55 resultados para statistical narrow band model


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Probabilistic modeling is the de�ning characteristic of estimation of distribution algorithms (EDAs) which determines their behavior and performance in optimization. Regularization is a well-known statistical technique used for obtaining an improved model by reducing the generalization error of estimation, especially in high-dimensional problems. `1-regularization is a type of this technique with the appealing variable selection property which results in sparse model estimations. In this thesis, we study the use of regularization techniques for model learning in EDAs. Several methods for regularized model estimation in continuous domains based on a Gaussian distribution assumption are presented, and analyzed from di�erent aspects when used for optimization in a high-dimensional setting, where the population size of EDA has a logarithmic scale with respect to the number of variables. The optimization results obtained for a number of continuous problems with an increasing number of variables show that the proposed EDA based on regularized model estimation performs a more robust optimization, and is able to achieve signi�cantly better results for larger dimensions than other Gaussian-based EDAs. We also propose a method for learning a marginally factorized Gaussian Markov random �eld model using regularization techniques and a clustering algorithm. The experimental results show notable optimization performance on continuous additively decomposable problems when using this model estimation method. Our study also covers multi-objective optimization and we propose joint probabilistic modeling of variables and objectives in EDAs based on Bayesian networks, speci�cally models inspired from multi-dimensional Bayesian network classi�ers. It is shown that with this approach to modeling, two new types of relationships are encoded in the estimated models in addition to the variable relationships captured in other EDAs: objectivevariable and objective-objective relationships. An extensive experimental study shows the e�ectiveness of this approach for multi- and many-objective optimization. With the proposed joint variable-objective modeling, in addition to the Pareto set approximation, the algorithm is also able to obtain an estimation of the multi-objective problem structure. Finally, the study of multi-objective optimization based on joint probabilistic modeling is extended to noisy domains, where the noise in objective values is represented by intervals. A new version of the Pareto dominance relation for ordering the solutions in these problems, namely �-degree Pareto dominance, is introduced and its properties are analyzed. We show that the ranking methods based on this dominance relation can result in competitive performance of EDAs with respect to the quality of the approximated Pareto sets. This dominance relation is then used together with a method for joint probabilistic modeling based on `1-regularization for multi-objective feature subset selection in classi�cation, where six di�erent measures of accuracy are considered as objectives with interval values. The individual assessment of the proposed joint probabilistic modeling and solution ranking methods on datasets with small-medium dimensionality, when using two di�erent Bayesian classi�ers, shows that comparable or better Pareto sets of feature subsets are approximated in comparison to standard methods.

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Although most of the research on Cognitive Radio is focused on communication bands above the HF upper limit (30 MHz), Cognitive Radio principles can also be applied to HF communications to make use of the extremely scarce spectrum more efficiently. In this work we consider legacy users as primary users since these users transmit without resorting to any smart procedure, and our stations using the HFDVL (HF Data+Voice Link) architecture as secondary users. Our goal is to enhance an efficient use of the HF band by detecting the presence of uncoordinated primary users and avoiding collisions with them while transmitting in different HF channels using our broad-band HF transceiver. A model of the primary user activity dynamics in the HF band is developed in this work to make short-term predictions of the sojourn time of a primary user in the band and avoid collisions. It is based on Hidden Markov Models (HMM) which are a powerful tool for modelling stochastic random processes and are trained with real measurements of the 14 MHz band. By using the proposed HMM based model, the prediction model achieves an average 10.3% prediction error rate with one minute-long channel knowledge but it can be reduced when this knowledge is extended: with the previous 8 min knowledge, an average 5.8% prediction error rate is achieved. These results suggest that the resulting activity model for the HF band could actually be used to predict primary users activity and included in a future HF cognitive radio based station.

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The characteristics of the power-line communication (PLC) channel are difficult to model due to the heterogeneity of the networks and the lack of common wiring practices. To obtain the full variability of the PLC channel, random channel generators are of great importance for the design and testing of communication algorithms. In this respect, we propose a random channel generator that is based on the top-down approach. Basically, we describe the multipath propagation and the coupling effects with an analytical model. We introduce the variability into a restricted set of parameters and, finally, we fit the model to a set of measured channels. The proposed model enables a closed-form description of both the mean path-loss profile and the statistical correlation function of the channel frequency response. As an example of application, we apply the procedure to a set of in-home measured channels in the band 2-100 MHz whose statistics are available in the literature. The measured channels are divided into nine classes according to their channel capacity. We provide the parameters for the random generation of channels for all nine classes, and we show that the results are consistent with the experimental ones. Finally, we merge the classes to capture the entire heterogeneity of in-home PLC channels. In detail, we introduce the class occurrence probability, and we present a random channel generator that targets the ensemble of all nine classes. The statistics of the composite set of channels are also studied, and they are compared to the results of experimental measurement campaigns in the literature.

