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A posteriori error estimation is an inseparable component of any reliable numerical method for solving partial differential equations. The aim of the goal-oriented a posteriori error estimates is to control the computational error directly with respect to some quantity of interest, which makes the method very convenient for many engineering applications. The resulting error estimates may be employed for mesh adaptation which enables to find a numerical approximation of the quantity of interest under some given tolerance in a very efficient manner. In this thesis, the goal-oriented error estimates are derived for discontinuous Galerkin discretizations of the linear scalar model problems, as well as of the Euler equations describing inviscid compressible flows. It focuses on several aspects of the goal-oriented error estimation method, in particular, higher order reconstructions, adjoint consistency of the discretizations, control of the algebraic errors arising from iterative solutions of both algebraic systems, and linking the estimates with the hp-anisotropic mesh adaptation. The computational performance is demonstrated by numerical experiments.

Interpolation error estimates in terms of geometric quality measures are established for harmonic coordinates on polytopes in two and three dimensions. First we derive interpolation error estimates over convex polygons that depend on the geometric quality of the triangles in the constrained Delaunay triangulation of the polygon. This characterization is sharp in the sense that families of polygons with poor quality triangles in their constrained Delaunay triangulations are shown to produce large error when interpolating a basic quadratic function. Non-convex polygons exhibit a similar limitation: large constrained Delaunay triangles caused by vertices approaching a non-adjacent edge also lead to large interpolation error. While this relationship is generalized to convex polyhedra in three dimensions, the possibility of sliver tetrahedra in the constrained Delaunay triangulation prevent the analogous estimate from sharply reflecting the actual interpolation error. Non-convex polyhedra are shown to be fundamentally different through an example of a family of polyhedra containing vertices which are arbitrarily close to non-adjacent faces yet the interpolation error remains bounded.

La thèse porte sur l’analyse d’erreur a posteriori pour la résolution numérique de l’équation linéaire des ondes , discrétisée en temps par le schéma de Newmark et en espace par la méthode des éléments finis. Nous adoptons un choix particulier de paramètres pour le schéma de Newmark, notamment β = 1/4, γ = 1/2, qui assure que la méthode est conservative en énergie et d’ordre deux en temps. L’estimation d’erreur a posteriori, d’un ordre optimal en temps et en espace, est élaborée à partir de la discrétisation complète. L’erreur est mesurée dans une norme qui découle naturellement de la physique: H1 en espace et Linf en temps. Nous proposons d’abord un estimateur dit «à 3 points» qui fait intervenir la solution discrète en 3 points successifs du temps à chaque pas de temps. Cet estimateur fait appel à une approximation du Laplacien de la solution discrète qui doit être calculée à chaque pas de temps, en résolvant un problème auxiliaire d'éléments finis. Nous proposons ensuite un estimateur d’erreur alternatif qui permet d’éviter ces calculs supplémentaires: l’estimateur dit «à 5 points» puisqu’il met en jeu le schéma des différences finies d’ordre 4, qui fait intervenir la solution discrète en 5 points successifs du temps à chaque pas de temps. Nous démontrons que nos estimateurs en temps sont d’ordre optimal pour des solutions suffisamment lisses, sur des maillages quasi-uniformes en espace et uniformes en temps, en supposant que les conditions initiales soient discrétisées à l’aide de la projection elliptique. La trouvaille la plus intéressante de cette analyse est le rôle capitale de cette discrétisation : des discrétisations standards pour les conditions initiales, telles que l’interpolation nodale, peuvent être néfastes pour les estimateurs d’erreur en détruisant leur ordre de convergence, bien qu’elles fournissent des solutions numériques tout à fait acceptables. Des expériences numériques prouvent que nos estimateurs d’erreur sont d’ordre optimal en temps comme en espace, même dans les situations non couvertes par la théorie. En outre, notre analyse a posteriori s’étend au schéma de Newmark d’ordre deux plus général (γ = 1/2). Nous présentons des comparaisons numériques entre notre estimateur à 3 points généralisé et l’estimateur sur des grilles décalées, proposé par Georgoulis et al. Finalement, nous implémentons un algorithme adaptatif en temps et en espace basé sur notre estimateur d’erreur a posteriori à 3 points. Nous concluons par des expériences numériques qui montrent l’efficacité de l’algorithme adaptatif et révèlent l’importance de l’interpolation appropriée de la solution numérique d’un maillage à un autre, surtout vis à vis de l’optimalité de l’estimation d’erreur en temps. / This thesis focuses on the a posteriori error analysis for the linear second-order wave equation discretized by the second order Newmark scheme in time and the finite element method in space. We adopt the particular choice for the parameters in the Newmark scheme, namely β = 1/4, γ = 1/2, since it provides a conservative method with respect to the energy norm. We derive a posteriori error estimates of optimal order in time and space for the fully discrete wave equation. The error is measured in a physically natural norm: H1 in space, Linf in time. Numerical experiments demonstrate that our error estimators are of optimal order in space and time. The resulting estimator in time is referred to as the 3-point estimator since it contains the discrete solution at 3 points in time. The 3-point time error estimator contains the Laplacian of the discrete solution which should be computed via auxiliary finite element problems at each time step. We propose an alternative time error estimator that avoids these additional computations. The resulting estimator is referred to as the 5-point estimator since it contains the fourth order finite differences in time and thus involves the discrete solution at 5 points in time at each time step. We prove that our time estimators are of optimal order at least on sufficiently smooth solutions, quasi-uniform meshes in space and uniform meshes in time. The most interesting finding of this analysis is the crucial importance of the way in which the initial conditions are discretized: a straightforward discretization, such as the nodal interpolation, may ruin the error estimators while providing quite acceptable numerical solution. We also extend the a posteriori error analysis to the general second order Newmark scheme (γ = 1/2) and present numerical comparasion between the general 3-point time error estimator and the staggered grid error estimator proposed by Georgoulis et al. In addition, using obtained a posteriori error bounds, we implement an efficient adaptive algorithm in space and time. We conclude with numerical experiments that show that the manner of interpolation of the numerical solution from one mesh to another plays an important role for optimal behavior of the time error estimator and thus of the whole adaptive algorithm.

