published_or_final_version / Literary and Cultural Studies / Master / Master of Arts

<p>Architected materials are a class of materials with novel properties that consist of numerous periodic unit cells. <a>In past investigations, researchers have demonstrated how architected materials can achieve these novel properties by </a><a>tailoring the features of the unit cells without changing the bulk materials</a>. <a>Here, a group of architected materials called Phase Transforming Cellular Materials (PXCMs) are investigated with the goal of mimicking the novel properties of shape-memory alloys.</a> <a>A general methodology is developed for creating 1D PXCMs that exhibit temperature-induced reverse phase transformations (i.e., shape memory effect) after undergoing large deformations. During this process, the PXCMs dissipate energy but remain elastic (i.e., superelasticity). </a>Next, inspired by the hydration-induced shape recovery of feathers, a PXCM-spring system is developed that uses the superelasticity of PXCMs to achieve shape recovery. Following these successes, the use of PXCMs to resist simulated seismic demands is evaluated. To study how they behave in a dynamic environment and how well their response can be estimated in such an environment, a single degree of freedom-PXCM system is subjected to a series of simulated ground motions. Lastly, the concept of PXCMs is extended into two dimensions by creating PXCMs that achieve superelasticity in two or more directions. Overall, the findings of this investigation indicate that PXCMs<a>: 1) can achieve shape memory and recovery effects through temperature changes, 2) offer a novel alternative to traditional building materials for resisting seismic demands, and 3) can be expanded into two dimensions while still exhibiting superelasticity. </a></p> <p> </p>

Radio frequency (RF) communications are limited to a number of frequency bands scattered over the radio spectrum. Applications over such bands increasingly require more versatile, data extensive wireless communications that leads to the necessity of high bandwidth efficient interfaces, operating over wideband frequency ranges. Whether for a base station or mobile device, the regulations and adequate transmission of such schemes place stringent requirements on the design of transmitter front-ends. Increasingly strenuous and challenging hardware design criteria are to be met, especially so in the design of power amplifiers (PA), the bottle neck of the transmitter’s design tradeoff between linearity and power efficiency. The power amplifier exhibits a nonideal behavior, characterized by both nonlinearity and memory effects, heavily affecting that tradeoff, and therefore requiring an effective linearization technique, namely Digital Predistortion (DPD). The effectiveness of the DPD is highly dependent on the modeling scheme used to compensate for the PA’s nonideal behavior. In fact, its viability is determined by the scheme’s accuracy and implementation complexity. Generic behavioral models for nonlinear systems with memory have been used, considering the PA as a black box, and requiring RF designers to perform extensive testing to determine the minimal complexity structure that achieves satisfactory results. This thesis first proposes a direct systematic approach based on the parallel Hammerstein structure to determine the exact number of coefficients needed in a DPD. Then a physical explanation of memory effects is detailed, which leads to a close-form expression for the characteristic behavior of the PA entirely based on circuit properties. The physical expression is implemented and tested as a modeling scheme. Moreover, a link between this formulation and the proven behavioral models is explored, namely the Volterra series and Memory Polynomial. The formulation shows the correlation between parameters of generic behavioral modeling schemes when applied to RF PAs and demonstrates redundancy based on the physical existence or absence of modeling terms, detailed for the proven Memory polynomial modeling and linearization scheme.

