Modélisation dynamique et commande optimale d'un système de réfrigération à base d'éjecteur

Recently, the ejector-based refrigeration system (ERS) has been widely used in the cooling industry as an appropriate alternative to the compressor-based cooling systems. However, the advantages of ERS such as the reliable operation and low operation and maintenance costs are overshadowed by its low efficiency and design complexity. In this context, this thesis presents the efforts to develop a control model enabling the ERS to operate in its optimal operational conditions. The extensive experimental studies of ERS revealed that at a fixed condenser inlet condition, there exists an optimal primary stream mass flow rate (generating pressure) that simultaneously maximizes the compression ratio (Cr) and exergy efficiency and minimizes the evaporating pressure. Then, the steady state models of the heat exchangers were developed and used to investigate the influence of the increase in generating pressure on the coefficient of performance (COP) of the system and it showed that increasing the generating pressure reduces the COP, linearly. In order to predict the choking regime of the ejector and explain the reasons of observed physical phenomenon, the 1D model of a fixed geometry ejector installed within an R245fa ERS was developed. The developed model demonstrated that the ejector operates in the subcritical mode when the generating pressure is below the Cr optimum point, while it operates in critical mode at or above the optimum generating pressure. Next, a dynamic model of the ERS was built to evaluate the ERS transient response to an increase in the primary stream mass flow rate. Since the ERS dynamics is mainly dominated by the thermal dynamics of the heat exchangers, the dynamic models of the heat exchangers were developed using the moving boundary approach and connected to the developed models of the ejector and steady state models of the pump and expansion valve to build a single dynamic model of the system. The built dynamic model of an ERS was used to estimate the time response of the system in the absence of accurate experimental data of the system’s dynamics. Finally, a control model was designed to drive an ERS towards its optimal operation condition. A self-optimizing, model-free control strategy known as Extremum seeking control (ESC) was adopted to minimize evaporating pressure in a fixed condenser thermal fluid inlet condition. The innovative ESC model named batch phasor ESC (BPESC) was proposed based on estimating the gradient by evaluating the phasor of the output, in batch time. The simulation results indicated that the designed BPESC model can seek and find the optimum evaporating pressure with good performance in terms of predicting the steady state optimal values and the convergence rates.Récemment, le système de réfrigération à éjecteur (SRE) a été largement utilisé dans l'industrie du refroidissement en tant que solution de remplacement appropriée aux systèmes de refroidissement à compresseur. Cependant, les avantages du SRE, tels que le fonctionnement fiable et les faibles couts d'exploitation et de maintenance, sont éclipsés par son faible rendement et sa complexité de conception. Dans ce contexte, ce projet de recherche de doctorat a détaillé les efforts déployés pour développer une stratégie de commande permettant au système de fonctionner dans ses conditions opérationnelles optimales. Les études expérimentales approfondies du SRE ont révélé que, dans une condition d'entrée de condensateur constante, il existe un débit massique optimal du flux primaire (générant une pression) qui maximise simultanément le taux de compression (Cr) et l'efficacité exergétique, et minimise la pression d’évaporation. Ensuite, les modèles à l’état d’équilibre des échangeurs de chaleur ont été développés et utilisés pour étudier l’influence de l’augmentation de la pression générée sur le coefficient de performance (COP) du système et il en ressort que l'augmentation de la pression génératrice réduit le COP de manière linéaire. Afin de prédire le régime d'étouffement de l'éjecteur et d'expliquer les raisons du phénomène physique observé, le modèle 1D d'un éjecteur à géométrie fixe installé dans un système SRE R245fa a été développé. Le modèle développé a démontré que l'éjecteur fonctionne en mode sous-critique lorsque la pression génératrice est inférieure au point optimal de Cr, alors qu'il fonctionne en mode critique à une pression égale ou supérieure à la pression génératrice optimale. Ensuite, un modèle dynamique du SRE a été développé pour étudier la réponse transitoire du SRE lors d’une augmentation du débit massique du flux primaire. Puisque la dynamique du SRE est principalement dominée par la dynamique thermique des échangeurs de chaleur, les modèles dynamiques des échangeurs de chaleur ont été développés à l'aide de l'approche des limites mobiles et connectés aux modèles développés de l'éjecteur et des modèles à l'état stationnaire de la pompe et de la vanne un seul modèle dynamique du système. En l’absence de données expérimentales précises sur la dynamique d’un système SRE, le modèle dynamique développé du SRE a été simulé numériquement pour étudier sa réponse temporelle. Enfin, une stratégie de commande extrêmale (ESC) a été élaboré pour régler automatiquement le SRE à ses conditions de fonctionnement optimales, c’est-à-dire pour trouver la vitesse de la pompe qui minimise la pression dans des conditions d'entrée de condenseur fixes. Afin de proposer une ESC implémentable en temps discret sur une installation réelle sujette à un bruit de mesure important et un traitement hors-ligne par trame, une nouvelle commande extrémale basée sur une approche par phaseur avec une procédure de traitement de signal par trame (BPESC) a été développée et simulée avec le modèle numérique. Les résultats de la simulation ont indiqué que le modèle BPESC peut trouver la vitesse optimale de la pompe avec de bonnes performances en termes de précision et de vitesse de convergence

