With their various structures and operations, the operational magnetic flux densities inside those energy conversion mechanisms are non-uniformly distributed, hence large deviations are exhibited among the actual and the estimated values of iron losses in those electric machines. The available datasheets provided by the steel manufacturers derived from standard measurement systems can only cover some typical information, accuracies of applying these data for related machine performance evaluations at those operational conditions are always uncertain. To establish more convincing datasheet for the calculation of iron loss in machines, standing between the steel manufacturers and the electric machine designers, the application of improved magnetic circuits analysis and the numerical Epstein Frame is proposed. The static transformers and the rotary synchronous switched-reluctance motors will be thoroughly calculated for illustrations. Based on the aforementioned datasheets and the iron losses evaluation procedure, when designing the similar machines, the iron losses could be appropriately estimated, and more detailed information could be supplied.

A system with hysteresis is one that exhibits path dependent but rate independent memory. Hysteresis can be observed physically through the magnetization of a ferromagnetic material. In order to mathematically describe systems with hysteresis, we use the Preisach model. A discussion of the Preisach model is given as well as a method for computing the hysteretic transformation of an input variable. The focus of this paper is hysteresis in economics, namely, unemployment. We consider essential time series techniques for analyzing time series data, i.e. unit root testing for stationarity. However, we point out problems in modeling hysteresis with these techniques and argue that unit root tests cannot capture the selective memory of a system with hysteresis. For that, hysteresis in economic time series data is modeled using the Preisach model. We test the explanatory power of the previous unemployment rate on the current unemployment rate using both a hysteretic and non-hysteretic model. We find that the non-hysteretic model is better at explaining current unemployment rates, which suggests hysteresis is not present in the United States unemployment rate. / Master of Science

The aim of this work is to present a model for the superelastic response of Shape Memory Alloys (SMAs) by developing a Preisach Model with thermodynamics basis. The special features of SMA superelastic response is useful in a variety of applications (eg. seismic dampers and arterial stents). For example, under seismic loads the SMA dampers undergo rapid loading{unloading cycles, thus going through a number of internal hysteresis loops, which are responsible for dissipating the vibration energy. Therefore the design for such applications requires the ability to predict the response, particularly internal loops. It is thus intended to develop a model for the superelastic response which is simple, computationally fast and can predict internal loops. The key idea here is to separate the elastic response of SMAs from the dissipative response and apply a Preisach Model to the dissipative response as opposed to the popular notion of applying the Preisach Model to the stress{strain response directly. Such a separation allows for the better prediction of internal hysteresis, avoids issues due to at/negative slopes in the stress{strain plot, and shows good match with experimental data, even when minimal input is given to the model. The model is developed from a Gibbs Potential, which allows us to compute a driving force for the underlying phase transformation in the superelastic response. The hysteresis between the driving force for transformation and the extent of transformation (volume fraction of martensite) is then used with a Preisach model. The Preisach model parameters are identi ed using a least squares approach. ASTM Standards for the testing of NiTi wires (F2516-07^sigma 2), are used for the identi cation of the parameters in the Gibbs Potential. The simulations are run using MATLAB R . Results under di erent input conditions are discussed. It is shown that the predicted response shows good agreement with the experimental data. A couple of attempts at extending the model to bending and more complex response of SMAs is also discussed.

The objective of this thesis is to provide a reliable and effective iron loss estimation scheme for the electromagnetic steel products in the design and on-line operation stages. To investigate the possible performance of electromagnetic steel products, proper iron loss information of the products that are constructed by different steels is one of the key concerns. Along with the various power electronic device applications and iron core structures, the magnetic fluxes flowing through the machine cores will be non-uniform and include harmonic terms. Unless excessive computation efforts in expensive software tools are performed, large discrepancies will be exhibited the estimated and actual values of machine iron losses. To overcome these drawbacks, a rational machine iron loss estimation scheme is proposed. By adopting the iterative magnetic equivalent circuits and the nonlinear magnetic characteristics of the electromagnetic steels, the preliminary operational flux information in the machine is first obtained, and then a numerical Epstein Frame test circuit with magnetizing inductance modeled by Preisach model is applied. With appropriate circuit input voltages devised from preliminary information, the detailed hysteresis inner-loop characteristics resulting from product structures and magnetization harmonics can be properly modeled. Based on the circuit results, the iron losses of electric machines with any operation can be rationally evaluated, and a valuable reference in machine designing can be provided.

