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

The compressible Euler equations describe the motion of compressible inviscid fluids. They are used in many areas ranging from aerospace, automotive, and nuclear engineering to chemistry, ecology, climatology, and others. Mathematically, the compressible Euler equations represent a hyperbolic system consisting of several nonlinear partial differential equations (conservation laws). These equations are solved most frequently by means of Finite Volume Methods (FVM) and low-order Finite Element Methods (FEM). However, both these approaches are lacking higher order accuracy and moreover, it is well known that conforming FEM is not the optimal tool for the discretization of first-order equations. The most promissing approach to the approximate solution of the compressible Euler equations is the discontinuous Galerkin method that combines the stability of FVM, with excellent approximation properties of higher-order FEM. The objective of this Master Thesis was to develop, implement and test new adaptive algorithms for the nonstationary compressible Euler equations based on higher-order discontinuous Galerkin (hp-DG) methods. The basis for the new methods were the discontinuous Galerkin methods and space-time adaptive hp-FEM algorithms on dynamical meshes for nonstationary second-order problems. The new algorithms...

Die Nanooptik beschäftigt sich mit der Wechselwirkung von Licht mit Materie, deren charakteristische Dimension im Nanometer Bereich liegt. Insbesondere wenn die Materie aus Metall besteht, zeigen sich interessante, wellenlängenabhängige Unterschiede in der Stärke der Wechselwirkung. Die Ursache dafür sind die kollektiven Moden der quasifreien Ladungsträger, die Plasmonen. Obgleich sich experimentelle Methoden in den letzten Jahren stetig verbessert haben, ist es nach wie vor nur mit erheblichem Aufwand möglich, sich Einblicke in die mikroskopischen Zusammenhänge zu verschaffen. Eine Ergänzung zu den Experimenten bieten theoretische Modelle. Auf Grund der sich mit der Zeit stetig verbesserten Leistung der Rechentechnik, kommen dabei zunehmend numerische Verfahren zum Einsatz. Eines dieser Verfahren ist das Unstetige Galerkin Verfahren, welches in dieser Arbeit auf folgende Fragestellungen der plasmonischen Nanooptik angewandt wurde: • Bei dem unstetigen Galerkin Verfahren werden die zu simulierenden Körper üblicherweise mittels Dreiecke und Tetraeder approximiert. Da die Geometrie der metallischen Systeme einen entscheidenden Einfluss auf die Wechselwirkung hat, wurde untersucht, inwieweit sich durch Einsatz von Elementen mit gekrümmten Flächen die Genauigkeit oder die Geschwindigkeit der Simulation steigern lässt. Es konnte gezeigt werden, dass runde Elemente die Genauigkeit bei gleicher Diskretisierung um bis zu zwei Größenordnungen steigern oder die Rechenzeit bei gleicher Genauigkeit auf ein Sechstel verkürzen können. • Bestrahlt man Metallnanopartikel mit intensiven Laserpulsen, so strahlen diese nicht nur bei der Frequenz des eingestrahlten Lichtes, sondern auch bei der doppelten Frequenz ab. Dieses Phänomen der Frequenzverdopplung (SHG, engl.: „Second-Harmonic-Generation“) ist unter anderem von der Form der Partikel und der Wellenlänge des Pulses abhängig. Da durchstimmbare gepulste Laser sehr teuer sind, wurde untersucht, ob sich mit Hilfe der linearen Partikelspektren Vorhersagen über die Stärke der Frequenzverdopplung machen lassen. Dabei wurde festgestellt, dass die Effizienz der Frequenzverdopplung zunimmt, wenn man die linearen Resonanzen der Partikel auf die SHG- oder Anregungswellenlänge abstimmt. Schafft man es, das plasmonische System so einzustellen, dass sowohl die Anregungswellenlänge, wie auch die SHG- Wellenlänge auf einer linearen Resonanz liegen, so kann die Effizienz der SHG weiter gesteigert werden. / Nanooptics is a discipline dealing with the interaction of light with matter where its characteristic dimensions are defined to be in the range of nanometers. In particular, if the matter consists of metal, i.e. conductive material, interesting wavelength dependent phenomena can be observed, which scale with the strength of the interaction. These phenomena are caused by the formation of collective modes between quasi-free charge carriers resulting in so called plasmons. Although improved experimental methods have evolved over the last few years, insight into the microscopic relationship between light and matter is only achievable with high effort. Supplemental information to experimental findings can be drawn from theoretical models. Due to the constantly improving computational power, numerical methods are progressively more employed. One of these methods is the discontinuous Galerkin method, which was applied to the following problems in plasmonic nanooptics: • Within the discontinuous Galerkin method the simulated objects are usually approximated by triangles or tetrahedrons. Since the geometry of conductive systems has a major impact on the interaction between light and matter, the usability of elements with curved surfaces for the discretisation of the space has been investigated with respect to accuracy and speed of the simulation. In this work, it could be shown that curved elements improve the simulations precision up to two orders of magnitude with the same amount of discretisation compared to linear elements. Related to speed, it has been found that the computational time is reduced by a factor of 6 with a comparable simulation accuracy. • By irradiating metallic nanoparticles with high power laser pulses these particles do not only emit light of the same frequency as the incident electromagnetic wave, but also with the doubled frequency (SHG, second harmonic generation). Among other things, this phenomenon of frequency doubling mainly depends on the geometry of the particle and the wavelength of the pulse. Since tunable pulsed laser sources are very expensive, it has been theoretically investigated if the strength of the frequency doubling can be deduced from the particles linear spectra. By this, it has been discovered that the efficiency of frequency doubling can be improved by adjusting the linear resonances of the particle to the SHG or excitation wavelength. The SHG efficiency can be increased even further, if the plasmonic system is tuned to a point where both the excitation and the SHG wavelength correspond to a linear resonance of the nanoparticle.