Convective heat transfer control in turbulent boundary layers

Mención Internacional en el título de doctorThe sustainable development of our society opens up concerns in several fields of engineering, including energy management, production, and the impact of our technology, being thermal management a common issue to be addressed. The investigation reported in this manuscript focuses on understanding, controlling and optimizing the physical processes involving convective heat transfer in turbulent wall-bounded flows. The content is divided into two main blocks, namely the investigation of classic open-loop active-control techniques to control heat transfer, and the technological development of machine-learning strategies to enhance the performance of flow control in the field of convective heat transfer. The first block focuses on actuator technology, applying dielectric-barrier discharge (DBD) plasma actuators and a pulsed slot jet in crossflow (JICF), respectively, to control the convective heat transfer in a turbulent boundary layer (TBL) over a flat plate. In the former, an array of DBD plasma actuators is employed to induce pairs of counter-rotating, streamwise-aligned vortices embedded in the TBL to reduce heat transfer downstream of the actuation. The whole three-dimensional mean flow field downstream of the plasma actuator is reconstructed from stereoscopic particle image velocimetry (PIV). Infrared thermography (IR) measurements coupled with a heated thin foil provide ensemble-averaged convective heat transfer distributions downstream of the actuators. The combination of the flow field and heat transfer measurements provides a complete picture of the fluid-dynamic interaction of plasma-induced flow with local turbulent transport effects. The plasmainduced streamwise vortices are stationary and confined across the spanwise direction due to the action of the plasma discharge. The opposing plasma discharge causes a mass- and momentum-flux deficit within the boundary layer, leading to a low-velocity region that grows in the streamwise direction and which is characterised by an increase in displacement and momentum thicknesses. This low-velocity ribbon travels downstream, promoting streak-alike patterns of reduction in the convective heat transfer distribution. Near the wall, the plasma-induced jets divert the main flow due to the DBD-actuator momentum injection and the suction on the surrounding fluid by the emerging jets. The stationarity of the plasma-induced vortices makes them persistent far downstream, reducing the convective heat transfer. Conversely, the target of the second paper in this first block is to enhance convective heat transfer rather than reduce it. A fully modulated, pulsed, slot JICF is used to perturb the TBL. The slot-jet actuator, flush-mounted and aligned in the spanwise direction, is controlled based on two design parameters, namely the duty cycle (DC) and the pulsation frequency (f). Heat transfer and flow-field measurements are performed to characterise the control performance using IR thermography and planar PIV, respectively. A parametric study on f and DC is carried out to assess their effect on the heat transfer distribution. The vorticity fields are reconstructed from the Proper Orthogonal Decomposition (POD) modes, retrieving phase information. The flow topology is considerably altered by the jet pulsation, even compared to the case of a steady jet. The results show that both the jet penetration in the streamwise direction and the overall Nusselt number increase with increasing DC. However, the frequency at which the Nusselt number is maximised is independent of the duty cycle. A wall-attached jet rises from the slot accompanied by a pair of counter-rotating vortices that promote flow entrainment and mixing. Eventually, a simplified model is proposed which decouples the effect of f and DC in the overall heat transfer enhancement, with a good agreement with experimental data. The cost of actuation is also quantified in terms of the amount of injected fluid during the actuation, leading to conclude that the lowest duty cycle is the most efficient for heat transfer enhancement among the tested set. The second block of the thesis splits into a comparative assessment of machine learning (ML) methods for active feedback flow control and an application of linear genetic algorithms to an experimental convective heat transfer enhancement problem. First, the