Shape Memory Alloy actuators can be used for morphing, or shape change, by controlling their temperature, which is effectively done by applying a voltage difference across their length. Control of these actuators requires determination of the relationship between voltage and strain so that an input-output map can be developed. In this research, a computer simulation uses a hyperbolic tangent curve to simulate the hysteresis behavior of a virtual Shape Memory Alloy wire in temperature-strain space, and uses a Reinforcement Learning algorithm called Sarsa to learn a near-optimal control policy and map the hysteretic region. The algorithm developed in simulation is then applied to an experimental apparatus where a Shape Memory Alloy wire is characterized in temperature-strain space. This algorithm is then modified so that the learning is done in voltage-strain space. This allows for the learning of a control policy that can provide a direct input-output mapping of voltage to position for a real wire. This research was successful in achieving its objectives. In the simulation phase, the Reinforcement Learning algorithm proved to be capable of controlling a virtual Shape Memory Alloy wire by determining an accurate input-output map of temperature to strain. The virtual model used was also shown to be accurate for characterizing Shape Memory Alloy hysteresis by validating it through comparison to the commonly used modified Preisach model. The validated algorithm was successfully applied to an experimental apparatus, in which both major and minor hysteresis loops were learned in temperature-strain space. Finally, the modified algorithm was able to learn the control policy in voltage-strain space with the capability of achieving all learned goal states within a tolerance of +-0.5% strain, or +-0.65mm. This policy provides the capability of achieving any learned goal when starting from any initial strain state. This research has validated that Reinforcement Learning is capable of determining a control policy for Shape Memory Alloy crystal phase transformations, and will open the door for research into the development of length controllable Shape Memory Alloy actuators.

Orientador: Kleber Roberto Pirota / Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Física Gleb Wataghin / Made available in DSpace on 2018-08-23T16:30:39Z (GMT). No. of bitstreams: 1 Almeida_PriscilaToderode_M.pdf: 4163268 bytes, checksum: 28aa8c398a21212739c3588c9ce78593 (MD5) Previous issue date: 2013 / Resumo: O principal objetivo desse trabalho consiste em uma nova abordagem para o tunelamento da magnetização do magneto molecular Mn12, embasado em uma ampliação do modelo de Preisach. Introduziremos novos operadores que levam em conta a possibilidade de efeitos quânticos. Implementamos esse novo modelo num programa de simulação que é capaz de simular curvas de histerese e curvas de relaxação magnética sem recorrer a resolução de hamiltonianas de spin. Além disso, este programa utiliza simulação estocástica, apresentando os resultados em poucos minutos. Os resultados obtidos concordam com os experimentos realizados de histerese e relaxação magnética. Apesar de ser um modelo de simulação simples, reproduz adequadamente a fenomenologia, pois introduz os dois ingredientes essenciais de um sistema com inversão da magnetização por efeito túnel termicamente ativado: a ativação térmica, descrita pela ocupação de níveis segundo a distribuição de Boltzmann e a possibilidade do efeito túnel descrita pelo modelo de Landau¿Zenner. A consistência física do modelo é estudada através da variação de parâmetros do modelo de forma sistemática / Abstract: The main objective of this work consists of a new approach concerning the tunneling of the magnetization of the molecular magnet Mn12, based on an extension of the Preisach model. We will introduce new operators that take into account the possibility of quantum effects. Thus, we have implemented this new model in a simulation software that is capable of simulating hysteresis curves and magnetic relaxation curves without utilizing resolution of spin Hamiltonians. Also, this program uses stochastic simulation, presenting the results in only a few minutes. The results obtained agree with the hysteresis and relaxation experiments. Despite being a simple simulation model, it adequately reproduces the phenomenology, because it introduces two key ingredients of a system with inversion of magnetization by thermally activated tunnel effect: the thermal activation, described by the occupation of levels according to the Boltzmann distribution and the possibility of tunnel effect described by the Landau-Zenner model. The physical consistency of the model is studied by systematically varying the model¿s parameters / Mestrado / Física / Mestra em Física

