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Contrôle d'un système multi-terminal HVDC (MTDC) et étude des interactions entre les réseaux AC et le réseau MTDC. / Control of a multi-terminal HVDC (MTDC) system and study of the interactions between the MTDC and the AC grids.Akkari, Samy 29 September 2016 (has links)
La multiplication des projets HVDC de par le monde démontre l'engouement toujours croissant pour cette technologie de transport de l'électricité. La grande majorité de ces transmissions HVDC correspondent à des liaisons point-à-point et se basent sur des convertisseurs AC/DC de type LCC ou VSC à 2 ou 3 niveaux. Les travaux de cette thèse se focalisent sur l'étude, le contrôle et la commande de systèmes HVDC de type multi-terminal (MTDC), avec des convertisseurs de type VSC classique ou modulaire multi-niveaux. La première étape consiste à obtenir les modèles moyens du VSC classique et du MMC. La différence fondamentale entre ces deux convertisseurs, à savoir la possibilité pour le MMC de stocker et de contrôler l'énergie des condensateurs des sous-modules, est détaillée et expliquée. Ces modèles et leurs commandes sont ensuite linéarisés et mis sous forme de représentations d'état, puis validés en comparant leur comportement à ceux de modèles de convertisseurs plus détaillés à l'aide de logiciels de type EMT. Une fois validés, les modèles d'état peuvent être utilisés afin de générer le modèle d'état de tout système de transmissions HVDC, qu'il soit point-à-point ou MTDC. La comparaison d'une liaison HVDC à base de VSCs classiques puis de MMCs est alors réalisée. Leurs valeurs propres sont étudiées et comparées, et les modes ayant un impact sur la tension DC sont identifiés et analysés. Cette étude est ensuite étendue à un système MTDC à 5 terminaux, et son analyse modale permet à la fois d'étudier la stabilité du système, mais aussi de comprendre l'origine de ses valeurs propres ainsi que leur impact sur la dynamique du système. La méthode de décomposition en valeurs singulières permet ensuite d'obtenir un intervalle de valeurs possibles pour le paramètre de"voltage droop", permettant ainsi le contrôle du système MTDC tout en s'assurant qu'il soit conforme à des contraintes bien définies, comme l'écart maximal admissible en tension DC. Enfin, une proposition de "frequency droop" (ou "statisme"), permettant aux convertisseurs de participer au réglage de la fréquence des réseaux AC auxquels ils sont connectés, est étudiée. Le frequency droop est utilisé conjointement avec le voltage droop afn de garantir le bon fonctionnement de la partie AC et de la partie DC. Cependant, l'utilisation des deux droop génère un couplage indésirable entre les deux commandes. Ces interactions sont mathématiquement quantifiées et une correction à apporter au paramètre de frequency droop est proposée. Ces résultats sont ensuite validés par des simulations EMT et par des essais sur la plate-forme MTDC du laboratoire L2EP. / HVDC transmission systems are largely used worldwide, mostly in the form of back-to-back and point-to-point HVDC, using either thyristor-based LCC or IGBT-based VSC. With the recent deployment of the INELFE HVDC link between France and Spain, and the commissioning in China of a three-terminal HVDC transmission system using Modular Multilevel Converters (MMCs), a modular design of voltage source converters, the focus of the scientific community has shifted onto the analysis and control of MMC-based HVDC transmission systems. In this thesis, the average value models of both a standard 2-level VSC and an MMC are proposed and the most interesting difference between the two converter technologies -the control of the stored energy in the MMC- is emphasised and explained. These models are then linearised, expressed in state-space form and validated by comparing their behaviour to more detailed models under EMT programs. Afterwards, these state-space representations are used in the modelling of HVDC transmission systems, either point-to-point or Multi-Terminal HVDC (MTDC). A modal analysis is performed on an HVDC link, for both 2-level VSCs and MMCs. The modes of these two systems are specifed and compared and the independent control of the DC voltage and the DC current in the case of an MMC is illustrated. This analysis is extended to the scope of a 5-terminal HVDC system in order to perform a stability analysis, understand the origin of the system dynamics and identify the dominant DC voltage mode that dictates the DC voltage response time. Using the Singular Value Decomposition method on the MTDC system, the proper design of the voltage-droop gains of the controllers is then achieved so that the system operation is ensured within physical constraints, such as the maximum DC voltage deviation and the maximum admissible current in the power electronics. Finally, a supplementary droop "the frequency-droop control" is proposed so that MTDC systems also participate to the onshore grids frequency regulation. However, this controller interacts with the voltage-droop controller. This interaction is mathematically quantified and a corrected frequency-droop gain is proposed. This control is then illustrated with an application to the physical converters of the Twenties project mock-up.