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Natural regeneration in Pinus pinea stands commonly fails throughout the Spanish Northern Plateau under current intensive regeneration treatments. As a result, extensive direct seeding is commonly conducted to guarantee regeneration occurrence. In a period of rationalization of the resources devoted to forest management, this kind of techniques may become unaffordable. Given that the climatic and stand factors driving germination remain unknown, tools are required to understand the process and temper the use of direct seeding. In this study, the spatio-temporal pattern of germination of P. pinea was modelled with those purposes. The resulting findings will allow us to (1) determine the main ecological variables involved in germination in the species and (2) infer adequate silvicultural alternatives. The modelling approach focuses on covariates which are readily available to forest managers. A two-step nonlinear mixed model was fitted to predict germination occurrence and abundance in P. pinea under varying climatic, environmental and stand conditions, based on a germination data set covering a 5-year period. The results obtained reveal that the process is primarily driven by climate variables. Favourable conditions for germination commonly occur in fall although the optimum window is often narrow and may not occur at all in some years. At spatial level, it would appear that germination is facilitated by high stand densities, suggesting that current felling intensity should be reduced. In accordance with other studies on P. pinea dispersal, it seems that denser stands during the regeneration period will reduce the present dependence on direct seeding.

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Algebraic topology (homology) is used to analyze the state of spiral defect chaos in both laboratory experiments and numerical simulations of Rayleigh-Bénard convection. The analysis reveals topological asymmetries that arise when non-Boussinesq effects are present. The asymmetries are found in different flow fields in the simulations and are robust to substantial alterations to flow visualization conditions in the experiment. However, the asymmetries are not observable using conventional statistical measures. These results suggest homology may provide a new and general approach for connecting spatiotemporal observations of chaotic or turbulent patterns to theoretical models.