comparative study is carried out numerically based on a well-established benchmark problem, the drag reduction of a two-dimensional Kármán vortex street past a circular cylinder at a low Reynolds number (Re = 100). The flow is manipulated with two blowing/suction actuators on the upper and lower side of a cylinder. The feedback employs several velocity sensors. Two probe configurations are evaluated: 5 and 11 velocity probes located at different points around the cylinder and in the wake. The control laws are optimized with Deep Reinforcement Learning (DRL) and Linear Genetic Programming Control (LGPC). Both methods successfully stabilize the vortex alley and effectively reduce drag while using small mass flow rates for the actuation. DRL features higher robustness with respect to variable initial conditions and noise contamination of the sensor data; on the other hand, LGPC can identify compact and interpretable control laws, which only use a subset of sensors, thus allowing reducing the system complexity with reasonably good results. The gained experience and knowledge of machine-learning methods motivated the last study enclosed in this thesis, which utilises linear genetic algorithm control (LGAC) to identify the best actuation parameters in an experimental application. The actuator is a set of six slot jets in crossflow aligned with the freestream. An open-loop optimal periodic forcing is defined by the carrier frequency (f), the duty cycle (DC) and the phase between actuators (ϕ) as control parameters. The control laws are optimised with respect to the unperturbed TBL and the steady-jet actuation. The cost function includes wall convective heat transfer and the cost of the actuation, thus leading to a multi-objective optimisation problem. Surprisingly, the LGAC algorithm converges to the same frequency and duty cycle for all the actuators. This frequency is equivalent to the optimal frequency reported in the second study of the first block of this thesis. The performance of the controller is characterised by IR thermography and PIV measurements. The action of the jets considerably alters the flow topology compared to the steady-jet actuation, yielding a slightly asymmetric flow field. The phase difference between multiple jet actuation has shown to be very relevant and the main driver of flow asymmetry. A POD analysis concludes the shedding phenomena characterising the steady-jet actuation, while the optimised controller exhibits an elongated large-scale structure just downstream of the actuator. The investigation carried out in this thesis sheds some light on the application of different flow control strategies to the field of convective heat transfer. From the utilisation of plasma actuators and a single jet in cross flow to the development of sophisticated control logic, the results point to the exceptional potential of machine learning control in unravelling unexplored controllers within the actuation space. Ultimately, this work demonstrates the viability of employing sophisticated measurement techniques together with advanced algorithms in an experimental investigation, paving the way towards more complex applications involving feedback information.El desarrollo sostenible de nuestra sociedad abre preocupaciones en varios campos de la ingeniería, incluyendo la gestión de la energía, la producción y el impacto de nuestra tecnología, siendo la gestión térmica un tema común a tratar. La investigación que se presenta en este manuscrito se centra en la comprensión, el control y la optimización de los procesos físicos que implican la transferencia de calor por convección en flujos turbulentos de pared. El contenido se divide en dos bloques principales: la investigación de las técnicas clásicas de control activo de lazo abierto para controlar la transferencia de calor, y el desarrollo tecnológico de estrategias de aprendizaje automático para mejorar el rendimiento del control del flujo en el campo de la transferencia de calor por convección. El primer bloque se centra en la tecnología de los actuadores, aplicando actuadores de plasma de descarga de barrera dieléctrica (dielectric barrier dicharge, DBD) y un chorro con forma de ranura pulsado en flujo cruzado (jet in crossflow, JICF), respectivamente, para controlar la transferencia de calor por convección en una capa límite turbulenta (turbulent boundary layer, TBL) sobre una placa plana. En el primero, se emplea un