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Adaptive finite elements for a contact problem in elastoplasticity with Lagrange techniquesWiedemann, Sebastian 18 March 2013 (has links)
Das Thema dieser Dissertation ist die Herleitung und numerische Analyse von finiten Elementen für ein Problem in der Elastoplastizität mit Kontaktbedingungen. Die hergeleiteten finite Elemente Verfahren basieren auf einer Formulierung als Sattelpunktproblem und der Nutzung von Polynomen höherer Ordnung. Die Analyse der vorgestellten Verfahren beginnt mit dem Zeigen der Wohldefiniertheit und der Konvergenz. Im nächsten Schritt werden a priori Abschätzungen der Konvergenzraten gezeigt. Weiterhin führt die Einführung von Lagrange Multiplikatoren zu einem einheitlichen Ansatz zur a posteriori Abschätzung des Diskretisierungfehlers unter der Verwendung von Elementen höherer Ordnung. Zusätzlich ermöglicht es der Zugang über Lagrange Multiplikatoren die Äquivalenz der Diskretisierungsfehler in den Spannungen und in den Energien für finite Elemente niederer Ordnung zu zeigen, was insbesondere neu für Viereckselemente ist. Diese Äquivalenz wiederum erlaubt nun den Beweis der Konvergenz von adaptiven finiten Elementen niederer Ordnung. Für Dreieckselemente wird sogar die optimale Konvergenz bewiesen. Die theoretischen Erkenntnisse werden durch numerische Experimente bestätigt. / The topic of this thesis is the derivation and analysis of some finite element schemes for a contact problem in elastoplasticity. These schemes are based on the formulation of the models as saddle point problems and use finite element spaces of arbitrary polynomial degrees. In this thesis, these new approaches with higher-order finite elements are shown to be well defined and convergent. Moreover, some a~priori estimates on the rates of convergences are proven. The use of Lagrange multipliers in the saddle point formulation yields a coherent approach to reliable a~posteriori error estimates for the proposed higher-order schemes. Additionally, the Lagrange multipliers are used to show the equivalence of the errors of the stresses and the energies, for low order finite elements using triangular or quadrilateral cells. For the first time, this allows for a proof of convergence for quadrilateral-based adaptive finite elements. Furthermore, the approach based on triangular cells is shown to be of optimal convergence. The theoretical findings are confirmed by numerical experiments.
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Computational modeling and optimization of proton exchange membrane fuel cellsSecanell Gallart, Marc 13 November 2007 (has links)
Improvements in performance, reliability and durability as well as reductions in production costs, remain critical prerequisites for the commercialization of proton exchange membrane fuel cells. In this thesis, a computational framework for fuel cell analysis and optimization is presented as an innovative alternative to the time consuming trial-and-error process currently used for fuel cell design. The framework is based on a two-dimensional through-the-channel isothermal, isobaric and single phase membrane electrode assembly (MEA) model. The model input parameters are the manufacturing parameters used to build the MEA: platinum loading, platinum to carbon ratio, electrolyte content and gas diffusion layer porosity. The governing equations of the fuel cell model are solved using Netwon's algorithm and an adaptive finite element method in order to achieve quadratic convergence and a mesh independent solution respectively. The analysis module is used to solve two optimization problems: i) maximize performance; and, ii) maximize performance while minimizing the production cost of the MEA. To solve these problems a gradient-based optimization algorithm is used in conjunction with analytical sensitivities. The presented computational framework is the first attempt in the literature to combine highly efficient analysis and optimization methods to perform optimization in order to tackle large-scale problems. The framework presented is capable of solving a complete MEA optimization problem with state-of-the-art electrode models in approximately 30 minutes. The optimization results show that it is possible to achieve Pt-specific power density for the optimized MEAs of 0.422 $g_{Pt}/kW$. This value is extremely close to the target of 0.4 $g_{Pt}/kW$ for large-scale implementation and demonstrate the potential of using numerical optimization for fuel cell design.
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Computational modeling and optimization of proton exchange membrane fuel cellsSecanell Gallart, Marc 13 November 2007 (has links)
Improvements in performance, reliability and durability as well as reductions in production costs, remain critical prerequisites for the commercialization of proton exchange membrane fuel cells. In this thesis, a computational framework for fuel cell analysis and optimization is presented as an innovative alternative to the time consuming trial-and-error process currently used for fuel cell design. The framework is based on a two-dimensional through-the-channel isothermal, isobaric and single phase membrane electrode assembly (MEA) model. The model input parameters are the manufacturing parameters used to build the MEA: platinum loading, platinum to carbon ratio, electrolyte content and gas diffusion layer porosity. The governing equations of the fuel cell model are solved using Netwon's algorithm and an adaptive finite element method in order to achieve quadratic convergence and a mesh independent solution respectively. The analysis module is used to solve two optimization problems: i) maximize performance; and, ii) maximize performance while minimizing the production cost of the MEA. To solve these problems a gradient-based optimization algorithm is used in conjunction with analytical sensitivities. The presented computational framework is the first attempt in the literature to combine highly efficient analysis and optimization methods to perform optimization in order to tackle large-scale problems. The framework presented is capable of solving a complete MEA optimization problem with state-of-the-art electrode models in approximately 30 minutes. The optimization results show that it is possible to achieve Pt-specific power density for the optimized MEAs of 0.422 $g_{Pt}/kW$. This value is extremely close to the target of 0.4 $g_{Pt}/kW$ for large-scale implementation and demonstrate the potential of using numerical optimization for fuel cell design.