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El objetivo de la tesis es investigar los beneficios que el atrapamiento de la luz mediante fenómenos difractivos puede suponer para las células solares de silicio cristalino y las de banda intermedia. Ambos tipos de células adolecen de una insuficiente absorción de fotones en alguna región del espectro solar. Las células solares de banda intermedia son teóricamente capaces de alcanzar eficiencias mucho mayores que los dispositivos convencionales (con una sola banda energética prohibida), pero los prototipos actuales se resienten de una absorción muy débil de los fotones con energías menores que la banda prohibida. Del mismo modo, las células solares de silicio cristalino absorben débilmente en el infrarrojo cercano debido al carácter indirecto de su banda prohibida. Se ha prestado mucha atención a este problema durante las últimas décadas, de modo que todas las células solares de silicio cristalino comerciales incorporan alguna forma de atrapamiento de luz. Por razones de economía, en la industria se persigue el uso de obleas cada vez más delgadas, con lo que el atrapamiento de la luz adquiere más importancia. Por tanto aumenta el interés en las estructuras difractivas, ya que podrían suponer una mejora sobre el estado del arte. Se comienza desarrollando un método de cálculo con el que simular células solares equipadas con redes de difracción. En este método, la red de difracción se analiza en el ámbito de la óptica física, mediante análisis riguroso con ondas acopladas (rigorous coupled wave analysis), y el sustrato de la célula solar, ópticamente grueso, se analiza en los términos de la óptica geométrica. El método se ha implementado en ordenador y se ha visto que es eficiente y da resultados en buen acuerdo con métodos diferentes descritos por otros autores. Utilizando el formalismo matricial así derivado, se calcula el límite teórico superior para el aumento de la absorción en células solares mediante el uso de redes de difracción. Este límite se compara con el llamado límite lambertiano del atrapamiento de la luz y con el límite absoluto en sustratos gruesos. Se encuentra que las redes biperiódicas (con geometría hexagonal o rectangular) pueden producir un atrapamiento mucho mejor que las redes uniperiódicas. El límite superior depende mucho del periodo de la red. Para periodos grandes, las redes son en teoría capaces de alcanzar el máximo atrapamiento, pero sólo si las eficiencias de difracción tienen una forma peculiar que parece inalcanzable con las herramientas actuales de diseño. Para periodos similares a la longitud de onda de la luz incidente, las redes de difracción pueden proporcionar atrapamiento por debajo del máximo teórico pero por encima del límite Lambertiano, sin imponer requisitos irrealizables a la forma de las eficiencias de difracción y en un margen de longitudes de onda razonablemente amplio. El método de cálculo desarrollado se usa también para diseñar y optimizar redes de difracción para el atrapamiento de la luz en células solares. La red propuesta consiste en un red hexagonal de pozos cilíndricos excavados en la cara posterior del sustrato absorbente de la célula solar. La red se encapsula en una capa dieléctrica y se cubre con un espejo posterior. Se simula esta estructura para una célula solar de silicio y para una de banda intermedia y puntos cuánticos. Numéricamente, se determinan los valores óptimos del periodo de la red y de la profundidad y las dimensiones laterales de los pozos para ambos tipos de células. Los valores se explican utilizando conceptos físicos sencillos, lo que nos permite extraer conclusiones generales que se pueden aplicar a células de otras tecnologías. Las texturas con redes de difracción se fabrican en sustratos de silicio cristalino mediante litografía por nanoimpresión y ataque con iones reactivos. De los cálculos precedentes, se conoce el periodo óptimo de la red que se toma como una constante de diseño. Los sustratos se procesan para obtener estructuras precursoras de células solares sobre las que se realizan medidas ópticas. Las medidas de reflexión en función de la longitud de onda confirman que las redes cuadradas biperiódicas consiguen mejor atrapamiento que las uniperiódicas. Las estructuras fabricadas se simulan con la herramienta de cálculo descrita en los párrafos precedentes y se obtiene un buen acuerdo entre la medida y los resultados de la simulación. Ésta revela que una fracción significativa de los fotones incidentes son absorbidos en el reflector posterior de aluminio, y por tanto desaprovechados, y que este efecto empeora por la rugosidad del espejo. Se desarrolla un método alternativo para crear la capa dieléctrica que consigue que el reflector se deposite sobre una superficie plana, encontrándose que en las muestras preparadas de esta manera la absorción parásita en el espejo es menor. La siguiente tarea descrita en la tesis es el estudio de la absorción de fotones en puntos cuánticos semiconductores. Con la aproximación de masa efectiva, se calculan los niveles de energía de los estados confinados en puntos cuánticos de InAs/GaAs. Se emplea un método de una y de cuatro bandas para el cálculo de la función de onda de electrones y huecos, respectivamente; en el último caso se utiliza un hamiltoniano empírico. La regla de oro de Fermi permite obtener la intensidad de las transiciones ópticas entre los estados confinados. Se investiga el efecto de las dimensiones del punto cuántico en los niveles de energía y la intensidad de las transiciones y se obtiene que, al disminuir la anchura del punto cuántico respecto a su valor en los prototipos actuales, se puede conseguir una transición más intensa entre el nivel intermedio fundamental y la banda de conducción. Tomando como datos de partida los niveles de energía y las intensidades de las transiciones calculados como se ha explicado, se desarrolla un modelo de equilibrio o balance detallado realista para células solares de puntos cuánticos. Con el modelo se calculan las diferentes corrientes debidas a transiciones ópticas entre los numerosos niveles intermedios y las bandas de conducción y de valencia bajo ciertas condiciones. Se distingue de modelos de equilibrio detallado previos, usados para calcular límites de eficiencia, en que se adoptan suposiciones realistas sobre la absorción de fotones para cada transición. Con este modelo se reproducen datos publicados de eficiencias cuánticas experimentales a diferentes temperaturas con un acuerdo muy bueno. Se muestra que el conocido fenómeno del escape térmico de los puntos cuánticos es de naturaleza fotónica; se debe a los fotones térmicos, que inducen transiciones entre los estados excitados que se encuentran escalonados en energía entre el estado intermedio fundamental y la banda de conducción. En el capítulo final, este modelo realista de equilibrio detallado se combina con el método de simulación de redes de difracción para predecir el efecto que tendría incorporar una red de difracción en una célula solar de banda intermedia y puntos cuánticos. Se ha de optimizar cuidadosamente el periodo de la red para equilibrar el aumento de las diferentes transiciones intermedias, que tienen lugar en serie. Debido a que la absorción en los puntos cuánticos es extremadamente débil, se deduce que el atrapamiento de la luz, por sí solo, no es suficiente para conseguir corrientes apreciables a partir de fotones con energía menor que la banda prohibida en las células con puntos cuánticos. Se requiere una combinación del atrapamiento de la luz con un incremento de la densidad de puntos cuánticos. En el límite radiativo y sin atrapamiento de la luz, se necesitaría que el número de puntos cuánticos de una célula solar se multiplicara por 1000 para superar la eficiencia de una célula de referencia con una sola banda