963 resultados para nonlinear electrical behaviour


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O comportamento cíclico das estruturas de betão armado é fortemente condicionado pelo mecanismo de aderência entre o betão e o aço. O escorregamento relativo entre os dois materiais, resultante da degradação progressiva da aderência em elementos solicitados por ações cíclicas, é uma causa frequente de danos graves e até do colapso de estruturas devido à ocorrência de sismos. Entre as estruturas existentes de betão armado que foram dimensionadas e construídas antes da entrada em vigor dos regulamentos sísmicos atuais, muitas foram construídas com armadura lisa, e portanto, possuem fracas propriedades de aderência. A informação disponível na literatura sobre o comportamento cíclico de elementos estruturais de betão armado com armadura lisa é reduzida e a influência das propriedades da aderência associadas a este tipo de armadura no comportamento cíclico das estruturas existentes não se encontra ainda devidamente estudada. O objectivo principal desta tese foi estudar a influência do escorregamento na resposta cíclica de elementos estruturais de betão armado com armadura lisa. Foram realizados ensaios cíclicos em elementos do tipo nó viga-pilar, construídos à escala real, representativos de ligações interiores em edifícios existentes sem pormenorização específica para resistir às ações sísmicas. Para comparação, foi realizado o ensaio de um nó construído com armadura nervurada. Foi ainda realizado o ensaio cíclico de uma viga de betão armado recolhida de uma estrutura antiga. Foram elaborados modelos numéricos não-lineares para simular a resposta dos elementos ensaiados, concentrando especial atenção no mecanismo do escorregamento. Os resultados obtidos no âmbito desta tese contribuem para o avanço do conhecimento sobre o comportamento cíclico de elementos estruturais de betão armado com armadura lisa. As análises numéricas realizadas comprovam a necessidade de incluir os efeitos do escorregamento na modelação numérica deste tipo de estruturas de forma a representar com rigor a sua resposta às ações cíclicas.

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A dissertação de doutoramento apresentada insere-se na área de electrónica não-linear de rádio-frequência (RF), UHF e microondas, tendo como principal campo de acção o estudo da distorção nãolinear em arquitecturas de recepção rádio, nomeadamente receptores de conversão directa como Power Meters, RFID (Radio Frequency IDentification) ou SDR (Software Define Radio) front-ends. Partindo de um estudo exaustivo das actuais arquitecturas de recepção de radiofrequência e revendo todos os conceitos teóricos relacionados com o desempenho não-linear dos sistemas/componentes electrónicos, foram desenvolvidos algoritmos matemáticos de modulação dos comportamentos não-lineares destas arquitecturas, simulados e testados em laboratório e propostas novas arquitecturas para a minimização ou cancelamento do impacto negativo de grandes interferidores em frequências vizinhas ao do sistema pretendido.

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Tese dout., Engenharia Electrónica e Computação, Universidade do Algarve, 2005

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The aim of this chapter is to introduce background concepts in nonlinear systems identification and control with artificial neural networks. As this chapter is just an overview, with a limited page space, only the basic ideas will be explained here. The reader is encouraged, for a more detailed explanation of a specific topic of interest, to consult the references given throughout the text. Additionally, as general books in the field of neural networks, the books by Haykin [1] and Principe et al. [2] are suggested. Regarding nonlinear systems identification, covering both classical and neural and neuro-fuzzy methodologies, Reference 3 is recommended. References 4 and 5 should be used in the context of B-spline networks.

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The objective of this thesis is to study the properties of resistive switching effect based on bistable resistive memory which is fabricated in the form of Al2O3/polymer diodes and to contribute to the elucidation of resistive switching mechanisms. Resistive memories were characterized using a variety of electrical techniques, including current-voltage measurements, small-signal impedance, and electrical noise based techniques. All the measurements were carried out over a large temperature range. Fast voltage ramps were used to elucidate the dynamic response of the memory to rapid varying electric fields. The temperature dependence of the current provided insight into the role of trapped charges in resistive switching. The analysis of fast current fluctuations using electric noise techniques contributed to the elucidation of the kinetics involved in filament formation/rupture, the filament size and correspondent current capabilities. The results reported in this thesis provide insight into a number of issues namely: (i) The fundamental limitations on the speed of operation of a bi-layer resistive memory are the time and voltage dependences of the switch-on mechanism. (ii) The results explain the wide spread in switching times reported in the literature and the apparently anomalous behaviour of the high conductance state namely the disappearance of the negative differential resistance region at high voltage scan rates which is commonly attributed to a “dead time” phenomenon which had remained elusive since it was first reported in the ‘60s. (iii) Assuming that the current is filamentary, Comsol simulations were performed and used to explain the observed dynamic properties of the current-voltage characteristics. Furthermore, the simulations suggest that filaments can interact with each other. (iv) The current-voltage characteristics have been studied as a function of temperature. The findings indicate that creation and annihilation of filaments is controlled by filling and neutralizing traps localized at the oxide/polymer interface. (v) Resistive switching was also studied in small-molecule OLEDs. It was shown that the degradation that leads to a loss of light output during operation is caused by the presence of a resistive switching layer. A diagnostic tool that predicts premature failure of OLEDs was devised and proposed. Resistive switching is a property of oxides. These layers can grow in a number of devices including, organic light emitting diodes (OLEDs), spin-valve transistors and photovoltaic devices fabricated in different types of material. Under strong electric fields the oxides can undergo dielectric breakdown and become resistive switching layers. Resistive switching strongly modifies the charge injection causing a number of deleterious effects and eventually device failure. In this respect the findings in this thesis are relevant to understand reliability issues in devices across a very broad field.

