Scalable parallel simulation of variably saturated flow

In this thesis we develop highly accurate simulation tools for variably saturated flow through porous media able to take advantage of the latest supercomputing resources. Hence, we aim for parallel scalability to very large compute resources of over 105 CPU cores. Our starting point is the parallel subsurface flow simulator ParFlow. This library is of widespread use in the hydrology community and known to have excellent parallel scalability up to 16k processes. We first investigate the numerical tools this library implements in order to perform the simulations it was designed for. ParFlow solves the governing equation for subsurface flow with a cell centered finite difference (FD) method. The code targets high performance computing (HPC) systems by means of distributed memory parallelism. We propose to reorganize ParFlow's mesh subsystem by using fast partitioning algorithms provided by the parallel adaptive mesh refinement (AMR) library p4est. We realize this in a minimally invasive manner by modifying selected parts of the code to reinterpret the existing mesh data structures. Furthermore, we evaluate the scaling performance of the modified version of ParFlow, demonstrating excellent weak and strong scaling up to 458k cores of the Juqueen supercomputer at the Jülich Supercomputing Centre. The above mentioned results were obtained for uniform meshes and hence without explicitly exploiting the AMR capabilities of the p4est library. A natural extension of our work is to activate such functionality and make ParFlow a true AMR application. Enabling ParFlow to use AMR is challenging for several reasons: It may be based on assumptions on the parallel partition that cannot be maintained with AMR, it may use mesh-related metadata that is replicated on all CPUs, and it may assume uniform meshes in the construction of mathematical operators. Additionally, the use of locally refined meshes will certainly change the spectral properties of these operators. In this work, we develop an algorithmic approach to activate the usage of locally refined grids in ParFlow. AMR allows meshes where elements of different size neighbor each other. In this case, ParFlow may incur erroneous results when it attempts to communicate data between inter-element boundaries. We propose and discuss two solutions to this issue operating at two different levels: The first manipulates the indices of the degrees of freedom, While the second operates directly on the degrees of freedom. Both approaches aim to introduce minimal changes to the original ParFlow code. In an AMR framework, the FD method taken by ParFlow will require modifications to correctly deal with different size elements. Mixed finite elements (MFE) are on the other hand better suited for the usage of AMR. It is known that the cell centered FD method used in ParFlow might be reinterpreted as a MFE discretization using Raviart-Thomas elements of lower order. We conclude this thesis presenting a block preconditioner for saddle point problems arising from a MFE on locally refined meshes. We evaluate its robustness with respect to various classes of coefficients for uniform and locally refined meshes

Recent Progress in Image Deblurring

This paper comprehensively reviews the recent development of image deblurring, including non-blind/blind, spatially invariant/variant deblurring techniques. Indeed, these techniques share the same objective of inferring a latent sharp image from one or several corresponding blurry images, while the blind deblurring techniques are also required to derive an accurate blur kernel. Considering the critical role of image restoration in modern imaging systems to provide high-quality images under complex environments such as motion, undesirable lighting conditions, and imperfect system components, image deblurring has attracted growing attention in recent years. From the viewpoint of how to handle the ill-posedness which is a crucial issue in deblurring tasks, existing methods can be grouped into five categories: Bayesian inference framework, variational methods, sparse representation-based methods, homography-based modeling, and region-based methods. In spite of achieving a certain level of development, image deblurring, especially the blind case, is limited in its success by complex application conditions which make the blur kernel hard to obtain and be spatially variant. We provide a holistic understanding and deep insight into image deblurring in this review. An analysis of the empirical evidence for representative methods, practical issues, as well as a discussion of promising future directions are also presented.Comment: 53 pages, 17 figure