prohibida. En cambio, una célula con red de difracción precisaría un incremento del número de puntos en un factor 10 a 100, dependiendo del nivel de la absorción parásita en el reflector posterior. Abstract The purpose of this thesis is to investigate the benefits that diffractive light trapping can offer to quantum dot intermediate band solar cells and crystalline silicon solar cells. Both solar cell technologies suffer from incomplete photon absorption in some part of the solar spectrum. Quantum dot intermediate band solar cells are theoretically capable of achieving much higher efficiencies than conventional single-gap devices. Present prototypes suffer from extremely weak absorption of subbandgap photons in the quantum dots. This problem has received little attention so far, yet it is a serious barrier to the technology approaching its theoretical efficiency limit. Crystalline silicon solar cells absorb weakly in the near infrared due to their indirect bandgap. This problem has received much attention over recent decades, and all commercial crystalline silicon solar cells employ some form of light trapping. With the industry moving toward thinner and thinner wafers, light trapping is becoming of greater importance and diffractive structures may offer an improvement over the state-of-the-art. We begin by constructing a computational method with which to simulate solar cells equipped with diffraction grating textures. The method employs a wave-optical treatment of the diffraction grating, via rigorous coupled wave analysis, with a geometric-optical treatment of the thick solar cell bulk. These are combined using a steady-state matrix formalism. The method has been implemented computationally, and is found to be efficient and to give results in good agreement with alternative methods from other authors. The theoretical upper limit to absorption enhancement in solar cells using diffractions gratings is calculated using the matrix formalism derived in the previous task. This limit is compared to the so-called Lambertian limit for light trapping with isotropic scatterers, and to the absolute upper limit to light trapping in bulk absorbers. It is found that bi-periodic gratings (square or hexagonal geometry) are capable of offering much better light trapping than uni-periodic line gratings. The upper limit depends strongly on the grating period. For large periods, diffraction gratings are theoretically able to offer light trapping at the absolute upper limit, but only if the scattering efficiencies have a particular form, which is deemed to be beyond present design capabilities. For periods similar to the incident wavelength, diffraction gratings can offer light trapping below the absolute limit but above the Lambertian limit without placing unrealistic demands on the exact form of the scattering efficiencies. This is possible for a reasonably broad wavelength range. The computational method is used to design and optimise diffraction gratings for light trapping in solar cells. The proposed diffraction grating consists of a hexagonal lattice of cylindrical wells etched into the rear of the bulk solar cell absorber. This is encapsulated in a dielectric buffer layer, and capped with a rear reflector. Simulations are made of this grating profile applied to a crystalline silicon solar cell and to a quantum dot intermediate band solar cell. The grating period, well depth, and lateral well dimensions are optimised numerically for both solar cell types. This yields the optimum parameters to be used in fabrication of grating equipped solar cells. The optimum parameters are explained using simple physical concepts, allowing us to make more general statements that can be applied to other solar cell technologies. Diffraction grating textures are fabricated on crystalline silicon substrates using nano-imprint lithography and reactive ion etching. The optimum grating period from the previous task has been used as a design parameter. The substrates have been processed into solar cell precursors for optical measurements. Reflection spectroscopy measurements confirm that bi-periodic square gratings offer better absorption enhancement than uni-periodic line gratings. The fabricated structures have been simulated with the previously developed computation tool, with good agreement between measurement and simulation results. The simulations reveal that a significant amount of the incident photons are absorbed parasitically in the rear reflector, and that this is exacerbated by the non-planarity of the rear reflector. An alternative method of depositing the dielectric buffer layer was developed, which leaves a planar surface onto which the reflector is deposited. It was found that samples prepared in this way suffered less from parasitic reflector absorption. The next task described in the thesis is the study of photon absorption in semiconductor quantum dots. The bound-state energy levels of in InAs/GaAs quantum dots is calculated using the effective mass approximation. A one- and four- band method is applied to the calculation of electron and hole wavefunctions respectively, with an empirical Hamiltonian being employed in the latter case. The strength of optical transitions between the bound states is calculated using the Fermi golden rule. The effect of the quantum dot dimensions on the energy levels and transition strengths is investigated. It is found that a strong direct transition between the ground intermediate state and the conduction band can be promoted by decreasing the quantum dot width from its value in present prototypes. This has the added benefit of reducing the ladder of excited states between the ground state and the conduction band, which may help to reduce thermal escape of electrons from quantum dots: an undesirable phenomenon from the point of view of the open circuit voltage of an intermediate band solar cell. A realistic detailed balance model is developed for quantum dot solar cells, which uses as input the energy levels and transition strengths calculated in the previous task. The model calculates the transition currents between the many intermediate levels and the valence and conduction bands under a given set of conditions. It is distinct from previous idealised detailed balance models, which are used to calculate limiting efficiencies, since it makes realistic assumptions about photon absorption by each transition. The model is used to reproduce published experimental quantum efficiency results at different temperatures, with quite good agreement. The much-studied phenomenon of thermal escape from quantum dots is found to be photonic; it is due to thermal photons, which induce transitions between the ladder of excited states between the ground intermediate state and the conduction band. In the final chapter, the realistic detailed balance model is combined with the diffraction grating simulation method to predict the effect of incorporating a diffraction grating into a quantum dot intermediate band solar cell. Careful optimisation of the grating period is made to balance the enhancement given to the different intermediate transitions, which occur in series. Due to the extremely weak absorption in the quantum dots, it is found that light trapping alone is not sufficient to achieve high subbandgap currents in quantum dot solar cells. Instead, a combination of light trapping and increased quantum dot density is required. Within the radiative limit, a quantum dot solar cell with no light trapping requires a 1000 fold increase in the number of quantum dots to supersede the efficiency of a single-gap reference cell. A quantum dot solar cell equipped with a diffraction grating requires between a 10 and 100 fold increase in the number of quantum dots, depending on the level of parasitic absorption in the rear reflector.

