Wireless sensor network is an intelligent network system which has the self-monitoring functionality. It consists of many low-cost, low-power and small-sized sensor nodes that can communicate with each other to perform sensing and data processing. Acting as an important role in the system, network coverage usually has a huge effect on the system’s lifetime.In this thesis, particle swarm algorithm was used as a method to optimize the coverage in the coverage of wireless sensor network. A network coverage optimization strategy based on particle swarm optimization was proposed and MATLAB was used as a tool to apply the algorithm. The model used in this thesis is the probability sensing model and the coverage type is area coverage. Effectiveness of the algorithm is proved by simulation. The simulation of the algorithm suggests the optimal deployment can be determined if a certain parameter which in this thesis is the sensing range is given.

The submicron-aperture fiber point-diffraction interferometer (SFPDI) can be applied to realize the measurement of three-dimensional absolute displacement within large range, in which the performance of point-diffraction wavefront and numerical iterative algorithm for displacement reconstruction determines the achievable measurement accuracy, reliability and efficiency of the system. A method based on fast searching particle swarm optimization (FS-PSO) algorithm is proposed to realize the rapid measurement of three-dimensional absolute displacement. Based on the SFPDI with two submicron-aperture fiber pairs, FS-PSO method and the corresponding model of the SFPDI, the measurement accuracy, reliability and efficiency of the SFPDI system are significantly improved, making it more feasible for practical application. The effect of point-diffraction wavefront error on the measurement is analyzed. The error of point-diffraction wavefront obtained in the experiment is in the order of 1x10(-4). (the wavelength. is 532 nm), and the corresponding displacement measurement error is smaller than 0.03 mu m. Both the numerical simulation and comparison experiments have been carried out to demonstrate the accuracy and feasibility of the proposed SFPDI system, high measurement accuracy in the order of 0.1 mu m, convergence rate (similar to 90.0%) and efficiency have been realized with the proposed method, providing a feasible way to measure three-dimensional absolute displacement in the case of no guide rail.

In this study, weight optimization of two dimensional steel frames is carried out in which the flexibility of beam-to-column connections and the soil-structure interaction are considered. In the analysis and design of steel frames, beam-tocolumn connections are assumed to be either fully rigid or perfectly pinned. However, the real behavior of beam-to-column connections is actually between these extremes. Namely, even the simple connections used in practice possess some stiffness falling between these two cases mentioned above. Moreover, it is found that there exists a nonlinear relationship between the moment and beam-to-column rotation when a moment is applied to a flexible connection. These partially restrained connections influence the drift (P- effect) of whole structure as well as the moment distribution in beams and columns. Use of a direct nonlinear inelastic analysis is one way to account for all these effects in frame design. To be able to implement such analysis, beam-to-column connections should be assumed and modeled as semi-rigid connections. In the present study, beam-to-column connections are modeled as &ldquo / end plate without column stiffeners&rdquo / and &ldquo / top and seat angle with web angles&rdquo / . Soil-structure interaction is also included in the analysis. Frames are assumed to be resting on nonlinear soil, which is represented by a set of axial elements. Particle swarm optimization method is used to develop the optimum design algorithm. The Particle Swarm method is a numerical optimization technique that simulates the social behavior of birds, fishes and bugs. In nature fish school, birds flock and bugs swarm not only for reproduction but for other reasons such as finding food and escaping predators. Similar to birds seek to find food, the optimum design process seeks to find the optimum solution. In the particle swarm optimization each particle in the swarm represents a candidate solution of the optimum design problem. The design algorithm presented selects sections for the members of steel frame from the complete list of sections given in LRFD- AISC (Load and Resistance Factor Design, American Institute of Steel Construction). Besides, the design constraints are implemented from the specifications of the same code which covers serviceability and strength limitations. The optimum design algorithm developed is used to design number of rigid and semi-rigid steel frames.

Afin de définir une conception optimale d’un système électromécanique, celui-ci doit intégrer des contraintes toujours plus drastiques et de nombreux phénomènes physiques issus de : l’électromagnétique, l’aérothermique, l’électronique, la mécanique et l’acoustique. L’originalité de cette thèse est de proposer une modélisation multi-physique pour la conception reposant sur des modèles à constantes localisées : solution intermédiaire entre la modélisation analytique et numérique. Ces différents modèles permettront l’étude et la conception sous contraintes d’une machine synchrone à aimants permanents dédiée pour la traction ferroviaire. Les résultats de simulations seront comparés à des résultats éléments finis mais aussi à des essais expérimentaux. Ce modèle multi-physique est entièrement paramétré afin d’être associé à des outils d’optimisation. On utilisera ici une optimisation par essaim de particules pour chercher des compromis entre différents objectifs sous forme de Front de Pareto. Dans ce papier, nous ciblerons les objectifs suivants : le couple d’origine électromagnétique et le bruit d’origine électromagnétique. Finalement une étude de sensibilité valide la robustesse de la conception retenue quand celle-ci est soumise aux contraintes de fabrication. L’objectif étant de poser les bases d’un outil d’aide à la décision pour le choix d’une machine électrique / In order to perform an optimal design of electromechanical system, the designer must take into account ever more stringent constraints and many physical phenomena from electric, magnetic, aeraulic, thermic, electronic, mechanic and acoustic. The originality of this thesis is to put forward a multi-physic design based on lumped models: halfway between analytical and numerical modeling. These models allow sizing a permanent magnet synchronous machine under constraints for rail traction. The results are validated with finite element simulations and experimental analysis. The multi-physic modeling is fully automated, parameterized, in order to combine the model with the optimization tool. We used here particle swarm optimization to search compromises between several objectives (Pareto Front). In this paper, we focus on electromagnetic torque and electromagnetic noise. Finally a sensitive study validates the robustness of selected design when it is subjected to manufacturing constraints. The aim of this work is to propose a decision tool to size electrical machines