Estudamos propriedades magnéticas de ligas nano cristalinas de Sm-F e-Co. As ligas foram preparadas por mecano-síntese e posterior tratamento térmico. Como resultado, obtivemos ímãs nanocristalinos de Sm18 (Fe,Co)82 , com Sm(Fe,Co)7 como fase principal. As ligas apresentaram excelentes propriedades magnéticas: remanências relativas Mn/ Ms ~ 0.6 e coercividades na faixa 5-20 kOe, dependendo do teor de Fe nos materiais. Interações magnéticas nas ligas foram estudadas com base nos gráficos ele Henkel. Interpretamos, nestes gráficos, de maneira consistente a influência elas interações e dos estados desmagnetizados. / We studied the magnetic properties of nanocrystalline Sm-Fe-Co alloys. These alloys were prepared by mechanical alloying and subsequent annealing. We obtained nanocrystalline rnagnets of composition Sm18 (Fe, Co )82 , for which the main hard magnetic phase is Sm(Fe, Co)82. The alloys showed excellent magnetic properties: relative remanence Mn/ Ms :2; 0.6 and coercive fields ranging from 5 to 20 k0e, depending upon the amount of Fe present. Henkel plots were used in order to study magnetic interactions in these alloys. The influence of the interactions and the demagnetized state on the Henkel plots was also studied.

Estudamos propriedades magnéticas de ligas nano cristalinas de Sm-F e-Co. As ligas foram preparadas por mecano-síntese e posterior tratamento térmico. Como resultado, obtivemos ímãs nanocristalinos de Sm18 (Fe,Co)82 , com Sm(Fe,Co)7 como fase principal. As ligas apresentaram excelentes propriedades magnéticas: remanências relativas Mn/ Ms ~ 0.6 e coercividades na faixa 5-20 kOe, dependendo do teor de Fe nos materiais. Interações magnéticas nas ligas foram estudadas com base nos gráficos ele Henkel. Interpretamos, nestes gráficos, de maneira consistente a influência elas interações e dos estados desmagnetizados. / We studied the magnetic properties of nanocrystalline Sm-Fe-Co alloys. These alloys were prepared by mechanical alloying and subsequent annealing. We obtained nanocrystalline rnagnets of composition Sm18 (Fe, Co )82 , for which the main hard magnetic phase is Sm(Fe, Co)82. The alloys showed excellent magnetic properties: relative remanence Mn/ Ms :2; 0.6 and coercive fields ranging from 5 to 20 k0e, depending upon the amount of Fe present. Henkel plots were used in order to study magnetic interactions in these alloys. The influence of the interactions and the demagnetized state on the Henkel plots was also studied.

The aim of this research is to calibrate conductive polymer nanocomposite materials for large strain sensing and develop a structural health monitoring algorithm for gossamer structures by using nanocomposites as strain sensors. Any health monitoring system works on the principle of sensing the response (strain, acceleration etc.) of the structure to an external excitation and analyzing the response to find out the location and the extent of the damage in the structure. A sensor network, a mathematical model of the structure, and a damage detection algorithm are necessary components of a structural health monitoring system. In normal operating conditions, a gossamer structure can experience normal strain as high as 50%. But presently available sensors can measure strain up to 10% only, as traditional strain sensor materials do not show low elastic modulus and high electrical conductivity simultaneously. Conductive polymer nanocomposite which can be stretched like rubber (up to 200%) and has high electrical conductivity (sheet resistance 100 Ohm/sq.) can be a possible large strain sensor material. But these materials show hysteresis and relaxation in the variation of electrical properties with mechanical strain. It makes the calibration of these materials difficult. We have carried out experiments on conductive polymer nanocomposite sensors to study the variation of electrical resistance with time dependent strain. Two mathematical models, based on the modified fractional calculus and the Preisach approaches, have been developed to model the variation of electrical resistance with strain in a conductive polymer. After that, a compensator based on a modified Preisach model has been developed. The compensator removes the effect of hysteresis and relaxation from the output (electrical resistance) obtained from the conductive polymer nanocomposite sensor. This helps in calibrating the material for its use in large strain sensing. Efficiency of both the mathematical models and the compensator has been shown by comparison of their results with the experimental data. A prestressed square membrane has been considered as an example structure for structural health monitoring. Finite element analysis using ABAQUS has been carried out to determine the response of the membrane to an uniform transverse dynamic pressure for different damage conditions. A neuro-fuzzy system has been designed to solve the inverse problem of detecting damages in the structure from the strain history sensed at different points of the structure by a sensor that may have a significant hysteresis. Damage feature index vector determined by wavelet analysis of the strain history at different points of the structure are taken by the neuro-fuzzy system as input. The neuro-fuzzy system detects the location and extent of the damage from the damage feature index vector by using some fuzzy rules. Rules associated with the fuzzy system are determined by a neural network training algorithm using a training dataset, containing a set of known input and output (damage feature index vectors, location and extent of damage for different damage conditions). This model is validated by using the sets of input-output other than those which were used to train the neural network. / Ph. D.