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La predicción de energía eólica ha desempeñado en la última década un papel fundamental en el aprovechamiento de este recurso renovable, ya que permite reducir el impacto que tiene la naturaleza fluctuante del viento en la actividad de diversos agentes implicados en su integración, tales como el operador del sistema o los agentes del mercado eléctrico. Los altos niveles de penetración eólica alcanzados recientemente por algunos países han puesto de manifiesto la necesidad de mejorar las predicciones durante eventos en los que se experimenta una variación importante de la potencia generada por un parque o un conjunto de ellos en un tiempo relativamente corto (del orden de unas pocas horas). Estos eventos, conocidos como rampas, no tienen una única causa, ya que pueden estar motivados por procesos meteorológicos que se dan en muy diferentes escalas espacio-temporales, desde el paso de grandes frentes en la macroescala a procesos convectivos locales como tormentas. Además, el propio proceso de conversión del viento en energía eléctrica juega un papel relevante en la ocurrencia de rampas debido, entre otros factores, a la relación no lineal que impone la curva de potencia del aerogenerador, la desalineación de la máquina con respecto al viento y la interacción aerodinámica entre aerogeneradores. En este trabajo se aborda la aplicación de modelos estadísticos a la predicción de rampas a muy corto plazo. Además, se investiga la relación de este tipo de eventos con procesos atmosféricos en la macroescala. Los modelos se emplean para generar predicciones de punto a partir del modelado estocástico de una serie temporal de potencia generada por un parque eólico. Los horizontes de predicción considerados van de una a seis horas. Como primer paso, se ha elaborado una metodología para caracterizar rampas en series temporales. La denominada función-rampa está basada en la transformada wavelet y proporciona un índice en cada paso temporal. Este índice caracteriza la intensidad de rampa en base a los gradientes de potencia experimentados en un rango determinado de escalas temporales. Se han implementado tres tipos de modelos predictivos de cara a evaluar el papel que juega la complejidad de un modelo en su desempeño: modelos lineales autorregresivos (AR), modelos de coeficientes variables (VCMs) y modelos basado en redes neuronales (ANNs). Los modelos se han entrenado en base a la minimización del error cuadrático medio y la configuración de cada uno de ellos se ha determinado mediante validación cruzada. De cara a analizar la contribución del estado macroescalar de la atmósfera en la predicción de rampas, se ha propuesto una metodología que permite extraer, a partir de las salidas de modelos meteorológicos, información relevante para explicar la ocurrencia de estos eventos. La metodología se basa en el análisis de componentes principales (PCA) para la síntesis de la datos de la atmósfera y en el uso de la información mutua (MI) para estimar la dependencia no lineal entre dos señales. Esta metodología se ha aplicado a datos de reanálisis generados con un modelo de circulación general (GCM) de cara a generar variables exógenas que posteriormente se han introducido en los modelos predictivos. Los casos de estudio considerados corresponden a dos parques eólicos ubicados en España. Los resultados muestran que el modelado de la serie de potencias permitió una mejora notable con respecto al modelo predictivo de referencia (la persistencia) y que al añadir información de la macroescala se obtuvieron mejoras adicionales del mismo orden. Estas mejoras resultaron mayores para el caso de rampas de bajada. Los resultados también indican distintos grados de conexión entre la macroescala y la ocurrencia de rampas en los dos parques considerados. Abstract One of the main drawbacks of wind energy is that it exhibits intermittent generation greatly depending on environmental conditions. Wind power forecasting has proven to be an effective tool for facilitating wind power integration from both the technical and the economical perspective. Indeed, system operators and energy traders benefit from the use of forecasting techniques, because the reduction of the inherent uncertainty of wind power allows them the adoption of optimal decisions. Wind power integration imposes new challenges as higher wind penetration levels are attained. Wind power ramp forecasting is an example of such a recent topic of interest. The term ramp makes reference to a large and rapid variation (1-4 hours) observed in the wind power output of a wind farm or portfolio. Ramp events can be motivated by a broad number of meteorological processes that occur at different time/spatial scales, from the passage of large-scale frontal systems to local processes such as thunderstorms and thermally-driven flows. Ramp events may also be conditioned by features related to the wind-to-power conversion process, such as yaw misalignment, the wind turbine shut-down and the aerodynamic interaction between wind turbines of a wind farm (wake effect). This work is devoted to wind power ramp forecasting, with special focus on the connection between the global scale and ramp events observed at the wind farm level. The framework of this study is the point-forecasting approach. Time series based models were implemented for very short-term prediction, this being characterised by prediction horizons up to six hours ahead. As a first step, a methodology to characterise ramps within a wind power time series was proposed. The so-called ramp function is based on the wavelet transform and it provides a continuous index related to the ramp intensity at each time step. The underlying idea is that ramps are characterised by high power output gradients evaluated under different time scales. A number of state-of-the-art time series based models were considered, namely linear autoregressive (AR) models, varying-coefficient models (VCMs) and artificial neural networks (ANNs). This allowed us to gain insights into how the complexity of the model contributes to the accuracy of the wind power time series modelling. The models were trained in base of a mean squared error criterion and the final set-up of each model was determined through cross-validation techniques. In order to investigate the contribution of the global scale into wind power ramp forecasting, a methodological proposal to identify features in atmospheric raw data that are relevant for explaining wind power ramp events was presented. The proposed methodology is based on two techniques: principal component analysis (PCA) for atmospheric data compression and mutual information (MI) for assessing non-linear dependence between variables. The methodology was applied to reanalysis data generated with a general circulation model (GCM). This allowed for the elaboration of explanatory variables meaningful for ramp forecasting that were utilized as exogenous variables by the forecasting models. The study covered two wind farms located in Spain. All the models outperformed the reference model (the persistence) during both ramp and non-ramp situations. Adding atmospheric information had a noticeable impact on the forecasting performance, specially during ramp-down events. Results also suggested different levels of connection between the ramp occurrence at the wind farm level and the global scale.

