Diese Dissertation verallgemeinert die nichtkonformen Finite-Elemente-Methoden (FEMn) nach Morley und Crouzeix und Raviart durch neue gemischte Formulierungen für das Poisson-Problem, die Stokes-Gleichungen, die Navier-Lamé-Gleichungen der linearen Elastizität und m-Laplace-Gleichungen der Form $(-1)^m\Delta^m u=f$ für beliebiges m=1,2,3,... Diese Formulierungen beruhen auf Helmholtz-Zerlegungen. Die neuen Formulierungen gestatten die Verwendung von Ansatzräumen beliebigen Polynomgrades und ihre Diskretisierungen stimmen für den niedrigsten Polynomgrad mit den genannten nicht-konformen FEMn überein. Auch für höhere Polynomgrade ergeben sich robuste Diskretisierungen für fast-inkompressible Materialien und Approximationen für die Lösungen der Stokes-Gleichungen, die punktweise die Masse erhalten. Dieser Ansatz erlaubt außerdem eine Verallgemeinerung der nichtkonformen FEMn von der Poisson- und der biharmonischen Gleichung auf m-Laplace-Gleichungen für beliebiges m>2. Ermöglicht wird dies durch eine neue Helmholtz-Zerlegung für tensorwertige Funktionen. Die neuen Diskretisierungen lassen sich nicht nur für beliebiges m einheitlich implementieren, sondern sie erlauben auch Ansatzräume niedrigster Ordnung, z.B. stückweise affine Polynome für beliebiges m. Hat eine Lösung der betrachteten Probleme Singularitäten, so beeinträchtigt dies in der Regel die Konvergenz so stark, dass höhere Polynomgrade in den Ansatzräumen auf uniformen Gittern dieselbe Konvergenzrate zeigen wie niedrigere Polynomgrade. Deshalb sind gerade für höhere Polynomgrade in den Ansatzräumen adaptiv generierte Gitter unabdingbar. Neben der A-priori- und der A-posteriori-Analysis werden in dieser Dissertation optimale Konvergenzraten für adaptive Algorithmen für die neuen Diskretisierungen des Poisson-Problems, der Stokes-Gleichungen und der m-Laplace-Gleichung bewiesen. Diese werden auch in den numerischen Beispielen dieser Dissertation empirisch nachgewiesen. / This thesis generalizes the non-conforming finite element methods (FEMs) of Morley and Crouzeix and Raviart by novel mixed formulations for the Poisson problem, the Stokes equations, the Navier-Lamé equations of linear elasticity, and mth-Laplace equations of the form $(-1)^m\Delta^m u=f$ for arbitrary m=1,2,3,... These formulations are based on Helmholtz decompositions. The new formulations allow for ansatz spaces of arbitrary polynomial degree and its discretizations coincide with the mentioned non-conforming FEMs for the lowest polynomial degree. Also for higher polynomial degrees, this results in robust discretizations for almost incompressible materials and approximations of the solution of the Stokes equations with pointwise mass conservation. Furthermore this approach also allows for a generalization of the non-conforming FEMs for the Poisson problem and the biharmonic equation to mth-Laplace equations for arbitrary m>2. A new Helmholtz decomposition for tensor-valued functions enables this. The new discretizations allow not only for a uniform implementation for arbitrary m, but they also allow for lowest-order ansatz spaces, e.g., piecewise affine polynomials for arbitrary m. The presence of singularities usually affects the convergence such that higher polynomial degrees in the ansatz spaces show the same convergence rate on uniform meshes as lower polynomial degrees. Therefore adaptive mesh-generation is indispensable especially for ansatz spaces of higher polynomial degree. Besides the a priori and a posteriori analysis, this thesis proves optimal convergence rates for adaptive algorithms for the new discretizations of the Poisson problem, the Stokes equations, and mth-Laplace equations. This is also demonstrated in the numerical experiments of this thesis.

