Um método SN híbrido direto para cálculos de sistemas combustível-moderador em geometria unidimensional

Desenvolvemos nesta dissertação um método híbrido direto para o cálculo do fator de desvantagem e descrição da distribuição do fluxo de nêutrons em sistemas combustível-moderador. Na modelagem matemática, utilizamos a equação de transporte de Boltzmann independente do tempo, considerando espalhamento linearmente anisotrópico no modelo monoenergético e espalhamento isotrópico no modelo multigrupo, na formulação de ordenadas discretas (SN), em geometria unidimensional. Desenvolvemos nesta dissertação um método híbrido direto para o cálculo do fator de desvantagem e descrição da distribuição do fluxo de nêutrons em sistemas combustível-moderador. Na modelagem matemática, utilizamos a equação de transporte de Boltzmann independente do tempo, considerando espalhamento linearmente anisotrópico no modelo monoenergético e espalhamento isotrópico no modelo multigrupo, na formulação de ordenadas discretas (SN), em geometria unidimensional. Descrevemos uma análise espectral das equações de ordenadas discretas (SN)a um grupo e a dois grupos de energia, onde seguimos uma analogia com o método de Case. Utilizamos, neste método, quadraturas angulares diferentes no combustível (NC) e no moderador (NM), onde em geral assumimos que NC > NM . Condições de continuidade especiais que acoplam os fluxos angulares que emergem do combustível (moderador) e incidem no moderador (combustível), foram utilizadas com base na equivalência entre as equações SN e PN-1, o que caracteriza a propriedade híbrida do modelo proposto. Sendo um método híbrido direto, utilizamos as NC + NM equações lineares e algébricas constituídas pelas (NC + NM)/2 condições de contorno reflexivas e (NC + NM)/2 condições de continuidade para determinarmos as NC + NM constantes. Com essas constantes podemos calcular os valores dos fluxos angulares e dos fluxos escalares em qualquer ponto do domínio. Apresentamos resultados numéricos para ilustrar a eficiência e a precisão do método proposto.

Fast numerical methods for mixed, singular Helmholtz boundary value problems and Laplace eigenvalue problems - with applications to antenna design, sloshing, electromagnetic scattering and spectral geometry

This thesis presents a novel class of algorithms for the solution of scattering and eigenvalue problems on general two-dimensional domains under a variety of boundary conditions, including non-smooth domains and certain "Zaremba" boundary conditions - for which Dirichlet and Neumann conditions are specified on various portions of the domain boundary. The theoretical basis of the methods for the Zaremba problems on smooth domains concern detailed information, which is put forth for the first time in this thesis, about the singularity structure of solutions of the Laplace operator under boundary conditions of Zaremba type. The new methods, which are based on use of Green functions and integral equations, incorporate a number of algorithmic innovations, including a fast and robust eigenvalue-search algorithm, use of the Fourier Continuation method for regularization of all smooth-domain Zaremba singularities, and newly derived quadrature rules which give rise to high-order convergence even around singular points for the Zaremba problem. The resulting algorithms enjoy high-order convergence, and they can tackle a variety of elliptic problems under general boundary conditions, including, for example, eigenvalue problems, scattering problems, and, in particular, eigenfunction expansion for time-domain problems in non-separable physical domains with mixed boundary conditions.

Algebraic Techniques in Coding Theory: Entropy Vectors, Frames, and Constrained Coding

The study of codes, classically motivated by the need to communicate information reliably in the presence of error, has found new life in fields as diverse as network communication, distributed storage of data, and even has connections to the design of linear measurements used in compressive sensing. But in all contexts, a code typically involves exploiting the algebraic or geometric structure underlying an application. In this thesis, we examine several problems in coding theory, and try to gain some insight into the algebraic structure behind them.

The first is the study of the entropy region - the space of all possible vectors of joint entropies which can arise from a set of discrete random variables. Understanding this region is essentially the key to optimizing network codes for a given network. To this end, we employ a group-theoretic method of constructing random variables producing so-called "group-characterizable" entropy vectors, which are capable of approximating any point in the entropy region. We show how small groups can be used to produce entropy vectors which violate the Ingleton inequality, a fundamental bound on entropy vectors arising from the random variables involved in linear network codes. We discuss the suitability of these groups to design codes for networks which could potentially outperform linear coding.

The second topic we discuss is the design of frames with low coherence, closely related to finding spherical codes in which the codewords are unit vectors spaced out around the unit sphere so as to minimize the magnitudes of their mutual inner products. We show how to build frames by selecting a cleverly chosen set of representations of a finite group to produce a "group code" as described by Slepian decades ago. We go on to reinterpret our method as selecting a subset of rows of a group Fourier matrix, allowing us to study and bound our frames' coherences using character theory. We discuss the usefulness of our frames in sparse signal recovery using linear measurements.

The final problem we investigate is that of coding with constraints, most recently motivated by the demand for ways to encode large amounts of data using error-correcting codes so that any small loss can be recovered from a small set of surviving data. Most often, this involves using a systematic linear error-correcting code in which each parity symbol is constrained to be a function of some subset of the message symbols. We derive bounds on the minimum distance of such a code based on its constraints, and characterize when these bounds can be achieved using subcodes of Reed-Solomon codes.

Directional algebraic reconstruction technique for electrical impedance tomography

We assume that the resistance matrix can be found in electrical impedance tomography from the assumption of linear dependence between the voltages and the currents and with the help of the resistance matrix and the transfer impedance between the electrodes, a directional algebraic reconstruction technique is proposed. The goal is to reconstruct the resistivity distribution by weighting the matrices that are obtained by calculating the orthogonal distance of the underlying mesh elements from the neighbouring port resistivity lines. These weighting matrices, which only depend on the topology of the underlying mesh, can be calculated offline and result in a computationally efficient online procedure with a reasonable image reconstruction performance. Simulation results are provided to validate this approach.