The radiative transfer equation (RTE) models the transport of radiation through a participating medium. In particular, it captures how radiation is scattered, emitted, and absorbed as it interacts with the medium. This process arises in numerous application areas, including: neutron transport in nuclear reactors, radiation therapy in cancer treatment planning, and the investigation of forming galaxies in astrophysics. As a result, there is great interest in the solution of the RTE in many different fields. We consider the energy dependent form of the RTE and allow media containing regions of negligible absorption. This particular case is not often considered due to the additional dimension and stability issues which arise by allowing vanishing absorption. In this thesis, we establish the existence and uniqueness of the underlying boundary value problem. We then proceed to develop a stable numerical algorithm for solving the RTE. Alongside the construction of the method, we derive corresponding error estimates. To show the validity of the algorithm in practice, we apply the algorithm to four different example problems. We also use these examples to validate our theoretical results.

Steuerungsprobleme treten in vielen Anwendungen in Naturwissenschaft und Technik auf. In dieser Arbeit werden Optimalsteuerungsprobleme mit semilinearen elliptischen partiellen Differentialgleichungen als Nebenbedingungen untersucht. Die Kontrolle wird durch Kontrollschranken als Ungleichungsnebenbedingungen eingeschränkt. Dabei ist die Zielfunktion quadratisch in der Kontrolle. Die Lösung des Optimierungsproblems kann dann durch die Projektionsbedingung mit Hilfe des adjungierten Zustandes dargestellt werden. Ein neuer Zugang ist die variationelle Diskretisierung. Bei dieser wird nur der Zustand und der adjungierte Zustand diskretisiert, nicht aber der Raum der Kontrollen. Dieser Zugang erlaubt höhere Konvergenzraten für die Kontrolle für kontrollrestingierte Probleme als bei einer Diskretisierung des Kontrollraumes. Die Projektionsbedingung für das variationell diskretisierte Problem ist dabei auf die gleiche zulässige Menge wie beim nicht diskretisierten Problem. In der vorliegenden Arbeit wird die Methode der variationellen Diskretisierung auf semilineare elliptische Optimalkontrollprobleme angewendet und Fehlerabschätzungen für die Kontrollen bewiesen. Dabei wird hauptsächlich auf die verteilte Steuerung Wert gelegt, aber auch die Neumann-Randsteuerung mitbehandelt. Nach einem Überblick über die Literatur wird die Aufgabenstellung mit den Voraussetzungen aufgeschrieben und die Optimalitätsbedingungen angegeben. Danach wird die Existenz einer Lösung, sowie die Konvergenz der diskreten Lösungen gegen eine kontinuierliche Lösung gezeigt. Außerdem werden Finite-Elemente-Konvergenzordnungen angegeben. Dann werden optimale Fehlerabschätzungen in verschiedenen Normen für die variationelle Kontrolle bewiesen. Insbesondere werden die Fehlerabschätzung in Abhängigkeit vom Finite-Elemente-Fehler des Zustandes und des adjungierten Zustandes angegeben. Dabei wird die nichtlineare Fixpunktgleichung mittels semismooth Newtonverfahrens