembles face in terms of generalization capacity. Algorithms such as Adaboost do not deal appropriately with the imbalances that arise in those situations. Several alternatives have been proposed, with varying degrees of success. This dissertation presents a new approach to building committees of support vector machines. The presented algorithm combines Adaboost algorithm with a layer of reinforcement learning to adjust committee parameters in order to avoid that imbalances on the committee components affect the generalization performance of the final hypothesis. Comparisons were made with ensembles using and not using the reinforcement learning layer, testing benchmark data sets widely known in area of pattern classification

Roteamento em Redes de Sensores Sem Fios Com Base Em Aprendizagem Por Reforço

The use of wireless sensor and actuator networks in industry has been increasing past few years, bringing multiple benefits compared to wired systems, like network flexibility and manageability. Such networks consists of a possibly large number of small and autonomous sensor and actuator devices with wireless communication capabilities. The data collected by sensors are sent directly or through intermediary nodes along the network to a base station called sink node. The data routing in this environment is an essential matter since it is strictly bounded to the energy efficiency, thus the network lifetime. This work investigates the application of a routing technique based on Reinforcement Learning s Q-Learning algorithm to a wireless sensor network by using an NS-2 simulated environment. Several metrics like energy consumption, data packet delivery rates and delays are used to validate de proposal comparing it with another solutions existing in the literature

Fibras de licuri: um reforço vegetal alternativo de compósitos poliméricos

This research is based, at first, on the seeking of alternatives naturals reinforced in place of polymeric composites, also named reinforced plastics. Therein, this work starts with a whole licuri fiber micro structural characterization, as alternative proposal to polymeric composites. Licuri fiber is abundant on the Bahia state flora, native from a palm tree called Syagrus Coronata (Martius) Beccari. After, it was done only licuri fiber laminar composite developing studies, in order to know its behavior when impregnated with thermofix resin. The composite was developed in laminar structure shape (plate with a single layer of reinforcement) and produced industrially. The layer of reinforcement is a fabric-fiber unidirectional of licuri up in a manual loom. Their structure was made of polyester resin ortofitálica (unsaturated) only reinforced with licuri fibers. Fiber characterization studies were based on physical chemistry properties and their constitution. It was made by tension, scanning electron microscopy (SEM), x-ray diffraction (RDX) and thermal analyses (TG and DTA) tests, besides fiber chemistry analyses. Relating their mechanical properties of strength and hardness testing, they were determined through unit axial tension test and flexion in three points. A study in order to know fiber/matrix interface effects, in the final composites results, was required. To better understand the mechanical behavior of the composite, macroscopic and microscopic optical analysis of the fracture was performed

Estudo da fibra de coco como reforço em tijolo de solocimento

To take care of to the demand of the new constructions in the low income communities and to develop the production of a strengthened alternative brick with staple fibers of coconut, capable to contribute mainly with the recycling of the green and mature coconut in the urban and agricultural lexes, this research was developed, to confection bricks of soil-cement with coconut fiber. Ecologically correct material and of low cost, since the greenhouse use of or oven for burning will be manufactured without. The study it presents a set of tables and graphs that prove good indices found in the values of the density, water absorption, axial compressive strength and isolation term acoustics, with evidential results that make possible the production in industrial character with press mechanics or the place of the workmanship with manual form. The preparation of coconut staple fibers was made of natural form without use of chemical products not to deprive of characteristics the properties mechanical physicist-chemistries and of the same ones. The sixty bricks produced in simple and manual press had been carried through in four lots of fifteen units. The mixture of aggregates was made in four different traces composites for: ground erinaceous, cement, fiber of dry coconut and water; the bricks had been compact in the press and cured in natural way under an area covered during the minimum time of seven days

Desenvolvimento de têxteis técnicos para reforço de compósitos poliméricos

Materials denominated technical textiles can be defined as structures designed and developed with function to fulfill specific functional requirements of various industrial sectors as are the cases of the automotive and aerospace industries. In this aspect the technical textiles are distinguished from conventional textile materials, in which the aesthetic and of comfort needs are of primordial importance. Based on these considerations, the subject of this dissertation was established having as its main focus the study of development of textile structures from aramid and glass fibers and acting in order to develop the manufacture of composite materials that combine properties of two different structures, manufactured in an identical operation, where each structure contributes to improving the properties of the resulting composite material. Therefore were created in laboratory scale, textile structures with low weight and different composition: aramid (100%), glass (100%) and aramid /glass (65/35%), in order to use them as a reinforcing element in composite materials with polyester matrix. These composites were tested in tension and its fracture surface, evaluated by MEV. Based on the analysis of mechanical properties of the developed composites, the efficiency of the structures prepared as reinforcing element were testified by reason of that the resistance values of the composites are far superior to the polyester matrix. It was also observed that hybridization in tissue structure was efficient, since the best results obtained were for hybrid composites, where strength to the rupture was similar to the steel 1020, reaching values on the order of 340 MPa

Estratégias de busca reativa utilizando aprendizagem por reforço e algoritmos de busca local