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Collective behaviours can be observed in both natural and man-made systems composed of a large number of elemental subsystems. Typically, each elemental subsystem has its own dynamics but, whenever interaction between individuals occurs, the individual behaviours tend to be relaxed, and collective behaviours emerge. In this paper, the collective behaviour of a large-scale system composed of several coupled elemental particles is analysed. The dynamics of the particles are governed by the same type of equations but having different parameter values and initial conditions. Coupling between particles is based on statistical feedback, which means that each particle is affected by the average behaviour of its neighbours. It is shown that the global system may unveil several types of collective behaviours, corresponding to partial synchronisation, characterised by the existence of several clusters of synchronised subsystems, and global synchronisation between particles, where all the elemental particles synchronise completely.

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Fractional calculus (FC) is currently being applied in many areas of science and technology. In fact, this mathematical concept helps the researches to have a deeper insight about several phenomena that integer order models overlook. Genetic algorithms (GA) are an important tool to solve optimization problems that occur in engineering. This methodology applies the concepts that describe biological evolution to obtain optimal solution in many different applications. In this line of thought, in this work we use the FC and the GA concepts to implement the electrical fractional order potential. The performance of the GA scheme, and the convergence of the resulting approximation, are analyzed. The results are analyzed for different number of charges and several fractional orders.

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The sugar beet cyst nematode, Heterodera schachtii, is a major agricultural pest. The disruption of the mating behaviour of this plant parasite in the field may provide a means of biological control, and a subsequent increase in crop yield. The H. schachtii female sex pheromone, which attracts homospecific males, was collected in an aqueous medium and isolated using high performance liquid chromatography. Characterization of the male-attractive material revealed that it was heat stable and water soluble. The aqueous medium conditioned by female H. schachtii was found to be biologically active and stimulated male behaviour in a concentration dependent manner. The activity of the crude pheromone was specific to males of H. schachtii and did not attract second stage juveniles. Results indicated that vanillic acid, a putative nematode pheromone, is not an active component of the H. schachtii sex pheromone. Male H. schachtii exhibited stylet thrusting, a poorly understood behaviour of the male, upon exposure to the female sex pheromone. This behaviour appeared to be associated with mate-finding and was used as a novel indicator of biological activity in bioassays. Serotonin, thought to be involved in the neural control of copulatory behaviour in nematodes, stimulated stylet thrusting. However, the relationship between stylet thrusting induced by the sex pheromone and stylet thrusting induced by serotonin is not clear. Extracellular electrical activity was recorded fi-om the anterior region of H. schachtii males during stylet thrusting, and appeared to be associated with this behaviour. The isolation of the female sex pheromone of H. schachtii may, ultimately, lead to the structural identification and synthesis of the active substance for use in a novel biological control strategy.

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The present work is an attempt to understand the characteristics of high energy ball milling on the structural, electrical and magnetic properties of some normal spinets in the ultra fine regime, Magnetism and magnetic materials have been a fascinating subject for the mankind ever since the discovery of lodestone. Since then, man has been applying this principle of magnetism to build devices for various applications. Magnetism can be classified broadly into five categories. They are diamagnetic, paramagnetic, ferromagnetic antiferromagnetic and ferrimagnetic. Of these, ferro and ferri magnetic materials assume great commercial importance due to their unique properties like appropriate magnetic characteristics, high resistivity and low eddy current losses. The emergence of nanoscience and nanotechnology during the last decade had its impact in the field of magnetism and magnetic materials too. Now, it is common knowledge that materials synthesized in the nanoregime exhibit novel and superlative properties with respect to their coarser sized counterparts in the micron regime. These studies reveal that dielectric properties can be varied appreciably by high-energy ball milling in nanosized zinc ferrites produced by coprecipitation method. A semi conducting behaviour was observed in these materials with the Oxygen vacancies acting as the main charge carrier for conduction, which was produced at the time of coprecipitation and milling. Thus through this study, it was possible to successfully investigate the finite size effects on the structural, electrical and magnetic properties of normal spinels in the ultra fine regime