linearisiert. Das Newtonverfahren wird auch für die numerische Lösung des Problems eingesetzt. Die Voraussetzung für die Konvergenzordnung ist dabei nicht die SSC, die hinreichende Bedingung zweiter Ordnung, welche eine lokale Konvexität in der Zielfunktion impliziert, sondern die Invertierbarkeit des Newtonoperators. Dies ist eine stationäre Bedingung in der optimalen Kontrolle. Dabei wird nur benötigt, dass der Rand der aktiven Menge eine Nullmenge ist und die Invertierbarkeit des Newtonoperators in der Optimallösung. Der Schaudersche Fixpunktsatz wird benutzt, um für die Newtongleichung die Existenz eines Fixpunktes innerhalb der gewünschten Umgebung zu beweisen. Außerdem wird die Eindeutigkeit eines solchen Fixpunktes für eine gegebene Triangulation bei hinreichend feiner Diskretisierung gezeigt. Das Ergebnis ist, dass die Konvergenzrate nur durch die Finite-Elemente-Konvergenzraten von Zustand und adjungiertem Zustand beschränkt wird. Diese Rate wird nicht nur durch die Ansatzfunktionen, sondern auch durch die Glattheit der rechten Seite beschränkt, so dass der Knick am Rand der aktiven Menge hier ein Grenze setzt. Außerdem wird die Implementation des semismooth Newtonverfahrens für den unendlichdimensionalen Kontrollraum für die variationelle Diskretisierung erläutert. Dabei wird besonders auf den zweidimensionalen verteilten Fall eingegangen. Es werden die bewiesenen Konvergenzraten an einigen semilinearen und linearen Beispielen mittels der variationellen Diskretisierung demonstriert. Es entsprechen sich die bei den analytische Beweisen und der numerischen Lösung eingesetzten Verfahren, die Fixpunktiteration sowie das nach Kontrolle oder adjungiertem Zustand aufgelöste Newtonverfahren. Dabei sind einige Besonderheiten bei der Implementation zu beachten, beispielsweise darf die Kontrolle nicht inkrementell mit dem Newtonverfahren oder der Fixpunktiteration aufdatiert werden, sondern muss in jedem Schritt neu berechnet werden.

<p>This thesis concerns the approximation of optimally controlled partial differential equations for applications in optimal design and reconstruction. Such optimal control problems are often ill-posed and need to be regularized to obtain good approximations. We here use the theory of the corresponding Hamilton-Jacobi-Bellman equations to construct regularizations and derive error estimates for optimal design problems. The constructed Pontryagin method is a simple and general method where the first, analytical, step is to regularize the Hamiltonian. Next its stationary Hamiltonian system, a nonlinear partial differential equation, is computed efficiently with the Newton method using a sparse Jacobian. An error estimate for the difference between exact and approximate objective functions is derived, depending only on the difference of the Hamiltonian and its finite dimensional regularization along the solution path and its<em> L</em>² projection, i.e. not on the difference of the exact and approximate solutions to the Hamiltonian systems. In the thesis we present solutions to applications such as optimal design and reconstruction of conducting materials and elastic structures.</p>

