L’épidémiologie d’intervention a pour objectif la détection précoce des situations d’alerte sanitaire afin d’apporter une aide à la décision pour le déclenchement d’une réponse visant à en limiter l’impact. Dans le domaine de la santé animale, l’épidémiologie d’intervention se développe sous l’influence d’enjeux sanitaires, économiques et de santé publique. La structuration des activités est nécessaire au développement performant de cette discipline.Dans ce contexte, un modèle pour la structuration opérationnelle de l’épidémiologie d’intervention a été développé selon les principes d’une méthode d’optimisation de la performance reconnue : l’approche processus. L’établissement de ce modèle a reposé sur l’identification des chaînes d’activités (processus) d’une épidémiologie d’intervention performante, adaptée à la santé animale, tout en capitalisant les acquis et les avancées de cette discipline dans le domaine de la santé publique. Ces chaînes d’activités ont été identifiées grâce à l’analyse qualitative rétrospective d’expériences en épidémiologie d’intervention dans différents domaines (santé publique, santé publique vétérinaire, santé animale), en réponse à des contextes variés.Ces analyses rétrospectives ont permis d’identifier des chaînes d’activités vectrices de performance en épidémiologie d’intervention. Ces activités ont été intégrées au modèle proposé pour la structuration opérationnelle de cette discipline.L’objectif serait désormais d’assurer la mise en œuvre des chaînes d’activités identifiées via un système intégré global, à même de détecter et de documenter toute maladie animale, ou menace liée aux animaux, et d’informer la prise de mesures adéquates pour son controle / Emerging disease surveillance and investigation aim at the early detection of any health threat in order to perform a comprehensive analysis of the disease situation to help target an appropriate response. Its expansion in the field of animal health is led by major health, economic, and public health drivers. In support of this ongoing development, a standard structure for improved emerging animal disease surveillance and investigation capacities was established. This structure was based on a Business Process Management (BPM) approach.The primary goal of this work was to identify chains of activities (processes) that can support the most successful implementation of emerging animal disease surveillance and investigation, while buidling on the achievements made in the public health area. These chains of activities were identified through a qualitative retrospective analysis of various experiences of emerging disease surveillance and investigation, in the domains of public health, veterinary public health and animal heath, in distinct contexts ranging from a routine investigation to a major sanitary crisis.These analysis resulted in the identification of standard chains of activities that can support a successful implementation of emerging disease surveillance and investigation. These chains of activities were integrated in a standard structure for enhanced emerging animal disease surveillance and investigation capacities.The goal should now be to set up an integrated global system that would routinely implement these chains of activities and allow for the detection and description of any animal disease or threat to help inform prevention and control strategies

This dissertation is motivated by the pressing need for solving real-world large-scale optimization problems with the main objective of developing scalable algorithms that are capable of solving such problems efficiently. Large-scale optimization problems naturally appear in complex systems such as power networks and distributed control systems, which are the main systems of interest in this work. This dissertation aims to address four problems with regards to the theory and application of large-scale optimization problems, which are explained below: Chapter 2: In this chapter, a fast and parallelizable algorithm is developed for an arbitrary decomposable semidefinite program (SDP). Based on the alternating direction method of multipliers, we design a numerical algorithm that has a guaranteed convergence under very mild assumptions. We show that each iteration of this algorithm has a simple closed-form solution, consisting of matrix multiplications and eigenvalue decompositions performed by individual agents as well as information exchanges between neighboring agents. The cheap iterations of the proposed algorithm enable solving a wide spectrum of real-world large-scale conic optimization problems that could be reformulated as SDP. Chapter 3: Motivated by the application of sparse SDPs to power networks, the objective of this chapter is to design a fast and parallelizable algorithm for solving the SDP relaxation of a large-scale optimal power flow (OPF) problem. OPF is fundamental problem used for the operation and planning of power networks, which is non-convex and NP-hard in the worst case. The proposed algorithm would enable a real-time power network management and improve the system's reliability. In particular, this algorithm helps with the realization of Smart Grid by allowing to make optimal decisions very fast in response to the stochastic nature of renewable