This is a book on numerical methods for singular perturbation problems - in particular stationary convection-dominated convection-diffusion problems. More precisely it is devoted to the construction and analysis of layer-adapted meshes underlying these numerical methods. An early important contribution towards the optimization of numerical methods by means of special meshes was made by N.S. Bakhvalov in 1969. His paper spawned a lively discussion in the literature with a number of further meshes being proposed and applied to various singular perturbation problems. However, in the mid 1980s this development stalled, but was enlivend again by G.I. Shishkin's proposal of piecewise- equidistant meshes in the early 1990s. Because of their very simple structure they are often much easier to analyse than other meshes, although they give numerical approximations that are inferior to solutions on competing meshes. Shishkin meshes for numerous problems and numerical methods have been studied since and they are still very much in vogue. With this contribution we try to counter this development and lay the emphasis on more general meshes that - apart from performing better than piecewise-uniform meshes - provide a much deeper insight in the course of their analysis. In this monograph a classification and a survey are given of layer-adapted meshes for convection-diffusion problems. It tries to give a comprehensive review of state-of-the art techniques used in the convergence analysis for various numerical methods: finite differences, finite elements and finite volumes. While for finite difference schemes applied to one-dimensional problems a rather complete convergence theory for arbitrary meshes is developed, the theory is more fragmentary for other methods and problems and still requires the restriction to certain classes of meshes.

Numerous vibrating electromechanical systems lack a rigid connection to the inertial frame. An artificial inertial frame can be generated by a shaker, which compensates for vibrations. In this article, we present an encapsulated and perforated unimorph bending plate for this purpose. Vibrations can be compensated up to the first eigenfrequency of the system. As basis for an efficient system simulation and optimization, a new three-port multi-domain network model was developed. An extension qualifies the network for the simulation of the acoustical behavior inside the capsule. Network parameters are determined using finite element simulations. The dynamic behavior of the network model agrees with the finite element simulation results up to the first resonance of the system. The network model was verified by measurements on a laboratory setup, too. Furthermore, the network model could be simplified and was applied to determine the influence of various parameters on the stabilization performance of the plate transducer. The performance of the piezoelectric bending plate for position stabilization had been in addition investigated experimentally by measurements on a macroscopic capsule.

This is a book on numerical methods for singular perturbation problems - in particular stationary convection-dominated convection-diffusion problems. More precisely it is devoted to the construction and analysis of layer-adapted meshes underlying these numerical methods. An early important contribution towards the optimization of numerical methods by means of special meshes was made by N.S. Bakhvalov in 1969. His paper spawned a lively discussion in the literature with a number of further meshes being proposed and applied to various singular perturbation problems. However, in the mid 1980s this development stalled, but was enlivend again by G.I. Shishkin's proposal of piecewise- equidistant meshes in the early 1990s. Because of their very simple structure they are often much easier to analyse than other meshes, although they give numerical approximations that are inferior to solutions on competing meshes. Shishkin meshes for numerous problems and numerical methods have been studied since and they are still very much in vogue. With this contribution we try to counter this development and lay the emphasis on more general meshes that - apart from performing better than piecewise-uniform meshes - provide a much deeper insight in the course of their analysis. In this monograph a classification and a survey are given of layer-adapted meshes for convection-diffusion problems. It tries to give a comprehensive review of state-of-the art techniques used in the convergence analysis for various numerical methods: finite differences, finite elements and finite volumes. While for finite difference schemes applied to one-dimensional problems a rather complete convergence theory for arbitrary meshes is developed, the theory is more fragmentary for other methods and problems and still requires the restriction to certain classes of meshes.

