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    Computational and numerical analysis of differential equations using spectral based collocation method.

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    Doctoral Degree. University of KwaZulu-Natal, Pietermaritzburg.In this thesis, we develop accurate and computationally eļ¬ƒcient spectral collocation-based methods, both modiļ¬ed and new, and apply them to solve diļ¬€erential equations. Spectral collocation-based methods are the most commonly used methods for approximating smooth solutions of diļ¬€erential equations deļ¬ned over simple geometries. Procedurally, these methods entail transforming the gov erning diļ¬€erential equation(s) into a system of linear algebraic equations that can be solved directly. Owing to the complexity of expanding the numerical algorithms to higher dimensions, as reported in the literature, researchers often transform their models to reduce the number of variables or narrow them down to problems with fewer dimensions. Such a process is accomplished by making a series of assumptions that limit the scope of the study. To address this deļ¬ciency, the present study explores the development of numerical algorithms for solving ordinary and partial diļ¬€erential equations deļ¬ned over simple geometries. The solutions of the diļ¬€erential equations considered are approximated using interpolating polynomials that satisfy the given diļ¬€erential equation at se lected distinct collocation points preferably the Chebyshev-Gauss-Lobatto points. The size of the computational domain is particularly emphasized as it plays a key role in determining the number of grid points that are used; a feature that dictates the accuracy and the computational expense of the spectral method. To solve diļ¬€erential equations deļ¬ned on large computational domains much eļ¬€ort is devoted to the development and application of new multidomain approaches, based on decomposing large spatial domain(s) into a sequence of overlapping subintervals and a large time interval into equal non-overlapping subintervals. The rigorous analysis of the numerical results con ļ¬rms the superiority of these multiple domain techniques in terms of accuracy and computational eļ¬ƒciency over the single domain approach when applied to problems deļ¬ned over large domains. The structure of the thesis indicates a smooth sequence of constructing spectral collocation method algorithms for problems across diļ¬€erent dimensions. The process of switching between dimensions is explained by presenting the work in chronological order from a simple one-dimensional problem to more complex higher-dimensional problems. The preliminary chapter explores solutions of or dinary diļ¬€erential equations. Subsequent chapters then build on solutions to partial diļ¬€erential i equations in order of increasing computational complexity. The transition between intermediate dimensions is demonstrated and reinforced while highlighting the computational complexities in volved. Discussions of the numerical methods terminate with development and application of a new method namely; the trivariate spectral collocation method for solving two-dimensional initial boundary value problems. Finally, the new error bound theorems on polynomial interpolation are presented with rigorous proofs in each chapter to benchmark the adoption of the diļ¬€erent numerical algorithms. The numerical results of the study conļ¬rm that incorporating domain decomposition techniques in spectral collocation methods work eļ¬€ectively for all dimensions, as we report highly accurate results obtained in a computationally eļ¬ƒcient manner for problems deļ¬ned on large do mains. The ļ¬ndings of this study thus lay a solid foundation to overcome major challenges that numerical analysts might encounter
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