No description available.

Vibration-based structural health monitoring (SHM) seeks to detect, quantify, locate, and prognosticate damage by processing vibration signals measured while the structure is operational. The basic premise of vibration-based SHM is that damage will affect the stiffness, mass or energy dissipation properties of the structure and in turn alter its measured dynamic characteristics. In order to make SHM a practical technology it is necessary to perform damage assessment using only a minimum number of permanently installed sensors. Deducing damage at unmeasured regions of the structural domain requires solving an inverse problem that is underdetermined and(or) ill-conditioned. In addition, the effects of local damage on global vibration response may be overshadowed by the effects of modelling error, environmental changes, sensor noise, and unmeasured excitation. These theoretical and practical challenges render the damage identification inverse problem ill-posed, and in some cases unsolvable with conventional inverse methods. This dissertation proposes and tests a novel interpretation of the damage identification inverse problem. Since damage is inherently local and strictly reduces stiffness and(or) mass, the underdetermined inverse problem can be made uniquely solvable by either imposing sparsity or non-negativity on the solution space. The goal of this research is to leverage this concept in order to prove that damage identification can be performed in practical applications using significantly less measurements than conventional inverse methods require. This dissertation investigates two sparsity inducing methods, L1-norm optimization and the non-negative least squares, in their application to identifying damage from eigenvalues, a minimal sensor-based feature that results in an underdetermined inverse problem. This work presents necessary conditions for solution uniqueness and a method to quantify the bounds on the non-unique solution space. The proposed methods are investigated using a wide range of numerical simulations and validated using a four-story lab-scale frame and a full-scale 17 m long aluminum truss. The findings of this study suggest that leveraging the attributes of both L1-norm optimization and non-negative constrained least squares can provide significant improvement over their standalone applications and over other existing methods of damage detection.

Knowledge about the dynamic behaviour is a basic condition for a secure operation of modern machine tools. Hence numerical methods predicting the dynamic properties are gaining in importance. Usually for complex and coupled structures, the results of dynamic property calculation are yet insufficient. Therefore Finite Element model updating is a tool to improve the hypothetical factor of the analysis. Within the present thesis Finite Element modelling is performed using the example of the “Scherenkinematik”, a machine tool based on hybrid-kinematics. Initially the results of an Experimental Modal Analysis are evaluated by identifying Modal parameters and deriving possible structural modifications. In the second part of the thesis, the machines Finite Element model is created using the FEA-Software ANSYS. Afterwards the Finite Element model updating is performed by coupling ANSYS and the CAE-Software FEMtools. Therefore two approaches are formulated and tracked. It turns out, that there is no improvement of the analytical and experimental models correlation, neighter with nor without a steady reduction of the search domain needed for mode coupling. It is reasoned, that the characteristics and the results of an Finite Element updating process are affected by the quality of the model at start time and the approach as well as the technique chosen for model updating and parameter modification. Therefore the CAE-Software FEMtools is suitable to only a limited extent for Finite Element updating of strongly coupled mechanical structures as a result of the sensitivity analysis used for parameter modification.

No description available.

To obtain predictive modeling of a spacecraft, the author investigates the effects of adding cables to a simple structure with the goal of developing an understanding of how cables interacting with a structure. In this research, the author presents predictive and accurate modeling of a cable-harnessed structure by means of the Spectral Element Method (SEM). A double beam model is used to emulate a cable-harnessed structure. SEM modeling can define the location and the number of connections between the two beams in a convenient fashion. The proposed modeling is applied and compared with the conventional FEM. The modeling approach was compared to and validated by measurement data. The validated modeling was implemented to investigate the effect of the number of connections, of the spring stiffness of interconnections, and of mass portion of an attached cable. Damping has an important role in structural design because it reduces the dynamic response, thereby avoiding excessive deflection or stress, fatigue loads, and settling times. Experimental results with some specimens indicate a clear change of damping on the main structure with the inclusion of cable dynamics. The author investigated the modification of the damping of the host structure induced by various attached cables. The identification of a damping matrix is performed using measured data. The effect of the flexibility of a cable harness on damping is observed through experiments with various types of cables. The effect of the number of connections on damping is also investigated by changing the number of connections. Moreover, to overcome the sensitivity to noise in measured data of damping matrix identification approach, various methods are compared with a simulated lumped model and real test results. An improved damping matrix identification approach is proposed and can generate the unique damping matrix over the full frequency range of interest. / Ph. D.