Garantierte untere Eigenwertschranken (GLB) für elliptische Eigenwertprobleme partieller Differentialgleichungen sind in der Theorie sowie in praktischen Anwendungen relevant. Auf Grund des Rayleigh-Ritz- (oder) min-max-Prinzips berechnen alle konformen Finite-Elemente-Methoden (FEM) garantierte obere Schranken. Ein Postprocessing nichtkonformer Methoden von Carstensen und Gedicke (Math. Comp., 83.290, 2014) sowie Carstensen und Gallistl (Numer. Math., 126.1, 2014) berechnet GLB. In diesen Schranken ist die maximale Netzweite ein globaler Parameter, das kann bei adaptiver Netzverfeinerung zu deutlichen Unterschätzungen führen. In einigen numerischen Beispielen versagt dieses Postprocessing für lokal verfeinerte Netze komplett. Diese Dissertation präsentiert, inspiriert von einer neuen skeletal-Methode von Carstensen, Zhai und Zhang (SIAM J. Numer. Anal., 58.1, 2020), einerseits eine modifizierte hybrid-high-order Methode (m=1) und andererseits ein allgemeines Framework für extra-stabilisierte nichtkonforme Crouzeix-Raviart (m=1) bzw. Morley (m=2) FEM. Diese neuen Methoden berechnen direkte GLB für den m-Laplace-Operator, bei denen eine leicht überprüfbare Bedingung an die maximale Netzweite garantiert, dass der k-te diskrete Eigenwert eine untere Schranke für den k-ten Dirichlet-Eigenwert ist. Diese GLB-Eigenschaft und a priori Konvergenzraten werden für jede Raumdimension etabliert. Der neu entwickelte Ansatz erlaubt adaptive Netzverfeinerung, die für optimale Konvergenzraten auch bei nichtglatten Eigenfunktionen erforderlich ist. Die Überlegenheit der neuen adaptiven FEM wird durch eine Vielzahl repräsentativer numerischer Beispiele illustriert. Für die extra-stabilisierte GLB wird bewiesen, dass sie mit optimalen Raten gegen einen einfachen Eigenwert konvergiert, indem die Axiome der Adaptivität von Carstensen, Feischl, Page und Praetorius (Comput. Math. Appl., 67.6, 2014) sowie Carstensen und Rabus (SIAM J. Numer. Anal., 55.6, 2017) verallgemeinert werden. / Guaranteed lower eigenvalue bounds (GLB) for elliptic eigenvalue problems of partial differential equation are of high relevance in theory and praxis. Due to the Rayleigh-Ritz (or) min-max principle all conforming finite element methods (FEM) provide guaranteed upper eigenvalue bounds. A post-processing for nonconforming FEM of Carstensen and Gedicke (Math. Comp., 83.290, 2014) as well as Carstensen and Gallistl (Numer. Math., 126.1,2014) computes GLB. However, the maximal mesh-size enters as a global parameter in the eigenvalue bound and may cause significant underestimation for adaptive mesh-refinement. There are numerical examples, where this post-processing on locally refined meshes fails completely. Inspired by a recent skeletal method from Carstensen, Zhai, and Zhang (SIAM J. Numer. Anal., 58.1, 2020) this thesis presents on the one hand a modified hybrid high-order method (m=1) and on the other hand a general framework for an extra-stabilized nonconforming Crouzeix-Raviart (m=1) or Morley (m=2) FEM. These novel methods compute direct GLB for the m-Laplace operator in that a specific smallness assumption on the maximal mesh-size guarantees that the computed k-th discrete eigenvalue is a lower bound for the k-th Dirichlet eigenvalue. This GLB property as well as a priori convergence rates are established in any space dimension. The novel ansatz allows for adaptive mesh-refinement necessary to recover optimal convergence rates for non-smooth eigenfunctions. Striking numerical evidence indicates the superiority of the new adaptive eigensolvers. For the extra-stabilized nonconforming methods (a generalization of) known abstract arguments entitled as the axioms of adaptivity from Carstensen, Feischl, Page, and Praetorius (Comput. Math. Appl., 67.6, 2014) as well as Carstensen and Rabus (SIAM J. Numer. Anal., 55.6, 2017) allow to prove the convergence of the GLB towards a simple eigenvalue with optimal rates.

