Considere $N$ pontos distribuídos de forma aleatória e uniforme num hipercubo $d$-dimensional. Cada ponto representa um sítio num meio desordenado. Um caminhante explora este meio saltando para os sítios mais próximos, que não tenham sido visitados nos últimos $\\mu$ (memoria) passos, inclusive o próprio sítio. A trajetória do caminhante é composta de uma parte transiente e de uma parte periódica (ciclos). Neste caso, o viajante pode ou não explorar todos espaço disponível. A partir de uma memória crítica, ocorre uma transição entre os regimes de exploração localizado e estendido. Para sistemas unidimensionais, essa transição ocorre na memória crítica $\\mu_1=\\log_2{N}$. A regra determinista pode ser suavizada, a fim de considerar situações mais realistas, com a inclusão do parâmetro estocástico $T$ (temperatura). Agora, os movimentos do caminhante são definidos por uma função densidade de probabilidade (PDF) que é parametrizada por $T$ e por uma função custo, que cresce à medida que a distância entre os sítios cresce. A PDF é escolhida de forma a favorecer saltos para sítios mais próximos. Com o aumento da temperatura, o caminhante pode sair de ciclos e estender sua exploração. Aqui, nós apresentamos os estudos analíticos e numéricos sobre a influência da temperatura e da memória crítica na exploração de um meio desordenado unidimensional. / Consider $N$ sites randomly and uniformly distributed in a $d$-dimensional hypercube. A walker explores this disordered medium going to the nearest site, which has not been visited in the last $\\mu$ (memory) steps. The walker trajectory is composed of a transient part and a periodic part (cycles). In this case, travelers can or cannot explore all available space, given rise to a crossover at critical memory, for one-dimensional systems $\\mu_1=\\log_2{N}$, between localized and extended regimes. % as function of $\\mu$. The deterministic rule can be softened to consider more realistic situations with the inclusion of a stochastic parameter $T$ (temperature). In this case, the walker movement is defined by a probability density function (PDF) that is parameterized by $T$ and a cost function, which increases as the distance among sites increases. The PDF is chosen to favor hops to nearest sites. As the temperature increases, the walker can escape from cycles and extend the exploration. Here we report the analytical and numerical studies of the influence of the temperature and the critical memory in the exploration of a one-dimensional disordered system.

Esta pesquisa trata do desenvolvimento de uma estrutura conceitual para um framework de maturidade, para o domínio de ecossistemas digitais de produção de software, utilizando a pesquisa-ação como paradigma de pesquisa. A estrutura de medição proposta tem como base o critério descrito no item 5 da Norma ISO/IEC 15504-2 Uma Estrutura de Medição para a capacidade de processo, com as adaptações necessárias para o domínio do Software Publico Brasileiro (SPB). O framework tem como objetivo o desenvolvimento de referências conceituais para um modelo de maturidade de um ecossistema público de software, considerando as referências do pensamento sistêmico. A abordagem do pensamento sistêmico permitiu identificar que o ecossistema evolui em ciclos de aprendizado que resultaram em um modelo de maturidade. Foi observado também que a mesma abordagem pode ser utilizada em outros ecossistemas. O objeto de pesquisa, o ecossistema do SPB, é uma experiência inovadora na administração pública, que combina características do modelo de produção de software livre com o conceito de bens públicos e é entregue por um portal que une pessoas e interesses diferentes. O portal do SPB é um espaço virtual para disseminação e aprimoramento de ferramentas de software. Em algumas comunidades acontecem atividades de desenvolvimento de novas funcionalidades ou mesmo de novas versões de ferramentas. Portanto, acontecem processos de desenvolvimento de software, porém ainda sem um processo de qualidade instituído. O desenvolvimento da pesquisa utilizou como referências teóricas frameworks de modelos de maturidade de processos, framework de métodos para construção de modelos, conceitos de sistemas complexos, pensamento sistêmico e ecossistemas digitais. A metodologia de pesquisa utilizada foi a pesquisa-ação e o trabalho de campo teve a duração de dois anos. / This research project addresses the development of a conceptual structure to measure the quality of software production in the digital ecosystem domain, using the action research paradigm. The proposed measurement framework is based on the criteria described in item 5 of ISO / IEC 15504-2 - A Measurement Framework for process capability, with the necessary adaptations to the Public Domain Software (PDS). Development of the structure aims to contribute