Dynamische Systeme mit Gedächtnis spielen in verschiedensten Anwendungen und Forschungsgebieten eine wesentliche Rolle. Gedächtnis bedeutet dabei, dass das zukünftige Systemverhalten nicht nur durch den aktuellen Zustand festgelegt wird, sondern im Allgemeinen auch durch vergangenen Zustände. Ein prominenter Vertreter für dieses Verhalten ist die Hysterese. Aufgrund der unterschiedlichen Mechanismen, welche zum Auftreten von Hysterese führen können, haben sich eine Vielzahl an Modellen etabliert, um diese zu beschreiben und zu modellieren. Zwei häufig verwendete Modelle sind dabei das Random Field Ising-Model und das Preisach-Model. Beide Modelle unterscheiden sich grundlegend in der Art, wie es zu Hysterese kommt. Während beim Random Field Ising-Model Hysterese aufgrund der Wechselwirkung benachbarter Spins auftritt, benutzt das Preisach-Model hingegen eine Vielzahl an elementaren bistabilen Relais, um komplexes hysteretisches Verhalten abzubilden. Trotz dieser Unterschiedlichkeit zeigen beide Modelle ähnliche Eigenschaften wie return point memory und wipe-out. Wir wollen in dieser Arbeit das dynamische Verhalten eines einfachen harmonischen Oszillators untersuchen, welcher mithilfe eines Feedback-Loops an ein hysteretisches Spinsystem gekoppelt wird. Es soll das Verhalten dieses Hybrid-Systems, das sowohl aus kontinuierlichen als auch aus diskreten Variablen besteht, für verschieden große Spinsysteme untersucht werden. Wir konzentrieren uns dabei auf drei vereinfachte Spinkonfigurationen. Dies ermöglicht uns, unter Verwendung der Preisach-Theorie, den Limes eines unendlich großen Spinsystems analytisch zu beschreiben. Wir zeigen, dass sich das Verhalten von dynamischen Systemen gekoppelt an ein endliches Spinsystem im Allgemeinen von Systemen gekoppelt an ein unendliches Spinsystem unterscheidet. Im Zuge dessen werden wir eine Methode vorstellen, um Lyapunov Spektren für dynamische Systeme mit preisachartiger Hysterese und glatter Dichte zu bestimmen. Wir zeigen weiterhin, dass bestimmte relevante Größen wie fraktale Dimension und Magnetisierung im Allgemeinen kein selbstmittelndes Verhalten aufweisen. Diese Resultate können erhebliche Auswirkungen auf die Vergleichbarkeit und Interpretation von Theorie und Experiment bei dynamischen Systemen mit Hysterese haben. / Dynamical systems with memory play a huge role in technical applications as well as in different research fields. In general memory means, the systems' behavior is not only determined by its last state, but also by the history of previous states. One prominent example of such behavior is the hysteresis. Caused by the many reasons for hysteretic behavior, multiple models for hysteresis have been developed over the past hundred years. Two commonly used models are the Random Field Ising Model and the Preisach model. Both models differ in the way, how the memory is build into the system. Whereas, the Random Field Ising Model shows hysteresis because of the interaction between nearby spins, the complex hysteresis of the Preisach model is build by a superposition of elementary bi-stable relays. Besides these differences, both models show similar hysteric behavior like return point memory and wipe-out. In this work, we want to investigate the dynamical behavior of a simple harmonic oscillator coupled to Ising spins in a closed loop way, showing hysteresis. The system consists of discrete and continuous degrees of freedom, and therefore it has a hybrid character. Concentrating on three simplified spin interactions, on one hand we investigate the dynamical properties of the system for a varying finite number of spins and on the other hand we use the Preisach model to calculate the limit of an infinite number of spins. We find, that dynamical systems coupled to a finite and infinite number of spins, respectively, in general behave differently. Thereby, we develop a method to determine the whole Lyapunov spectrum for systems with Preisach like hysteresis and a smooth density. Furthermore, we show that some dynamical properties like the fractal dimension and the magnetization in general do not show self-averaging. These findings could have a huge impact on the comparability and interpretation of theoretical and experimental results in the context of dynamical systems with hysteresis.