The reduction of noise generated by new and existing engineering products is of increasing importance commercially, socially and environmentally. Commercially, the noise emission of vehicles, such as cars and aircraft, may often be considered a selling point and the effects of noise pollution on human health and the environment has led to legislation restricting the noise emissions of many engineering products. Noise prediction schemes are important tools to help us understand and develop a means of controlling noise. Acoustic problems present numerous challenges to traditional CFD-type numerical methods rendering all but the most trivial problems unsuitable. Difficulties relate to the length scale discrepancies which arise due to the relatively tiny pressure and density fluctuations of an acoustic wave propagating over large distancesto the point of interest; the result being large computational domains to capture wave behaviour accurately between source and observer. Noise prediction may be performed using a hybrid Computational Aero-Acoustics (CAA) scheme, an approach to noise prediction which alleviates many issues associated with exclusively numerical or analytical approaches. Hybrid schemes often rely on knowledge of a Green’s function, representing the scattering of the geometry, to propagate source fluctuations to the far-field. Presently, these functions only exist in analytical form for relatively simple geometries. This research develops principles for the robust calculation of Green’s functions for general situations. In order to achieve this, three techniques to computeGreen’s functions for the Helmholtz equation within an extended class of 2D geometries are developed, evaluated and compared. Where appropriate, their extension to 3D is described. Guidance is provided on the selection of a suitable numerical method in practice given knowledge of the geometry of interest. Through inclusion of the numerical methods for the construction of Green’s functions presented here, the applicability of existing hybrid schemes will be significantly extended. Thus, it is expected that noise predictions may be performed on a more general range of geometries while exploiting the computational efficiency of hybrid prediction schemes.

No description available.

The techniques of surface deformation and mapping are useful tools for the visualization of medical surfaces, especially for highly undulated or branched surfaces. In this thesis, two algorithms are presented for flattened visualizations of multi-branched medical surfaces, such as vessels. The first algorithm is an angle preserving approach, which is based on conformal analysis. The mapping function is obtained by minimizing two Dirichlet functionals. On a triangulated representation of vessel surfaces, this algorithm can be implemented efficiently using a finite element method. The second algorithm adjusts the result from conformal mapping to produce a flattened representation of the original surface while preserving areas. It employs the theory of optimal mass transport via a gradient descent approach. A new class of image morphing algorithms is also considered based on the theory of optimal mass transport. The mass moving energy functional is revised by adding an intensity penalizing term, in order to reduce the undesired "fading" effects. It is a parameter free approach. This technique has been applied on several natural and medical images to generate in-between image sequences.

Wind power is a renewable energy source that is today the fastest growing solution to reduce CO2 emissions in the electric energy mix. Upwind horizontal axis wind turbine with three blades has been the preferred technical choice for more than two decades. This horizontal axis concept is today widely leading the market. The current PhD thesis will cover an alternative type of wind turbine with straight blades and rotating along the vertical axis. A brief overview of the main differences between the horizontal and vertical axis concept has been made. However the main focus of this thesis is the aerodynamics of the wind turbine blades. Making aerodynamically efficient turbines starts with efficient blades. Making efficient blades requires a good understanding of the physical phenomena and effective simulations tools to model them. The specific aerodynamics for straight bladed vertical axis turbine flow are reviewed together with the standard aerodynamic simulations tools that have been used in the past by blade and rotor designer. A reasonably fast (regarding computer power) and accurate (regarding comparison with experimental results) simulation method was still lacking in the field prior to the current work. This thesis aims at designing such a method. Analytical methods can be used to model complex flow if the geometry is simple. Therefore, a conformal mapping method is derived to transform any set of section into a set of standard circles. Then analytical procedures are generalized to simulate moving multibody sections in the complex vertical flows and forces experienced by the blades. Finally the fast semi analytical aerodynamic algorithm boosted by fast multipole methods to handle high number of vortices is coupled with a simple structural model of the rotor to investigate potential aeroelastic instabilities. Together with these advanced simulation tools, a standard double multiple streamtube model has been developed and used to design several straight bladed rotor ranging from 2 kW to 20 kW. / Felaktigt tryckt som Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology 704

