The thesis concentrates on a methodological research on categorical structural optimization by means of manifold learning. The main difficulty of handling the categorical optimization problems lies in the description of the design variables: they are presented in a discrete manner and do not have any orders. Thus the treatment of the design space is a key issue. In this thesis, the non-ordinal categorical variables are treated as multi-dimensional discrete variables, thus the dimensionality of corresponding design space becomes high. In order to reduce the dimensionality, the manifold learning techniques are introduced to find the intrinsic dimensionality and map the original design space to a reduced-order space. The mechanisms of both linear and non-linear manifold learning techniques are firstly studied. Then numerical examples are tested to compare the performance of manifold learning techniques. It is found that Principal Component Analysis (PCA) and Multi-dimensional Scaling (MDS) can only deal with linear or globally approximately linear cases. Isomap preserves the geodesic distances for non-linear manifold, however, its time consuming is the most. Locally Linear Embedding (LLE) preserves the neighbour weights and can yield good results in a short time. Kernel Principal Component Analysis (KPCA) works as a non-linear classifier and we proves the reason why it cannot preserve distances or angles in some cases.Based on the reduced-order representation obtained by Isomap, the graph-based evolutionary crossover and mutation operators are proposed to deal with categorical structural optimization problems, including the design of dome, six-story rigid frame and dame-like structures. The results show that the proposed graph-based evolutionary approach constructed on the reduced-order space performs more efficiently than traditional methods including simplex approach or evolutionary approach without reduced-order space.The Locally Linear Embedding is applied to reduce the data dimensionality and a polynomial interpolation helps to construct the responding surface from lower dimensional representation to original data. Then the continuous search method of moving asymptotes is executed and yields a competitively good but inadmissible solution within only a few of iteration numbers. Then in the second stage, a discrete search strategy is proposed to find out better solutions based on a neighbour search. The ten-bar truss and dome structural design problems are tested to show the validity of the method. In the end, this method is compared to the Simulated Annealing algorithm and Covariance Matrix Adaptation Evolutionary Strategy, showing its better optimization efficiency.In order to deal with the case in which the categorical design instances are distributed on several manifolds, we propose a k-manifolds learning method based on the Weighted Principal Component Analysis. The obtained manifolds are integrated in the lower dimensional design space. Then the two-stage search method is applied to solve the ten-bar truss, the dome and the dam-like structural design problems. / Doctorat en Sciences de l'ingénieur et technologie / info:eu-repo/semantics/nonPublished

Lightweight designs in engineering applications give rise to flexible structures with extremely low internal damping. Vibrations of these flexible structures due to an unwanted excitation of system resonances may lead to high cycle fatigue failure and noise propagation. A common method to suppress the vibrations is to increase the damping of the system using one of the classical control techniques i.e. passive, active, and/or hybrid. Passive techniques are those control systems that are simply integrated into the structures with no need of external power source for their operations, like viscoelastic damping, piezoelectric and electromagnetic shunt damping, tuned mass damper, etc. However, the control performance of these systems, in terms of the damping ratio and the robustness to uncertainties, is highly limited to the system properties. For example, viscoelastic damping may not perform well at low frequencies and the performance of shunt damping is dependent on the electromechanical coupling between the structure and the transducer. To overcome the limitations associated with passive controls, it has been proposed to use active control systems, which are less sensitive to the system's parameters, to improve the control performance. It requires an integration of sensors and actuators with a feedback loop containing control laws. However, the high requirement of the external power source is not favorable for engineering applications where energy efficiency is the key parameter. The combination of active and passive strategies, known as hybrid control systems, can provide a fail-safe configuration with a high control performance and low power consumption. The price to pay for such configurations is the complexity of the design. This doctoral thesis first investigates the conceptual designs of all kinds of classical control systems for a simplified mechanical system. They include 1) the passive shunt using an