In this dissertation we present an analysis for the discontinuous Galerkin discretization error of multi-dimensional first-order linear symmetric and symmetrizable hyperbolic systems of conservation laws. We explicitly write the leading term of the local DG error, which is spanned by Legendre polynomials of degree p and p+1 when p-th degree polynomial spaces are used for the solution. For special hyperbolic systems, where the coefficient matrices are nonsingular, we show that the leading term of the error is spanned by (p+1)-th degree Radau polynomials. We apply these asymptotic results to observe that projections of the error are pointwise O(h^p+2)-superconvergent in some cases and establish superconvergence results for some integrals of the error. We develop an efficient implicit residual-based a posteriori error estimation scheme by solving local finite element problems to compute estimates of the leading term of the discretization error. For smooth solutions we obtain error estimates that converge to the true error under mesh refinement. We first show these results for linear symmetric systems that satisfy certain assumptions, then for general linear symmetric systems. We further generalize these results to linear symmetrizable systems by considering an equivalent symmetric formulation, which requires us to make small modifications in the error estimation procedure. We also investigate the behavior of the discretization error when the Lax-Friedrichs numerical flux is used, and we construct asymptotically exact a posteriori error estimates. While no superconvergence results can be obtained for this flux, the error estimation results can be recovered in most cases. These error estimates are used to drive h- and p-adaptive algorithms and assess the numerical accuracy of the solution. We present computational results for different fluxes and several linear and nonlinear hyperbolic systems in one, two and three dimensions to validate our theory. Examples include the wave equation, Maxwell's equations, and the acoustic equation. / Ph. D.

A Flexible Galerkin Finite Element Method (FGM) is a hybrid class of finite element methods that combine the usual continuous Galerkin method with the now popular discontinuous Galerkin method (DGM). A detailed description of the formulation of the FGM on a hyperbolic partial differential equation, as well as the data structures used in the FGM algorithm is presented. Some hp-convergence results and computational cost are included. Additionally, an a posteriori error estimate for the DGM applied to a two-dimensional hyperbolic partial differential equation is constructed. Several examples, both linear and nonlinear, indicating the effectiveness of the error estimate are included. / Ph. D.

In this thesis, we present a simple and efficient \emph{a posteriori} error estimation procedure for a discontinuous finite element method applied to scalar first-order hyperbolic problems on structured and unstructured tetrahedral meshes. We present a local error analysis to derive a discontinuous Galerkin orthogonality condition for the leading term of the discretization error and find basis functions spanning the error for several finite element spaces. We describe an implicit error estimation procedure for the leading term of the discretization error by solving a local problem on each tetrahedron. Numerical computations show that the implicit \emph{a posteriori} error estimation procedure yields accurate estimates for linear and nonlinear problems with smooth solutions. Furthermore, we show the performance of our error estimates on problems with discontinuous solutions. We investigate pointwise superconvergence properties of the discontinuous Galerkin (DG) method using enriched polynomial spaces. We study the effect of finite element spaces on the superconvergence properties of DG solutions on each class and type of tetrahedral elements. We show that, using enriched polynomial spaces, the discretization error on tetrahedral elements having one inflow face, is O(h^{p+2}) superconvergent on the three edges of the inflow face, while on elements with one inflow and one outflow faces the DG solution is O(h^{p+2}) superconvergent on the outflow face in addition to the three edges of the inflow face. Furthermore, we show that, on tetrahedral elements with two inflow faces, the DG solution is O(h^{p+2}) superconvergent on the edge shared by two of the inflow faces. On elements with two inflow and one outflow faces and on elements with three inflow faces, the DG solution is O(h^{p+2}) superconvergent on two edges of the inflow faces. We also show that using enriched polynomial spaces lead to a simpler{a posterior error estimation procedure. Finally, we extend our error analysis for the discontinuous Galerkin method applied to linear three-dimensional hyperbolic systems of conservation laws with smooth solutions. We perform a local error analysis by expanding the local error as a series and showing that its leading term is O( h^{p+1}). We further simplify the leading term and express it in terms of an optimal set of polynomials which can be used to estimate the error. / Ph. D.