This Ph.D thesis work is dedicated to 3D facial surface analysis, processing as well as to the newly proposed 3D face recognition modality, which is based on mapping techniques. Facial surface processing and analysis is one of the most important steps for 3Dface recognition algorithms. Automatic anthropometric facial features localization also plays an important role for face localization, face expression recognition, face registration ect., thus its automatic localization is a crucial step for 3D face processing algorithms. In this work we focused on precise and rotation invariant landmarks localization, which are later used directly for face recognition. The landmarks are localized combining local surface properties expressed in terms of differential geometry tools and global facial generic model, used for face validation. Since curvatures, which are differential geometry properties, are sensitive to surface noise, one of the main contributions of this thesis is a modification of curvatures calculation method. The modification incorporates the surface noise into the calculation method and helps to control smoothness of the curvatures. Therefore the main facial points can be reliably and precisely localized (100% nose tip localization using 8 mm precision)under the influence of rotations and surface noise. The modification of the curvatures calculation method was also tested under different face model resolutions, resulting in stable curvature values. Finally, since curvatures analysis leads to many facial landmark candidates, the validation of which is time consuming, facial landmarks localization based on learning technique was proposed. The learning technique helps to reject incorrect landmark candidates with a high probability, thus accelerating landmarks localization. Face recognition using 3D models is a relatively new subject, which has been proposed to overcome shortcomings of 2D face recognition modality. However, 3Dface recognition algorithms are likely more complicated. Additionally, since 3D face models describe facial surface geometry, they are more sensitive to facial expression changes. Our contribution is reducing dimensionality of the input data by mapping3D facial models on to 2D domain using non-rigid, conformal mapping techniques. Having 2D images which represent facial models, all previously developed 2D face recognition algorithms can be used. In our work, conformal shape images of 3Dfacial surfaces were fed in to 2D2 PCA, achieving more than 86% recognition rate rank-one using the FRGC data set. The effectiveness of all the methods has been evaluated using the FRGC and Bosphorus datasets.

Thesis (Ph. D.)--Electrical and Computer Engineering, Georgia Institute of Technology, 2005. / Madhavan Swaminathan, Committee Chair ; Sung Kyu Lim, Committee Member ; Abhijit Chatterjee, Committee Member ; David C. Keezer, Committee Member ; C. P. Wong, Committee Member. Vita. Includes bibliographical references.

Ce travail de thèse concerne l’analyse de surfaces faciales en 3D, ainsi que leur traitement, dans le récent cadre de la modalité de reconnaissance de visages en 3D,basé sur des techniques d’appariement. Le traitement de la surface faciale et son analyse constituent une étape importante dans les algorithmes de reconnaissance de visage en 3D. La localisation de points d’intérêt anthropométriques du visage joue par ailleurs un rôle important dans les techniques de localisation du visage, de reconnaissance d’expression, de recalage, etc. Ainsi, leur localisation automatique joue un rôle crucial dans les algorithmes de traitement du visage 3D. Dans ce travail, nous avons mis l’accent sur la localisation précise et invariante en rotation des points d’intérêt, qui seront utilisés plus tard pour la reconnaissance de visages. Ces points d’intérêt sont localisés en combinant les propriétés locales de la surface faciale, exprimées en termes de géométrie différentielle, et un modèle global et générique du visage. Etant donné que la sensibilité des courbures, qui sont des propriétés de géométrie différentielle, au bruit, une des contributions de cette thèse est la modification d’une méthode de calcul de courbures. Cette modification incorpore le bruit de la surface dans la méthode de calcul, et permet de contrôler la progressivité des courbures. Par conséquent, nous pouvons localiser les points d’intérêt de la surface faciale avec précision et fiabilité (100% de bonnes localisation du bout du nez avec une erreur maximale de 8mmpar exemple) y compris en présence de rotations et de bruit. La modification de la méthode de calcul de courbure a été également testée pour différentes résolutions de visage, présentant des valeurs de courbure stables. Enfin, étant donné que donné que l’analyse de courbures mène à de nombreux candidats de points d’intérêt du visage, dont la validation est coûteuse, nous proposons de localiser les points d’intérêt grâce à une méthode d’apprentissage. Cette méthode permet de rejeter précocement des faux candidats avec une grande confiance, accélérant d’autant la localisation des points d’intérêt. La reconnaissance de visages à l’aide de modèles 3D est un sujet relativement nouveau, qui a été propose pour palier aux insuffisantes de la modalité de reconnaissance de visages en 2D. Cependant, les algorithmes de reconnaissance de visage en 3D sont généralement plus complexes. De plus, étant donné que les modèles de visage 3D décrivent la géométrie du visage, ils sont plus sensibles que les images 2Dde texture aux expressions faciales. Notre contribution est de réduire la dimensionnalité des données de départ en appariant les modèles de visage 3D au domaine 2Dà l’aide de méthodes, non rigides, d’appariement conformal. L’existence de modèles2D représentant les visages permet alors d’utiliser les techniques précédemment développées dans le domaine de la reconnaissance de visages en 2D. Dans nos travaux, nous avons utilisé les cartes conformales de visages 3D en conjonction avec l’algorithme2D2 PCA, atteignant le score de 86% en reconnaissance de rang 1 sur la base de données FRGC. L’efficacité de toutes les méthodes a été évaluée sur les bases FRGC et Bosphorus. / This Ph.D thesis work is dedicated to 3D facial surface analysis, processing as well as to the newly proposed 3D face recognition modality, which is based on mapping techniques. Facial surface processing and analysis is one of the most important steps for 3Dface recognition algorithms. Automatic anthropometric facial features localization also plays an important role for face localization, face expression recognition, face registration ect., thus its automatic localization is a crucial step for 3D face processing algorithms. In this work we focused on precise and rotation invariant landmarks localization, which are later used directly for face recognition. The landmarks are localized combining local surface properties expressed in terms of differential geometry tools and global facial generic model, used for face validation. Since curvatures, which are differential geometry properties, are sensitive to surface noise, one of the main contributions of this thesis is a modification of curvatures calculation method. The modification incorporates the surface noise into the calculation method and helps to control smoothness of the curvatures. Therefore the main facial points can be reliably and precisely localized (100% nose tip localization using 8 mm precision)under the influence of rotations and surface noise. The modification of the curvatures calculation method was also tested under different face model resolutions, resulting in stable curvature values. Finally, since curvatures analysis leads to many facial landmark candidates, the validation of which is time consuming, facial landmarks localization based on learning technique was proposed. The learning technique helps to reject incorrect landmark candidates with a high probability, thus accelerating landmarks localization. Face recognition using 3D models is a relatively new subject, which has been proposed to overcome shortcomings of 2D face recognition modality. However, 3Dface recognition algorithms are likely more complicated. Additionally, since 3D face models describe facial surface geometry, they are more sensitive to facial expression changes. Our contribution is reducing dimensionality of the input data by mapping3D facial models on to 2D domain using non-rigid, conformal mapping techniques. Having 2D images which represent facial models, all previously developed 2D face recognition algorithms can be used. In our work, conformal shape images of 3Dfacial surfaces were fed in to 2D2 PCA, achieving more than 86% recognition rate rank-one using the FRGC data set. The effectiveness of all the methods has been evaluated using the FRGC and Bosphorus datasets.