energy. The proposed algorithm is evaluated on IEEE benchmark systems. Chapter 4: The design of an optimal distributed controller using an efficient computational method is one of the most fundamental problems in the area of control systems, which remains as an open problem due to its NP-hardness in the worst case. In this chapter, we first study the infinite-horizon optimal distributed control (ODC) problem (for deterministic systems) and then generalize the results to a stochastic ODC problem (for stochastic systems). Our approach rests on formulating each of these problems as a rank-constrained optimization from which an SDP relaxation can be derived. We show that both problems admit sparse SDP relaxations with solutions of rank at most~3. Since a rank-1 SDP matrix can be mapped back into a globally-optimal controller, the rank-3 solution may be deployed to retrieve a near-global controller. We also propose computationally cheap SDP relaxation for each problem and then develop effective heuristic methods to recover a near-optimal controller from the low-rank SDP solution. The design of several near-optimal structured controllers with global optimality degrees above 99\% will be demonstrated. Chapter 5: The frequency control problem in power networks aims to control the global frequency of the system within a tight range by adjusting the output of generators in response to the uncertain and stochastic demand. The intermittent nature of distributed power generation in smart grid makes the traditional decentralized frequency controllers less efficient and demands distributed controllers that are able to deal with the uncertainty in the system introduced by non-dispatchable supplies (such as renewable energy), fluctuating loads, and measurement noise. Motivated by this need, we study the frequency control problem using the results developed in Chapter 4. In particular, we formulate the problem and then conduct a case study on the IEEE 39-Bus New England system. The objective is to design a near-global optimal distributed frequency controller for the New England test system by optimally adjusting the mechanical power input to each generator based on the real-time measurement received from neighboring generators through a user-defined communication topology.

Conselho Nacional de Desenvolvimento Científico e Tecnológico / This work presents an optimization methodology for lighting systems that employ LED. Initially, this work brings a calculation methodology capable of obtaining a thermal resistance of heat sink from their dimensions of area, besides enable optimization of the system through reducing their volume by through of change in the number of finned, length and consequently the weight of heat sink. Subsequently, the thesis present a new optimization methodology that has the objective of find the optimal point of operation lighting system taking into consideration the parameters of application current in the device, luminous flux, junction temperature, thermal resistance heat sink, number of LED and lifetime. An example of project is shown, confirming the theory, where the obtained results through of routine calculation coincided with the values found in experimental. The work also present the development of electronic topologies to power a public lighting system employing LED. Therefore, a driver to power of LED based in the integrated two-flyback converters was proposed. One prototype this system was implemented, where the luminaire provide a power of 63W. The experimental results proved the project methodology through of system satisfactory operation, presenting power factor near unit, high efficiency and a low input current distortion was obtained. / Este trabalho apresenta uma metodologia de otimização para sistemas de iluminação que empregam LEDs. Inicialmente, traz-se uma metodologia de cálculos capaz de obter a resistência térmica de dissipadores de calor a partir de suas dimensões de área, além de possibilitar a otimização do sistema através da redução do volume do mesmo por meio da variação do número de aletas, do comprimento e consequentemente da massa do dissipador. Posteriormente o trabalho apresenta uma nova metodologia de otimização que tem o objetivo de encontrar o ponto ótimo de operação do sistema de iluminação, levando-se em conta os parâmetros de corrente direta aplicada no dispositivo, fluxo luminoso, temperatura de junção, resistência térmica do dissipador, número de LEDs e vida útil dos mesmos. Um exemplo de projeto é demonstrado confirmando a teoria apresentada, onde os resultados obtidos através da rotina de cálculos coincidiram com os valores encontrados experimentalmente. O trabalho também apresenta o desenvolvimento de uma topologia eletrônica para alimentar um sistema de iluminação pública empregando LEDs. Dessa maneira, um driver para acionamento de LEDs baseado na integração de dois conversores flyback foi proposto. Um protótipo desse sistema foi implementado, onde a luminária apresenta uma potência de 63W. Resultados experimentais comprovam a metodologia de projeto através da operação satisfatória do sistema, apresentando fator de potência próximo ao unitário, elevada eficiência e o conteúdo harmônico da corrente de entrada do sistema de iluminação atendeu a norma.

