Orientadores: Joerg Schleicher, Amelia Novais / Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Matematica, Estatistica e Computação Cientifica / Made available in DSpace on 2018-08-06T03:30:50Z (GMT). No. of bitstreams: 1 Munerato_FernandoPerin_M.pdf: 1553622 bytes, checksum: 5cb80dbf31a93da9d201b78855292dfc (MD5) Previous issue date: 2006 / Resumo: Este trabalho aborda a questão de como resolver a equação da onda imagem para o problema de remigração na profundidade através de métodos numéricos. O objetivo deste problema é a reconstrução de uma imagem das camadas geológicas do subsolo a partir de uma imagem previamente migrada com um modelo de velocidade, geralmente, incorreto. Nosso principal objetivo neste trabalho é a investigação de possíveis métodos que possam resolver os problemas que surgiram ao usarmos esquemas explícitos do método de diferenças _nitas na solução da equação da onda imagem em trabalhos anteriores, como, por exemplo, a dispersão numérica. Para isso, estudamos aqui o método de volumes _nitos, assim como esquemas implícitos do método de diferenças _nitas. O método de volumes _nitos possui como característica principal propagar as médias das células da malha ao invés de simplesmente os dados pontuais como é feito no método de diferenças _nitas. As outras tentativas para solucionar o problema da dispersão foram dois tipos de implementação de esquemas implícitos do método de diferenças _nitas, isto é, implementações implícitas de esquemas convencionais avaliados em pontos da malha e um esquema avaliado nos centros das células. A qualidade dos algoritmos estudados foi testada numericamente. Estes testes numéricos mostram que o método de volumes _nitos não é adequado para resolver o problema da dispersão, uma vez que a média calculada a cada passo aumenta o estiramento do pulso. Além disso, as implementações implícitas dos esquemas convencionais mostram o mesmo comportamento de dispersão que as implementações explícitas. Unicamente o esquema centrado foi capaz de melhorar a dispersão numérica em comparação com as implementações anteriores,porém somente para dados contendo exclusivamente baixas freqüências / Abstract: This work approaches the question of how to solve the image-wave equation for depth remigration by numerical methods. The objective is the reconstruction of an image of the geologic layers of the subsoil from a previously migrated image with a different velocity model. Our main objective in this work is the investigation of possible methods that can solve the problems that appeared when using explicit _nite-difference schemes for the solution of the image-wave equation in previous works, particularly numerical dispersion. For this purpose, we study the method of _nite volumes, as well as implicit _nite-difference schemes. The main characteristic of the _nite-volume method is to simply propagate the averages in the cells of the mesh instead of the discretized data themselves as it is done in the _nitedifference method. As another attempt to solve the problem of the dispersion, we study two types of implementation of implicit _nite-difference schemes, that is, implicit implementations of conventional schemes evaluated out the edge of the cell and a scheme evaluated in the center of the cell. The quality of the studied algoritms has been tested numerically. These numerical tests show that the method of _nite volumes is not adequate to solve the problem of dispersion, for the average calculated in each step additionally increases the pulse stretch. Moreover, the implicit implementations of the conventional schemes show the same dispersion behavior as the explicit implementations. Solely the centered scheme was capable to improve the numerical dispersion in comparison with the previous implementations, however only for data containing / Mestrado / Geofisica Computacional / Mestre em Matemática Aplicada

Este trabalho propõe um esquema de diferenças finitas compacta de alta ordem para resolver problemas elípticos com coeficientes variáveis em malhas composta. São apresentados a formulação matemática e a dedução do método compacto de quarta ordem aplicado à problemas elípticos bidimensionais, em malha regular e composta. Foi adotado o uso da biblioteca PETSc com os seus pré-condicionadores e métodos numéricos para resolver os sistemas lineares resultantes da discretização do problema. Por fim, testes visando verificar o código foram feitos, utilizando o método de soluções manufaturadas, para mostrar alta eficiência e acurácia do método desenvolvido. / This paper proposes a scheme of compact finite difference higher order for solve elliptic problems with variable coeficients in composite meshes. we present the mathematical formulation and the deduction of the compact method of fourth order applied to two-dimensional elliptic problems in regular and composite mesh . It was adopted using the PETSc library with its pre- conditioners and numerical methods for solving linear systems resulting from discretization of the problem. Finally , tests to verify the code were made using the method of manufactured solutions to show high eficiency and accuracy of the method developed .