conjunto de actuadores de plasma DBD para inducir pares de vórtices contra-rotativos, alineados con la corriente e incrustados en la TBL para reducir la transferencia de calor aguas abajo de la actuación. El campo de flujo medio tridimensional completo aguas abajo del actuador de plasma se reconstruye a partir de la velocimetría de imagen de partículas estereoscópica (particle image velocimetry, PIV). Las mediciones de termografía infrarroja (IR) junto a una fina lámina calentada proporcionan distribuciones de transferencia de calor convectiva promediadas aguas abajo de los actuadores. La combinación de las mediciones del campo de flujo y de la transferencia de calor proporciona una imagen completa de la interacción fluido-dinámica del flujo inducido por el plasma con los efectos locales de transporte turbulento. Los vórtices en el sentido de la corriente inducidos por plasma son estacionarios y están confinados transversalmente debido a la acción de la descarga de plasma. La descarga de plasma en oposición causa un déficit de flujo de masa y de momento dentro de la capa límite, lo que conduce a una región de baja velocidad que crece en la dirección de la corriente y que se caracteriza por un aumento de los espesores de desplazamiento y de momento. Esta zona de baja velocidad se desplaza corriente abajo, promoviendo patrones de reducción similares a rayas en los que se reduce la transferencia de calor por convección. Cerca de la pared, los chorros inducidos por el plasma desvían el flujo principal debido a la inyección de momento del actuador DBD y a la succión sobre el fluido circundante por parte de los chorros emergentes. La estacionariedad de los vórtices inducidos por el plasma los hace persistentes aguas abajo, reduciendo la transferencia de calor por convección. Por el contrario, el objetivo del segundo trabajo de este primer bloque es mejorar la transferencia de calor por convección en lugar de reducirla. Se utiliza un JICF, pulsado y con forma de ranura, totalmente modulado para perturbar la TBL. El actuador de chorro, montado a ras y alineado en la dirección transversal, se controla en base a dos parámetros de diseño, a saber, el ciclo de trabajo (DC) y la frecuencia de pulsación (f). Se realizan mediciones de la transferencia de calor y del campo de flujo para caracterizar el rendimiento del control mediante termografía IR y PIV planar, respectivamente. Se lleva a cabo un estudio paramétrico de f y DC para evaluar su efecto en la distribución de la transferencia de calor. Los campos de vorticidad se reconstruyen a partir de los modos de descomposición ortogonal adecuada (POD), recuperando la información de fase. La topología del flujo se ve considerablemente alterada por la pulsación del chorro, incluso en comparación con el caso de un chorro estacionario. Los resultados muestran que tanto la penetración del chorro en la dirección de la corriente como el número Nusselt global aumentan con el incremento de DC. Sin embargo, la frecuencia a la que se maximiza el número Nusselt es independiente del ciclo de trabajo. Un chorro adherido a la pared sale de la ranura acompañado de un par de vórtices contrarrotantes que promueven el arrastre y la mezcla del flujo. Finalmente, se propone un modelo simplificado que desacopla el efecto de f y DC en la mejora global de la transferencia de calor, con un buen acuerdo con los datos experimentales. También se cuantifica el coste de la actuación en términos de la cantidad de fluido inyectado durante la actuación, llegando a la conclusión de que el ciclo de trabajo más bajo es el más eficiente para la mejora de la transferencia de calor entre el conjunto probado. El segundo bloque de la tesis se divide en una evaluación comparativa de los métodos de aprendizaje automático (machine learning, ML) para el control activo del flujo por retroalimentación y una aplicación de algoritmos genéticos lineales a un problema experimental de mejora de la transferencia de calor por convección. En primer lugar, el estudio comparativo se realiza numéricamente a partir de un problema de referencia bien establecido: la reducción de la resistencia aerodinámica de una calle de vórtices de Kármán bidimensional tras un cilindro circular a un número de Reynolds bajo (Re = 100). El flujo se manipula con dos actuadores de soplado/succión en la parte superior e inferior de un cilindro. La retroalimentación emplea varios sensores de velocidad. Se evalúan dos configuraciones