No description available.

Neste trabalho estabelecemos o Teorema Central do Limite para o modelo O(N) de Heisenberg hierárquico na criticalidade via equação a derivadas parciais no limite N -> infinito. Por simplicidade consideramos apenas o caso d = 4, sendo o teorema também válido para d > 4. Pelo estudo de uma dada equação a derivadas parciais (EDP) determinamos a temperatura inversa crítica do modelo esférico hierárquico contínuo para um d > 2 qualquer, havendo conexão entre criticalidade e o ponto fixo da EDP. Por meio de uma análise geométrica da trajetória crítica obtemos informações sobre a dinâmica e distribuição dos zeros de Lee-Yang. / In this work we stablish the Central Limit Theorem for the hierarchical O(N) Heisenberg model at criticality via partial differential equation in the limit N -> infinity. For simplicity we only treat the d = 4 case but the theorem is still valid for d > 4. By studying a given partial differential equation (PDE) we determine for any d > 2 the critical inverse temperature of the continuum hierarchical spherical model, and we show a connection between criticality and the fixed point of PDE. By means of a geometric analysis of the critical trajectory we obtain some informations about Lee-Yang zeros´s dynamics and distribution.

Made available in DSpace on 2014-07-29T15:08:21Z (GMT). No. of bitstreams: 1 dissertacao wesley.pdf: 2546407 bytes, checksum: 1c1c0ce0780c785a8633268a8ba0eae0 (MD5) Previous issue date: 2008-06-06 / The present work proposes a numeric formulation for the determination of Carter's factor as a function of the geometry of the slot of electric machines. This task is made by the use of the Schwarz-Christoffel transformation. In order to reach the objective, there is the need to calculate the Schwarz-Christoffel inverse transformation. This represents a non-linear optimization problem. Therefore, it is proposed a methodology to calculate the parameters of the Schwarz-Christoffel inverse transformation using genetic algorithms. The assessment of Carter s factor is achieved considering polygonal domains with many vertices. The transformation leads to a rectangular domain approach. Moreover, some case studies are proposed and the methodology results are compared to traditional formulation results for the Carter s factor, yielding some disparities. / O presente trabalho propõe obter uma formulação numérica para a determinação do fator de Carter em função da geometria da ranhura de máquinas elétricas, utilizando o cálculo numérico da transformação de Schwarz-Christoffel. Com este objetivo, verifica-se a necessidade do cálculo da transformação inversa de Schwarz-Christoffel. Este problema representa um problema de otimização não linear. Desta forma, propõe-se uma metodologia que implementa um algoritmo genético para resolver o problema de cálculo dos parâmetros da Transformação inversa de Schwarz-Christoffel, considerando domínios poligonais com muitos vértices. Em seguida, obtém-se um domínio retangular para o qual o problema do cálculo do fator de Carter é resolvido. Desta forma, apresentam-se vários casos de estudos onde a metodologia proposta é comparada com as formulações tradicionalmente utilizadas para o cálculo do fator de Carter. Os resultados obtidos pelas diferentes metodologias são confrontados, mostrando certas disparidades.