Este trabalho tem como objetivo o desenvolvimento de um método numérico para simular escoamentos viscoelásticos tridimensionais com superfícies livres governados pelo modelo constitutivo Giesekus. As equações governantes são resolvidas pelo método de diferenças finitas numa malha deslocada. A superfície livre do fluido é modelada por partículas marcadoras, possibilitando assim a visualização e localização da superfície livre do fluido. A equação constitutiva de Giesekus é resolvida utilizando as seguintes formulações: método de Runge-Kutta de segunda ordem (também conhecido como método de Euler modificado) e transformação logarítmica do tensor conformação. O método numérico apresentado é verificado comparando-se os resultados obtidos por meio de refinamento de malha para os escoamentos em um tubo e de um jato incidindo em uma placa plana. Resultados de convergência foram obtidos por meio de refinamento de malha do escoamento totalmente desenvolvido em um tubo. Os resultados numéricos obtidos incluem a simulação de um jato incidindo em uma caixa vazia e a simulação do inchamento do extrudado (dieswell) para vários números de Weissenberg utilizando diferentes valores do fator de mobilidade do fluido. Resultados adicionais incluem simulações do fenômeno delayed dieswell para altos números de Weissenberg e altos valores do número de Reynolds. Uma comparação qualitativa com resultados experimentais é apresentada. / In this work, a numerical method for simulating viscoelastic free surface flows governed by the Giesekus constitutive equation is developed. The governing equations are solved by the finite difference method on a staggered grid. The fluid free surface is approximated by marker particles which enables the visualization and location of the free surface fluid. The Giesekus constitutive equation is solved by the following techniques: second-order Runge-Kutta, conformation tensor and logarithmic transformation of the conformation tensor. The numerical method is verified by comparing the numerical solutions obtained on a series of embedding meshes of the flow in a tube and by the flow produced by a jet flowing onto a planar surface. Additional verification and convergence results are obtained by solving tube flow employing several meshes. Results obtained include the simulation of a jet flowing into a three dimensional container and the simulation of extrudate swell using several values of the Reynolds and Weissenberg numbers and different values of the mobility parameter a. Furthermore, we present results from the simulation of the phenomenon know as delayed dieswell using highWeissenberg and Reynolds numbers. Comparisons with experimental results are given.

Magister Scientiae - MSc / Efficient numerical approaches for parameter dependent problems have been an inter- esting subject to numerical analysts and engineers over the past decades. This is due to the prominent role that these problems play in modeling many real life situations in applied sciences. Often, the choice and the e ciency of the approaches depend on the nature of the problem to solve. In this work, we consider the general linear first-order singularly perturbed Volterra integro-differential equations (SPVIDEs). These singularly perturbed problems (SPPs) are governed by integro-differential equations in which the derivative term is multiplied by a small parameter, known as "perturbation parameter". It is known that when this perturbation parameter approaches zero, the solution undergoes fast transitions across narrow regions of the domain (termed boundary or interior layer) thus affecting the convergence of the standard numerical methods. Therefore one often seeks for numerical approaches which preserve stability for all the values of the perturbation parameter, that is "numerical methods. This work seeks to investigate some "numerical methods that have been used to solve SPVIDEs. It also proposes alternative ones. The various numerical methods are composed of a fitted finite difference scheme used along with suitably chosen interpolating quadrature rules. For each method investigated or designed, we analyse its stability and convergence. Finally, numerical computations are carried out on some test examples to con rm the robustness and competitiveness of the proposed methods.

High-order accurate finite difference methods have been applied to the acoustic wave equation in discontinuous media and curvilinear geometries, using the SBP-SAT method. Strict stability is shown for the 2-D wave equation with general boundary conditions. The fourth-order accurate method for the 3-D wave equation has been implemented in C and parallelized using MPI. The implementation has been verified against an analytical solution and runs efficiently on a large number of processors.

Master of Science / Department of Industrial & Manufacturing Systems Engineering / Chih-Hang Wu / The fast advancement in computer technologies in the recent years has made the use of simulation to estimate stock/equity performances and pricing possible; however, determining the optimal exercise time and prices of American options using Monte-Carlo simulation is still a computationally challenging task due to the involved computer memory and computational complexity requirements. At each time step, the investor must decide whether to exercise the option to get the immediate payoff, or hold on to the option until a later time. Traditionally, the stock options are simulated using Monte-Carlo methods and all stock prices along the path are stored, and then the optimal exercise time is determined starting at the final time period and continuing backward in time. Also, as the number of paths simulated increases, the number of simultaneous equations that need to be solved at each time step grow proportionally. Currently, two theoretical methods have emerged in determining the optimal exercise problem. The first method uses the concept of least-squares approach in linear regression to estimate the value of continuing to hold on to the option via a set of randomly generated future stock prices. Then, the value of continuing can be compared to the payoff at current time from exercising the option and a decision can be reached, which gives the investor a higher value. The second method uses the finite difference approach to establish an exercise boundary for the American option via an artificially generated mesh on both possible stock prices and decision times. Then, the stock price is simulated and the method checks to see if it is inside the exercise boundary. In this research, these two solution approaches are evaluated and compared using discrete event simulation. This allows complex methods to be simulated with minimal coding efforts. Finally, the results from each method are compared. Although a more conservative method cannot be determined, the least-squares method is faster, more concise, easier to implement, and requires less memory than the mesh method. The motivation for this research stems from interest in simulating and evaluating complicated solution methods to the optimal exercise problem, yet requiring little programming effort to produce accurate and efficient estimation results.

