Though lots of numerical methods have been proposed in the literature to optimize me-chanical structures at the final stage of the design process, few designers use these tools since the first stage. However, a minor modification at the first step can bring significant change to the global performances of the structure. Usually, during the initial stage, models are based on theoretical and empirical equations, which are often characterized by mixed variables: continuous (e.g. geometrical dimensions), discrete (e.g. the cross section of a beam available in a catalogue) and/or integer (e.g. the number of layers in a composite material). Furthermore, the functions involved may be non differentiable, or even discontinuous. Therefore, classical algorithms based on the computation of sensi-tivities are no more applicable. <p><p>Consequently, to solve these problems, the most wide-spread meta-heuristic methods are evolutionary algorithms (EAs), which work as follows: the best individuals among an initial population of randomly generated potential solutions are favoured and com-bined (by specific operators like crossover and mutation) in order to create potentially better individuals at the next generation. The creation of new generations is repeated till the convergence is reached. The ability of EAs to explore widely the design space is useful to solve single-objective unconstrained optimization problems, because it gener-ally prevents from getting trapped into a local optimum, but it is also well known that they do not perform very efficiently in the presence of constraints. Furthermore, in many industrial applications, multiple objectives are pursued together. <p><p>Therefore, to take into account the constrained and multicriteria aspects of optimization problems in EAs, a new method called PAMUC (Preferences Applied to MUltiobjectiv-ity and Constraints) has been proposed in this dissertation. First the user has to assign weights to the m objectives. Then, an additional objective function is built by linearly aggregating the normalized constraints. Finally, a multicriteria decision aid method, PROMETHEE II, is used in order to rank the individuals of the population following the m+1 objectives. <p><p>PAMUC has been validated on standard multiobjective test cases, as well as on the pa-rametrical optimization of the purge valve and the feed valve of the Vinci engine, both designed by Techspace Aero for launcher Ariane 5.<p>\ / Doctorat en sciences appliquées / info:eu-repo/semantics/nonPublished

This thesis focuses on the development of a new method for the continuous<p>monitoring of civil engineering structures in order to locate small damages automatically. A<p>review of the very wide literature on Structural Health Monitoring (SHM) points first out that<p>the methods can be grouped in four categories based on their need or not of a numerical model,<p>as well as their need or not of information of the damaged structure to be applied. This state<p>of the art of the SHM methods highlights the requirement to reach each levels of SHM, which<p>is in particular for the localization of small damages in civil engineering structures the needs<p>for a non-model based output-only damage sensitive feature extraction technique. The origin of<p>the local sensitivity of strains to damages is also analyzed, which justifies their use for damage<p>localization.<p>A new method based on the modal filtering technique which consists in combining linearly<p>the sensor responses in a specific way to mimic a single degree of freedom system and which<p>was previously developed for damage detection is proposed. A very large network of dynamic<p>strain sensors is deployed on the structure and split into several independent local sensor networks.<p>Low computational cost and fast signal processing techniques are coupled to statistical<p>control charts for robust and fully automated damage localization.<p>The efficiency of the method is demonstrated using time-domain simulated data on a simply<p>supported beam and a three-dimensional bridge structure. The method is able to detect and<p>locate very small damages even in the presence of noise on the measurements and variability<p>of the baseline structure if strain sensors are used. The difficulty to locate damages from acceleration<p>sensors is also clearly illustrated. The most common classical methods for damage<p>localization are applied on the simply supported beam and the results show that the modal filtering<p>technique presents much better performances for an accurate localization of small damages<p>and is easier to automate.<p>An improvement of the modal filters method referred to as adaptive modal filters is next<p>proposed in order to enhance the ability to localize small damages, as well as to follow their<p>evolution through modal filters updating. Based on this study, a new damage sensitive feature<p>is proposed and is compared with other damage sensitive features to detect the damages with<p>modal filters to demonstrate its interest. These expectations are verified numerically with the<p>three-dimensional bridge structure, and the results show that the adaptation of the modal filters<p>increases the sensitivity of local filters to damages.<p>Experimental tests have been led first to check the feasibility of modal filters to detect damages<p>when they are used with accelerometers. Two case studies are considered. The first work<p>investigates the experimental damage detection of a small aircraft wing equipped with a network<p>of 15 accelerometers, one force transducer and excited with an electro-dynamic shaker. A<p>damage is introduced by replacing inspection panels with damaged panels. A modified version<p>of the modal filtering technique is applied and compared with the damage detection based principal<p>component analysis of FRFs as well as of transmissibilities. The three approaches succeed<p>in the damage detection but we illustrate the advantage of using the modal filtering algorithm as<p>well as of the new damage sensitive feature. The second experimental application aims at detecting<p>both linear and nonlinear damage scenarios using the responses of four accelerometers<p>installed on the three-storey frame structure previously developed and studied at Los Alamos<p>National Labs. In particular, modal filters are shown to be sensitive to both types of damages,<p>but cannot make the distinction between linear and nonlinear damages.<p>Finally, the new method is tested experimentally to locate damages by considering cheap<p>piezoelectric patches (PVDF) for dynamic strain measurements. Again, two case studies are investigated.<p>The first work investigates a small clamped-free steel plate equipped with 8 PVDFs sensors, and excited with a PZT patch. A small damage is introduced at different locations by<p>fixing a stiffener. The modal filters are applied on three local filters in order to locate damage.<p>Univariate control charts allow to locate automatically all the damage positions correctly.<p>The last experimental investigation is devoted to a 3.78m long I-steel beam equipped with 20<p>PVDFs sensors and excited with an electro-dynamic shaker. Again, a small stiffener is added to<p>mimic the effect of a small damage and five local filters are defined to locate the damage. The<p>damage is correctly located for several positions, and the interest of including measurements<p>under different environmental conditions for the baseline as well as overlapping the local filters<p>is illustrated.<p>The very nice results obtained with these first experimental applications of modal filters<p>based on strains show the real interest of this very low computational cost method for outputonly<p>non-model based automated damage localization of real structures. / Doctorat en Sciences de l'ingénieur / info:eu-repo/semantics/nonPublished