to the creation of conceptual references for a maturity model for a public software development ecosystem, using the literature on Systems Thinking. The Systems Thinking Approach identified the ecosystem evolves in learning cycles that resulted in a maturity model. It was also observed that the same approach can be used in other ecosystems. The research object is the Brazilian Public Software Ecosystem (BPS), an innovative experience in public administration that combines features of the free software production model with the concept of public goods and is delivered by a portal that links different people and interests. The BPS portal is a virtual space for the development, dissemination and enhancement of software by software communities. These communities engage in activities involving the development of new functionality or even new versions of solutions. Thus they involve software development processes but without a minimum of quality assurance. The theoretical references for the research project ranged from frameworks for process maturity models and frameworks for model construction to concepts of complex systems, systemic thinking and digital ecosystems. The research methodology used was action research and the field work had duration of two years.

Em distintos momentos da história, pesquisadores investigaram e propuseram, com relativo sucesso, modelos locacionais que explicassem a origem e os processos dos crescimentos das cidades, mas, de modo frequente, esbarrando na complexidade desses sistemas. Recentemente, apoiados nas teorias sobre Sistemas Complexos, Nova Geografia Econômica e Modelos Configuracionais Urbanos, alguns conceitos proporcionam uma fundamentação mais consistente para a verificação das variáveis e suas interações espaciais, as quais identifiquem esses processos. Dentre os sistemas complexos, são representativos os conceitos sobre a resiliência e a criticalidade auto-organizada enquanto os conceitos do modelo centro-periferia, propostos pela nova geografia econômica, contribuem para compreensão das formações de aglomerações econômicas e populacionais. Tais abordagens conduzem ao desenvolvimento da hipótese de que a localização relativa dos serviços urbanos e dos moradores, no espaço intraurbano, estaria condicionada a duas forças que se contrapõem, “centrípeta e centrífuga”, que são geradoras de “tensões” as quais conduzem o sistema a atingir níveis críticos por determinados períodos até que novas condições movam o sistema, de maneira surpreendente, a um novo limiar. O processo de crescimento do sistema urbano seria, assim, sujeito às variações de densidades populacionais e das localizações dos diferentes serviços urbanos e suas externalidades econômicas existentes na cidade. A averiguação e os comportamentos destas forças foram testados em uma situação real, na cidade de Santa Maria – RS. Os dados populacionais e dos serviços urbanos foram espacializados recorrendo a um Sistema de Informação Geográfica – SIG e suas interações avaliadas com o uso de medidas configuracionais urbanas. Espera-se, com isso, contribuir para a consolidação do conhecimento da dinâmica urbana e das condições dos diversos estados do sistema urbano. / At different times, researchers have investigated and proposed, with relative success, locational models that explain the origin and the processes of urban growth, but, often, failing to account for the complexity of these systems. Recently, the theories of Complex Systems, New Economic Geography and Urban Configurational Models, have provided concepts with a more consistent rationale for checking variables and the spatial interactions that identify these processes. The Complex Systems framework has provided the concepts of resiliency and self-organized criticality, whereas New Economic Geography has furnished the center-periphery model, which aids in understanding economic and population agglomerations. These approaches support the hypothesis that the relative location of urban services and residents in the intraurban space is subject to centripetal and centrifugal forces, which generate tensions that lead the system toward critical levels for determined periods until new conditions move the system, unexpectedly, to a new threshold. The growth process of the urban system is thus subject to variations in population density and in localization of the different urban services and their economic externalities that exist in the city. The behaviors of these forces were tested in a real situation, in the city of Santa Maria, RS. Population and urban services data were spatialized using a Geographic Information System – GIS and their interactions were evaluated with the use of urban configurational measures to contribute to our knowledge of urban dynamics and the conditions of the various states of the urban system.