El trabajo presentado en esta Tesis está motivado por la necesidad de los motores de combustión interna alternativos de reducir el consumo de combustible y las emisiones de CO2 mientras se satisfacen las cada vez más restrictivas regulaciones de emisiones contaminantes. Por lo tanto, el objetivo principal de este estudio es optimizar un sistema de combustión de encendido por compresión controlado por mezcla para probar su potencial como motores de futura generación. Con esta meta se ha desarrollado un sistema automático que combina CFD con métodos de optimización avanzados para analizar y entender las configuraciones óptimas. Los resultados presentados en este trabajo se dividen en dos bloques principales. El primero corresponde a la optimización de un sistema de encendido por compresión convencional alimentado con diésel. El segundo se centra en un concepto de combustión avanzado donde se ha sustituido el fuel por Dimetil-eter. En ambos casos, el estudio no sólo halla una configuración óptima sino que también se describen las relaciones causa/efecto entre los parámetros más relevantes del sistema de combustión. El primer bloque aplica métodos de optimización no-evolutivos a un motor medium-duty alimentado por diésel tratando de minimizar consumo a la vez que se mantienen las emisiones contaminantes por debajo de los estándares de emisiones contaminantes impuestos. Una primera parte se centra en la optimización de la geometría de la cámara de combustión y el inyector. Seguidamente se extiende el estudio añadiendo los settings de renovación de la carga de y de inyección al estudio, ampliando el potencial de la optimización. El estudio demuestra el limitado potencial de mejora de consumo que tiene el motor de referencia al mantener los niveles de emisiones contaminantes. Esto demuestra la importancia de incluir parámetros de renovación de la carga e inyección al proceso de optimización. El segundo bloque aplica una metodología basada en algoritmos genéticos al diseño del sistema de combustión de un motor heavy-duty alimentado con Dimetileter. El estudio tiene dos objetivos, primero la optimización de un sistema de combustión convencional controlado por mezcla con el objetivo de lograr mejorar el consumo y reducir las emisiones contaminantes hasta niveles inferiores a los estándares US2010. Segundo la optimización de un sistema de combustión trabajando en condiciones estequiométricas acoplado con un catalizador de tres vías buscando reducir consumo y controlar las emisiones contaminantes por debajo de los estándares 2030. Ambas optimizaciones incluyen tanto la geometría como los parámetros más relevantes de renovación de la carga y de inyección. Los resultados presentan un sistema de combustión convencional óptimo con una notable mejora en rendimiento y un sistema de combustión estequiométrica que es capaz de ofrecer niveles de NOx menores al 1% de los niveles de referencia manteniendo niveles competitivos de rendimiento. Los resultados presentados en esta Tesis ofrecen una visión extendida de las ventajas y limitaciones de los motores MCCI y el camino a seguir para reducir las emisiones de futuros sistemas de combustión por debajo de los estándares establecidos. A su vez, este trabajo también demuestra el gran potencial que tiene el Dimetil-eter como combustible para futuras generaciones de motores. / The work presented in this Thesis was motivated by the needs of internal combustion engines (ICE) to decrease fuel consumption and CO2 emissions, while fulfilling the increasingly stringent pollutant emission regulations. Then, the main objective of this study is to optimize a mixing-controlled compression ignition (MCCI) combustion system to show its potential for future generation engines. For this purpose an automatic system based on CFD coupled with different optimization methods capable of optimizing a complete combustion system with a reasonable time cost was designed together with the methodology to analyze and understand the new optimum systems. The results presented in this work can be divided in two main blocks, firstly an optimization of a conventional diesel combustion system and then an optimization of a MCCI system using an alternative fuel with improved characteristics compared to diesel. Due to the methodologies used in this Thesis, not only the optimum combustion system configurations are described, but also the cause/effect relations between the most relevant inputs and outputs are identified and analyzed. The first optimization block applies non-evolutionary optimization methods in two sequential studies to optimize a medium-duty engine, minimizing the fuel consumption while fulfilling the emission limits in terms of NOx and soot. The first study targeted four optimization parameters related to the engine hardware including piston bowl geometry, injector nozzle configuration and mean swirl number. After the analysis of the results, the second study extended to six parameters, limiting the optimization of the engine hardware to the bowl geometry, but including the key air management and injection settings. The results confirmed the limited benefits, in terms of fuel consumption, with constant NOx emission achieved when optimizing the engine hardware, while keeping air management and injection settings. Thus, including air management and injection settings in the optimization is mandatory to significantly decrease the fuel consumption while keeping the emission limits. The second optimization block applies a genetic algorithm optimization methodology to the design of the combustion system of a heavy-duty Diesel engine fueled with dimethyl ether (DME). The study has two objectives, the optimization of a conventional mixing-controlled combustion system aiming to achieve US2010 targets and the optimization of a