Effects of rotor deformation in wind-turbine performance: The Dynamic Rotor Deformation Blade Element Momentum model (DRD-BEM)

Understanding the multi-physics phenomena associated with blade dynamics constitutes a fundamental factor for the continuous development of wind-turbine technology and the optimization of the efficiency of wind farms. Large size differences between wind-tunnel models and full scale prototypes preclude the proper extrapolation of experimental data, especially when several coupled physical phenomena are acting simultaneously; thus the need of an advanced Virtual Test Environment where innovative designs could be tested at reasonable computational cost.We present a novel approach that we call the Dynamic Rotor Deformation - Blade Element Momentum model (DRD-BEM), which effectively takes into account the effects of the complex deformation modes of the rotor structure mentioned above. It is based on a combination of two advanced numerical schemes: First, a model of the structural response of composite blades, which allows full representation of the complex modes of blade deformation at a reduced computational cost; and second, a novel aerodynamic momentum model where all the velocities, forces, and geometrical features involved are transformed by orthogonal matrices representing the instantaneous deformed configuration, which fully incorporates the effects of rotor deformation into the computation of aerodynamic loads.Results of validation cases for the NREL-5MW Wind Reference Turbine are presented and discussed.Fil: Ponta, Fernando Luis. Michigan Technological University; Estados UnidosFil: Otero, Alejandro Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Simulación Computacional para Aplicaciones Tecnológicas; Argentina. Michigan Technological University; Estados Unidos. Universidad de Buenos Aires. Facultad de Ingeniería; ArgentinaFil: Lago, Lucas Ignacio. Michigan Technological University; Estados UnidosFil: Rajan, Anurag. Michigan Technological University; Estados Unido

Analysis of elastic-plastic shells of revolution under axisymmetric loading by the finite element method

Analysis of elastic-plastic shells of revolution under axisymmetric loading by finite element metho

Coupled structural, thermal, phase-change and electromagnetic analysis for superconductors, volume 1

This research program has dealt with the theoretical development and computer implementation of reliable and efficient methods for the analysis of coupled mechanical problems that involve the interaction of mechanical, thermal, phase-change and electromagnetic subproblems. The focus application has been the modeling of superconductivity and associated quantum-state phase-change phenomena. In support of this objective the work has addressed the following issues: (1) development of variational principles for finite elements; (2) finite element modeling of the electromagnetic problem; (3) coupling of thermal and mechanical effects; and (4) computer implementation and solution of the superconductivity transition problem. The research was carried out over the period September 1988 through March 1993. The main accomplishments have been: (1) the development of the theory of parametrized and gauged variational principles; (2) the application of those principled to the construction of electromagnetic, thermal and mechanical finite elements; and (3) the coupling of electromagnetic finite elements with thermal and superconducting effects; and (4) the first detailed finite element simulations of bulk superconductors, in particular the Meissner effect and the nature of the normal conducting boundary layer. The grant has fully supported the thesis work of one doctoral student (James Schuler, who started on January 1989 and completed on January 1993), and partly supported another thesis (Carmelo Militello, who started graduate work on January 1988 completing on August 1991). Twenty-three publications have acknowledged full or part support from this grant, with 16 having appeared in archival journals and 3 in edited books or proceedings

Entanglement renormalization and gauge symmetry

A lattice gauge theory is described by a redundantly large vector space that is subject to local constraints, and can be regarded as the low energy limit of an extended lattice model with a local symmetry. We propose a numerical coarse-graining scheme to produce low energy, effective descriptions of lattice models with a local symmetry, such that the local symmetry is exactly preserved during coarse-graining. Our approach results in a variational ansatz for the ground state(s) and low energy excitations of such models and, by extension, of lattice gauge theories. This ansatz incorporates the local symmetry in its structure, and exploits it to obtain a significant reduction of computational costs. We test the approach in the context of the toric code with a magnetic field, equivalent to Z2 lattice gauge theory, for lattices with up to 16 x 16 sites (16^2 x 2 = 512 spins) on a torus. We reproduce the well-known ground state phase diagram of the model, consisting of a deconfined and spin polarized phases separated by a continuous quantum phase transition, and obtain accurate estimates of energy gaps, ground state fidelities, Wilson loops, and several other quantities.Comment: reviewed version as published in PRB; this version includes a new section about the accuracy of the results several corrections and added citation