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Magnetic APFC modeling and the influence of magneto-structural interactions on grain shrinkageBackofen, Rainer, Salvalaglio, Marco, Voigt, Axel 22 February 2024 (has links)
We derive the amplitude expansion for a phase-field-crystal (APFC) model that captures the basic physics of magneto-structural interactions. The symmetry breaking due to magnetization is demonstrated, and the characterization of the magnetic anisotropy for a bcc crystal is provided. This model enables a convenient coarse-grained description of crystalline structures, in particular when considering the features of the APFC model combined with numerical methods featuring inhomogeneous spatial resolution. This is shown by addressing the shrinkage of a spherical grainwithin amatrix, chosen as a prototypical system to demonstrate the influence of different magnetizations. These simulations serve as a proof of concept for the modeling of manipulation of dislocation networks and microstructures in ferromagnetic materials within the APFC model.
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Existence Theorems, Stationarity Conditions and Adaptive Numerical Methods for Generalized Nash Equilibrium Problems Constrained by Partial Differential EquationsStengl, Steven-Marian 18 November 2024 (has links)
Die vorliegende Arbeit befasst sich mit verallg. Nash-Gleichgewichtsproblemen im Zusammenhang mit Optimalsteuerungsproblemen mit (nichtlinearen) partiellen Differentialgleichungen. Ausgehend von der Existenzfrage von Nash-Gleichgewichten werden Bedingungen an Optimalsteuerungsprobleme mit nichtlinearen Lösungsoperatoren hergeleitet, welche die Konvexität des reduzierten Problems garantieren. Dazu nutzen wir die verallg. Konvexität von vektorwertigen Operatoren. Da keine expl. Darstellung des Lösungsoperators bekannt ist, werden hinreichende Bedingungen an die Operatorgleichung formuliert. Zusammen mit Anforderungen an das Zielfunktional wird so die Konvexität des reduzierten Problems garantiert. Das erlaubt auch Stationaritätssysteme im nichtglatten Fall herzuleiten. Eine zusätzliche Bedingung an die Lösung der Operatorgleichung koppelt die Strategien der Spieler. Das markiert den Übergang zu verallgemeinerten Nash-Spielen. Um diese Probleme anzugehen, wenden wir eine Penalty-Technik an. Damit wird die beschriebene Abhängigkeit vermieden und zum Zielfunktional transportiert. Damit wird eine Folge von Ersatzproblemen formuliert, deren Grenze das ursprüngliche Problem ist. Für die mathematische Beschreibung entwickeln wir eine erweiterte Γ-Konvergenz für Gleichgewichtsprobleme. Das Verhalten der Lagrange-Multiplikatoren im Stationaritätssystem wird unter Verwendung einer Pfadverfolgungstechnik analysiert und eine numerisch nutzbare Updatestrategie wird hergeleitet. Für ein praktisch anwendbares Lösungsverfahren ist eine Diskretisierung notwendig. Dazu verwenden wir eine Finite-Elemente-Methode. Die Herleitung der A-priori-Konvergenz basierend auf der zuvor verallgemeinerten Γ-Konvergenz wird für Gleichgewichtsprobleme mit gleichzeitiger Regularisierung etabliert. Im Blick auf durch Hindernisbedingungen erzeugte Kontaktmengen wenden wir uns auch adaptiven Finite-Elemente-Methoden zu.
Unsere theoretischen Ergebnisse werden durch mehrere akademische Anwendungen illustriert. / The present work deals with generalized Nash equilibrium problems related to optimal control problems on (nonlinear) partial differential equations. Starting from the question of the existence of Nash equilibria, conditions for optimal control problems with nonlinear solution operators are derived that guarantee the convexity of the reduced problem. To do so, we discuss generalized convexity of vector-valued operators. As no explicit representation of the solution operator is known, conditions on the operator equation that imply this property are formulated. In combination with requirements for the objective functional, the convexity of the reduced problem can be guaranteed. This approach also allows us to derive stationarity systems even in the nonsmooth case.
The presence of a condition on the solution of the operator equation couples the players' strategies. This marks the transition to generalized Nash games. To address these problems, we apply a penalty technique. Hence, the described dependency is avoided and transported to the objective. As the penalty functional is scaled with a parameter, a sequence of surrogate problems, whose limit is the original problem, is formulated. For its mathematical description, we introduce an extended Γ-convergence for equilibrium problems. The behavior of the Lagrangian multipliers in the stationarity system is analyzed using a path-following technique, and a numerically usable update strategy is derived. A discretization is necessary for a practically applicable solution method. For this, we use a finite element method. The derivation of the a priori convergence based on the previously generalized Γ-convergence is established for equilibrium problems with simultaneous regularization. With regard to the presence of contact sets induced by obstacle conditions, we also turn to adaptive finite element methods. Our theoretical results are illustrated by several academic applications.
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