O aprendizado de máquina consiste de conceitos e técnicas que permitem aos computadores melhorar seu desempenho com a experiência, ou, em outras palavras, aprender com dados. Um dos principais tópicos do aprendizado de máquina é o agrupamento de dados que, como o nome sugere, procura agrupar os dados de acordo com sua similaridade. Apesar de sua definição relativamente simples, o agrupamento é uma tarefa computacionalmente complexa, tornando proibitivo o emprego de algoritmos exaustivos, na busca pela solução ótima do problema. A importância do agrupamento de dados, aliada aos seus desafios, faz desse campo um ambiente de intensa pesquisa. Também a classe de fenômenos naturais conhecida como comportamento coletivo tem despertado muito interesse. Isso decorre da observação de um estado organizado e global que surge espontaneamente das interações locais presentes em grandes grupos de indivíduos, caracterizando, pois, o que se chama auto-organização ou emergência, para ser mais preciso. Os desafios intrínsecos e a relevância do tema vêm motivando sua pesquisa em diversos ramos da ciência e da engenharia. Ao mesmo tempo, técnicas baseadas em comportamento coletivo vêm sendo empregadas em tarefas de aprendizado de máquina, mostrando-se promissoras e ganhando bastante atenção. No presente trabalho, objetivou-se o desenvolvimento de técnicas de agrupamento baseadas em comportamento coletivo. Faz-se cada item do conjunto de dados corresponder a um indivíduo, definem-se as leis de interação local, e então os indivíduos são colocados a interagir entre si, de modo que os padrões que surgem reflitam os padrões originalmente presentes no conjunto de dados. Abordagens baseadas em dinâmica de troca de energia foram propostas. Os dados permanecem fixos em seu espaço de atributos, mas carregam certa informação a energia , a qual é progressivamente trocada entre eles. Os grupos são estabelecidos entre dados que tomam estados de energia semelhantes. Este trabalho abordou também o aprendizado semissupervisionado, cuja tarefa é rotular dados em bases parcialmente rotuladas. Nesse caso, foi adotada uma abordagem baseada na movimentação dos próprios dados pelo espaço de atributos. Procurou-se, durante todo este trabalho, não apenas propor novas técnicas de aprendizado, mas principalmente, por meio de muitas simulações e ilustrações, mostrar como elas se comportam em diferentes cenários, num esforço em mostrar onde reside a vantagem de se utilizar a dinâmica coletiva na concepção dessas técnicas / Machine learning consists of concepts and techniques that enable computers to improve their performance with experience, i.e., enable computers to learn from data. Data clustering (or just clustering) is one of its main topics, which aims to group data according to their similarities. Regardless of its simple definition, clustering is a complex computational task. Its relevance and challenges make this field an environment of intense research. The class of natural phenomena known as collective behavior has also attracted much interest. This is due to the observation that global patterns may spontaneously arise from local interactions among large groups of individuals, what is know as self-organization (or emergence). The challenges and relevance of the subject are encouraging its research in many branches of science and engineering. At the same time, techniques based on collective behavior are being employed in machine learning tasks, showing to be promising. The objective of the present work was to develop clustering techniques based on collective behavior. Each dataset item corresponds to an individual. Once the local interactions are defined, the individuals begin to interact with each other. It is expected that the patterns arising from these interactions match the patterns originally present in the dataset. Approaches based on dynamics of energy exchange have been proposed. The data are kept fixed in their feature space, but they carry some sort of information (the energy), which is progressively exchanged among them. The groups are established among data that take similar energy states. This work has also addressed the semi-supervised learning task, which aims to label data in partially labeled datasets. In this case, it has been proposed an approach based on the motion of the data themselves around the feature space. More than just providing new machine learning techniques, this research has tried to show how the techniques behave in different scenarios, in an effort to show where lies the advantage of using collective dynamics in the design of such techniques