O trabalho aborda a questão das estimativas a posteriori dos erros de discretização e particularmente a recuperação dos gradientes de soluções numéricas obtidas com o método dos elementos finitos (MEF) e com o método dos elementos finitos generalizados (MEFG). Inicialmente, apresenta-se, em relação ao MEF, um resumido estado da arte e conceitos fundamentais sobre este tema. Em seguida, descrevem-se os estimadores propostos para o MEF denominados Estimador Z e \"Superconvergent Patch Recovery\" (SPR). No âmbito do MEF propõe-se de modo original a incorporação do \"Singular Value Decomposition\" (SVD) ao SPR aqui mencionada como SPR Modificado. Já no contexto do MEFG, apresenta-se um novo estimador do erro intitulado EPMEFG, estendendo-se para aquele método as idéias do SPR Modificado. No EPMEFG, a função polinomial local que permite recuperar os valores nodais dos gradientes da solução tem por suporte nuvens (conjunto de elementos finitos que dividem um nó comum) e resulta da aplicação de um critério de aproximação por mínimos quadrados em relação aos pontos de superconvergência. O número destes pontos é definido a partir de uma análise em cada elemento que compõe a nuvem, considerando-se o grau da aproximação local do campo de deslocamentos enriquecidos. Exemplos numéricos elaborados com elementos lineares triangulares e quadrilaterais são resolvidos com o Estimador Z, o SPR Modificado e o EPMEFG para avaliar a eficiência de cada estimador. Essa avaliação é realizada mediante o cálculo dos índices de efetividade. / The paper addresses the issue of a posteriori estimates of discretization errors and particularly the recovery of gradients of numerical solutions obtained with the finite element method (FEM) and the generalized finite element method (GFEM). Initially, it is presented, for the MEF, a brief state of the art and fundamental concepts about this topic. Next, it is described the proposed estimators for the FEM called Z-Estimator and Superconvergent Patch Recovery (SPR). It is proposed, originally, in the ambit of the FEM, the incorporation of the \"Singular Value Decomposition (SVD) to SPR mentioned here as Modified SPR. On the other hand, in the context of GFEM, it is presented a new error estimator entitled EPMEFG in order to expand the ideas of Modified SPR to that method. In EPMEFG, the local polynomial function that allows to recover the nodal values of the gradients of the solution has for support clouds (set of finite elements that share a common node) and results from the applying of a criterion of least squares approximation in relation to the superconvergent points. The number of these points is defined from an analysis of each cloud\'s element, considering the degree of local approximation of the displacement field enriched. Numerical examples elaborated with linear triangular and quadrilateral elements are solved with the Z-Estimator, the Modified SPR and the EPMEFG to evaluate the efficiency of each estimator. This evaluation is done calculating the effectivity indexes.

L'objectif de la thèse est l'étude mathématique et l'analyse numérique du problème non linéaire de Sobolev. Un premier chapitre est consacré à l'analyse a priori pour le problème de Sobolev où on utilise des méthodes de semi-discrétisation explicite en temps. Des estimations d'erreurs ont été obtenues assurant que les schémas numériques utilisés convergent lorsque le pas de discrétisation en temps et le pas de discrétisation en espace tendent vers zéro. Dans le second chapitre, on s'intéresse au problème de Sobolev singulièrement perturbé. En vue de la stabilité des schémas numériques, on utilise dans cette partie des méthodes numériques implicites (la méthode d'Euler et la méthode de Crank- Nicolson) pour discrétiser le problème par rapport au temps. Dans le troisième chapitre, on présente des applications et des illustrations où on utilise le logiciel "FreeFem++". Dans le dernier chapitre, on considère une équation de type Sobolev et on s'intéresse à la dérivation d'estimations d'erreur a posteriori pour la discrétisation de cette équation par la méthode des éléments finis conforme en espace et un schéma d'Euler implicite en temps. La borne supérieure est globale en espace et en temps et permet le contrôle effectif de l'erreur globale. A la fin du chapitre, on propose un algorithme adaptatif qui permet d'atteindre une précision relative fixée par l'utilisateur en raffinant les maillages adaptativement et en équilibrant les contributions en espace et en temps de l'erreur. On présente également des essais numériques. / The purpose of this work is the mathematical study and the numerical analysis of the nonlinear Sobolev problem. A first chapter is devoted to the a priori analysis for the Sobolev problem, where we use an explicit semidiscretization in time. A priori error estimates were obtained ensuring that the used numerical schemes converge when the time step discretization and the spatial step discretization tend to zero. In a second chapter, we are interested in the singularly perturbed Sobolev problem. For the stability of numerical schemes, we used in this part implicit semidiscretizations in time (the Euler method and the Crank-Nicolson method). Our estimates of Chapters 1 and 2 are confirmed in the third chapter by some numerical experiments. In the last chapter, we consider a Sobolev equation and we derive a posteriori error estimates for the discretization of this equation by a conforming finite element method in space and an implicit Euler scheme in time. The upper bound is global in space and time and allows effective control of the global error. At the end of the chapter, we propose an adaptive algorithm which ensures the control of the total error with respect to a user-defined relative precision by refining the meshes adaptively, equilibrating the time and space contributions of the error. We also present numerical experiments.