Radio frequency (RF) communications are limited to a number of frequency bands scattered over the radio spectrum. Applications over such bands increasingly require more versatile, data extensive wireless communications that leads to the necessity of high bandwidth efficient interfaces, operating over wideband frequency ranges. Whether for a base station or mobile device, the regulations and adequate transmission of such schemes place stringent requirements on the design of transmitter front-ends. Increasingly strenuous and challenging hardware design criteria are to be met, especially so in the design of power amplifiers (PA), the bottle neck of the transmitter’s design tradeoff between linearity and power efficiency. The power amplifier exhibits a nonideal behavior, characterized by both nonlinearity and memory effects, heavily affecting that tradeoff, and therefore requiring an effective linearization technique, namely Digital Predistortion (DPD). The effectiveness of the DPD is highly dependent on the modeling scheme used to compensate for the PA’s nonideal behavior. In fact, its viability is determined by the scheme’s accuracy and implementation complexity. Generic behavioral models for nonlinear systems with memory have been used, considering the PA as a black box, and requiring RF designers to perform extensive testing to determine the minimal complexity structure that achieves satisfactory results. This thesis first proposes a direct systematic approach based on the parallel Hammerstein structure to determine the exact number of coefficients needed in a DPD. Then a physical explanation of memory effects is detailed, which leads to a close-form expression for the characteristic behavior of the PA entirely based on circuit properties. The physical expression is implemented and tested as a modeling scheme. Moreover, a link between this formulation and the proven behavioral models is explored, namely the Volterra series and Memory Polynomial. The formulation shows the correlation between parameters of generic behavioral modeling schemes when applied to RF PAs and demonstrates redundancy based on the physical existence or absence of modeling terms, detailed for the proven Memory polynomial modeling and linearization scheme.

Abstract The modern wireless communication techniques are aiming on increasing bandwidth and the number of carriers for higher data rate. This sets challenging linearity requirements for RF power amplifiers (PAs). Unfortunately, high linearity can only be obtained at the cost of efficiency. In order to improve the performance of the PA, in-depth understanding of nonlinear behaviour is mandatory. This calls for techniques that can give componentwise information of the causes of the distortion. The aim of this thesis is to develop a technique that can provide such information. This thesis proposes a detailed distortion analysis technique that is based on frequency domain fitting of polynomial models. Simulated large-signal spectra are used for fitting as these contain the necessary information about the large-signal bias point and amplitude range. Moreover, in the frequency domain the delays are easy to compensate, and detailed analysis to any fitted tone can be performed. The fitting procedure as such is simple but becomes difficult in multi-dimensional nonlinearities if the controlling voltages correlate strongly. In this thesis the solvability and reliability of the fitting procedure is increased by numerical operations, model-degree reduction and by using different excitations. A simplified Volterra method is used to calculate the distortion contributions by using the fitted model. The overall distortion is analysed by calculating the voltage response of the contributions of each nonlinearity to the terminal nodes of the device by the use of linear transfer functions of the circuit. The componentwise analysis is performed by phasor presentation enabling the cancelling mechanisms to be seen. The proposed technique is implemented on top of harmonic balance simulation in an APLAC circuit simulator in which extensive distortion simulations are performed. The technique relies on the existing device model and thus the fitted model can be only as accurate as the particular simulation model. However, two different RF PAs are analysed that show a good agreement between measurements and simulations. The proposed technique is verified with several test cases including amplitude dependent amplitude and phase distortion, intermodulation distortion sweet spots, bandwidth dependent memory effects and impedance optimization. The main finding of the detailed analysis is that the distortion is a result of several cancelling mechanisms. In general, cubic nonlinearity of transconductance is dominating the in-band distortion but is cancelled by the 2nd-degree nonlinearity that is mixed to the fundamental band from envelope and 2nd harmonic bands that is usually the main cause of memory effects.

Abstract The main emphasis in modern RF power amplifier (PA) research is on improving linearity while at the same time maintaining reasonably good efficiency, for which purpose external linearization in the form of feedforward or predistortion is often used. Linearity and linearization can be considered from both a fundamental signal (amplitude and phase conversions, AM-AM &amp; AM-PM) and an intermodulation distortion (IMD) regeneration point of view, and since a study of intermodulation gives more information on the behaviour of an amplifier, linearity is studied in this thesis by analysing the amplitude and phase of IM components under varying signal conditions, i.e. as functions of temperature, modulation bandwidth and amplitude. To study the behaviour of IM components analytically, a Volterra model including electro-thermal distortion mechanisms is developed and a simulation technique is introduced to determine how easily the amplifier can be linearized. An S-parameter characterization method for extracting the Volterra model and the simulation model is developed, and the amplitude and phase dependences of the IM components are shown by means of measurements performed by a novel technique developed here. The results show that the behaviour of IM components is more complicated than had commonly been expected. Three techniques are developed for eliminating the frequency dependence of IM components, impedance optimization, envelope filtering and envelope injection. In the envelope injection technique, a low frequency envelope signal is added to the input of the amplifier in order to improve both the bandwidth and amplitude range of the memoryless predistortion. The functionality of envelope injection is demonstrated by Volterra calculations, simulations and measurements, and the technique is applied to 1W, 1.8 GHz common-emitter BJT and common-source MESFET amplifiers. IM cancellation better than 20 dB is achieved over a wide range of bandwidths and amplitudes. It is concluded that an inherently linear amplifier is not necessarily easy to linearize any further using external techniques, but that the part of the distortion that varies with bandwidth and amplitude can be cancelled out using envelope injection and the remaining memoryless distortion by means of a simple polynomial RF predistorter. This results in good cancellation of distortion, and since both envelope injection and RF predistortion consume little power, both good efficiency and linearity can be achieved.