de sondas: 5 y 11 sondas de velocidad situadas en diferentes puntos alrededor del cilindro y en la estela. Las leyes de control se optimizan con el aprendizaje profundo por refuerzo (Deep Reinforcement Learning, DRL) y el control por programación genética lineal (Linear Genetic Programming Control, LGPC). Ambos métodos estabilizan con éxito la calle de vórtices y reducen de manera efectiva la resistencia al tiempo que usan caudales másicos pequeños para la actuación. El DRL se caracteriza por una mayor robustez con respecto a la variación de la condición inicial y a la contaminación por ruido de los datos de los sensores; por otro lado, el LGPC puede identificar leyes de control compactas e interpretables, que sólo utilizan un subconjunto de sensores, lo que permite reducir la complejidad del sistema con resultados razonablemente buenos. La experiencia adquirida y el conocimiento de los métodos de aprendizaje automático motivaron el último estudio incluido en esta tesis, que utiliza el control por algoritmo genético lineal (Linear Genetic Algorithm Control, LGAC) para identificar los mejores parámetros de actuación en una aplicación experimental. El actuador es un conjunto de seis chorros con forma de ranura en flujo cruzado y alineados con la corriente principal. Se define una ley de forzado periódica en lazo abierto mediante la frecuencia portadora (f), el ciclo de trabajo (DC) y la fase entre actuadores (ϕ) como parámetros de control. Las leyes de control se optimizan con respecto a la TBL no perturbada y la actuación de chorro constante. La función de coste incluye la transferencia de calor por convección de la pared y el coste de la actuación, lo que da lugar a un problema de optimización multiobjetivo. Sorprendentemente, el algoritmo LGAC converge a la misma frecuencia y ciclo de trabajo para todos los actuadores. Esta frecuencia es equivalente a la frecuencia óptima reportada en el segundo estudio del primer bloque de esta tesis. El rendimiento del controlador se caracteriza mediante termografía IR y mediciones PIV. La acción de los chorros altera considerablemente la topología del flujo en comparación con la actuación de los chorros constantes, dando lugar a un campo de flujo ligeramente asimétrico. La diferencia de fase entre la actuación de múltiples chorros ha demostrado ser muy relevante y el principal impulsor de la asimetría del flujo. Un análisis POD concluye los fenómenos de desprendimiento de vórtices que caracterizan la actuación de chorro constante, mientras que el controlador optimizado muestra una estructura alargada a gran escala justo aguas abajo del actuador. La investigación llevada a cabo en esta tesis arroja algo de luz sobre la aplicación de diferentes estrategias de control de flujo en el campo de la transferencia de calor por convección. Desde la utilización de actuadores de plasma y un único chorro en flujo cruzado hasta el desarrollo de una sofisticada lógica de control, los resultados apuntan al excepcional potencial del control por aprendizaje automático para desentrañar controladores inexplorados dentro del espacio de actuación. En última instancia, este trabajo demuestra la viabilidad de emplear sofisticadas técnicas de medición junto con algoritmos avanzados en una investigación experimental, allanando el camino hacia aplicaciones más complejas que implican información de retroalimentación.The work enclosed in this thesis has been partially supported by the Universidad Carlos III de Madrid through a PIPF scholarship awarded on a competitive basis, and by the following research projects: ARTURO (Active contRol of Turbulence for sUstainable aiRcraft propulsiOn), ref. PID2019-109717RB-I00/AEI/10.13039/501100011033, funded by the Spanish State Research Agency (SRA); the 2020 Leonardo Grant for Researchers and Cultural Creators AEROMATIC (Active flow control of aerodynamic flows with machine learning), funded by the BBVA Foundation with grant number IN[20]_ING_ING_0163; and GloWing Starting Grant, funded by the European Research Council (ERC), under grant agreement ERC-2018.StG-803082.Programa de Doctorado en Mecánica de Fluidos por la Universidad Carlos III de Madrid; la Universidad de Jaén; la Universidad de Zaragoza; la Universidad Nacional de Educación a Distancia; la Universidad Politécnica de Madrid y la Universidad Rovira i VirgiliPresidente: Octavio Armas Vergel.- Secretario: Manuel García-Villalba Navaridas.- Vocal: Gioacchino Cafier