Minimal Solutions to Geometric Problems with Multiple Cameras or Multiple Sensor Modalities

Tese de doutoramento em Engenharia Electrotécnica e de Computadores, no ramo de Especialização em Automação e Robótica, apresentada ao Departamento de Engenharia Electrotécnica e de Computadores da Universidade de CoimbraThis thesis addresses minimal problems that involve multiple cameras or a combination of cameras with other sensors, particularly focusing on four cases: extrinsic calibration between a camera and a laser rangefinder (LRF); full calibration of an ultrasound array (US) with a camera; full calibration of a camera within a calibrated network; relative pose between axial systems. The first problem (LRF-Camera) is highly important in the context of mobile robotics in order to fuse the information of an LRF and a Camera in localization maps. The second problem (US-Camera) is becoming increasingly relevant in the context of medical imaging to perform guided intervention and 3D reconstruction with US probes. Both these problems use a planar calibration target to obtain a minimal solution from 3 and 4 correspondences respectively. They are formulated as the registration between planes detected by the camera and lines detected by either the LRF or the US. The third problem (Camera-Network) is concerned with two application scenarios: addition of a new camera to a calibrated network, and tracking of a hand-held camera within the field of view of a calibrated network. The last problem (Axial System) has its main application in motion estimation of stereo camera pairs. Both these problems introduce a 5-dimensional linear subspace to model line incidence relations of an axial system, of which a pair of calibrated cameras is a particular example. In the Camera-Network problem a generalized fundamental matrix is derived to obtain a 11-correspondence minimal solution. In the Axial System problem a generalized essential matrix is derived to obtain a 10-correspondence non-minimal solution. Although it should be possible to solve this last problem with as few as 6 correspondences, the proposed solution is the closest to minimal in the literature. Additionally this thesis addresses the use of the RANSAC framework in the context of the problems mentioned above. While RANSAC is the most widely used method in computer vision for robust estimation when minimal solutions are available, it cannot be applied directly to some of the problems discussed here. A new framework -- multi-RANSAC -- is presented as an adaptation of RANSAC to problems with multiple sampling datasets. Problems with multiple cameras or multiple sensors often fall in this category and thus this new framework can greatly improve their results. Its applicability is demonstrated in both the US-Camera and the Camera-Network problems.Esta tese aborda os problemas mínimos no contexto de visão por computador, isto é, problemas com o mesmo número de restrições e de parâmetros desconhecidos, para os quais existe um conjunto finito e discreto de soluções. A tese foca-se em particular nos seguintes problemas: calibração extrínseca entre uma câmara e um sensor laser rangefinder (LRF); calibração completa de uma sonda ultrasom (US) com uma câmara; calibração completa de uma câmara dentro de uma rede calibrada; estimação de pose relativa entre sistema axiais. O primeiro problema (LRF-Camera) é extremamente importante no contexto de robótica móvel para fundir a informação de um sensor LRF e uma câmara em mapas de localização. O segundo problema (US-Camera) está-se a tornar cada vez mais relevante no contexto de imagiologia médica para realizar intervenções guiadas e reconstrução 3D com sondas ecográficas. Ambos os problemas usam um alvo de calibração planar para obter uma solução mínima usando 3 e 4 correspondências respectivamente, e são formulados como o registo 3D entre planos detectados pela câmara e linhas detectadas pelo LRF ou US. O terceiro problema (Camera-Network) tem duas aplicações em mente: a introdução de uma nova câmara numa rede calibrada, e o seguimento de uma câmara guiada manualmente dentro do campo de visão de uma rede calibrada. O último problema (Axial System) tem a sua maior aplicação na estimação de pose relativa entre pares de câmaras estéreo. Em ambos os problemas é introduzido um subespaço linear em 5 dimensões que modela as relações de incidência de linhas num sistema axial, do qual as câmaras estéreo são um caso particular. No problema Camera- Network é introduzida uma generalização da matriz fundamental que permite obter uma solução mínima com 11 correspondências. No problema Axial System é introduzida uma generalização da matrix essencial que permite obter uma solução não mínima com 10 correspondências. Apesar de ser possível, em teoria, resolver este último problema com apenas 6 correspondências, a solução apresentada nesta tese usa um menor número de correspondências que as alternativas existentes. Adicionalmente esta tese aborda o uso de RANSAC no contexto dos problemas anteriormente descritos. O RANSAC é o estimador robusto mais utilizado em visão por computador quando existem soluções mínimas para um determinado problema, no entanto não pode ser aplicado directamente em algumas das aplicações aqui descritas. Um novo método é proposto – multiset-RANSAC – que adapta o RANSAC para situações que envolvem a amostragem de múltiplos conjuntos de dados. Os problemas com múltiplas câmaras ou múltiplos sensores encontram-se mutas vezes nesta categoria, tornando o multiset-RANSAC numa ferramenta que pode melhorar bastante os resultados em alguns dos problemas focados nesta tese. A utilidade deste método é demonstrada nos problemas US-Camera e Camera-Network