Orientador: Renato Pavanello / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia mecanica / Made available in DSpace on 2018-08-04T08:49:46Z (GMT). No. of bitstreams: 1 PoelFilho_CornelisJoannesvander_D.pdf: 8296875 bytes, checksum: 048da8ba9cfe029f98229ac0b593f989 (MD5) Previous issue date: 2005 / Resumo: Microsistemas eletromecânicos geralmente têm seu princípio de funcionamento baseado na interação entre dois ou mais campos físicos. Para seu projeto são necessárias ferramentas de simulação multi-domínios. Este trabalho visa estudar o fenômeno de acoplamento eletromecânico em microsistemas e construir uma ferramenta de simulação numérica para este tipo de problema. São apresentados métodos de análise estática, modal e transiente baseados em modelos de elementos finitos e de ordem reduzida. Na análise estática cada domínio é resolvido separadamente. Foi mostrado um método de transferência das forças eletrostáticas para o domínio mecânico e proposto e testado um esquema de atualização da malha elétrica. Para a análise dinâmica transiente foi implementado um método de Newmark adaptado de forma a considerar os efeitos do acoplamento eletromecânico. Outro método de análise dinâmica apresentado é baseado numa estratégia de perturbação do sistema em equilíbrio em conjunto com a resolução de um problema de autovalor / autovetor. O método de perturbação fornece diretamente as freqüências naturais de vibração do sistema acoplado. A técnica de redução de ordem apresentada é baseada numa projeção de Galerkin da equação diferencial governante utilizando como funções de base os modos empíricos do sistema dinâmico. Um programa computacional para modelagem numérica multi-domínios com solução particionada para o acoplamento eletromecânico foi proposto e implementado. O código computacional, denominado MefLab, onde os métodos numéricos foram programados, usa o paradigma de orientação a objetos e a linguagem C++. Resultados com as diversas metodologias são mostrados e analisados / Abstract: Microelectromechanical systems have their working principIes based on the interaction between two or more physical fields. To design them, multi-physics simulation tools are needed. This work aims to study the coupled field effects in microsystems and build a computer code for numerical simulation of this problem. Static, dynamic modal and transient methods are introduced. They are based on finite elements and reduced order models. The static analysis is done by a staggered treatment. A method for transfering electrostatic pressures to the mechanical domain was shown and a mesh updating scheme was proposed and tested. For the transient analysis, in order to consider the electromechanical coupling effects, an adaptation was inserted in the classical Newmark direct integration method. A dynamical modal method based in a perturbation strategy was presented. It involves the staggered static algorithm and the solution of an eigenvalue/eigenvector problem. This method is able to give the natural coupled frequencies of the system with low computational costs. A reduced order modeI was constructed by using a Galekin projection of the governing differential equations in an empirical basis. This basis was obtained through results of transient finite element analysis. A multi-domain project with staggered procedures for the electromechanical coupling was proposed and implemented. It refers to the software MefLab++, a computer code written in C++ where numerical strategies are programmed according to the oriented object paradigm. Numerical results for the static, dynamic modal and transient methodologies are shown / Doutorado / Mecanica dos Sólidos e Projeto Mecanico / Doutor em Engenharia Mecânica

Au cours des dernières décennies, avec un fort développement de l'économie mondiale et des nouvelles technologies, la structure des systèmes industriels devient de plus en plus complexe. Elle peut être une combinaison des structures élémentaires telles que structures séries, structures parallèles, structures séries-parallèles, etc. Dans la littérature, la plupart des travaux s'intéressent à développer des stratégies de regroupement en considérant des structures séries. Cette hypothèse est parfois très pénalisée et se limite l'application de ces stratégies dans la réalité. C'est pourquoi, l'objectif principal de cette thèse est de développer des stratégies de regroupement (dynamique et stationnaire) pour la maintenance des systèmes multi-composants avec structure complexe. Ces stratégies développées se basent sur des modèles de durée de vie avec la durée de maintenance non-négligeable. De plus, les conditions dynamiques (contextes dynamiques) telles que opportunités de faire la maintenance, changements de la structure, etc. sont étudiées et intégrées dans la planification de