Die Least-Squares Finite-Elemente-Methoden (LSFEMn) basieren auf der Minimierung des Least-Squares-Funktionals, das aus quadrierten Normen der Residuen eines Systems von partiellen Differentialgleichungen erster Ordnung besteht. Dieses Funktional liefert einen a posteriori Fehlerschätzer und ermöglicht die adaptive Verfeinerung des zugrundeliegenden Netzes. Aus zwei Gründen versagen die gängigen Methoden zum Beweis optimaler Konvergenzraten, wie sie in Carstensen, Feischl, Page und Praetorius (Comp. Math. Appl., 67(6), 2014) zusammengefasst werden. Erstens scheinen fehlende Vorfaktoren proportional zur Netzweite den Beweis einer schrittweisen Reduktion der Least-Squares-Schätzerterme zu verhindern. Zweitens kontrolliert das Least-Squares-Funktional den Fehler der Fluss- beziehungsweise Spannungsvariablen in der H(div)-Norm, wodurch ein Datenapproximationsfehler der rechten Seite f auftritt. Diese Schwierigkeiten führten zu einem zweifachen Paradigmenwechsel in der Konvergenzanalyse adaptiver LSFEMn in Carstensen und Park (SIAM J. Numer. Anal., 53(1), 2015) für das 2D-Poisson-Modellproblem mit Diskretisierung niedrigster Ordnung und homogenen Dirichlet-Randdaten. Ein neuartiger expliziter residuenbasierter Fehlerschätzer ermöglicht den Beweis der Reduktionseigenschaft. Durch separiertes Markieren im adaptiven Algorithmus wird zudem der Datenapproximationsfehler reduziert. Die vorliegende Arbeit verallgemeinert diese Techniken auf die drei linearen Modellprobleme das Poisson-Problem, die Stokes-Gleichungen und das lineare Elastizitätsproblem. Die Axiome der Adaptivität mit separiertem Markieren nach Carstensen und Rabus (SIAM J. Numer. Anal., 55(6), 2017) werden in drei Raumdimensionen nachgewiesen. Die Analysis umfasst Diskretisierungen mit beliebigem Polynomgrad sowie inhomogene Dirichlet- und Neumann-Randbedingungen. Abschließend bestätigen numerische Experimente mit dem h-adaptiven Algorithmus die theoretisch bewiesenen optimalen Konvergenzraten. / The least-squares finite element methods (LSFEMs) base on the minimisation of the least-squares functional consisting of the squared norms of the residuals of first-order systems of partial differential equations. This functional provides a reliable and efficient built-in a posteriori error estimator and allows for adaptive mesh-refinement. The established convergence analysis with rates for adaptive algorithms, as summarised in the axiomatic framework by Carstensen, Feischl, Page, and Praetorius (Comp. Math. Appl., 67(6), 2014), fails for two reasons. First, the least-squares estimator lacks prefactors in terms of the mesh-size, what seemingly prevents a reduction under mesh-refinement. Second, the first-order divergence LSFEMs measure the flux or stress errors in the H(div) norm and, thus, involve a data resolution error of the right-hand side f. These difficulties led to a twofold paradigm shift in the convergence analysis with rates for adaptive LSFEMs in Carstensen and Park (SIAM J. Numer. Anal., 53(1), 2015) for the lowest-order discretisation of the 2D Poisson model problem with homogeneous Dirichlet boundary conditions. Accordingly, some novel explicit residual-based a posteriori error estimator accomplishes the reduction property. Furthermore, a separate marking strategy in the adaptive algorithm ensures the sufficient data resolution. This thesis presents the generalisation of these techniques to three linear model problems, namely, the Poisson problem, the Stokes equations, and the linear elasticity problem. It verifies the axioms of adaptivity with separate marking by Carstensen and Rabus (SIAM J. Numer. Anal., 55(6), 2017) in three spatial dimensions. The analysis covers discretisations with arbitrary polynomial degree and inhomogeneous Dirichlet and Neumann boundary conditions. Numerical experiments confirm the theoretically proven optimal convergence rates of the h-adaptive algorithm.