Ce travail de thèse concerne la caractérisation de la structure spatio-temporelle des fortes précipitations dans la région Cévennes-Vivarais. La région est soumise à des événements de pluie catastrophiques dont la magnitude gouverne les conséquences à différentes échelles de temps et d'espace. La détermination de la probabilité d'occurrence des orages est problématique à cause du caractère extrême des ces événements, de leur dimension spatio-temporelle et du manque de données pluviométriques aux échelles d'intérêt. Nous proposons d'adopter des approches d'invariance d'échelles afin d'estimer la fréquence d'occurrence de ces événements. Ces approches permettent d'extrapoler la distribution de la pluie à haute résolution à partir de données d'intensité pluvieuse à plus faible résolution. La paramétrisation de ces modèles étant fortement dépendante de l'incertitude de la mesure, nous avons d'abord caractérisé l'erreur commise dans la mesure de la pluie par un réseau de pluviomètres à augets. Nous avons ensuite exploré le comportement des pluies extrêmes dans la région d'étude, identifiant les gammes d'invariance d'échelles des extrêmes. Dans cette gamme d'échelles, nous présentons un modèle régional Intensité-Durée-Fréquence qui prend en considération l'hétérogénéité spatiale des extrêmes dans la région. Étant donné que le réseau pluviométrique ne permet pas de détecter les propriétés d'invariance d'échelle spatiale des champs de pluie, nous avons adopté une méthode semi-empirique pour modéliser des intensités de pluie intégrés sur des surfaces données (pluie surfacique) sur la base du concept de la mise en échelle dynamique (" dynamic scaling "). Cette modélisation permet la construction d'un modèle régional Intensité-Durée-Fréquence-Surface. Enfin, nous avons appliqué ce modèle à la construction des diagrammes de sévérité pour trois événements marquants en région Cévennes-Vivarais, afin d'identifier les échelles spatio-temporelles critiques pour chaque événement. Grâce aux diagrammes de sévérité, nous avons pu évaluer, pour ces mêmes événements, la performance d'un modèle météorologique de méso-échelle.

No description available.

No description available.

No description available.

No description available.

No description available.

This thesis investigates the computation of invariance kernels for planar nonlinear systems with one input, with application to wind turbine stability. Given a known bound on the absolute value of the input variations (possibly around a fixed non-zero value), it is of interest to determine if the system's state can be guaranteed to stay within a desired region K of the state space irrespective of the input variations. The collection of all initial conditions for which trajectories will never exit K irrespective of input variations is called the invariance kernel. This thesis develops theory to characterize the boundary of the invariance kernel and develops an algorithm to compute the exact boundary of the invariance kernel. The algorithm is applied to two simplified wind turbine systems that tap kinetic energy of the turbine to support the frequency of the grid. One system provides power smoothing, and the other provides inertial response. For these models, limits on speed and torque specify a desired region of operation K in the state space, while the wind is represented as a bounded input. The theory developed in the thesis makes it possible to define a measure called the wind disturbance margin. This measure quantifies the largest range of wind variations under which the specified type of grid support may be provided. The wind disturbance margin quantifies how the exploitation of kinetic energy reduces a turbine's tolerance to wind disturbances. The improvement in power smoothing and inertial response made available by the increased speed range of a full converter-interfaced turbine is quantified as an example.

Understanding physical configurations and how these can emerge from the underlying gauge theory is a fundamental problem in modern particle physics. This thesis investigates the study of these configurations primarily focussing on the need for gauge invariance in constructing the gauge invariant fields for any physical theory. We consider Wu’s approach to gauge invariance by identifying the gauge symmetry preserving conditions in quantum electrodynamics and demonstrate how Wu’s conditions for one-loop order calculations (under various regularisation schemes) leads to the maintenance of gauge invariance. The need for gauge invariance is stressed and the consequences discussed in terms of the Ward identities for which various examples and proofs are presented in this thesis. We next consider Zwanziger’s description of a mass term in Yang-Mills theory, where an expansion is introduced in terms of the quadratic and cubic powers of the field strength. Although Zwanziger introduced this expansion there is, however, no derivation or discussion about how it arises and how it may be extended to higher orders. We show how Zwanziger’s expansion in terms of the inverse covariant Laplacian can be derived and extended to higher orders. An explicit derivation is presented, for the first time, for the next to next to leading order term. The role of dressings and their factorisation lies at the heart of this analysis.