electromagnetic transducer, 2) the active control system using positive and negative feedback, and 3) the hybrid electromagnetic shunt damper using both an active voltage source as well as an active current source. The next part of this thesis is focused on bladed structures as real-life applications which highly require vibration control due to their low internal damping. Because of practical reasons, piezoelectric transducers are used for the application of control systems. The finite element model of the structure is made first without piezoelectric patches to optimize the best locations of piezoelectric patches. Then, the model is updated with the piezoelectric patches to numerically simulate different control strategies. The experiments are performed to validate the numerical designs. / Doctorat en Sciences de l'ingénieur et technologie / info:eu-repo/semantics/nonPublished

This thesis investigates various active control aspects of large aperture telescopes; both Earth-based and space telescopes are considered.The first part proposes a concept of piezoelectric adaptive thin shell reflector for future space telescopes; it exhibits excellent areal density and stowability, and thus, paves the way to future large aperture space telescopes. Controlling the surface figure of spherical or parabolic shell with in-plane stresses induced by a piezoelectric layer raises two problems: (i) Doubly curved shells are significantly stiffer than flat plates (especially for the optical modes associated with hoop strains) and (ii) When using segmented electrodes with different voltages, the surface figure is subject to edge fluctuations with a characteristic length depending on the reflector curvature R_c and thickness t according to sqrt(R_ct). Accurate surface figure corrections require that the electrode size D_e satisfies D_e<sqrt(R_ct). This results in a very large number of electrodes, leading to ill-conditioning in the Jacobian matrix of the system; to solve this, a hierarchical approach is proposed to inverse the Jacobian, based on Saint-Venant's principle. This chapter also proposes a petal configuration which aims at reducing the hoop stiffness and improving the foldability of the reflector. A small scale technology demonstrator has been manufactured in the framework of the ESA-GSTP project Multilayer Adaptive Thin Shell Reflectors for Future Space Telescopes (MATS). The demonstrator includes a polymer substrate (PEEK) and a spin-coated PVDF-TrFE piezoelectric layer activated by independent electrodes; it is used to validate the manufacturing process and the independent actuation of the electrodes.The second part deals with control-structure interaction in flat deformable mirrors for Adaptive Optics. The problem arises because of the increasing size of AO mirrors, leading to lower resonance frequencies, and the control bandwidth requirements to achieve a good wavefront error compensation. This chapter studies the conditions for spillover instability and highlights the main parameters controlling the phenomenon: the ratio between the control bandwidth and the resonance frequency and the modal damping. Two methods for damping augmentation are discussed, one passive, using inductive shunting of piezoelectric elements, and the other active, using the wavefront sensor and the array of control actuators as a modal filter.The third part focuses on the field stabilization control of the tip/tilt mirror under wind disturbances of the E-ELT telescope (a distinctive feature of the E-ELT as compared to other smaller telescopes is that it will be a wind-limited instead of a seeing-limited telescope). A literature survey is conducted of the spectral content of the wind disturbances on large telescopes, with a special attention on the high frequency decay rate. The analysis confirms the adequacy of a decoupled design of the field stabilization (M5) control loop. However, the reaction torques necessary to control the tip/tilt mirror M5 have been found to depend critically on the asymptotic decay rate of the wind tilt disturbance. These torques act as a disturbance on the telescope structure and, if the wind disturbance does not decay fast enough with the frequency (a>-3), it may generate significant wavefront errors in the primary mirror M1, in a frequency range (30-100Hz) which may be difficult to eliminate by Adaptive Optics. / Doctorat en Sciences de l'ingénieur et technologie / info:eu-repo/semantics/nonPublished