Cette thèse traite de la résolution du système de la Magnéto-Hydro-Dynamique (MHD) sur architectures massivement parallèles. Ce système est un système hyperbolique de lois de conservation. Pour des raisons de coût en termes de temps et d'espace, nous utilisons la méthode des volumes finis. Ces critères sont particulièrement importants dans le cas de la MHD, car les solutions obtenues peuvent présenter de nombreuses ondes de choc et être très turbulentes. L'approche d'un phénomène physique nécessite par conséquent de travailler sur un maillage fin entrainant une grande quantité de calcul. Afin de réduire les temps d'exécution des algorithmes proposés, nous proposons des méthodes d'optimisations pour l'exécution sur CPU telles que l'utilisation d'OpenMP pour une parallélisation automatique ou le parcours optimisé afin de bénéficier des effets de cache. Une implémentation sur architecture GPU à l'aide de la librairie OpenCL est également proposée. Dans le but de conserver une coalescence maximale des données en mémoire, nous proposons une méthode utilisant un splitting directionnel associé à une méthode de transposition optimisée pour les implémentations parallèle. Dans la dernière partie, nous présentons la librairie SCHNAPS. Ce solveur utilisant la méthode Galerkin Discontinu (GD) utilise des implémentations OpenCL et StarPU afin de profiter au maximum des avantages de la programmation hybride. / This thesis deals with the resolution of the Magneto-Hydro-Dynamic (MHD) system on massively parallel architectures. This problem is an hyperbolic system of conservation laws. For cost reasons in terms of time and space, we use the finite volume method. These criteria are particularly important in the case of MHD because the solutions obtained may have many shock waves and be very turbulent. The approach of a physical phenomenon requires working on a fine mesh which involves a large quantity of computations. In order to reduce the execution time of the proposed algorithms, we present several optimization methods for CPU execution such as the use of OpenMP for an automatic parallelization or an optimized way to browse a grid in order to benefit from cache effects. An implementation on GPU architecture using the OpenCL library is also available. To maintain a maximal coalescence of the data in memory, we propose a method using a directional splitting associated with an optimized transposition method for parallel implementations. In the last part, we present the SCHNAPS library. This solver using the Galerkin Disontinu (GD) method uses OpenCL and StarPU implementations in order to maximize the benefits of hybrid programming.