Acceleration of FEM procedures in Python: application to the RVE analysis of composite materials

In this thesis project, an originally very simple Finite Element Method (FEM) code written in Python is accelerated using well-known techniques: sparse format for matrices and vectorization of operations. The estimate of the transverse elastic modulus of unidirectional fiber-reinforced composite is used as a real-world testing situation for the FEM package called feat [9]. For this purpose, a simple Representative Volume Element (RVE) analysis is created

Generalizations of the projective reconstruction theorem

We present generalizations of the classic theorem of projective reconstruction as a tool for the design and analysis of the projective reconstruction algorithms. Our main focus is algorithms such as bundle adjustment and factorization-based techniques, which try to solve the projective equations directly for the structure points and projection matrices, rather than the so called tensor-based approaches. First, we consider the classic case of 3D to 2D projections. Our new theorem shows that projective reconstruction is possible under a much weaker restriction than requiring, a priori, that all estimated projective depths are nonzero. By completely specifying possible forms of wrong configurations when some of the projective depths are allowed to be zero, the theory enables us to present a class of depth constraints under which any reconstruction of cameras and points projecting into given image points is projectively equivalent to the true camera-point configuration. This is very useful for the design and analysis of different factorization-based algorithms. Here, we analyse several constraints used in the literature using our theory, and also demonstrate how our theory can be used for the design of new constraints with desirable properties. The next part of the thesis is devoted to projective reconstruction in arbitrary dimensions, which is important due to its applications in the analysis of dynamical scenes. The current theory, due to Hartley and Schaffalitzky, is based on the Grassmann tensor, generalizing the notions of Fundamental matrix, trifocal tensor and quardifocal tensor used for 3D to 2D projections. We extend their work by giving a theory whose point of departure is the projective equations rather than the Grassmann tensor. First, we prove the uniqueness of the Grassmann tensor corresponding to each set of image points, a question that remained open in the work of Hartley and Schaffalitzky. Then, we show that projective equivalence follows from the set of projective equations, provided that the depths are all nonzero. Finally, we classify possible wrong solutions to the projective factorization problem, where not all the projective depths are restricted to be nonzero. We test our theory experimentally by running the factorization based algorithms for rigid structure and motion in the case of 3D to 2D projections. We further run simulations for projections from higher dimensions. In each case, we present examples demonstrating how the algorithm can converge to the degenerate solutions introduced in the earlier chapters. We also show how the use of proper constraints can result in a better performance in terms of finding a correct solution

Nonlinear probabilistic finite element models of laminated composite shells

A probabilistic finite element analysis procedure for laminated composite shells has been developed. A total Lagrangian finite element formulation, employing a degenerated 3-D laminated composite shell with the full Green-Lagrange strains and first-order shear deformable kinematics, forms the modeling foundation. The first-order second-moment technique for probabilistic finite element analysis of random fields is employed and results are presented in the form of mean and variance of the structural response. The effects of material nonlinearity are included through the use of a rate-independent anisotropic plasticity formulation with the macroscopic point of view. Both ply-level and micromechanics-level random variables can be selected, the latter by means of the Aboudi micromechanics model. A number of sample problems are solved to verify the accuracy of the procedures developed and to quantify the variability of certain material type/structure combinations. Experimental data is compared in many cases, and the Monte Carlo simulation method is used to check the probabilistic results. In general, the procedure is quite effective in modeling the mean and variance response of the linear and nonlinear behavior of laminated composite shells