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L’étude expérimentale du transport de soluté dans les milieux poreux montre des écarts à la loi de Fick. D’autre part, des progrès importants ont été accomplis sur le transport en milieu poreux, en supposant que les fluides (et les traceurs) en mouvement dans ces milieux sont arrêtés pendant des durées aléatoires. La matrice solide rend cette idée plausible. Nous étudions un modèle utilisant cette idée en l’associant à des durées d’immobilisation sans moyenne finie, en fait distribuées par des lois de Lévy. On arrive ainsi au modèle MIM fractionnaire, ou fractal.Ce modèle est une équation aux dérivées partielles pour la densité de traceur. Il équivaut à supposer que les particules de fluide et de traceur font des déplacements régis par un processus stochastique. Ce dernier est la limite hydrodynamique de marches au hasard fondées sur des déplacements convectifs, des sauts gaussiens, et des arrêts distribués suivant une loi de Lévy. Ces deux versions du même modèle donnent deux méthodes de simulation numérique.Nous montrons comment mettre en œuvre ces méthodes. Ceci a pour but la maîtrise d’outils de simulation, afin de comparer avec des données expérimentales pour savoir si ce modèle convient pour décrire le transport dans un milieu donné. Cette simulation, pour être efficace, nécessite la connaissance des paramètres du transport de soluté au sein du milieu donné. Ils sont difficilement mesurables et/ou identifiables en pratique. Donc, il faut pouvoir les estimer à partir de grandeurs qu’on sait mesurer directement, comme la densité d’un traceur. Pour cela, nous avons mis en place une méthode d’inversion qui permet d’extraire les paramètres du modèle MIM fractionnaire, à partir de données expérimentales. Cette méthode d’inversion est basée sur la transformation de Laplace. Elle utilise le lien entre les paramètres de transport du modèle MIM fractionnaire, et les dérivées de la transformée de Laplace des solutions de ce modèle. Ce lien est exact dans un milieu semi-infini, et seulement approché dans un milieu fini.Après avoir testé cette méthode en l’appliquant à des données numériques en essayant de retrouver leurs paramètres à "l’aveugle", nous l’appliquons à des données issues d’une expérience de traçage en milieu poreux insaturé / Appealing models for mass transport in porous media assume that fluid and tracer particles can be trapped during random periods. Among them, the fractional version of the Mobile Immobile Model (f-MIM) was found to agree with several tracer test data recorded in environmental media.This model is equivalent to a stochastic process whose density probability function satisfies an advection-diffusion equation equipped with a supplementary time derivative, of non-integer order. The stochastic process is the hydrodynamic limit of random walks accumulating convective displacements, diffusive displacements, and stagnation steps of random duration distributed by a stable Lévy law having no finite average. Random walk and fractional differential equation provide complementary simulation methods.We describe that methods, in view of having tools for comparing the model with tracer test data consisting of time concentration curves. An other essential step in this direction is finding the four parameters of the fractional equation which make its solutions fit at best given sets of such data. Hence, we also present an inversion method adapted to the f-MIM. This method is based on Laplace transform. It exploits the link between model's parameters and Laplace transformed solutions to f-MIM equation. The link is exact in semi-infinite domains. After having checked inverse method's efficiency for numerical artificial data, we apply it to real tracer test data recorded in non-saturated porous sand