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Los materiales de banda intermedia han atraido la atención de la comunidad científica en el campo de la energía solar fotovoltaica en los últimos años. Sin embargo, con el objetivo de entender los fundamentos de las células solares de banda intermedia, se debe llevar a cabo un estudio profundo de la características de los materiales. Esto se puede hacer mediante un modelo teórico usando Primeros Principios. A partir de este enfoque se pueden obtener resultados tales como la estructura electrónica y propiedades ópticas, entre otras, de los semiconductores fuertemente dopados y sus precursores. Con el fin de desentrañar las estructuras de estos sistemas electrónicos, esta tesis presenta un estudio termodinámico y optoelectrónico de varios materiales fotovoltaicos. Específicamente se caracterizaron los materiales avanzados de banda intermedia y sus precursores. El estudio se hizo en términos de caracterización teórica de la estructura electrónica, la energética del sistema, entre otros. Además la estabilidad se obtuvo usando configuraciones adaptadas a la simetría del sistema y basado en la combinatoria. Las configuraciones de los sitios ocupados por defectos permiten obtener información sobre un espacio de configuraciones donde las posiciones de los dopantes sustituidos se basan en la simetría del sólido cristalino. El resultado puede ser tratado usando elementos de termodinámica estadística y da información de la estabilidad de todo el espacio simétrico. Además se estudiaron otras características importantes de los semiconductores de base. En concreto, el análisis de las interacciones de van der Waals fueron incluidas en el semiconductor en capas SnS2, y el grado de inversión en el caso de las espinelas [M]In2S4. En este trabajo además realizamos una descripción teórica exhaustiva del sistema CdTe:Bi. Este material de banda-intermedia muestra características que son distintas a las de los otros materiales estudiados. También se analizó el Zn como agente modulador de la posición de las sub-bandas prohibidas en el material de banda-intermedia CuGaS2:Ti. Analizándose además la viabilidad termodinámica de la formación de este compuesto. Finalmente, también se describió el GaN:Cr como material de banda intermedia, en la estructura zinc-blenda y en wurtztite, usando configuraciones de sitios ocupados de acuerdo a la simetría del sistema cristalino del semiconductor de base. Todos los resultados, siempre que fue posible, fueron comparados con los resultados experimentales. ABSTRACT The intermediate-band materials have attracted the attention of the scientific community in the field of the photovoltaics in recent years. Nevertheless, in order to understand the intermediate-band solar cell fundamentals, a profound study of the characteristics of the materials is required. This can be done using theoretical modelling from first-principles. The electronic structure and optical properties of heavily doped semiconductors and their precursor semiconductors are, among others, results that can be obtained from this approach. In order to unravel the structures of these crystalline systems, this thesis presents a thermodynamic and optoelectronic study of several photovoltaic materials. Specifically advanced intermediate-band materials and their precursor semiconductors were characterized. The study was made in terms of theoretical characterization of the electronic structure, energetics among others. The stability was obtained using site-occupancy-disorder configurations adapted to the symmetry of the system and based on combinatorics. The site-occupancy-disorder method allows the formation of a configurational space of substitutional dopant positions based on the symmetry of the crystalline solid. The result, that can be treated using statistical thermodynamics, gives information of the stability of the whole space of symmetry of the crystalline lattice. Furthermore, certain other important characteristics of host semiconductors were studied. Specifically, the van der Waal interactions were included in the SnS2 layered semiconductor, and the inversion degree in cases of [M]In2S4 spinels. In this work we also carried out an exhaustive theoretical description of the CdTe:Bi system. This intermediate-band material shows characteristics that are distinct from those of the other studied intermediate-band materials. In addition, Zn was analysed as a modulator of the positions of the sub-band gaps in the CuGaS2:Ti intermediate-band material. The thermodynamic feasibility of the formation of this compound was also carried out. Finally GaN:Cr intermediate-band material was also described both in the zinc-blende and the wurtztite type structures, using the symmetry-adapted-space of configurations. All results, whenever possible, were compared with experimental results.