More and more pressure is exerted on railway infrastructure due to an increasing transportation demand and population density. Instead of expanding the net, a possible solution could lie in the enlargement of the capacity by operating longer trains rather than more short ones. However, close attention has to be paid to the behaviour and the lifetime of the infrastructure under these changed loads. In special bridges are delicate aspects in this matter. In the current thesis the simply supported Banafjäl bridge located on the Bothnia Line in the North of Sweden is studied more in detail with regards to this aspect. It is a high-speed composite railway bridge with a span of 42 m. A detailed 3D finite element (FE) model is made available. However in order to make reliable predictions about the behaviour under increasing train length loads, it had to be further improved. Different methods of calibrating measured response data to an existing FE model, finite element model updating (FEMU), are available and a detailed overview is given at the beginning of this thesis. Next a sensitivity analysis was performed to select the material parameters which are most influential for the result and will be updated. In the following, FEMU is carried out by means of two iterative updating methods, genetic and gradient-based optimization, after which also a combination of these two is implemented. Two objective functions are chosen and it is shown that all methods converge to a global optimal solution. After adjusting the initial model with the updated parameter values, a fatigue analysis on this updated model is carried out for high-speed trains of multiple lengthsby means of the Palmgren-Miner rule. The fatigue is found to increase with increasing train length and in particular when the speed approaches resonance speed. By extension an operating chart is created to indicate the maximum amount of train passages per day in function of speed and train length for a type 4 fatigue train. Furthermore, damping has been shown to have a positive effect on the fatigue, the larger this effect for shorter trains. The static behaviour has been proven not to be a problem and so will solely the weight of trains induce little to no fatigue problems in this particular bridge.

Structural Health Monitoring (SHM) is a promising tool for condition assessment of bridge structures. SHM of bridges can be performed for different purposes in long or short-term. A few aspects of short- and long-term monitoring of highway bridges are addressed in this research. Without quantifying environmental effects, applying vibration-based damage detection techniques may result in false damage identification. As part of a long-term monitoring project, the effect of temperature on vibrational characteristics of two continuously monitored bridges are studied. Natural frequencies of the structures are identified from ambient vibration data using the Natural Excitation Technique (NExT) along with the Eigen System Realization (ERA) algorithm. Variability of identified natural frequencies is investigated based on statistical properties of identified frequencies. Different statistical models are tested and the most accurate model is selected to remove the effect of temperature from the identified frequencies. After removing temperature effects, different damage cases are simulated on calibrated finite-element models. Comparing the effect of simulated damages on natural frequencies showed what levels of damage could be detected with this method. Evaluating traffic loads can be helpful to different areas including bridge design and assessment, pavement design and maintenance, fatigue analysis, economic studies and enforcement of legal weight limits. In this study, feasibility of using a single-span bridge as a weigh-in-motion tool to quantify the gross vehicle weights (GVW) of trucks is studied. As part of a short-term monitoring project, this bridge was subjected to four sets of high speed, live-load tests. Measured strain data are used to implement bridge weigh-in-motion (B-WIM) algorithms and calculate the corresponding velocities and GVWs. A comparison is made between calculated and static weights, and furthermore, between supposed speeds and estimated speeds of the trucks. Vibration-based techniques that use finite-element (FE) model updating for SHM of bridges are common for infrastructure applications. This study presents the application of both static and dynamic-based FE model updating of a full scale bridge. Both dynamic and live-load testing were conducted on this bridge and vibration, strain, and deflections were measured at different locations. A FE model is calibrated using different error functions. This model could capture both global and local response of the structure and the performance of the updated model is validated with part of the collected measurements that were not included in the calibration process.