京都大学 / 0048 / 新制・課程博士 / 博士(農学) / 甲第21374号 / 農博第2298号 / 新制||農||1066(附属図書館) / 学位論文||H30||N5147(農学部図書室) / 京都大学大学院農学研究科地域環境科学専攻 / (主査)教授 村上 章, 教授 藤原 正幸, 教授 渦岡 良介 / 学位規則第4条第1項該当 / Doctor of Agricultural Science / Kyoto University / DFAM

In computational fluid dynamics, we often need to solve complex problems with high precision and efficiency. We propose a three-pronged approach to attain this goal. First, we use the discontinuous Galerkin spectral element method (DG-SEM) for its high accuracy. Second, we use graphics processing units (GPUs) to perform our computations to exploit available parallel computing power. Third, we implement a parallel adaptive mesh refinement (AMR) algorithm to efficiently use our computing power where it is most needed. We present a GPU DG-SEM solver with AMR and dynamic load balancing for the 2D wave equation. The DG-SEM is a higher-order method that splits a domain into elements and represents the solution within these elements as a truncated series of orthogonal polynomials. This approach combines the geometric flexibility of finite-element methods with the exponential convergence of spectral methods. GPUs provide a massively parallel architecture, achieving a higher throughput than traditional CPUs. They are relatively new as a platform in the scientific community, therefore most algorithms need to be adapted to that new architecture. We perform most of our computations in parallel on multiple GPUs. AMR selectively refines elements in the domain where the error is estimated to be higher than a prescribed tolerance, via two mechanisms: p-refinement increases the polynomial order within elements, and h-refinement splits elements into several smaller ones. This provides a higher accuracy in important flow regions and increases capabilities of modeling complex flows, while saving computing power in other parts of the domain. We use the mortar element method to retain the exponential convergence of high-order methods at the non-conforming interfaces created by AMR. We implement a parallel dynamic load balancing algorithm to even out the load imbalance caused by solving problems in parallel over multiple GPUs with AMR. We implement a space-filling curve-based repartitioning algorithm which ensures good locality and small interfaces. While the intense calculations of the high order approach suit the GPU architecture, programming of the highly dynamic adaptive algorithm on GPUs is the most challenging aspect of this work. The resulting solver is tested on up to 64 GPUs on HPC platforms, where it shows good strong and weak scaling characteristics. Several example problems of increasing complexity are performed, showing a reduction in computation time of up to 3× on GPUs vs CPUs, depending on the loading of the GPUs and other user-defined choices of parameters. AMR is shown to improve computation times by an order of magnitude or more.

Underwater explosions (UNDEX) and a ship's vulnerability to them are problems of interest in early-stage ship design. A series of events occur sequentially in an UNDEX scenario in both the fluid and structural domains and these events happen over a wide range of time and spatial scales. Because of the complexity of the physics involved, it is a common practice to separate the description of UNDEX into early-time and late-time, and far-field and near-field. The research described in this dissertation is focused on the simulation of near-field and early-time UNDEX. It assembles a hybrid framework of algorithms to provide results while maintaining computational efficiency. These algorithms include Runge-Kutta, Discontinuous Galerkin, Level Set, Direct Ghost Fluid and Embedded Boundary methods. Computational fluid dynamics (CFD) solvers are developed using this framework of algorithms to demonstrate the computational methods and their ability to effectively and efficiently solve UNDEX problems. Contributions, made in the process of satisfying the objective of this research include: the derivation of eigenvectors of flux Jacobians and their application to the implementation of the slope limiter in the fluid discretization; the three-dimensional extension of Direct Ghost Fluid Method and its application to the multi-fluid treatment in UNDEX flows; the enforcement of an improved non-reflecting boundary condition and its application to UNDEX simulations; and an improvement to the projection-based embedded boundary method and its application to fluid-structure interaction simulations of UNDEX problems. / Doctor of Philosophy / Underwater explosions (UNDEX) and a ship's vulnerability to them are problems of interest in early-stage ship design. A series of events occur sequentially in an UNDEX scenario in both the fluid and structural domains and these events happen over a wide range of time and spatial scales. Because of the complexity of the physics involved, it is a common practice to separate the description of UNDEX into early-time and late-time, and far-field and near-field. The research described in this dissertation is focused on the simulation of near-field and early-time UNDEX. It assembles a hybrid framework of algorithms to provide results while maintaining computational efficiency. These algorithms include Runge-Kutta, Discontinuous Galerkin, Level Set, Direct Ghost Fluid and Embedded Boundary methods. Computational fluid dynamics (CFD) solvers are developed using this framework of algorithms to demonstrate these computational methods and their ability to effectively and efficiently solve UNDEX problems.

