Thesis (M.App.Sc.) - Carleton University, 2006. / Includes bibliographical references (p. 127-131). Also available in electronic format on the Internet.

Thesis (Ph.D. (Physics & Electronics)) - Rhodes University, 2008.

Thesis (Ph.D.) - Carleton University, 2007. / Includes bibliographical references (p. 211-219). Also available in electronic format on the Internet.

Thesis (Ph. D.)--University of Texas at Austin, 2005. / Vita. Includes bibliographical references.

Sistemas de ensaios não destrutivos por ondas guiadas despertam cada vez mais a atenção tanto da indústria, como da academia. Isso deve-se, principalmente, às possibilidades que as ondas guiadas permitem, como maior área de triagem que o ultrassom convencional. Porém a técnica tem suas limitações, já que esta apenas gera uma estimativa da localização de um defeito e não a sua dimensão. Nessa limitação, algoritmos tomográficos apresentam uma possibilidade de avanço da técnica, pois permitem determinar não só a localização de corrosões e defeitos, mas também seu dimensionamento. Este trabalho apresenta tomografia de difração como uma alternativa para avaliação de integridade estrutural. Primeiramente, utilizou-se análise por métodos numéricos para mostrar a validade dos algoritmos e posteriormente foi realizado um experimento em uma chapa real com o objetivo de reconstruir a imagem do defeito. / Guided waves nondestructive testing systems are increasingly attracting industrial and academic attention. The mainly reason for this attention is the possibility of screening a large area than conventional ultrasound technique. However, Guided Waves Testing has limitations, since it gives only an estimation of the location of a defect, but not the dimensions. Tomographic algorithms come up with an improvement of the technique, because it allows discovery not only the location of corrosions and defects, but the dimensions too. This work brings Diffraction Tomography as an alternative to structural health monitoring. First, a numerical analysis was implemented to demonstrate the validity of the algorithms, after that an experiment in a real plate was made with the objective to recover the defect image.

abstract: All structures suffer wear and tear because of impact, excessive load, fatigue, corrosion, etc. in addition to inherent defects during their manufacturing processes and their exposure to various environmental effects. These structural degradations are often imperceptible, but they can severely affect the structural performance of a component, thereby severely decreasing its service life. Although previous studies of Structural Health Monitoring (SHM) have revealed extensive prior knowledge on the parts of SHM processes, such as the operational evaluation, data processing, and feature extraction, few studies have been conducted from a systematical perspective, the statistical model development. The first part of this dissertation, the characteristics of inverse scattering problems, such as ill-posedness and nonlinearity, reviews ultrasonic guided wave-based structural health monitoring problems. The distinctive features and the selection of the domain analysis are investigated by analytically searching the conditions of the uniqueness solutions for ill-posedness and are validated experimentally. Based on the distinctive features, a novel wave packet tracing (WPT) method for damage localization and size quantification is presented. This method involves creating time-space representations of the guided Lamb waves (GLWs), collected at a series of locations, with a spatially dense distribution along paths at pre-selected angles with respect to the direction, normal to the direction of wave propagation. The fringe patterns due to wave dispersion, which depends on the phase velocity, are selected as the primary features that carry information, regarding the wave propagation and scattering. The following part of this dissertation presents a novel damage-localization framework, using a fully automated process. In order to construct the statistical model for autonomous damage localization deep-learning techniques, such as restricted Boltzmann machine and deep belief network, are trained and utilized to interpret nonlinear far-field wave patterns. Next, a novel bridge scour estimation approach that comprises advantages of both empirical and data-driven models is developed. Two field datasets from the literature are used, and a Support Vector Machine (SVM), a machine-learning algorithm, is used to fuse the field data samples and classify the data with physical phenomena. The Fast Non-dominated Sorting Genetic Algorithm (NSGA-II) is evaluated on the model performance objective functions to search for Pareto optimal fronts. / Dissertation/Thesis / Doctoral Dissertation Mechanical Engineering 2016

Made available in DSpace on 2014-10-09T12:53:40Z (GMT). No. of bitstreams: 0 / Made available in DSpace on 2014-10-09T13:58:44Z (GMT). No. of bitstreams: 0 / Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) / Dissertação (Mestrado) / IPEN/D / Instituto de Pesquisas Energéticas e Nucleares - IPEN-CNEN/SP / FAPESP:05/03612-0

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Fundação de Amparo à Pesquisa do Estado do Rio de Janeiro / Uma forma de generalizar a teoria de Einstein da gravitação é incorporar na lagrangiana termos que dependem de escalares formados com os tensores de Ricci e Riemann, tais como (Ricci)2, ou (Riemann)2. Estas teorias tem sido estudadas intensamente nos últimos anos, já que elas podem ser usadas para descrever a expansão acelerada do universo no modelo cosmológico standard. Entre os desfios de modificar a teoria de Einstein, se encontra o de limitar a ambiguidade na escolha da dependência da lagrangiana com os escalares antes mencionados. A proposta desta dissertação é a de colocar limites sobre as possíveis lagrangianas impondo que as ondas (isto é, perturbações lineares) se propaguem no vácuo sem que apareça, shocks. / One way to generalize Einstein's theory of gravitation is by the addition of terms that depend on scalar formed with Ricci and Riemann tensors, such as (Ricci)2 or (Riemann)2 in the lagrangians.These theories have been intensively studied in recent years, since they can be used to describe the accelerated expansion of the universe in the standard cosmological model. One of the challenges to modify Einstein's theory is to limit the ambiguity in the choice of the dependence of the Lagrangian with the aforementioned scalars. The purpose of this dissertation is to put limits on the possible Lagrangians imposing that the waves(ie, linear perturbations) propagate in a vacuum without the appearance of shocks.