This dissertation is devoted to the finite element (FE) approximation of equations describing the motion of a class of non-Newtonian fluids. The main focus is on incompressible fluids whose viscosity nonlinearly depends on the shear rate and pressure. The equations of motion are discretized with equal-order d-linear finite elements, which fail to satisfy the inf-sup stability condition. In this thesis a stabilization technique for the pressure-gradient is proposed that is based on the well-known local projection stabilization (LPS) method. If the viscosity solely depends on the shear rate, the well-posedness of the stabilized discrete systems is shown and a priori error estimates quantifying the convergence of the method are proven. In the shear thinning case, the derived error estimates provide optimal rates of convergence with respect to the regularity of the solution. As is well-known, the Galerkin FE method may suffer from instabilities resulting not only from lacking inf-sup stability but also from dominating convection. The proposed LPS approach is then extended in order to cope with both instability phenomena. Finally, shear-rate- and pressure-dependent viscosities are considered. The Galerkin discretization of the governing equations is analyzed and the convergence of discrete solutions is...

<div> <div> <div> <p>This dissertation contains two parts: one part is about the error estimate for the finite element approximation to elliptic PDEs with discontinuous Dirichlet boundary data, the other is about the error estimate of the DG method for elliptic equations with low regularity. </p> <p>Elliptic problems with low regularities arise in many applications, error estimate for sufficiently smooth solutions have been thoroughly studied but few results have been obtained for elliptic problems with low regularities. Part I provides an error estimate for finite element approximation to elliptic partial differential equations (PDEs) with discontinuous Dirichlet boundary data. Solutions of problems of this type are not in H1 and, hence, the standard variational formulation is not valid. To circumvent this difficulty, an error estimate of a finite element approximation in the W1,r(Ω) (0 < r < 2) norm is obtained through a regularization by constructing a continuous approximation of the Dirichlet boundary data. With discontinuous boundary data, the variational form is not valid since the solution for the general elliptic equations is not in H1. By using the W1,r (1 < r < 2) regularity and constructing continuous approximation to the boundary data, here we present error estimates for general elliptic equations. </p> <p>Part II presents a class of DG methods and proves the stability when the solution belong to H1+ε where ε < 1/2 could be very small. we derive a non-standard variational formulation for advection-diffusion-reaction problems. The formulation is defined in an appropriate function space that permits discontinuity across element </p> </div> </div> <div> <div> <p>viii </p> </div> </div> </div> <div> <div> <div> <p>interfaces and does not require piece wise Hs(Ω), s ≥ 3/2, smoothness. Hence, both continuous and discontinuous (including Crouzeix-Raviart) finite element spaces may be used and are conforming with respect to this variational formulation. Then it establishes the a priori error estimates of these methods when the underlying problem is not piece wise H3/2 regular. The constant in the estimate is independent of the parameters of the underlying problem. Error analysis presented here is new. The analysis makes use of the discrete coercivity of the bilinear form, an error equation, and an efficiency bound of the continuous finite element approximation obtained in the a posteriori error estimation. Finally a new DG method is introduced i to over- come the difficulty in convergence analysis in the standard DG methods and also proves the stability. </p> </div> </div> </div>

Analytic functions in a domain Ω are uniquely determined by their values on any curve Γ ⊂ Ω. We provide sharp quantitative version of this statement. Namely, let f be of order E on Γ relative to its global size in Ω (measured in some Hilbert space norm). How large can f be at a point z away from the curve? We give a sharp upper bound on |f(z)| in terms of a solution of a linear integral equation of Fredholm type and demonstrate that the bound behaves like a power law: E^γ(z). In special geometries, such as the upper halfplane, annulus or ellipse the integral equation can be solved explicitly, giving exact formulas for the optimal exponent γ(z). Our methods can be applied to non-Hilbertian settings as well. Further, we apply the developed theory to study the degree of reliability of extrapolation of the complex electromagentic permittivity function based on its analyticity properties. Given two analytic functions, representing extrapolants of the same experimental data, we quantify how much they can differ at an extrapolation point outside of the experimentally accessible frequency band.