maintenance. Les études montrent la nécessité et les difficultés de la prise en compte de la structure complexe dans les décisions de maintenance. Exemples numériques confirment les avantages de nos stratégies de maintenance en comparant avec les autres stratégies existantes dans la littérature / In the recent decades, with a strong development of the global economy and new technologies, the structure of industrial systems is more and more complex. It can be a combination of elementary structures such as series structures, parallel structures, series-parallel structures, etc. In the literature, the most work focused on developing grouping strategies by considering series structures. This assumption is sometimes much penalized and limited the application of these strategies in reality. Therefore, the main objective of this thesis is to develop dynamic and stationary grouping strategies for the maintenance of multi-component systems with complex structure. These strategies have been developed for age-based models with non-negligible maintenance durations. In addition, dynamic conditions (dynamic context) such as maintenance opportunities, changes of the structure, etc., are considered and integrated into the maintenance scheduling.Our studies show the necessity and the difficulties of taking into account of the complex structure in the maintenance decisions. Numerical examples confirm the advantages of our maintenance strategies by comparing with other existing strategies in the literature

Dans le contexte actuel de globalisation des marchés, le processus classique de conception par essais et erreurs n'est plus capable de répondre aux exigences de plus en plus accrues en termes de délais très courts, réduction des coûts de production, etc. L'outil d'optimisation propose une réponse à ces questions, en accompagnant les ingénieurs dans la tâche de conception optimale.L'objectif de cette thèse est centré sur la conception optimale des systèmes complexes. Deux approches sont abordées dans ce travail: l'optimisation par modèles de substitution et la conception optimale basée sur la décomposition des systèmes complexes.L'utilisation de la conception assistée par ordinateur (CAO) est devenue une pratique régulière dans l’industrie. La démarche d'optimisation basée sur modèles de substitution est destinée à répondre à l'optimisation des dispositifs bénéficiant d’une telle modélisation précise, mais couteuse en temps de calcul.Les chaînes de traction ferroviaire sont trop complexes pour être traités comme un tout. La décomposition de ces systèmes s’impose en vue de simplifier le problème et de repartir la charge de calcul. Des stratégies appropries à la résolution de telles structures ont été analysées dans ce travail. Ces approches permettent à chaque équipe de spécialistes de travailler de façon autonome à l'objet de leur expertise.Les approches d'optimisation développées au sein de ce travail ont été appliquées pour résoudre plusieurs problèmes d'optimisation électromagnétiques, ainsi que la conception optimale d’un système de traction ferroviaire de la Société Alstom / Within a globalized market context, the classical trial-and-error design process is no longer capable of answering to the ever-growing demands in terms of short deadlines, reduced production costs, etc. The optimization tool presents itself as an answer to these issues, accompanying the engineers in the optimal design task.The focus of this thesis is centered on the optimal design of complex systems. Two main optimization approaches are addressed within this work: the metamodel-based design optimization and the decomposition-based complex systems optimal design.The use of computer-aided design/engineering (CAD/CAE) software has become a regular practice in the engineering design process. The metamodel-based optimization approach is intended to address the optimization of devices represented by such accurate but computationally expensive simulation models, as the finite element analysis (FEA) in electromagnetics.Engineering systems such as railway traction systems are too complex to be addressed as a whole. The decomposition-based optimization strategies are intended to address the optimal design of such systems. The decomposition of such systems is required in order to simplify the problem and to distribute the computational burden across the decomposed structure. Appropriate multi-level strategies have been identified and analyzed within this work. Such approaches allow each team of specialists to work independently at the object of their expertise.The optimization approaches developed within this work are applied for solving several electromagnetic optimization problems and a railway traction system optimal design problem of the Alstom Company