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The spectral and nonlinear optical characteristics of nano ZnO and its composites are investigated. The fluorescence behaviour of nano colloids of ZnO has been studied as a function of the excitation wavelength and there is a red shift in emission peak with excitation wavelength. Apart from the observation of the reported ultra violet and green emissions, our results reveal that additional blue emissions at 420 nm and 490 nm are developed with increasing particle size. Systematic studies on nano ZnO have indicated the presence of luminescence due to excitonic emissions when excited with 255 nm as well as significant contribution from surface defect states when excited with 325 nm. In the weak confinement regime, the third-order optical susceptibility χ(3) increases with increasing particle size (R) and annealing temperature (T) and a R2 and T2.5 dependence of χ(3) is obtained for nano ZnO. ZnO nanocolloids exhibit induced absorption whereas the self assembled films of ZnO exhibit saturable absorption due to saturation of linear absorption of ZnO defect states and electronic effects. ZnO nanocomposites exhibit negative nonlinear index of refraction which can be attributed to two photon absorption followed by weak free carrier absorption. The increase of the third-order nonlinearity in the composites can be attributed to the enhancement of exciton oscillator strength. The nonlinear response of ZnO nanocomposites is wavelength dependent and switching from induced absorption to saturable absorption has been observed at resonant wavelengths. Such a change-over is related to the interplay of plasmon/exciton band bleach and optical limiting mechanisms. This study is important in identifying the spectral range and the composition over which the nonlinear material acts as an optical limiter. ZnO based nanocomposites are potential materials for enhanced and tunable light emission and for the development of nonlinear optical devices with a relatively small optical limiting threshold.

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The brain with its highly complex structure made up of simple units,imterconnected information pathways and specialized functions has always been an object of mystery and sceintific fascination for physiologists,neuroscientists and lately to mathematicians and physicists. The stream of biophysicists are engaged in building the bridge between the biological and physical sciences guided by a conviction that natural scenarios that appear extraordinarily complex may be tackled by application of principles from the realm of physical sciences. In a similar vein, this report aims to describe how nerve cells execute transmission of signals ,how these are put together and how out of this integration higher functions emerge and get reflected in the electrical signals that are produced in the brain.Viewing the E E G Signal through the looking glass of nonlinear theory, the dynamics of the underlying complex system-the brain ,is inferred and significant implications of the findings are explored.

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Nonlinear optical processes in organic compounds have attracted considerable interest in the field of science and technology because of their compelling technological promises in fields of optical communication,computing,switching and signal processing.As a result of the synthesis of novel organic compounds with varying degree of nonlinear optical strength, many practical devices based on these are getting realised giving new theoretical insights into the nonolinear optical behaviour of materials.Organic compounds like phthalocyanines and porphyrins have evoked great deal of interest in the field of photonic technology.The present thesis describes the results obtained from the investigations carried out on the nonlinear optical properties of certain organo-metallic compounds using Z-Scan and DFWM techniques.

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Dual-beam transient thermal lens studies were carried out in aqueous solutions of rhodamine 6G using 532 nm pulses from a frequency-doubled Nd:YAG laser. The analysis of the observed data showed that the thermal lens method can effectively be utilized to study the nonlinear absorption and aggregation which are taking place in a dye medium.

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Identification and Control of Non‐linear dynamical systems are challenging problems to the control engineers.The topic is equally relevant in communication,weather prediction ,bio medical systems and even in social systems,where nonlinearity is an integral part of the system behavior.Most of the real world systems are nonlinear in nature and wide applications are there for nonlinear system identification/modeling.The basic approach in analyzing the nonlinear systems is to build a model from known behavior manifest in the form of system output.The problem of modeling boils down to computing a suitably parameterized model,representing the process.The parameters of the model are adjusted to optimize a performanace function,based on error between the given process output and identified process/model output.While the linear system identification is well established with many classical approaches,most of those methods cannot be directly applied for nonlinear system identification.The problem becomes more complex if the system is completely unknown but only the output time series is available.Blind recognition problem is the direct consequence of such a situation.The thesis concentrates on such problems.Capability of Artificial Neural Networks to approximate many nonlinear input-output maps makes it predominantly suitable for building a function for the identification of nonlinear systems,where only the time series is available.The literature is rich with a variety of algorithms to train the Neural Network model.A comprehensive study of the computation of the model parameters,using the different algorithms and the comparison among them to choose the best technique is still a demanding requirement from practical system designers,which is not available in a concise form in the literature.The thesis is thus an attempt to develop and evaluate some of the well known algorithms and propose some new techniques,in the context of Blind recognition of nonlinear systems.It also attempts to establish the relative merits and demerits of the different approaches.comprehensiveness is achieved in utilizing the benefits of well known evaluation techniques from statistics. The study concludes by providing the results of implementation of the currently available and modified versions and newly introduced techniques for nonlinear blind system modeling followed by a comparison of their performance.It is expected that,such comprehensive study and the comparison process can be of great relevance in many fields including chemical,electrical,biological,financial and weather data analysis.Further the results reported would be of immense help for practical system designers and analysts in selecting the most appropriate method based on the goodness of the model for the particular context.