Philosophiae Doctor - PhD / In this thesis, we consider some nonlinear differential models that govern unsteady magneto-hydrodynamic convective flow and mass transfer of viscous, incompressible,electrically conducting fluid past a porous plate with/without heat sources. The study focusses on the effect of a combination of a number of physical parameters (e.g., chemical reaction, suction, radiation, soret effect,thermophoresis and radiation absorption) which play vital role in these models.Non dimensionalization of these models gives us sets of differential equations. Reliable solutions of such differential equations can-not be obtained by standard numerical techniques. We therefore resorted to the use of the singular perturbation approaches. To proceed, each of these model problems is discretized in time by using a suitable time-stepping method and then by using a fitted operator finite difference method in spatial direction. The combined methods are then analyzed for stability and convergence. Aiming to study the robustness of the proposed numerical schemes with respect to change in the values of the key parame- ters, we present extensive numerical simulations for each of these models. Finally, we confirm theoretical results through a set of specificc numerical experiments.

Computer simulation of electromagnetic behaviour of a device is a common practice in modern engineering. Maxwell's equations are solved on a computer with help of numerical methods. Contemporary devices constantly grow in size and complexity. Therefore, new numerical methods should be highly efficient. Many industrial and research applications of numerical methods need to account for the frequency dependent materials. The Finite-Difference Time-Domain (FDTD) method is one of the most widely adopted algorithms for the numerical solution of Maxwell's equations. A major drawback of the FDTD method is the interdependence of the spatial and temporal discretisation steps, known as the Courant-Friedrichs-Lewy (CFL) stability criterion. Due to the CFL condition the simulation of a large object with delicate geometry will require a high spatio-temporal resolution everywhere in the FDTD grid. Application of subgridding increases the efficiency of the FDTD method. Subgridding decomposes the simulation domain into several subdomains with different spatio-temporal resolutions. The research project described in this dissertation uses the Huygens Subgridding (HSG) method. The frequency dependence is included with the Auxiliary Differential Equation (ADE) approach based on the one-pole Debye relaxation model. The main contributions of this work are (i) extension of the one-dimensional (1D) frequency-dependent HSG method to three dimensions (3D), (ii) implementation of the frequency-dependent HSG method, termed the dispersive HSG, in Fortran 90, (iii) implementation of the radio environment setting from the PGM-files, (iv) simulation of the electromagnetic wave propagating from the defibrillator through the human torso and (v) analysis of the computational requirements of the dispersive HSG program.

Wave propagation problems can be modeled by partial differential equations. In this thesis, we study wave propagation in fluids and in solids, modeled by the acoustic wave equation and the elastic wave equation, respectively. In real-world applications, waves often propagate in heterogeneous media with complex geometries, which makes it impossible to derive exact solutions to the governing equations. Alternatively, we seek approximated solutions by constructing numerical methods and implementing on modern computers. An efficient numerical method produces accurate approximations at low computational cost. There are many choices of numerical methods for solving partial differential equations. Which method is more efficient than the others depends on the particular problem we consider. In this thesis, we study two numerical methods: the finite difference method and the discontinuous Galerkin method. The finite difference method is conceptually simple and easy to implement, but has difficulties in handling complex geometries of the computational domain. We construct high order finite difference methods for wave propagation in heterogeneous media with complex geometries. In addition, we derive error estimates to a class of finite difference operators applied to the acoustic wave equation. The discontinuous Galerkin method is flexible with complex geometries. Moreover, the discontinuous nature between elements makes the method suitable for multiphysics problems. We use an energy based discontinuous Galerkin method to solve a coupled acoustic-elastic problem.

Magnetic induction tomography (MIT) is a non-invasive, soft field imaging modality that has the potential to map the electrical conductivity (σ) distribution inside an object under investigation. In MIT, a number of exciter and receiver coils are distributed around the periphery of the object. A primary magnetic field is emitted by each exciter, and interacts with the object. This induces eddy currents in the object, which in turn create a secondary field. This latter is coupled to the receiver coils and voltages are induced. An image reconstruction algorithm is then used to infer the conductivity map of the object. In this thesis, the application of MIT for volumetric imaging of objects with low conductivity materials (< 5 Sm-1) and dimensions < 1 m is investigated. In particular, two low conductivity applications are approached: imaging cerebral stroke and imaging the saline water in multiphase flows. In low conductivity applications, the measured signals are small and the spatial sensitivity is critically compromised making the associated inverse problem severely non-linear and ill-posed.The main contribution from this study is to investigate three non-linear optimisation techniques for solving the MIT inverse problem. The first two methods, namely regularised Levenberg Marquardt method and trust region Powell's Dog Leg method, employ damping and trust region strategies respectively. The third method is a modification of the Gauss Newton method and utilises a damping regularisation technique. An optimisation in the convergence and stability of the inverse solution was observed with these methods compared to standard Gauss Newton method. For such non linear treatment, re-evaluation of the forward problem is also required. The forward problem is solved numerically using the impedance method and a weakly coupled field approximation is employed to reduce the computation time and memory requirements. For treating the ill-posedness, different regularisation methods are investigated. Results show that the subspace regularisation technique is suitable for absolute imaging of the stroke in a real head model with synthetic data. Tikhonov based smoothing and edge preserving regularisation methods also produced successful results from simulations of oil/water. However, in a practical setup, still large geometrical and positioning noise causes a major problem and only difference imaging was viable to achieve a reasonable reconstruction.