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Semi-Automatic Analysis and Visualization of Cardiac 4D Flow CTvan Oosten, Anthony January 2022 (has links)
The data obtained from computational fluid dynamics (CFD) simulations of blood flow in the heart is plentiful, and processing this data takes time and the procedure for that is not straightforward. This project aims to develop a tool that can semi-automatically process CFD simulation data, which is based on 4D flow computed tomography (CT) data, with minimal user input. The tool should be able to time efficiently calculate flow parameters from the data, and automatically create overview images of the flow field while doing so, to aid the user's analysis process. The tool is coded using Python programming language, and the Python scripts are inputted to the application ParaView for processing of the simulation data. The tool generates 3 chamber views of the heart by calculating three points from the given patient data, which represent the aortic and mitral valves, and the apex of the heart. A plane is generated that pass through these three points, and the heart is sliced along this plane to visualize 3 chambers of the heart. The camera position is also manipulated to optimize the 3 chamber view. The maximum outflow velocity over the cardiac cycle in the left atrial appendage (LAA) is determined by searching in a time range around the maximum outflow rate of the LAA in a cardiac cycle, and finding the highest velocity value that points away from the LAA in this range. The flow component analysis is calculated in the LAA and left ventricle (LV) by seeding particles in each at the start of the cardiac cycle, and tracking these particles forwards and backwards in time to determine where the particles end up and come from, respectively. By knowing these two aspects, the four different flow components of the blood can be determined in both the LAA and LV. The tool can successfully create 3 chamber views of the heart model from three semi-automatically determined points, at a manipulated camera location. It can also calculate the maximum outflow velocity of the flow field over a cardiac cycle in the LAA, and perform a flow component analysis of the LAA and the LV by tracking particles forwards and backwards in time through a cardiac cycle. The maximum velocity calculation is relatively time efficient and produces results similar to those found manually, yet the output is dependent on the user-defined inputs and processing techniques, and varies between users. The flow component analysis is also time efficient, produces results for the LV that are comparable to pre-existing research, and produces results for the LAA that are comparable to the LVs' results. Although, the extraction process of the LAA sometimes includes part of the left atrium, which impacts the accuracy of the results. After processing each part, the tool creates a single file containing each part's main results for easier analysis of the patient data. In conclusion, the tool is capable of semi-automatically processing CFD simulation data which saves the user time, and it has thus met all the project aims
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Síntesis Audiovisual Realista PersonalizableMelenchón Maldonado, Javier 13 July 2007 (has links)
Es presenta un esquema únic per a la síntesi i anàlisi audiovisual personalitzable realista de seqüències audiovisuals de cares parlants i seqüències visuals de llengua de signes en àmbit domèstic. En el primer cas, amb animació totalment sincronitzada a través d'una font de text o veu; en el segon, utilitzant la tècnica de lletrejar paraules mitjançant la ma. Les seves possibilitats de personalització faciliten la creació de seqüències audiovisuals per part d'usuaris no experts. Les aplicacions possibles d'aquest esquema de síntesis comprenen des de la creació de personatges virtuals realistes per interacció natural o vídeo jocs fins vídeo conferència des de molt baix ample de banda i telefonia visual per a les persones amb problemes d'oïda, passant per oferir ajuda a la pronunciació i la comunicació a aquest mateix col·lectiu. El sistema permet processar seqüències llargues amb un consum de recursos molt reduït, sobre tot, en el referent a l'emmagatzematge, gràcies al desenvolupament d'un nou procediment de càlcul incremental per a la descomposició en valors singulars amb actualització de la informació mitja. Aquest procediment es complementa amb altres tres: el decremental, el de partició i el de composició. / Se presenta un esquema único para la síntesis y análisis audiovisual personalizable realista de secuencias audiovisuales de caras parlantes