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Submitted by Erika Demachki (erikademachki@gmail.com) on 2014-09-22T20:32:01Z No. of bitstreams: 2 Lara Rodrigues.pdf: 17878503 bytes, checksum: a51778a9fbf6a31b2a71fe0c9c462105 (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) / Approved for entry into archive by Luciana Ferreira (lucgeral@gmail.com) on 2014-09-23T15:24:03Z (GMT) No. of bitstreams: 2 Lara Rodrigues.pdf: 17878503 bytes, checksum: a51778a9fbf6a31b2a71fe0c9c462105 (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) / Made available in DSpace on 2014-09-23T15:24:03Z (GMT). No. of bitstreams: 2 Lara Rodrigues.pdf: 17878503 bytes, checksum: a51778a9fbf6a31b2a71fe0c9c462105 (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) Previous issue date: 2013-02-14 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / The aim of this work is to investigate the interaction and modal coupling phenomena on the nonlinear vibrations of simply supported cylindrical shell subject to both harmonic axial and lateral loads. The equations of motion of the cylindrical shell are deduced from their energy functionals and the strain field is based on the nonlinear Donnell shallow shell theory. Finally, the problem is reduced to a system of nonlinear ordinary differential equations by the application of the standard Galerkin method. The modal expansion that describes the transverse displacement of the shell is obtained by applying perturbation techniques, which identifies the importance of each term in the modal expansion by the power of the perturbation parameter. The Karhunen-Loève method is applied in order to verify the importance of each term in the modal expansion, quantifying the contribution of each of these terms in the total energy of the system. The starting solution used in the perturbation procedure contains two modes of vibration with the same natural frequency and their respective companion modes, yielding a modal expansion able to describe the modal interaction between these two modes. Then, the influence of modal interaction on the nonlinear behavior of the cylindrical shell, subjected to both lateral and axial harmonic load is studied. From the analysis of the resonance curves, the parametric instability and escape boundaries, the bifurcation diagrams, the basins of attraction and phase portraits of the cylindrical shell is possible to identify situations in which the consideration of modal interaction is necessary. / Neste trabalho estudam-se as vibrações não lineares de cascas cilíndricas simplesmente apoiadas sujeitas a um carregamento lateral e a um carregamento axial, ambos harmônicos, com o objetivo de se analisar fenômenos como o acoplamento e a interação modal. As equações de movimento da casca cilíndrica são deduzidas a partir de seus funcionais de energia. O campo de deformações da casca cilíndrica é descrito com base na teoria não linear de Donnell para cascas esbeltas e o problema é reduzido a um sistema de equações diferenciais ordinárias não lineares a partir da aplicação do método de Galerkin. As expansões modais que descrevem o campo de deslocamento transversal da casca são obtidas através da aplicação do método da perturbação, que identifica a importância de cada termo da expansão modal a partir da potência do parâmetro de perturbação. O método de Karhunen-Loève é aplicado a fim de se verificar a importância de cada termo da expansão modal, quantificando a participação de cada um desses termos na energia total do sistema. Utilizam-se, como solução inicial do método da perturbação, dois modos de vibração com frequência natural igual e com seus respectivos companion modes, obtendo-se uma expansão modal capaz de descrever a interação modal entre esses dois modos. Em seguida, analisa-se a influência da interação modal no comportamento não linear da casca cilíndrica submetidas a cargas laterais e axiais harmônicas. A partir da análise das curvas de ressonância, das fronteiras de instabilidade paramétrica, dos diagramas de bifurcação, das bacias de atração e dos planosfase da casca cilíndrica é possível identificar em quais situações de carregamento a consideração da interação modal se faz necessária.

In the spring of 1999 NASA will launch the scatterometer SeaWinds, beginning a 3 year mission to measure the ocean winds. SeaWinds is different from previous spaceborne scatterometers in that it employs a rotating pencil-beam antenna as opposed to fixed fan-beam antennas. The scanning beam provides greater coverage but causes the wind retrieval accuracy to vary across the swath. This thesis develops a filed-wise wind retrieval algorithm to improve the overall wind retrieval accuracy for use with SeaWinds data. In order to test the field-wise wind retrieval algorithm, methods for simulating wind fields are developed. A realistic approach interpolates the NASA Scatterometer (NSCAT) estimates to fill a SeaWinds swath using optimal interpolation along with linear wind filed models. The two stages of the field-wise wind retrieval algorithm are filed-wise estimation and field-wise ambiguity selection. Field-wise estimation is implemented using a 22 parameter Karhunen-Loeve (KL) wind field model in conjunction with a maximum likelihood objective function. An augmented multi-start global optimization is developed which uses information from the point-wise estimates to aid in a global search of the objective function. The local minima in the objective function are located using the augmented multi-start search techniques and are stored as field-wise ambiguities. The ambiguity selection algorithm uses a field-wise median filter to select the field-wise ambiguity closest to the true wind in each region. Point-wise nudging is used to further improve the filed-wise estimate using information from the point-wise estimates. Combined, these two techniques select a good estimate of the wind 95% of the time. The overall performance of the field-wise wind retrieval algorithm is compared with the performance of the current point-wise techniques. Field-wise estimation techniques are shown to be potentially better than point-wise techniques. The field-wise estimates are also shown to be very useful tools in point-wise ambiguity selection since 95.8%-96.6% of the point-wise estimates closest to the field-wise estimates are the correct aliases.