Técnicas de otimização conhecidas como as metaheurísticas tem conseguido resolversatisfatoriamente problemas conhecidos, mas desenvolvimento das metaheurísticas écaracterizado por escolha de parâmetros para sua execução, na qual a opção apropriadadestes parâmetros (valores). Onde o ajuste de parâmetro é essencial testa-se os parâmetrosaté que resultados viáveis sejam obtidos, normalmente feita pelo desenvolvedor que estaimplementando a metaheuristica. A qualidade dos resultados de uma instância1 de testenão será transferida para outras instâncias a serem testadas e seu feedback pode requererum processo lento de “tentativa e erro” onde o algoritmo têm que ser ajustado para umaaplicação especifica. Diante deste contexto das metaheurísticas surgiu a Busca Reativaque defende a integração entre o aprendizado de máquina dentro de buscas heurísticaspara solucionar problemas de otimização complexos. A partir da integração que a BuscaReativa propõe entre o aprendizado de máquina e as metaheurísticas, surgiu a ideia dese colocar a Aprendizagem por Reforço mais especificamente o algoritmo Q-learning deforma reativa, para selecionar qual busca local é a mais indicada em determinado instanteda busca, para suceder uma outra busca local que não pode mais melhorar a soluçãocorrente na metaheurística VNS. Assim, neste trabalho propomos uma implementação reativa,utilizando aprendizado por reforço para o auto-tuning do algoritmo implementado,aplicado ao problema do caixeiro viajante simétrico e ao problema escalonamento sondaspara manutenção de poços.

Técnicas de conformação de feixe em arranjo de antenas utilizando aprendizagem por reforço

Beamforming is a technique widely used in various fields. With the aid of an antenna array, the beamforming aims to minimize the contribution of unknown interferents directions, while capturing the desired signal in a given direction. In this thesis are proposed beamforming techniques using Reinforcement Learning (RL) through the Q-Learning algorithm in antennas array. One proposal is to use RL to find the optimal policy selection between the beamforming (BF) and power control (PC) in order to better leverage the individual characteristics of each of them for a certain amount of Signal to Interference plus noise Ration (SINR). Another proposal is to use RL to determine the optimal policy between blind beamforming algorithm of CMA (Constant Modulus Algorithm) and DD (Decision Direct) in multipath environments. Results from simulations showed that the RL technique could be effective in achieving na optimal of switching between different techniques.

Obtenção e caracterização de um compósito polimérico de matriz poliéster e reforço/carga de tecido plano de algodão

He was obtained and studied the feasibility of using TPA (Tissue Cotton Plan) screen type, for bagging, with a weight of 207.9 g / m2 in a composite of orthophthalic crystal polyester resin matrix. The process for obtaining the composite was tested against the maximum number of layers that could be used without compromising the processability and manufacturing of CPs in compression mold. Five configurations / formulations were selected and tested at 1, 4, 8, 10 and 12 layers of cotton tissue - TPA. TPA was not subjected to chemical treatment, only by passing a mechanical washing process. The composite in its various configurations / formulations was characterized to determine its physical properties. The properties of the composite were higher viability resistance to bending, approaching the matrix and impact resistance, superiority in relation to the polyester resin. Another property that has shown good result compared to other composite has water absorption. Analyzing all the properties set the settings / formulations with higher viability were TA8 and TA10, by combining good processability and higher mechanical strength, with lower loss compared to polyester resin matrix. The composite showed lower mechanical behavior of the resin matrix for all the formulations studied except the impact resistance. The SEM showed a good adhesion between the layers of TPA and polyester resin matrix, without the presence of micro voids in the matrix confirming the efficient manufacturing process of the samples for characterization. The composite proposed proved to be viable for the fabrication of structures with low requests from mechanical stresses, and as demonstrated for the manufacture of solar and wind prototypes, and packaging, shelving, decorative items, crafts and shelves, with good visual appearance.

Obtenção e caracterização de um compósito polimérico de matriz poliéster e reforço/carga de tecido plano de algodão

He was obtained and studied the feasibility of using TPA (Tissue Cotton Plan) screen type, for bagging, with a weight of 207.9 g / m2 in a composite of orthophthalic crystal polyester resin matrix. The process for obtaining the composite was tested against the maximum number of layers that could be used without compromising the processability and manufacturing of CPs in compression mold. Five configurations / formulations were selected and tested at 1, 4, 8, 10 and 12 layers of cotton tissue - TPA. TPA was not subjected to chemical treatment, only by passing a mechanical washing process. The composite in its various configurations / formulations was characterized to determine its physical properties. The properties of the composite were higher viability resistance to bending, approaching the matrix and impact resistance, superiority in relation to the polyester resin. Another property that has shown good result compared to other composite has water absorption. Analyzing all the properties set the settings / formulations with higher viability were TA8 and TA10, by combining good processability and higher mechanical strength, with lower loss compared to polyester resin matrix. The composite showed lower mechanical behavior of the resin matrix for all the formulations studied except the impact resistance. The SEM showed a good adhesion between the layers of TPA and polyester resin matrix, without the presence of micro voids in the matrix confirming the efficient manufacturing process of the samples for characterization. The composite proposed proved to be viable for the fabrication of structures with low requests from mechanical stresses, and as demonstrated for the manufacture of solar and wind prototypes, and packaging, shelving, decorative items, crafts and shelves, with good visual appearance.

Caracterização de atapulgita visando aplicação para reforço de materiais poloméricos

The clay mineral attapulgite is a group of hormitas, which has its structures formed by microchannels, which give superior technological properties classified the industrial clays, clays of this group has a very versatile range of applications, ranging from the drilling fluid for wells oil has applications in the pharmaceutical industry. Such properties can be improved by activating acid and / or thermal activation. The attapulgite when activated can improve by up to 5-8 times some of its properties. The clay was characterized by X-ray diffraction, fluorescence, thermogravimetric analysis, differential thermal analysis, scanning electron microscopy and transmission electron microscopy before and after chemical activation. It can be seen through the results the efficiency of chemical treatment, which modified the clay without damaging its structure, as well as production of polymer matrix composites with particles dispersed atapugita