The solution of a single optimization problem often requires computationally-demanding evaluations; this is especially true in optimal design of engineering components and systems described by partial differential equations. We present a technique for the rapid and reliable optimization of systems characterized by linear-functional outputs of partial differential equations with affine parameter dependence. The critical ingredients of the method are: (i) reduced-basis techniques for dimension reduction in computational requirements; (ii) an "off-line/on-line" computational decomposition for the rapid calculation of outputs of interest and respective sensitivities in the limit of many queries; (iii) a posteriori error bounds for rigorous uncertainty and feasibility control; (iv) Interior Point Methods (IPMs) for efficient solution of the optimization problem; and (v) a trust-region Sequential Quadratic Programming (SQP) interpretation of IPMs for treatment of possibly non-convex costs and constraints. / Singapore-MIT Alliance (SMA)

To simulate real world problems modeled by differential equations, it is often not sufficient to  consider and tackle a single equation. Rather, complex phenomena are modeled by several partial dierential equations that are coupled to each other. For example, a heart beat involve electric activity, mechanics of the movement of the walls and valves, as well as blood fow - a true multiphysics problem. There may also be ordinary differential equations modeling the reactions on a cellular level, and these may act on a much finer scale in both space and time. Determining efficient and accurate simulation tools for such multiscalar multiphysics problems is a challenge. The five scientific papers constituting this thesis investigate and present solutions to issues regarding accurate and efficient simulation using adaptive finite element methods. These include handling local accuracy through submodeling, analyzing error propagation in time-dependent  multiphysics problems, developing efficient algorithms for adaptivity in time and space, and deriving error analysis for coupled PDE-ODE systems. In all these examples, the error is analyzed and controlled using the framework of dual-weighted residuals, and the spatial meshes are handled using octree based data structures. However, few realistic geometries fit such grid and to address this issue a discontinuous Galerkin Nitsche method is presented and analyzed.

This research is concerned with the self-adaptive numerical solution of the neutral particle radiation transport problem. Radiation transport is an extremely challenging computational problem since the governing equation is seven-dimensional (3 in space, 2 in direction, 1 in energy, and 1 in time) with a high degree of coupling between these variables. If not careful, this relatively large number of independent variables when discretized can potentially lead to sets of linear equations of intractable size. Though parallel computing has allowed the solution of very large problems, available computational resources will always be finite due to the fact that ever more sophisticated multiphysics models are being demanded by industry. There is thus the pressing requirement to optimize the discretizations so as to minimize the effort and maximize the accuracy. One way to achieve this goal is through adaptive phase-space refinement. Unfortunately, the quality of discretization (and its solution) is, in general, not known a priori; accurate error estimates can only be attained via the a posteriori error analysis. In particular, in the context of the finite element method, the a posteriori error analysis provides a rigorous error bound. The main difficulty in applying a well-established a posteriori error analysis and subsequent adaptive refinement in the context of radiation transport is the strong coupling between spatial and angular variables. This research attempts to address this issue within the context of the second-order, even-parity form of the transport equation discretized with the finite-element spherical harmonics method. The objective of this thesis is to develop a posteriori error analysis in a coupled space-angle framework and an efficient adaptive algorithm. Moreover, the mesh refinement strategy which is tuned for minimizing the error in the target engineering output has been developed by employing the dual argument of the problem. This numerical framework has been implemented in the general-purpose neutral particle code EVENT for assessment.

In this thesis we focus on multiscale and multiphysics problems. We derive a posteriori error estimates for a one way coupled multiphysics problem, using the dual weighted residual method. Such estimates can be used to drive local mesh refinement in adaptive algorithms, in order to efficiently obtain good accuracy in a desired goal quantity, which we demonstrate numerically. Furthermore we prove existence and uniqueness of finite element solutions for a two way coupled multiphysics problem. The possibility of deriving dual weighted a posteriori error estimates for two way coupled problems is also addressed. For a two way coupled linear problem, we show numerically that unless the coupling of the equations is to strong the propagation of errors between the solvers goes to zero. We also apply a variational multiscale method to both an elliptic and a hyperbolic problem that exhibits multiscale features. The method is based on numerical solutions of decoupled local fine scale problems on patches. For the elliptic problem we derive an a posteriori error estimate and use an adaptive algorithm to automatically tune the resolution and patch size of the local problems. For the hyperbolic problem we demonstrate the importance of how to construct the patches of the local problems, by numerically comparing the results obtained for symmetric and directed patches.

This work develops finite element methods with high order stabilization, and robust and efficient adaptive algorithms for Large Eddy Simulation of turbulent compressible flows. The equations are approximated by continuous piecewise linear functions in space, and the time discretization is done in implicit/explicit fashion: the second order Crank-Nicholson method and third/fourth order explicit Runge-Kutta methods. The full residual of the system and the entropy residual, are used in the construction of the stabilization terms. These methods are consistent for the exact solution, conserves all the quantities, such as mass, momentum and energy, is accurate and very simple to implement. We prove convergence of the method for scalar conservation laws in the case of an implicit scheme. The convergence analysis is based on showing that the approximation is uniformly bounded, weakly consistent with all entropy inequalities, and strongly consistent with the initial data. The convergence of the explicit schemes is tested in numerical examples in 1D, 2D and 3D. To resolve the small scales of the flow, such as turbulence fluctuations, shocks, discontinuities and acoustic waves, the simulation needs very fine meshes. In this thesis, a robust adjoint based adaptive algorithm is developed for the time-dependent compressible Euler/Navier-Stokes equations. The adaptation is driven by the minimization of the error in quantities of interest such as stresses, drag and lift forces, or the mean value of some quantity. The implementation and analysis are validated in computational tests, both with respect to the stabilization and the duality based adaptation. / QC 20110627