This dissertation consists of three studies of immersed finite element (IFE) methods for inter- face problems related to partial differential equations (PDEs) with discontinuous coefficients. These three topics together form a continuation of the research in IFE method including the extension to elasticity systems, new breakthroughs to higher degree IFE methods, and its application to inverse problems. First, we extend the current construction and analysis approach of IFE methods in the literature for scalar elliptic equations to elasticity systems in the vector format. In particular, we construct a group of low-degree IFE functions formed by linear, bilinear, and rotated Q1 polynomials to weakly satisfy the jump conditions of elasticity interface problems. Then we analyze the trace inequalities of these IFE functions and the approximation capabilities of the resulted IFE spaces. Based on these preparations, we develop a partially penalized IFE (PPIFE) scheme and prove its optimal convergence rates. Secondly, we discuss the limitations of the current approaches of IFE methods when we try to extend them to higher degree IFE methods. Then we develop a new framework to construct and analyze arbitrary p-th degree IFE methods. In this framework, each IFE function is the extension of a p-th degree polynomial from one subelement to the whole interface element by solving a local Cauchy problem on interface elements in which the jump conditions across the interface are employed as the boundary conditions. All the components in the analysis, including existence of IFE functions, the optimal approximation capabilities and the trace inequalities, are all reduced to key properties of the related discrete extension operator. We employ these results to show the optimal convergence of a discontinuous Galerkin IFE (DGIFE) method. In the last part, we apply the linear IFE methods in the literature together with the shape optimization technique to solve a group of interface inverse problems. In this algorithm, both the governing PDEs and the objective functional for interface inverse problems are discretized optimally by the IFE method regardless of the location of the interface in a chosen mesh. We derive the formulas for the gradients of the objective function in the optimization problem which can be implemented efficiently in the IFE framework through a discrete adjoint method. We demonstrate the properties of the proposed algorithm by applying it to three representative applications. / Doctor of Philosophy / Interface problems arise from many science and engineering applications modeling the transmission of some physical quantities between multiple materials. Mathematically, these multiple materials in general are modeled by partial differential equations (PDEs) with discontinuous parameters, which poses challenges to developing efficient and reliable numerical methods and the related theoretical error analysis. The main contributions of this dissertation is on the development of a special finite element method, the so called immersed finite element (IFE) method, to solve the interface problems on a mesh independent of the interface geometry which can be advantageous especially when the interface is moving. Specifically, this dissertation consists of three projects of IFE methods: elasticity interface problems, higher-order IFE methods and interface inverse problems, including their design, analysis, and application.