stoichiometric mixing-controlled combustion system coupled with a three way catalyst to further control NOx emissions and achieve US2030 emission standards. These optimizations include the key combustion system related hardware, bowl geometry and injection nozzle design as input factors, together with the most relevant air management and injection settings. The target of the optimizations is to improve net indicated efficiency while keeping NOx emissions, peak pressure and pressure rise rate under their corresponding target levels. Compared to the baseline engine fueled with DME, the results of the study provide an optimum conventional combustion system with a noticeable NIE improvement and an optimum stoichiometric combustion system that offers a limited NIE improvement keeping tailpipe NOx values below 1% of the original levels. The results presented in this Thesis provide an extended view of the advantages and limitations of MCCI engines and the optimization path required to achieve future emission standards with these engines. Additionally, this work showed how DME is a promising fuel for future generation engines since it is able to achieve future emission standards while maintaining diesel-like efficiency / El treball presentat en esta Tesi està motivat per la necessitat dels motors de combustió interna alternatius de reduir el consum de combustible i les emissions de CO2 mentres se satisfan les cada vegada mes restrictives regulacions d'emissions contaminants. Per tant, l'objectiu principal d'este estudi es optimitzar un sistema de combustió d'encesa per compressió controlat per mescla per a provar el seu potencial com a motors de futura generació. Amb esta meta s'ha desenrotllat un sistema automàtic que combina CFD amb mètodes d'optimització avançats per a analitzar i entendre les configuracions òptimes. Els resultats presentats en este treball es dividixen en dos blocs principals. El primer correspon a l'optimització d'un sistema d'encesa per compressió convencional alimentat amb dièsel. El segon se centra en un concepte de combustió avançat on s'ha substituït el fuel per Dimetil-eter. En ambdós casos, l'estudi no sols troba una configuració òptima sinó que també es descriuen les relacions causa/efecte entre els paràmetres més rellevants del sistema de combustió. El primer bloc aplica mètodes d'optimització no-evolutius a un motor mediumduty alimentat per dièsel tractant de minimitzar consum al mateix temps que es mantenen les emissions contaminants per davall dels estàndards d'emissions contaminants impostos. Una primera part se centra en l'optimització de la geometria de la cambra de combustió i l'injector. A continuació s'estén l'estudi afegint els settings de renovació de la càrrega de i d'injecció a l'estudi, ampliant el potencial de l'optimització. L'estudi demostra el limitat potencial de millora de consum que té el motor de referència al mantindre els nivells d'emissions contaminants. Açò demostra la importància d'incloure paràmetres de renovació de la càrrega i injecció al procés d'optimització. El segon bloc aplica una metodologia basada en algoritmes genètics al disseny del sistema de combustió d'un motor heavy-duty alimentat amb Dimetil-eter. L'estudi té dos objectius, primer l'optimització d'un sistema de combustió convencional controlat per mescla amb l'objectiu d'aconseguir millorar el consum i reduir les emissions contaminants fins nivells inferiors als estàndards US2010. Segon l'optimització d'un sistema de combustió treballant en condicions estequiomètriques acoblat amb un catalitzador de tres vies buscant reduir consum i controlar les emissions contaminants per davall dels estàndards 2030. Ambdós optimitzacions inclouen tant la geometria com els paràmetres més rellevants de renovació de la càrrega i d'injecció. Els resultats presenten un sistema de combustió convencional òptim amb una notable millora en rendiment i un sistema de combustió estequiomètrica que és capaç d'oferir nivells de NOx menors al 1% dels nivells de referència mantenint nivells competitius de rendiment. Els resultats presentats en esta Tesi oferixen una visió estesa dels avantatges i limitacions dels motors MCCI i el camï que s'ha de seguir per a reduir les emissions de futurs sistemes de combustió per davall dels estàndards establits. Al seu torn, este treball també demostra el gran potencial que té el Dimetil-eter com a combustible per a futures generacions de motors. / Hernández López, A. (2018). Optimization and analysis by CFD of mixing-controlled combustion concepts in compression ignition engines [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/103826 / TESIS

Statistical research can be more difficult to plan than other kinds of projects, since the research must adapt as knowledge is gained. This dissertation establishes a formal language and methodology for designing experimental research strategies with limited resources. It is a mathematically rigorous extension of a sequential and adaptive form of statistical research called response surface methodology. It uses sponsor-given information, conditions, and resource constraints to decompose an overall project into individual stages. At each stage, a "parent" decision-maker determines what design of experimentation to do for its stage of research, and adapts to the feedback from that research's potential "children", each of whom deal with a different possible state of knowledge resulting from the experimentation of the "parent". The research of this dissertation extends the real-world rigor of the statistical field of design of experiments to develop an deterministic, adaptive algorithm that produces deterministically generated, reproducible, testable, defendable, adaptive, resource-constrained multi-stage experimental schedules without having to spend physical resource.