L’amélioration du caractère prédictif des simulations numériques requiert une meilleure maîtrise des modèles constitutifs. Des procédures d’identification exploitant des mesures de champs ont été développées afin de valider les modèles et d’identifier un jeu de paramètres constitutifs à partir d’un nombre réduit d’essais hétérogènes. Bien évidemment, les résultats de telles procédures dépendent grandement des incertitudes des mesures. Dans cette thèse, une stratégie d’identification de paramètres constitutifs à partir de mesures de champs par corrélation d’images numériques éléments finis (CIN-EF) multi-échelles est proposée et développée. Une variante régularisée du recalage par éléments finis (FEMU-R) est adaptée à cette approche multi-échelles. Elle exploite des champs de déplacements mesurés par CIN-EF d'une part à l’échelle de la structure (fournissant les conditions aux limites pour la simulation EF) et d’autre part à une échelle plus locale (fournissant des champs de déplacements mieux résolus pour la comparaison essais/calculs). Un algorithme de recalage d’images est développé pour faire le lien entre les échelles. D’abord validée à l’aide d’images de synthèse, la procédure est ensuite appliquée à un essai de traction sur plaque trouée réalisé sur un composite stratifié verre/époxy. On montre qu’une telle stratégie permet de diminuer nettement non seulement les incertitudes de mesure mais également les incertitudes d’identification. Finalement, la question d’un mouchetis adapté à cette approche multi-échelles est évoquée et des éléments de solutions sont proposés et testés. / Improving the prediction of numerical simulations requires a better control of constitutive models. Identification methods exploiting full-field measurements have been developed in order to validate models and to identify a set of constitutive parameters from a reduced number of heterogeneous tests. The results of those methods largely depends on measurement uncertainties. In this PhD thesis, a strategy is proposed and developed for the identification of constitutive parameters from full-field measurements obtained by multiscale finite element digital image correlation (FE-DIC). A Regularised Finite Element Model Updating method (FEMU-R) is adapted to this multiscale approach. It exploits displacement fields measured by FE-DIC at a structural scale (in order to obtain the boundary conditions for FE simulation)and at a local scale (giving a better resolution on the displacement field for the comparison between experiment and simulation). An image registration algorithm is developed to bridge these scales. First validated on synthetic images, the multiscale approach is then applied to an open-hole tensile test of a glass/epoxy composite laminate. It is shown that such a strategy allows to reduce not only the measurement uncertainties but also the identification uncertainties. Finally the question of a speckle pattern suitable for this approach is discussed and some first technical solutions are proposed and tested.

Le contexte de ce travail concerne le process d'Infusion de Résine Liquide (LRI) développé dans le cadre du projet « FUSelage COMPosite » par DAHER SOCATA. Ce process de fabrication permet de réaliser des pièces de formes complexes et des panneaux entiers de fuselage en composites, ce qui réduit considérablement les étapes d'assemblages et donc les temps de production. Les travaux de thèse portent sur l'identification expérimentale du comportement d'un fuselage composite. Ce travail se divise en deux parties qui sont la qualification du contrôle non destructif (CND) par rapport à une taille de défaut critique et l'identification du comportement d'une structure composite orthotrope en présence de ce défaut. Le premier volet consiste à évaluer les techniques de CND basées sur des mesures de champs (acoustiques, thermiques et densimétriques), capables de détecter des défauts internes de types délaminage et porosité au sein de structures composites monolithiques et sandwichs, et fournissant une visualisation des résultats par une cartographie de défauts 2D ou 3D. Le choix de ces méthodes a été motivé par la volonté de DAHER SOCATA d'acquérir de nouvelles compétences en matière de CND. Le deuxième volet consiste à évaluer les paramètres élastiques d'une structure composite orthotrope (structure comprenant une zone saine et une zone localement dégradée) via une procédure d'identification, à partir de mesures de champs, globale et locale par recalage de modèles éléments finis. Cette procédure se décompose en quatre parties avec tout d'abord l'identification des propriétés de la structure saine, ensuite la localisation de la zone dégradée, l'intégration de celle-ci dans le modèle éléments finis, et l'identification des propriétés de cette dernière. / The context of this work concerns the process of Liquid Resin Infusion (LRI) developed under the project "composite fuselage" by DAHER SOCATA. This manufacturing process can produce parts with complex shapes and entire panels of composite fuselage, reducing assembly steps and therefore the production time. The thesis work focused on the experimental identification of the behavior of a composite fuselage. This work is divided into two parts which are the qualification of non destructive testing (NDT) compared to a critical defect size and the identification of the behavior of an orthotropic composite structure with defect. The first part is to evaluate the NDT techniques based on full field measurements (acoustic, thermal and densimetric), capable of detecting internal defects as porosities and delaminations in monolithic and sandwich composite structures, and providing a results visualization by a 2D or 3D defects map. The choice of these methods was motivated by DAHER SOCATA which wants to learn new NDT skills. The second part is to evaluate the elastic parameters of an orthotropic composite structure (structure composed by a virgin zone and a damaged zone) through an identification process from field measurements, by global and local step. This procedure is divided into four parts with two identification steps and a image processing step.

Thesis deals with determination of layerwise mechanical properties of composite ceramics by indirect method, namely Youngs modulus. Based on literature review, it was found that a method to determine elastic properties of one or more components of multi layered composites based on experimental modal analysis and finite element modal analysis, or analytical approach exists. Method based on FE modal analysis was applied to ceramic laminate, where it was attempt to determine youngs modulus of one component. Beyond that, it was attempt to determine Youngs moduli of both components using first two bending resonant frequencies. Results were unsatisfying. Sensitivity analysis showed that layers with unknown Youngs modulus were overly sensitive to small changes in input parameters due to their small relative thickness with respect to thickness of laminate and due to location in laminate. Based on this conclusion, recommendations were made with respect to suitable geometry of test specimens.