Artificial Neural Networks (ANNs) can be viewed as a mathematical model to simulate natural and biological systems on the basis of mimicking the information processing methods in the human brain. The capability of current ANNs only focuses on approximating arbitrary deterministic input-output mappings. However, these ANNs do not adequately represent the variability which is observed in the systems’ natural settings as well as capture the complexity of the whole system behaviour. This thesis addresses the development of a new class of neural networks called Stochastic Neural Networks (SNNs) in order to simulate internal stochastic properties of systems. Developing a suitable mathematical model for SNNs is based on canonical representation of stochastic processes or systems by means of Karhunen-Loève Theorem. Some successful real examples, such as analysis of full displacement field of wood in compression, confirm the validity of the proposed neural networks. Furthermore, analysis of internal workings of SNNs provides an in-depth view on the operation of SNNs that help to gain a better understanding of the simulation of stochastic processes by SNNs.

In many instances arising prominently, but not exclusively, in imaging problems, it is important to condense the salient information so as to obtain a low-dimensional approximant of the data. This thesis is concerned with two basic situations which call for such a dimension reduction. The first of these is the statistical recovery of smooth edges in regression and density surfaces. The edges are understood to be contiguous curves, although they are allowed to meander almost arbitrarily through the plane, and may even split at a finite number of points to yield an edge graph. A novel locally-parametric nonparametric method is proposed which enjoys the benefit of being relatively easy to implement via a `tracking' approach. These topics are discussed in Chapters 2 and 3, with pertaining background material being given in the Appendix. In Chapter 4 we construct concomitant confidence bands for this estimator, which have asymptotically correct coverage probability. The construction can be likened to only a few existing approaches, and may thus be considered as our main contribution. ¶ Chapter 5 discusses numerical issues pertaining to the edge and confidence band estimators of Chapters 2-4. Connections are drawn to popular topics which originated in the fields of computer vision and signal processing, and which surround edge detection. These connections are exploited so as to obtain greater robustness of the likelihood estimator, such as with the presence of sharp corners. ¶ Chapter 6 addresses a dimension reduction problem for spatial data where the ultimate objective of the analysis is the discrimination of these data into one of a few pre-specified groups. In the dimension reduction step, an instrumental role is played by the recently developed methodology of functional data analysis. Relatively standar non-linear image processing techniques, as well as wavelet shrinkage, are used prior to this step. A case study for remotely-sensed navigation radar data exemplifies the methodology of Chapter 6.

La problématique du calage d'historique en ingénierie de réservoir, c'est-à-dire le calage des modèles géostatistiques aux données de production, est un problème inverse mal posé. Dans un cadre bayésien, sa résolution suppose l'inférence de la distribution de probabilité du modèle géostatistique conditionné aux données dynamiques, rendant compte à la fois de l'a priori géologique, exprimé dans le modèle géostatistique, et de l'adéquation aux données de production. Typiquement, la résolution de ce problème passe par la génération d'un ensemble de réalisations calées aux données, échantillon représentatif de cette distribution. Les modèles géostatistiques sont en général discrétisés sur des grilles de plusieurs centaines de milliers, voire des millions de blocs ; les approches classiques tentent de résoudre le problème inverse en considérant l'ensemble des blocs comme paramètres du modèle. Sa dimension est alors considérable et les méthodes d'échantillonnages deviennent impraticables sur un cas réel. Il convient alors de choisir une paramétrisation susceptible de réduire la dimension du problème. Dans la première partie de cette thèse, nous présentons une méthode de paramétrisation optimale des modèles géostatistiques basés sur les champs aléatoires gaussiens, à partir de leur décomposition de Karhunen-Loève (KL). Nous en décrivons les fondements théo- riques, puis, sur des applications aux modèles de champs aléatoires gaussiens courants en géostatistique, selon des critères d'abord statistiques puis hydrodynamiques, nous quantifions la réduction de la dimension du problème offerte par cette paramétrisation. Dans la seconde partie, nous présentons les principes des méthodes de Monte-Carlo par Chaînes de Markov (MCMC) et les défauts des méthodes classiques pour la résolution du problème inverse dans le cadre bayésien. Nous développons alors l'approche par chaînes de Markov en interaction dont nous exposons les avantages. Enfin, les résultats obtenus par l'emploi conjoint de ces deux méthodes sont présentés dans deux articles. Une approche différente, passant par l'emploi de méthodes d'analyse de sensibilité, est également décrite dans un troisième article.