Thin and slender structures are widely occurring both in nature and in human creations. Clever geometries of thin structures can produce strong constructions while using a minimal amount of material. Computer modeling and analysis of thin and slender structures has its own set of problems stemming from assumptions made when deriving the equations modeling their behavior from the theory of continuum mechanics. In this thesis we consider two kinds of thin elastic structures; threads and plates. Real-time simulation of threads are of interest in various types of virtual simulations such as surgery simulation for instance. In the first paper of this thesis we develop a thread model for use in interactive applications. By viewing the thread as a continuum rather than a truly one dimensional object existing in three dimensional space we derive a thread model that naturally handles both bending, torsion and inertial effects. We apply a corotational framework to simulate large deformation in real-time. On the fly adaptive resolution is used to minimize corotational artifacts. Plates are flat elastic structures only allowing deflection in the normal direction. In the second paper in this thesis we propose a family of finite elements for approximating solutions to the Kirchhoff-Love plate equation using a continuous piecewise linear deflection field. We reconstruct a discontinuous piecewise quadratic deflection field which is applied in a discontinuous Galerkin method. Given a criterion on the reconstruction operator we prove a priori estimates in energy and L2 norms. Numerical results for the method using three possible reconstructions are presented.

Problems governed by partial differential equations (PDEs) in deformable domains, t Rd; d = 2; 3; are of fundamental importance in science and engineering. They are of particular relevance in the design of many engineering systems e.g., aircrafts and bridges as well as to the analysis of several biological phenomena e.g., blood ow in arteries. However, developing numerical scheme for such problems is still very challenging even when the deformation of the boundary of domain is prescribed a priori. Possibility of excessive mesh distortion is one of the major challenge when solving such problems with numerical methods using boundary tted meshes. The arbitrary Lagrangian- Eulerian (ALE) approach is a way to overcome this difficulty. Numerical simulations of convection-dominated problems have for long been the subject to many researchers. Galerkin formulations, which yield the best approximations for differential equations with high diffusivity, tend to induce spurious oscillations in the numerical solution of convection dominated equations. Though such spurious oscillations can be avoided by adaptive meshing, which is computationally very expensive on ne grids. Alternatively, stabilization methods can be used to suppress the spurious oscillations. In this work, the considered equation is designed within the framework of ALE formulation. In the first part, Streamline Upwind Petrov-Galerkin (SUPG) finite element method with conservative ALE formulation is proposed. Further, the first order backward Euler and the second order Crank-Nicolson methods are used for the temporal discretization. It is shown that the stability of the semi-discrete (continuous in time) ALE-SUPG equation is independent of the mesh velocity, whereas the stability of the fully discrete problem is unconditionally stable for implicit Euler method and is only conditionally stable for Crank-Nicolson time discretization. Numerical results are presented to support the stability estimates and to show the influence of the SUPG stabilization parameter in a time-dependent domain. In the second part of this work, SUPG stabilization method with non-conservative ALE formulation is proposed. The implicit Euler, Crank-Nicolson and backward difference methods are used for the temporal discretization. At the discrete level in time, the ALE map influences the stability of the corresponding discrete scheme with different time discretizations, and it leads to schemes where conservative and non-conservative formulations are no longer equivalent. The stability of the fully discrete scheme, irrespective of the temporal discretization, is only conditionally stable. It is observed from numerical results that the Crank-Nicolson scheme induces high oscillations in the numerical solution compare to the implicit Euler and the backward difference time discretiza-tions. Moreover, the backward difference scheme is more sensitive to the stabilization parameter k than the other time discretizations. Further, the difference between the solutions obtained with the conservative and non-conservative ALE forms is significant when the deformation of domain is large, whereas it is negligible in domains with small deformation. Finally, the local projection stabilization (LPS) and the higher order dG time stepping scheme are studied for convection dominated problems. The analysis is based on the quadrature formula for approximating the integrals in time. We considered the exact integration in time, which is impractical to implement and the Radau quadrature in time, which can be used in practice. The stability and error estimates are shown for the mathematical basis of considered numerical scheme with both time integration methods. The numerical analysis reveals that the proposed stabilized scheme with exact integration in time is unconditionally stable, whereas Radau quadrature in time is conditionally stable with time-step restriction depending on the ALE map. The theoretical estimates are illustrated with appropriate numerical examples with distinct features. The second order dG(1) time discretization is unconditionally stable while Crank-Nicolson gives the conditional stable estimates only. The convergence order for dG(1) is two which supports the error estimate.