Submitted by Renata Lopes (renatasil82@gmail.com) on 2016-04-06T14:20:59Z No. of bitstreams: 1 israelfilipelopes.pdf: 3821077 bytes, checksum: 03973b1d4356ce4b46316762af40ac71 (MD5) / Approved for entry into archive by Adriana Oliveira (adriana.oliveira@ufjf.edu.br) on 2016-04-24T03:51:36Z (GMT) No. of bitstreams: 1 israelfilipelopes.pdf: 3821077 bytes, checksum: 03973b1d4356ce4b46316762af40ac71 (MD5) / Made available in DSpace on 2016-04-24T03:51:36Z (GMT). No. of bitstreams: 1 israelfilipelopes.pdf: 3821077 bytes, checksum: 03973b1d4356ce4b46316762af40ac71 (MD5) Previous issue date: 2013-02-26 / Este trabalho apresenta um estudo sobre transferência de energia elétrica sem contato para carregamento de baterias de veículos autônomos subaquáticos (AUV - Autonomous Underwater Vehicles) utilizando transformadores de núcleo separado (TNS). Inicialmente, é feito um projeto para construção de um transformador de núcleo separado. Posteriormente, são desenvolvidas as equações que modelam o funcionamento do transformador, com base em seu circuito elétrico equivalente. Em seguida, o trabalho propõe uma alternativa para estimar os parâmetros do circuito equivalente do transformador operando com valores de entreferro diferentes, validando seu modelo matemático aproximado com simulações realizadas no software PSIM, versão 9.0. Com o modelo matemático do TNS, é feita uma avaliação da sua capacidade de transferência de energia, mostrando que, em virtude do entreferro, o transformador apresenta baixa eficiência e baixos valores de tensão de saída. Nesse sentido, metodologias para compensar os efeitos de queda de tensão na impedância de dispersão, bem como aumentar a eficiência do transformador, são investigadas introduzindo-se capacitâncias no circuito elétrico equivalente e variando-se a frequência de operação. Aplicando os resultados dessa metodologia de otimização, é mostrado, por meio de experimentos em laboratório, que o TNS é capaz de transmitir energia através de um entreferro de 10 mm, atendendo às condições de tensão e potência da carga, com eficiência relativamente elevada. Em seguida, é feito um experimento com água do mar a fim de verificar a aplicabilidade do TNS em veículos subaquáticos. Por fim, é apresentada uma simulação digital realizada no software PSIM, versão 9.0, com um conversor c.c./c.c. controlador de carga para o sistema de carregamento de bateria. Os resultados obtidos demonstram o funcionamento do sistema, verificando a metodologia para estimativa do modelo e a metodologia de otimização do TNS. / This work presents a study on contactless electrical energy power transfer for charging batteries of autonomous underwater vehicles (AUV - Autonomous Underwater Vehicles) using transformers with separated core (TNS). Initially, a project is made for building a transformer with separated core. After, the equations that model the operation of the transformer, based on its electrical equivalent circuit, are developed. Then, the work proposes an alternative to estimate the parameters of the equivalent circuit of the transformer operating with different gap values, validating its mathematical model with simulations in PSIM software, version 9.0. With the mathematical model of TNS, an evaluation of its ability to transfer power is made, showing that, because of the air gap, the transformer has a low efficiency and low output voltage. Therefore, methodologies to compensate for the effects of voltage drop in the leakage impedance and increase the efficiency of the transformer are investigated by introducing capacitances in the equivalent circuit and varying the of operating frequency. Applying the results of optimization methodology is shown, through laboratory experiments, that the TNS is capable of transmitting power through an air gap of 10 mm, given the voltage and load power conditions, with relatively high efficiency. Then, an experiment is done with seawater in order to verify the applicability of TNS for underwater vehicles. Finally, the work presents a simulation in PSIM with a d.c./d.c. charge controller for battery. The results demonstrate the operation of the system, verifying the methodology for estimation of the model and optimization methodology of TNS.