Les études des phénomènes d'interaction sismique sol-structure pour le dimensionnement d'ouvrages en génie civil sont fondées sur deux hypothèses simplificatrices fortes : l'homogénéité latérale du sol sous la fondation, et la représentation du mouvement sismique par des ondes planes à incidences verticales ou inclinées. Pour de grands ouvrages reposant sur des radiers flexibles étendus, ces hypothèses ne sont plus valides, d'autant que les observations in situ des ondes sismiques font apparaître une variabilité spatiale importante même sur de courtes distances et indépendamment de l'effet du passage d'onde. Dans ce travail sont développés les outils de modélisation et d'analyse numérique permettant de tenir compte de cette variabilité ainsi que de celle des caractéristiques mécaniques du sol. Une approche probabiliste est retenue, et leur influence est directement reliée à la réponse de la structure au séisme par une formulation intégrale incorporant ces deux aspects simultanément. Pour une mise en oeuvre numérique efficace, la dimension aléatoire des fluctuations - grandes ou petites - aléatoires des caractéristiques mécaniques du sol est réduite par l'introduction du développement de Karhunen-Loeve de l'opérateur de raideur dynamique associé. Cette technique est aussi appliquée au champ sismique incident. Les résultats obtenus pour des cas complexes réalistes permettent de mettre en évidence certains phénomènes dont l'appréhension apparaît indispensable dans le cadre d'une étude industrielle. Ils donnent notamment quelques indications utiles sur la sensibilité de la réponse de la structure à la variabilité spatiale du mouvement sismique ou des paramètres du sol.

Des modèles dynamiques sont souvent utilisés pour simuler l'impact des pratiques agricoles et parfois pour tester des règles de décision. Ces modèles incluent de nombreux paramètres incertains et il est parfois difficile voire impossible de tous les estimer. Une pratique courante dans la littérature consiste à sélectionner les paramètres clés à l'aide d'indices de sensibilité calculés par simulation et de n'estimer que les paramètres les plus influents. Bien que cette démarche soit intuitive, son intérêt réel et ses conséquences sur la qualité prédictive des modèles ne sont pas connus. Nos travaux de recherches ont pour ambition d'évaluer cette pratique des modélisateurs en établissant une relation entre les indices de sensibilité des paramètres d'un modèle et des critères d'évaluation de modèles tels que le MSEP (Mean Square Error of Prediction) et le MSE (Mean Square Error), souvent utilisés en agronomie. L'établissement d'une telle relation nécessite le développement d'une méthode d'AS qui fournit un unique indice par facteur qui prend en compte les corrélations entre les différentes sorties du modèle obtenues à différentes dates. Nous proposons un nouvel indice de sensibilité global qui permet de synthétiser les effets des facteurs incertains sur l'ensemble des dynamiques simulées à l'aide de modèle. Plusieurs méthodes sont présentées dans ce mémoire pour calculer ces nouveaux indices. Les performances de ces méthodes sont évaluées pour deux modèles agronomiques dynamiques: Azodyn et WWDM. Nous établissons également dans ce mémoire, une relation formelle entre le MSE, le MSEP et les indices de sensibilité dans le cas d'un modèle linéaire et une relation empirique entre le MSEP et les indices dans le cas du modèle dynamique non linéaire CERES-EGC. Ces relations montrent que la sélection de paramètres à l'aide d'indices de sensibilité n'améliore les performances des modèles que sous certaines conditions.

The Poiseuille Flow is the flow of a viscous incompressible fluid in a channel between two infinite parallel plates. The behaviour of flow is properly described by the well-known Navier-Stokes Equations. The fact that Navier-Stokes equations are partial differential equations makes their solution difficult. They can rarely be solved in closed form. On the other hand, numerical techniques can be applied successfully to the well-posed partial differential equations. In the present study pseudo-spectral method is implemented to analyze the Poiseuille Flow. The pseudo-spectral method is a high-accuracy numerical modelling technique. It is an optimum choice for the Poiseuille flow analysis due to the flows simple geometry. The method makes use of Fourier Transform and by handling operations in the Fourier space reduces the difficulty in the solution. Fewer terms are required in a pseudo-spectral orthogonal expansion to achieve the same accuracy as a lower order method. Karhunen-Lo&egrave / ve (KL) decomposition is widely used in computational fluid dynamics to achieve reduced storage requirements or construction of relatively low-dimensional models. In this study the KL basis is extracted from the flow field obtained from the direct numerical simulation of the Poiseuille flow.

Ground Moving Target Indicator (GMTI) is a well-known and widely used signal processing method in airborne and spaceborne radars. In airborne radar and GMTI literature, many radar designs and signal processing techniques have been developed to increase the detection and estimation performance under heavy interference conditions. The motion of the aircraft on which the radar is mounted, high altitudes and ranges, targets with low radar cross sections and slowly moving targets complicates the problem of localization and observation of moving targets on a huge area of interest. In order to overcome these problems, engineers developed more complex radar hardwares with many receiver channels and signal processing algorithms. Multi-channel receivers provide adaptive digital beam-forming and adaptive Doppler processing capabilities. However, designing a cost efficient and light multi-channel receiver and a signal processing unit, which can handle a huge amount of received data from multi channels, is a difficult task to accomplish. Therefore, this thesis aims to propose non-adaptive antenna beams to reduce the number of channels to two in GMTI processing. This reduction yields a simplification both in receiver structure and signal processing unit. The measure of excellence of these propositions will be the ability to detect slowly moving targets with nearly optimum performance.