There is a paucity of research juxtaposing parental education level and teacher emotional support in a single study which examines their relative impacts on students’ academic achievements. Therefore, the first objective of this dissertation is to study the influence of parental education level, in comparison to the influence of teacher emotional support, on students’ math performance, by using more representative data and a rigorous statistical method. The second objective is to identify and examine how some important psychological traits (both affective and cognitive) mediate the effects of social factors on students’ math performance. The third objective is to examine whether those relationships are moderated by gender. Hong Kong’s survey data is extracted from the Program of International Students Assessment (2003) as organized by Organization for Economic Co-operation and Development (OECD), on the math performances of 4,478 students at the age of fifteen. Measurement invariance was first tested, and then followed by Confirmatory Factor Analysis. Two structural models were tested by Structural Equation Modeling using Linear Structural Relations (LISREL) 8.5 which is computer software for SEM. Results indicated that first, parental education level affects children’s math scores by providing home education resources and enhancing children’s math self-efficacy, and second the Self Determination Theory is applicable in supporting the hypothesis that teachers affects their students’ math scores by providing a cooperative learning environment, which in turn, enhances students’ affective and cognitive factors. Three important mediators, namely cooperative learning environment, math self-efficacy, and home education resources are concluded as significant mediating factors upon the effects of parents and teachers on students’ math performance. The perceived support from parents and teachers are not significantly different across gender in Hong Kong. This is consistent with recent studies that differences favoring males in mathematics achievement are disappearing. Theoretical contributions and practical implications are discussed in the final part of the dissertation.

This thesis is divided into two parts: In the first one (Chapters 1 and 2), we deal with problems arising from quantitative homogenization of the random elliptic operator in divergence form $-\\nabla \\cdot a \\nabla$. In Chapter 1 we study existence and stochastic bounds for the Green function $G$ associated to $-\\nabla \\cdot a \\nabla$ in the case of systems. Without assuming any regularity on the coefficient field $a= a(x)$, we prove that for every (measurable) uniformly elliptic tensor field $a$ and for almost every point $y \\in \\mathbb^d$, there exists a unique Green\'s function centred in $y$ associated to the vectorial operator $-\\nabla \\cdot a\\nabla $ in $\\mathbb{R}^d$, $d> 2$. In addition, we prove that if we introduce a shift-invariant ensemble $\\langle\\cdot \\rangle$ over the set of uniformly elliptic tensor fields, then $\\nabla G$ and its mixed derivatives $\\nabla \\nabla G$ satisfy optimal pointwise $L^1$-bounds in probability. Chapter 2 deals with the homogenization of $-\\nabla \\cdot a \\nabla$ to $-\\nabla \\ah \\nabla$ in the sense that we study the large-scale behaviour of $a$-harmonic functions in exterior domains $\\{ |x| > r \\}$ by comparing them with functions which are $\\ah$-harmonic. More precisely, we make use of the first and second-order correctors to compare an $a$-harmonic function $u$ to the two-scale expansion of suitable $\\ah$-harmonic function $u_h$. We show that there is a direct correspondence between the rate of the sublinear growth of the correctors and the smallness of the relative homogenization error $u- u_h$. The theory of stochastic homogenization of elliptic operators admits an equivalent probabilistic counterpart, which follows from the link between parabolic equations with elliptic operators in divergence form and random walks. This allows to reformulate the problem of homogenization in terms of invariance principle for random walks. The second part of thesis (Chapters 3 and 4) focusses on this interplay between probabilistic and analytic approaches and aims at exploiting it to study invariance principles in the case of degenerate random conductance models and systems of interacting particles. In Chapter 3 we study a random conductance model where we assume that the conductances are independent, stationary and bounded from above but not uniformly away from $0$. We give a simple necessary and sufficient condition for the relaxation of the environment seen by the particle to be diffusive in the sense of every polynomial moment. As a consequence, we derive polynomial moment estimates on the corrector which imply that the discrete elliptic operator homogenises or, equivalently, that the random conductance model satisfies a quenched invariance principle. In Chapter 4 we turn to a more complicated model, namely the symmetric exclusion process. We show a diffusive upper bound on the transition probability of a tagged particle in this process. The proof relies on optimal spectral gap estimates for the dynamics in finite volume, which are of independent interest. We also show off-diagonal estimates of Carne-Varopoulos type.