Optimization Methods Applied to Power Systems Ⅱ

Electrical power systems are complex networks that include a set of electrical components that allow distributing the electricity generated in the conventional and renewable power plants to distribution systems so it can be received by final consumers (businesses and homes). In practice, power system management requires solving different design, operation, and control problems. Bearing in mind that computers are used to solve these complex optimization problems, this book includes some recent contributions to this field that cover a large variety of problems. More specifically, the book includes contributions about topics such as controllers for the frequency response of microgrids, post-contingency overflow analysis, line overloads after line and generation contingences, power quality disturbances, earthing system touch voltages, security-constrained optimal power flow, voltage regulation planning, intermittent generation in power systems, location of partial discharge source in gas-insulated switchgear, electric vehicle charging stations, optimal power flow with photovoltaic generation, hydroelectric plant location selection, cold-thermal-electric integrated energy systems, high-efficiency resonant devices for microwave power generation, security-constrained unit commitment, and economic dispatch problems

Model Predictive Control of Impedance Source Inverter for Photovoltaic Applications

A model predictive controlled power electronics interface (PEI) based on impedance source inverter for photovoltaic (PV) applications is proposed in this disssertation. The proposed system has the capability of operation in both grid-connected and islanded mode. Firstly, a model predictive based maximum power point tracking (MPPT) method is proposed for PV applications based on single stage grid-connected Z-source inverter (ZSI). This technique predicts the future behavior of the PV side voltage and current using a digital observer that estimates the parameters of the PV module. Therefore, by predicting a priori the behavior of the PV module and its corresponding effects on the system, it improves the control efficacy. The proposed method adaptively updates the perturbation size in the PV voltage using the predicted model of the system to reduce oscillations and increase convergence speed. The experimental results demonstrate fast dynamic response to changes in solar irradiance level, small oscillations around maximum power point at steady-state, and high MPPT effectiveness from low to high solar irradiance level. The second part of this work focuses on the dual-mode operation of the proposed PEI based on ZSI with capability to operate in islanded and grid-connected mode. The transition from islanded to grid-connected mode and vice versa can cause significant deviation in voltage and current due to mismatch in phase, frequency, and amplitude of voltages. The proposed controller using MPC offers seamless transition between the two modes of operations. The main predictive controller objectives are decoupled power control in grid-connected mode and load voltage regulation in islanded mode. The proposed direct decoupled active and reactive power control in grid connected mode enables the dual-mode ZSI to behave as a power conditioning unit for ancillary services such as reactive power compensation. The proposed controller features simplicity, seamless transition between modes of operations, fast dynamic response, and small tracking error in steady state condition of controller objectives. The operation of the proposed system is verified experimentally. The final part of this dissertation focuses on the low voltage ride through (LVRT) capability of the proposed PV systems during grid faults such as voltage sag. In normal grid condition mode, the maximum available power from the PV panels is injected into the grid. In this mode, the system can provide reactive power compensation as a power conditioning unit for ancillary services from DG systems to main ac grid. In case of grid faults, the proposed system changes the behavior of reactive power injection into the grid for LVRT operation according to the grid requirements. Thus, the proposed controller for ZSI is taking into account both the power quality issues and reactive power injection under abnormal grid conditions

Design and Implementation of Internal Model Based Controllers for DC/ AC Power Converters

The aim of this thesis is to design and implement an advanced control system for a working three-phase DC to AC power converter. Compared to' the traditional PI controller used widely in industry, the new voltage controller can track the reference voltage with improved accuracy and efficiency in the presence of different kind of local loads, and also works well in the single phase voltage control. This voltage controller is combined with a power controller to yield a complete controller. An important aspect of this work is the hardware implementation of the whole system. Main parts ofthis thesis are: ???????? 1. Review ofH-infinity and repetitive control techniques and their applications in power converters. 2. Design of a new voltage controller to eliminate the DC component in the output voltages, and taking into account the practical issues such as the processing delay due to the digital signal processor (DSP) implementation. 3. Modelling and simulation of the converter system incorporating different control techniques and with different kinds of loads. 4. Hardware implementation and the two-processor controller. The parallel communication between the DSPs. 5. The main problems encountered in???????????????????? hardware implementation and programming. The software used to initialize DSPs, implement the discretetime voltage controller and other functions such ~ generations of space vector pulse width modulation (SVPWM) signals, circuit protections, analog to digital (AD) cOl)versions, data transmission, etc. 6. Experimental results the under circumstances of no load connected to the converter, pure three-phase resistive loads, three-phase unbalanced resistive' loads and the series resistor-inductor loads. /Imperial Users onl

