Ziel dieser Arbeit ist die Simulation der Deformation von Bauteilen, welche aus nahezu inkompressiblem Material bestehen. Dabei soll sich das Material sowohl linear als auch nichtlinear elastisch verhalten können. Zusätzlich soll die Belastung des Bauteils beliebig gewählt werden können, das heißt, es sollen kleine als auch große Deformationen möglich sein.:1. Einleitung 2. Grundlagen 3. Aufgabenstellung für linear elastisches Material unter kleinen Deformationen 4. Gemischte Methode der finiten Elemente 5. Herleitung der Fehlerschätzung 6. Aufgabenstellung für nichtlinear elastisches Material unter großen Deformationen 7. Lösungsstrategie A. Anhang

Im Rahmen des Modellierungsseminars wurde die Kopplung einer Strömung mit der Ausbreitung einer reaktiven Substanz im Strömungsgebiet untersucht. Die Strömung wurde dabei durch die inkompressiblen Navier-Stokes-Gleichungen beschrieben. Zusätzlich wurde ein mathematisches Modell für die Ausbreitung der Substanz durch eine Diffusions-Konvektions-Gleichung bestimmt. Beide wurden durch die FEM- Sofware NAVIER berechnet und simuliert.:0 Notation 3 1 Aufgabenstellung 4 1.1 Projekt 4 1.2 Navier-Stokes-Strömung gekoppelt mit (passivem) Transport einiger (reaktiver) Substanzen 4 2 Einleitung 6 2.1 Strömungslehre 6 2.2 Regelungstheorie 7 3 Mathematische Modellierung 8 3.1 Strömungsmodellierung 8 3.2 Modell zur Ausbreitung des gelösten Stoffes 8 3.3 Gekoppeltes Modell und Randbedingungen 12 3.4 Grenzschichten 13 3.5 Feedback-Steuerung 15 4 Numerische Simulation 19 4.1 Umsetzung des Modells in NAVIER 19 4.1.1 Mathematische Grundlagen für NAVIER 20 4.1.2 Problemimplementation 21 4.2 Beispielsimulation 24 4.2.1 Gebietstriangulation 24 4.2.2 Konfigurationsdaten sowie Anfangs- und Randbedingungen 25 4.2.3 Ergebnisauswertung 28 4.3 Zusatzfunktionen für die Regelung 34 4.3.1 outflow-Funktion 34 4.3.2 Systemmatrizen 34 4.3.3 Feedback-Funktion 34 5 Zusammenfassung/Ausblick 35 5.1 Zusammenfassung 35 5.2 Ausblick 36 6 Schlusswort 37 7 Quellenverzeichnis 38 8 Verzeichnisse 39

This paper presents three new coupling methods for interior penalty discontinuous Galerkin finite element methods and boundary element methods. The new methods allow one to use discontinuous basis functions on the interface between the subdomains represented by the finite element and boundary element methods. This feature is particularly important when discontinuous Galerkin finite element methods are used. Error and stability analysis is presented for some of the methods. Numerical examples suggest that all three methods exhibit very similar convergence properties, consistent with available theoretical results.:1. Introduction 2. Model Problem and Background 3. New Coupling Methods 4. Stability and Error Analysis 5. Numerical Examples 6. Summary A. Appendix

In the simulation of deformations of plates it is well known that we have to use a special treatment of the thickness dependence. Therewith we achieve a reduction of dimension from 3D to 2D. For linear elasticity and small deformations several techniques are well established to handle the reduction of dimension and achieve acceptable numerical results. In the case of large deformations of plates with non-linear material behaviour there exist different problems. For example the analytical integration over the thickness of the plate is not possible due to the non-linearities arising from the material law and the large deformations themselves. There are several possibilities to introduce a hypothesis for the treatment of the plate thickness from the strong Kirchhoff assumption on one hand up to some hierarchical approaches on the other hand.:1. Introduction 2. The 3D-deformation energy 3. Basic differential geometry of shells 4. Kirchhoff assumption and the deformed plate 5. Plate energy and boundary conditions 6. Numerical example

Ill-posed inverse problems with quadratic structure are introduced, studied and solved. As an example an inverse problem appearing in laser optics is solved numerically based on a new regularized inversion algorithm. In addition, the theory of sparsity promoting regularization is extended to situations in which sparsity cannot be expected and also to equations with non-injective operators.