Les travaux effectués dans le cadre de cette thèse présentent une nouvelle approche permettant d’estimer et si possible minimiser l’écart maximum de la sortie par rapport à l’objectif dans le cas des processus non linéaires pour lesquels il n’est pas toujours possible de déterminer une commande permettant d’atteindre exactement un objectif donné.Le concept de norme vectorielle, associé à la définition des systèmes de comparaison par l'approche de la stabilité Borne et Gentina, et le choix de la représentation matricielle qui s’avère particulièrement importante pour l’étude de la stabilité, est proposé dans ce travail, avec succès, pour étudier la stabilité des processus complexes de modèles éventuellement incertainsNous avons défini une technique d’estimation des attracteurs caractérisant le maximum de l’erreur par rapport à l’objectif et par la prise en compte des résultats ainsi obtenus de les affiner par des itérations successives de la procédure présentée.Dans la recherche de commandes, l’approche a été réalisée en définissant celle-ci par retours d’état calculés soit directement, soit à partir d’une linéarisation du modèle du processus dans le voisinage de l’objectif. Une attention toute particulière a été accordée aux processus du type Lur’e Postnikov / A new approach of the estimation of the error between the desired output of a nonlinear complex system and the real one’s is studied by the use of Borne-Gentina vector norm approach and the Benrejeb arrow form description.A new technique of definition of the attractors characterizing the precision of control laws is defined, implementing successive improved determinations. The research of control laws by various types of state or output feedback in presence of uncertainties is proposed, based on a local linearization and control of the system.A special attention has been devoted to the control of nonlinear Lur’e Postnikov type systems

In view of the fact that a same complex phenomenon can be approached by different conceptual frameworks, it is natural to inquire on the possibility to find connections between different types of quantities, such as topological, dynamical, statistical or thermodynamical, characterizing the same system. The present work is built on the idea that this line of approach can provide interesting insights on possible universal principles governing complex phenomena. In Chapter I we introduce concepts and tools of dynamical systems and thermodynamics as applied in macroscopic scale description as well as, for a later use, a number of selected representative models. In Chapter II we briefly present the elements of the theory of Markov processes describing a large class of stochastic process and also introduce some important concepts on the probabilistic description of deterministic systems. This chapter ends with a thermodynamic formulation accounting for the evolution of the entropy under the effect of stochastic fluctuations. In Chapter III, after introducing the main concepts and recent advances in network theory, we provide a connection between dynamical systems and network theory, which shows how universal structural properties of evolving networks can arise from deterministic dynamics. More specifically, we show explicitly the relation between the connectivity patterns of these networks and the indicators of the underlying dynamics, such as the local Lyapunov exponents. Our analysis is applied to representative models of chaotic maps, chaotic flows and is finally extended to stochastic processes. In Chapter IV we address the inverse problem, namely, processes whose dynamics is determined, in part, by the structure of the network in which they are embedded. In particular, we focus on systems of particles diffusing on a lattice and reacting instantaneously upon encountering each other. We study the role of the topology, the degree of synchronicity of motion and the reaction mechanism on the efficiency of the process. This lead us to identify a common generic mechanism responsible for the behavior of the efficiency, as a function of the control parameters. Finally, in Chapter V we study the connection between the topology and the thermodynamic properties of reaction networks, with focus on the entropy production and the system’s efficiency at nonequilibrium steady states. We also explore the connection between dynamic and thermodynamic properties of nonlinear feedbacks, as well as the response properties of reaction networks against both deterministic and stochastic external perturbations. We address networks of varying topologies, from regular lattices to complex structures./Le présent