Nonlinear hydrodynamic modelling of wave energy converters under controlled conditions

One of the major challenges facing modern industrialized countries is the provision of energy: traditional sources, mainly based on fossil fuels, are not only growing scarcer and more expensive, but are also irremediably damaging the environment. Renewable and sustainable energy sources are attractive alternatives that can substantially diversify the energy mix, cut down pollution, and reduce the human footprint on the environment. Ocean energy, including energy generated from the motion of wave, is a tremendous untapped energy resource that could make a decisive contribution to the future supply of clean energy. However, numerous obstacles must be overcome for ocean energy to reach economic viability and compete with other energy sources. Energy can be generated from ocean waves by wave energy converters (WECs). The amount of energy extracted from ocean waves, and therefore the profitability of the extraction, can be increased by optimizing the geometry and the control strategy of the wave energy converter, both of which require mathematical hydrodynamic models that are able to correctly describe the WEC- uid interaction. On the one hand, the accuracy and representativeness of such models have a major in uence on the effectiveness of the WEC design. On the other hand, the computational time required by a model limits its applicability, since many iterations or real-time calculations may be required. Critically, computational time and accuracy are often mutually contrasting features of a mathematical model, so an appropriate compromise should be defined in accordance with the purpose of the model, the device type, and the operational conditions. Linear models, often chosen due to their computational convenience, are likely to be imprecise when a control strategy is implemented in a WEC: under controlled conditions, the motion of the device is exaggerated in order to maximize power absorption, which invalidates the assumption of linearity. The inclusion of nonlinearities in a model is likely to improve the model's accuracy, but increases the computational burden. Therefore, the objective is to define a parsimonious model, in which only relevant nonlinearities are modelled in order to obtain an appropriate compromise between accuracy and computational time. In addition to presenting a wider discussion of nonlinear hydrodynamic modelling for WECs, this thesis contributes the development of a computationally efficient nonlinear hydrodynamic model for axisymmetric WEC devices, from one to six degrees of freedom, based on a novel approach to the nonlinear computation of static and dynamic Froude-Krylov forces

Symmetry in Electromagnetism

Electromagnetism plays a crucial role in basic and applied physics research. The discovery of electromagnetism as the unifying theory for electricity and magnetism represents a cornerstone in modern physics. Symmetry was crucial to the concept of unification: electromagnetism was soon formulated as a gauge theory in which local phase symmetry explained its mathematical formulation. This early connection between symmetry and electromagnetism shows that a symmetry-based approach to many electromagnetic phenomena is recurrent, even today. Moreover, many recent technological advances are based on the control of electromagnetic radiation in nearly all its spectra and scales, the manipulation of matter–radiation interactions with unprecedented levels of sophistication, or new generations of electromagnetic materials. This is a fertile field for applications and for basic understanding in which symmetry, as in the past, bridges apparently unrelated phenomena―from condensed matter to high-energy physics. In this book, we present modern contributions in which symmetry proves its value as a key tool. From dual-symmetry electrodynamics to applications to sustainable smart buildings, or magnetocardiography, we can find a plentiful crop, full of exciting examples of modern approaches to electromagnetism. In all cases, symmetry sheds light on the theoretical and applied works presented in this book

Advances in Computer Science and Engineering

The book Advances in Computer Science and Engineering constitutes the revised selection of 23 chapters written by scientists and researchers from all over the world. The chapters cover topics in the scientific fields of Applied Computing Techniques, Innovations in Mechanical Engineering, Electrical Engineering and Applications and Advances in Applied Modeling