In der vorliegenden Arbeit wird ein neues Tensorformat vorgestellt und eingehend analysiert. Das hierarchische Format verwendet einen binären Baum, um den Tensorraum der Ordnung d mit einer geschachtelten Unterraumstruktur zu versehen. Der Speicheraufwand für diese Darstellung ist von der Größenordnung O(dnr + dr^3), wobei n den Speicheraufwand in den Ansatzräumen kennzeichnet und r ein Rangparameter ist, der durch die Dimensionen der geschachtelten Unterräume bestimmt wird. Das hierarchische Format umfasst verschiedene Standardformate zur Tensordarstellung wie das kanonische oder r-Term-Format und die Unterraum-/Tucker-Darstellung. Die in dieser Arbeit entwickelte zugehörige Arithmetik inklusive mehrerer Approximationsmethoden basiert auf stabilen Methoden der Linearen Algebra, insbesondere die Singulärwertzerlegung und die QR-Zerlegung sind von zentraler Bedeutung. Die rechnerische Komplexität ist hierbei O(dnr^2+dr^4). Die lineare Abhängigkeit von der Ordnung d des Tensorraumes ist hervorzuheben. Für die verschiedenen Approximationsmethoden, deren Effizienz und Effektivität für die Anwendbarkeit des neuen Formates entscheidend sind, werden qualitative und quantitative Fehlerabschätzungen gezeigt. Umfassende numerische Experimente mit einem Fokus auf den Approximationsmethoden bestätigen zum einen die theoretischen Resultate und belegen die Stärken der neuen Tensordarstellung, zeigen aber zum anderen auch weitere, eher überraschende positive Eigenschaften der mit FastHOSVD bezeichneten schnellsten Kürzungsmethode. / In this dissertation we present and a new format for the representation of tensors and analyse its properties. The hierarchical format uses a binary tree in order to define a hierarchical structure of nested subspaces in the tensor space of order d. The strorage requirements are O(dnr+dr^3) where n is determined by the storage requirements in the ansatz spaces and r is a rank parameter determined by the dimensions of the nested subspaces. The hierarchichal representation contains the standard representation like canonical or r-term representation and subspace or Tucker representation. The arithmetical operations that have been developed in this work, including several approximation methods, are based on stable Linear Alebra methods, especially the singular value decomposition (SVD) and the QR decomposition are of importance. The computational complexity is O(dnr^2+dr^4). The linear dependence from the order d of the tensor space is important. The approximation methods are one of the key ingredients for the applicability of the new format and we present qualitative and quantitative error estimates. Numerical experiments approve the theoretical results and show some additional, but unexpected positive aspects of the fastest method called FastHOSVD.

We give an alternate description of the usual shell equation that does not depend on the special mid surface coordinates, but uses differential operators defined on the mid surface.:1 Introduction 2 Basic differential geometry 3 The strain tensor and its simplifications 4 The resulting shell energy 5 Introducing the Kirchhoff-Hypothesis towards Koiter-shell

This thesis investigates the numerical simulation of three-dimensional, mechanical deformation problems in the context of large deformations. The main focus lies on the prediction of non-linearly elastic, incompressible material. Based on the equilibrium of forces, we present the weak formulation of the large deformation problem. The discrete version can be derived by using linearisation techniques and an adaptive mixed finite element method. This problem turns out to be a saddle point problem that can, among other methods, be solved via the Bramble-Pasciak conjugate gradient method or the minimal residual algorithm. With some modifications the resulting simulation can be improved but we also address remaining limitations. Some numerical examples show the capability of the final FEM software. In addition, we briefly discuss the special case of linear elasticity with small deformations. Here we directly derive a linear weak formulation with a saddle point structure and apply the adaptive mixed finite element method. It is shown that the presented findings can also be used to treat the nearly incompressible case.

We consider a family of generalized Procrustes problems. In this class of problems, one aims at aligning a set of vectors to a given second set of vectors. The distance between both sets is measured in the q norm, and for the alignment, isometries with respect to the p norm are allowed. In contrast to the classical Procrustes problem with p = q = 2, we allow p and q to differ. We will see that it makes a difference whether the problem is real or cast over the complex field. Therefore, we discuss the solutions for p = 2 separately for these cases. We show that all the real cases can be solved efficiently. Most of the complex cases can up to now only be solved approximately in polynomial time, but we show the existence of polynomial time algorithms for q ∈ {2, 4, ∞}. Computational experiments illustrate the suggested algorithms.

We consider a family of generalized Procrustes problems. In this class of problems, one aims at aligning a set of vectors to a given second set of vectors. The distance between both sets is measured in the q norm, and for the alignment, isometries with respect to the p norm are allowed. In contrast to the classical Procrustes problem with p = q = 2, we allow p and q to differ. We will see that it makes a difference whether the problem is real or cast over the complex field. Therefore, we discuss the solutions for p = 2 separately for these cases. We show that all the real cases can be solved efficiently. Most of the complex cases can up to now only be solved approximately in polynomial time, but we show the existence of polynomial time algorithms for q ∈ {2, 4, ∞}. Computational experiments illustrate the suggested algorithms.:1. Introduction 2. The (lp, lq)-Procrustes problem 3. Optimization methods for the remaining cases with p not equal to 2 4. The one-dimensional complex optimization problems with p, q unequal to 2 5. Conclusions