In this work, a Representative Volume Element (RVE) generator based on the distance fields of arbitrary shaped inclusion packing is used to obtain morphologies of open-foam materials. When the inclusions are spherical, the tessellations of the resultant packing creates morphologies that are similar to physical foam samples in terms of their face-to-pore ratio, edge-to-face ratio and strut length distribution among others. Functions that combine the distance fields can be used to obtain the tessellations along with the necessary variations in the strut geometry and extract these open-foam morphologies. It is also possible to replace the inclusion packing with a predefined set of inclusions that are directly extracted from CT-scan based images.The use of discrete level-set functions results in steep discontinuities in the distance function derivatives. A multiple level-set based approach is presented that can appropriately capture the sharp edges of the open-foam struts from the resultant distance fields. Such an approach can circumvent the discontinuities presented by the distance fields which might lead to spurious stress concentrations in a material behavior analysis.The individual cells are then extracted as inclusion surfaces based on said combinations of the distance functions and their modifications. These surfaces can be joined together to obtain the final geometry of the open-foam morphologies. The physical attributes of the extracted geometries are compared to the experimental data. A statistical comparison is presented outlining the various features. The study is extended to morphologies that have been extracted using CT-scan images. With the help of mesh optimization tools, surface triangulations can be obtained, merged and developed as finite element (FE) models. The models are ready to use in a multi-scale study to obtain the homogenized material behavior. The upscaling can help assess the practical applications of these models by comparing with experimental data of physical samples. The material behavior of the RVEs are also compared with the experimental observations. To increase the computational efficiency of the study, a neural network based surrogate is presented that can replace the micro-scale boundary value problem (BVP) in the multi-scale analysis. The neural networks are built with the help of modules that are specifically designed to predict history dependent behavior and are called Recurrent Neural Networks (RNN). The surrogates are trained to take into account the randomness of the loading that complex material undergo during any given material behavior analysis. / Dans ce travail, un générateur de volumes élémentaires représentatifs (VER) basé sur les champs de distance d'un agrégat d'inclusions de forme arbitraire est développé dans le cadre de matériaux moussés à structure ouverte. Lorsque les inclusions sont sphériques, la tessellation de l'agrégat résulte en des morphologies similaires aux échantillons de mousse physique en termes de rapports des nombres de face par pores et de bords par faces, ainsi que de la distribution de la longueur des entretoises, entre autres. Les fonctions qui combinent les champs de distance peuvent être utilisées pour obtenir des tesselations avec les variations nécessaires aux géométries des entretoises et extraire ces morphologies de mousse ouverte. Il est également possible de remplacer l'agrégat d'inclusions par un ensemble prédéfini d'inclusions qui sont directement extraites d'images tomographiques.L'utilisation de fonctions de niveaux discrètes entraîne de fortes discontinuités dans les dérivées des champs de distance. Une approche basée sur des ensembles de niveaux multiples est présentée qui peut capturer de manière appropriée les arêtes vives des entretoises des mousses ouvertes à partir des champs de distance résultants. Une telle approche peut contourner les discontinuités présentées par les champs de distance qui pourraient conduire à des concentrations de contraintes parasites dans une analyse ducomportement des matériaux.Les pores individuels sont ensuite extraits en tant que surfaces d'inclusions sur la base desdites combinaisons des fonctions de distance et de leurs modifications. Ces surfaces peuvent être réunies pour obtenir la géométrie finale des morphologies de mousse ouverte. Les attributs physiques des géométries extraites sont comparés aux données expérimentales. Une comparaison statistique est présentée décrivant les différentes caractéristiques. L'étude est étendue aux morphologies qui ont été extraites à l'aide d'images tomographiques.À l'aide d'outils d'optimisation de maillage, les triangulations des surfaces peuvent être obtenues, fusionnées et développées sous forme de modèles d'éléments finis (FE). Les modèles sont prêts à être utilisés dans une étude multi-échelle pour obtenir le comportement homogénéisé du matériau. La mise à l'échelle peut aider à évaluer les applications pratiques de ces modèles en les comparant aux données expérimentales d'échantillons physiques. Le comportement des matériaux des VERs est également comparé aux observations expérimentales.Pour augmenter l'efficacité de calcul de l'étude, un modèle de substitution basé sur un réseau neuronal est présenté. Ce modèle peut remplacer le problème aux valeurs limites à l'échelle micro dans une analyse multi-échelle. Les réseaux de neurones sont construits à l'aide de modules spécialement conçus pour prédire le comportement dépendant de l'histoire et sont appelés réseaux de neurones récurrents (RNN). Les modèles de substitution sont entrainés pour prendre en compte le caractère aléatoire du chargement que subit un matériau complexe lors d'une analyse de comportement d'un matériau. / Doctorat en Sciences de l'ingénieur et technologie / info:eu-repo/semantics/nonPublished