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Stochastic model updating must be considered for quantifying uncertainties inherently existing in real-world engineering structures. By this means the statistical properties,instead of deterministic values, of structural parameters can be sought indicating the parameter variability. However, the implementation of stochastic model updating is much more complicated than that of deterministic methods particularly in the aspects of theoretical complexity and low computational efficiency. This study attempts to propose a simple and cost-efficient method by decomposing a stochastic updating process into a series of deterministic ones with the aid of response surface models and Monte Carlo simulation. The response surface models are used as surrogates for original FE models in the interest of programming simplification, fast response computation and easy inverse optimization. Monte Carlo simulation is adopted for generating samples from the assumed or measured probability distributions of responses. Each sample corresponds to an individual deterministic inverse process predicting the deterministic values of parameters. Then the parameter means and variances can be statistically estimated based on all the parameter predictions by running all the samples. Meanwhile, the analysis of variance approach is employed for the evaluation of parameter variability significance. The proposed method has been demonstrated firstly on a numerical beam and then a set of nominally identical steel plates tested in the laboratory. It is found that compared with the existing stochastic model updating methods, the proposed method presents similar accuracy while its primary merits consist in its simple implementation and cost efficiency in response computation and inverse optimization.

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We have fabricated titanium and vanadium supersaturated silicon layers on top of a silicon substrate by means of ion implantation and pulsed laser melting processes. This procedure has proven to be suitable to fabricate an intermediate band (IB) material, i.e. a semiconductor material with a band of allowed states within the bandgap. Sheet resistance and Hall mobility measurements as a function of the temperature show an unusual behavior that has been well explained in the framework of the IB material theory, supposing that we are dealing with a junction formed by the IB material top layer and the n-Si substrate. Using an analytical model that fits with accuracy the experimental sheet resistance and mobility curves, we have obtained the values of the exponential factor for the thermically activated junction resistance of the bilayer, showing important differences as a function of the implanted element. These results could allow us to engineer the IB properties selecting the implanted element depending on the required properties for a specific application.

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Caracterización de los procesos de disipación mecánica basándose en la microestructura de los tejidos blandos. We present a continuous damage model with regularized softening (smeared crack models) for fiber reinforced soft tissues. Material parameters of the continuous model derive from the mesoscopic scale. In the mesoscopic scale continuum is considered as a collagenous fibrilreinforced composite. We want to study the continnumlevel response as a function of the nanoscale properties of the collagen and the adherent forces between the tropocollagen molecules.

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We investigated the electrical transport properties of ultraheavily Ti-implanted silicon layers subsequently pulsed laser melted (PLM). After PLM, the samples exhibit anomalous electrical behaviour in sheet resistance and Hall mobility measurements, which is associated with the formation of an intermediate band (IB) in the implanted layer. An analytical model that assumes IB formation and a current limitation effect between the implanted layer and the substrate was developed to analyse this anomalous behaviour. This model also describes the behaviour of the function V/Delta V and the electrical function F that can be extracted from the electrical measurements in the bilayer. After chemical etching of the implanted layer, the anomalous electrical behaviour observed in sheet resistance and Hall mobility measurements vanishes, recovering the unimplanted Si behaviour, in agreement with the analytical model. The behaviour of V/Delta V and the electrical function F can also be successfully described in terms of the analytical model in the bilayer structure with the implanted layer entirely stripped.

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We present an undergraduate course on concurrent programming where formal models are used in different stages of the learning process. The main practical difference with other approaches lies in the fact that the ability to develop correct concurrent software relies on a systematic transformation of formal models of inter-process interaction (so called shared resources), rather than on the specific constructs of some programming language. Using a resource-centric rather than a language-centric approach has some benefits for both teachers and students. Besides the obvious advantage of being independent of the programming language, the models help in the early validation of concurrent software design, provide students and teachers with a lingua franca that greatly simplifies communication at the classroom and during supervision, and help in the automatic generation of tests for the practical assignments. This method has been in use, with slight variations, for some 15 years, surviving changes in the programming language and course length. In this article, we describe the components and structure of the current incarnation of the course?which uses Java as target language?and some tools used to support our method. We provide a detailed description of the different outcomes that the model-driven approach delivers (validation of the initial design, automatic generation of tests, and mechanical generation of code) from a teaching perspective. A critical discussion on the perceived advantages and risks of our approach follows, including some proposals on how these risks can be minimized. We include a statistical analysis to show that our method has a positive impact in the student ability to understand concurrency and to generate correct code.