y secuencias visuales de lengua de signos en entorno doméstico. En el primer caso, con animación totalmente sincronizada a través de una fuente de texto o voz; en el segundo, utilizando la técnica de deletreo de palabras mediante la mano. Sus posibilidades de personalización facilitan la creación de secuencias audiovisuales por parte de usuarios no expertos. Las aplicaciones posibles de este esquema de síntesis comprenden desde la creación de personajes virtuales realistas para interacción natural o vídeo juegos hasta vídeo conferencia de muy bajo ancho de banda y telefonía visual para las personas con problemas de oído, pasando por ofrecer ayuda en la pronunciación y la comunicación a este mismo colectivo. El sistema permite procesar secuencias largas con un consumo de recursos muy reducido gracias al desarrollo de un nuevo procedimiento de cálculo incremental para la descomposición en valores singulares con actualización de la información media. / A shared framework for realistic and personalizable audiovisual synthesis and analysis of audiovisual sequences of talking heads and visual sequences of sign language is presented in a domestic environment. The former has full synchronized animation using a text or auditory source of information; the latter consists in finger spelling. Their personalization capabilities ease the creation of audiovisual sequences by non expert users. The applications range from realistic virtual avatars for natural interaction or videogames to low bandwidth videoconference and visual telephony for the hard of hearing, including help to speech therapists. Long sequences can be processed with reduced resources, specially storing ones. This is allowed thanks to the proposed scheme for the incremental singular value decomposition with mean preservation. This scheme is complemented with another three: the decremental, the split and the composed ones.
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Advanced Modeling of Longitudinal Spectroscopy DataKundu, Madan Gopal January 2014 (has links)
Indiana University-Purdue University Indianapolis (IUPUI) / Magnetic resonance (MR) spectroscopy is a neuroimaging technique. It is widely used to quantify the concentration of important metabolites in a brain tissue. Imbalance in concentration of brain metabolites has been found to be associated with development of neurological impairment. There has been increasing trend of using MR spectroscopy as a diagnosis tool for neurological disorders. We established statistical methodology to analyze data obtained from the MR spectroscopy in the context of the HIV associated neurological disorder. First, we have developed novel methodology to study the association of marker of neurological disorder with MR spectrum from brain and how this association evolves with time. The entire problem fits into the framework of scalar-on-function regression model with individual spectrum being the functional predictor. We have extended one of the existing cross-sectional scalar-on-function regression techniques to longitudinal set-up. Advantage of proposed method includes: 1) ability to model flexible time-varying association between response and functional predictor and (2) ability to incorporate prior information.
Second part of research attempts to study the influence of the clinical and demographic factors on the progression of brain metabolites over time. In order to understand the influence of these factors in fully non-parametric way, we proposed LongCART algorithm to construct regression tree with longitudinal data. Such a regression tree helps to identify smaller subpopulations (characterized by baseline factors) with differential longitudinal profile and hence helps us to identify influence of baseline factors. Advantage of LongCART algorithm includes: (1) it maintains of type-I error in determining best split, (2) substantially reduces computation time and (2) applicable even observations are taken at subject-specific time-points.
Finally, we carried out an in-depth analysis of longitudinal changes in the brain metabolite concentrations in three brain regions, namely, white matter, gray matter and basal ganglia in chronically infected HIV patients enrolled in HIV Neuroimaging Consortium study. We studied the influence of important baseline factors (clinical and demographic) on these longitudinal profiles of brain metabolites using LongCART algorithm in order to identify subgroup of patients at higher risk of neurological impairment. / Partial research support was provided by the National Institutes of Health grants U01-MH083545, R01-CA126205 and U01-CA086368
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