travail s’inscrit dans le domaine de recherche sur les systèmes complexes. Différentes approches, basées des systèmes dynamiques, de la thermodynamique des systèmes hors d’équilibre, de la physique statistique et, plus récemment, de la théorie des réseaux, sont combinés afin d’explorer des liens entre différentes types de grandeurs qui caractérisent certaines classes de comportements complexes. Dans le Chapitre I nous introduisons les principaux concepts et outils de systèmes dynamiques et de thermodynamique. Dans le Chapitre II nous présentons premièrement des éléments de la théorie de processus de Markov, ainsi que les concepts à la base de la description probabiliste des systèmes déterministes. Nous finissons le chapitre en proposant une formulation thermodynamique qui décrit l’évolution de l’entropie hors d’équilibre, soumis à l’influence de fluctuations stochastiques. Dans le Chapitre III nous introduisons les concepts de base en théorie des réseaux, ainsi qu’un résumé générale des progrès récents dans le domaine. Nous établissons ensuite une connexion entre la théorie des systèmes dynamiques et la théorie de réseaux. Celle-ci permet d’approfondir la compréhension des mécanismes responsables de l’émergence des propriétés structurelles dans des réseaux crées par des lois dynamiques déterministes. En particulier, nous mettons en évidence la relation entre des motifs de connectivité de ce type de réseaux et des indicateurs de la dynamique sous-jacente, tel que des exposant de Lyapounov locaux. Notre analyse est illustrée par des applications et des flots chaotiques et étendue à des processus stochastiques. Dans le Chapitre IV nous étudions le problème complémentaire, à savoir, celui de processus dont la dynamique est déterminée, en partie, par la structure du réseau dans lequel elle se déroule. Plus précisément, nous nous concentrons sur le cas de systèmes de particules réactives, diffusent au travers d’un réseau et réagissant instantanément lorsqu’un rencontre se produit entre elles. Nous étudions le rôle de la topologie, du degré de synchronicité des mouvements et aussi celui du mécanisme de réaction sur l’efficacité du processus. Dans les différents modèles étudiés, nous identifions un mécanisme générique commun, responsable du comportement de l’efficacité comme fonction des paramètres de contrôle. Enfin, dans le Chapitre V nous abordons la connexion entre la topologie et les propriétés thermodynamiques des réseaux de réactions, en analysant le comportement local et global de la production d’entropie et l’efficacité du système dans des état stationnaires de non-équilibre. Nous explorons aussi la connexion entre la dynamique et les propriétés de boucles de rétroaction non linéaires, ainsi que les propriétés de réponse des réseaux de réaction à des perturbations stochastiques et déterministes externes. Nous considérons le cas de réseaux à caractère régulier aussi bien que celui de réseaux complexes.<p><p> / Doctorat en Sciences / info:eu-repo/semantics/nonPublished

<p align="justify">Ce travail consiste à étudier des systèmes constitués par un grand nombre de grains, auxquels de l’énergie cinétique est fournie, et à étudier leurs similarités et leurs différences avec des fluides traditionnels. Je me concentre principalement sur la nature de non-équilibre de ces fluides granulaires, en montrant que, même si les méthodes de méchanique statistique y sont applicables, leurs propriétés sont très différentes de celles de systèmes à l’équilibre ou proches de l’équilibre :</p><p><p><ul><li>Les fluides granulaires présentent des phénomènes de transport qui n’ont pas d’équivalent dans des fluides moléculaires, tels qu’un couplage spécifique entre flux de chaleur et gradient de densité.<p><li>Leur distribution de vitesse est en général différente de la distribution de Maxwell-Boltzmann, et présente une surpopulation pour les grandes vitesses. <p><li>Dans le cas de mélanges, différentes espèces de grains sont en général caractérisées par des énergies cinétiques différentes, i.e. ces systèmes sont sujet à une non-equipartition de leur énergie.<p><li>Ces fluides ont tendance à former des inhomogénéités spatiales spontanément. Cette propriété est illustrée en étudiant l’expérience du Demon de Maxwell appliquée aux systèmes granulaires.</ul><p><p align="justify">Chacune de ces particularités est discutée en détail dans des chapitres distincts, où l’on applique différentes méthodes de méchanique statistique (équation de Boltzmann, transition de phase, mean field models…) et où l’on vérifie les prédictions théoriques par simulations numériques (MD, Monte Carlo…).</p> / Doctorat en sciences, Spécialisation physique / info:eu-repo/semantics/nonPublished