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Computing the modal parameters of large structures in Operational Modal Analysis often requires to process data from multiple non simultaneously recorded setups of sensors. These setups share some sensors in common, the so-called reference sensors that are fixed for all the measurements, while the other sensors are moved from one setup to the next. One possibility is to process the setups separately what result in different modal parameter estimates for each setup. Then the reference sensors are used to merge or glue the different parts of the mode shapes to obtain global modes, while the natural frequencies and damping ratios are usually averaged. In this paper we present a state space model that can be used to process all setups at once so the global mode shapes are obtained automatically and subsequently only a value for the natural frequency and damping ratio of each mode is computed. We also present how this model can be estimated using maximum likelihood and the Expectation Maximization algorithm. We apply this technique to real data measured at a footbridge.

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Los sistemas de telecomunicación que trabajan en frecuencias milimétricas pueden verse severamente afectados por varios fenómenos atmosféricos, tales como la atenuación por gases, nubes y el centelleo troposférico. Una adecuada caracterización es imprescindible en el diseño e implementación de estos sistemas. El presente Proyecto Fin de Grado tiene como objetivo el estudio estadístico a largo plazo de series temporales de centelleo troposférico en enlaces de comunicaciones en trayecto inclinado sobre la banda Ka a 19,7 GHz. Para la realización de este estudio, se dispone como punto de partida de datos experimentales procedentes de la baliza en banda Ka a 19,7 GHz del satélite Eutelsat Hot Bird 13A que han sido recopilados durante siete años entre julio de 2006 y junio de 2013. Además, se cuenta como referencia teórica con la aplicación práctica del método UIT-R P.618-10 para el modelado del centelleo troposférico en sistemas de telecomunicación Tierra-espacio. Esta información permite examinar la validez de la aplicación práctica del método UIT-R P.1853-1 para la síntesis de series temporales de centelleo troposférico. Sobre este sintetizador se variará la serie temporal de contenido integrado de vapor de agua en una columna vertical por datos reales obtenidos de bases de datos meteorológicas ERA-Interim y GNSS con el objetivo de comprobar el impacto de este cambio. La primera parte del Proyecto comienza con la exposición de los fundamentos teóricos de los distintos fenómenos que afectan a la propagación en un enlace por satélite, incluyendo los modelos de predicción más importantes. Posteriormente, se presentan los fundamentos teóricos que describen las series temporales, así como su aplicación al modelado de enlaces de comunicaciones. Por último, se describen los recursos específicos empleados en la realización del experimento. La segunda parte del Proyecto se inicia con la muestra del proceso de análisis de los datos disponibles que, más tarde, permiten obtener resultados que caracterizan el centelleo troposférico en ausencia de precipitación, o centelleo seco, para los tres casos de estudio sobre los datos experimentales, sobre el modelo P.618-10 y sobre el sintetizador P.1853-1 con sus modificaciones. Al haber mantenido en todo momento las mismas condiciones de frecuencia, localización, clima y periodo de análisis, el estudio comparativo de los resultados obtenidos permite extraer las conclusiones oportunas y proponer líneas futuras de investigación. ABSTRACT. Telecommunication systems working in the millimetre band are severely affected by various atmospheric impairments, such as attenuation due to clouds, gases and tropospheric scintillation. An adequate characterization is essential in the design and implementation of these systems. This Final Degree Project aims to a long-term statistical study of time series of tropospheric scintillation on slant path communications links in Ka band at 19.7 GHz. To carry out this study, experimental data from the beacon in Ka band at 19.7 GHz for the Eutelsat Hot Bird 13A satellite are available as a starting point. These data have been collected during seven years between July 2006 and June 2013. In addition, the practical application of the ITU-R P.618-10 method for tropospheric scintillation modeling of Earth-space telecommunication systems has been the theoretical reference used. This information allows us to examine the validity of the practical application of the ITU-R P.1853-1 method for tropospheric scintillation time series synthesis. In this synthesizer, the time series of water vapor content in a vertical column will be substituted by actual data from meteorological databases ERA-Interim and GNSS in order to test the impact of this change. The first part of the Project begins with the exposition of the theoretical foundations of the various impairments that affect propagation in a satellite link, including the most important prediction models. Subsequently, it presents the theoretical foundations that describe the time series, and its application to communication links modeling. Finally, the specific resources used in the experiment are described. The second part of the Project starts with the exhibition of the data analysis process to obtain results that characterize the tropospheric scintillation in the absence of precipitation, or dry scintillation, for the three study cases on the experimental data, on the P.618-10 model and on the P.1853-1 synthesizer with its modifications. The fact that the same conditions of frequency, location, climate and period of analysis are always maintained, allows us to draw conclusions and propose future research lines by comparing the results.