Processing Elastic Surfaces and Related Gradient Flows

Surface processing tools and techniques have a long history in the fields of computer graphics, computer aided geometric design and engineering. In this thesis we consider variational methods and geometric evolution problems for various surface processing applications including surface fairing, surface restoration and surface matching. Geometric evolution problems are often based on the gradient flow of geometric energies. The Willmore functional, defined as the integral of the squared mean curvature over the surface, is a geometric energy that measures the deviation of a surface from a sphere. Therefore, it is a suitable functional for surface restoration, where a destroyed surface patch is replaced by a smooth patch defined as the minimizer of the Willmore functional with boundary conditions for the position and the normal at the patch boundary. However, using the Willmore functional does not lead to satisfying results if an edge or a corner of the surface is destroyed. The anisotropic Willmore energy is a natural generalization of the Willmore energy which has crystal-shaped surfaces like cubes or octahedra as minimizers. The corresponding L2-gradient flow, the anisotropic Willmore flow, leads to a fourth-order partial differential equation that can be written as a system of two coupled second second order equations. Using linear Finite Elements, we develop a semi-implicit scheme for the anisotropic Willmore flow with boundary conditions. This approach suffer from significant restrictions on the time step size. Effectively, one usually has to enforce time steps smaller than the squared spatial grid size. Based on a natural approach for the time discretization of gradient flows we present a new scheme for the time and space discretization of the isotropic and anisotropic Willmore flow. The approach is variational and takes into account an approximation of the L2-distance between the surface at the current time step and the unknown surface at the new time step as well as a fully implicity approximation of the anisotropic Willmore functional at the new time step. To evaluate the anisotropic Willmore energy on the unknown surface of the next time step, we first ask for the solution of an inner, secondary variational problem describing a time step of anisotropic mean curvature motion. The time discrete velocity deduced from the solution of the latter problem is regarded as an approximation of the anisotropic mean curvature vector and enters the approximation of the actual anisotropic Willmore functional. The resulting two step time discretization of the Willmore flow is applied to polygonal curves and triangular surfaces and is independent of the co-dimension. Various numerical examples underline the stability of the new scheme, which enables time steps of the order of the spatial grid size. The Willmore functional of a surface is referred to as the elastic surface energy. Another interesting application of modeling elastic surfaces as minimizers of elastic energies is surface matching, where a correspondence between two surfaces is subject of investigation. There, we seek a mapping between two surfaces respecting certain properties of the surfaces. The approach is variational and based on well-established matching methods from image processing in the parameter domains of the surfaces instead of finding a correspondence between the two surfaces directly in 3D. Besides the appropriate modeling we analyze the derived model theoretically. The resulting deformations are globally smooth, one-to-one mappings. A physically proper morphing of characters in computer graphic is capable with the resulting computational approach

H-P adaptive methods for finite element analysis of aerothermal loads in high-speed flows

The commitment to develop the National Aerospace Plane and Maneuvering Reentry Vehicles has generated resurgent interest in the technology required to design structures for hypersonic flight. The principal objective of this research and development effort has been to formulate and implement a new class of computational methodologies for accurately predicting fine scale phenomena associated with this class of problems. The initial focus of this effort was to develop optimal h-refinement and p-enrichment adaptive finite element methods which utilize a-posteriori estimates of the local errors to drive the adaptive methodology. Over the past year this work has specifically focused on two issues which are related to overall performance of a flow solver. These issues include the formulation and implementation (in two dimensions) of an implicit/explicit flow solver compatible with the hp-adaptive methodology, and the design and implementation of computational algorithm for automatically selecting optimal directions in which to enrich the mesh. These concepts and algorithms have been implemented in a two-dimensional finite element code and used to solve three hypersonic flow benchmark problems (Holden Mach 14.1, Edney shock on shock interaction Mach 8.03, and the viscous backstep Mach 4.08)

A Parallel and Adaptive Space-Time Method for Maxwell\u27s Equations

In this work a space-time discretization for linear hyperbolic evolution systems is introduced. A discontinuous Galerkin approximation in space is combined and analyzed together with a Petrov-Galerkin scheme in time. The idea of DWR methods is applied to derive a p-adaptive strategy. The full linear system is solved in parallel in space and time by using a multilevel preconditioner. Numerical test validate the efficiency of the method in case of linear transport and Maxwell\u27s equations in 2D

Isogeometric finite element methods for liquid metal magnetohydrodynamics

A fusion blanket is a key component in a fusion reactor which extracts heat energy, protects the surrounding structure and possibly produces tritium, one of the fuels required for the deuterium-tritium fusion reaction. Interest in magneto-hydrodynamic (MHD) effects in the fusion blanket has been growing due to the promising prospect of a liquid breeder blanket, due to its high power density and the possibility of sustainable production of tritium. However, MHD effects can significantly influence the operating performance of the fusion blanket and an accurate and reliable analysis of the MHD effects are critical in its design. Significant progress in the numerical study of MHD has been made recently, due in large part to the advancement in computing power. However, its maturity has not yet reached a point comparable with standard CFD solvers. In particular, complex domains and complex externally applied magnetic fields present additional challenges for numerical schemes in MHD. For that reason, the application of isogeometric analysis is considered in this thesis. Isogeometric Analysis (IGA) is a new class of numerical method which integrates Computer Aided Design (CAD) into Finite Element Analysis (FEA). In IGA, B-splines and NURBS, which are the building blocks used to construct a geometry in CAD, are also used to build the finite element spaces. This allows to represent geometries more accurately, and in some cases exactly. This may help advance the progress of numerical studies of MHD effects, not only in fusion blanket scenarios, but more widely. In this thesis, we develop and study a number of types of IGA based MHD solver; a fully-developed MHD flow solver, a steady-state MHD solver and a time-dependent MHD solver. These solvers are validated using analytical methods and methods of manufactured solution and are compared with other numerical schemes on a number of benchmark problems.Open Acces

Modeling EMI Resulting from a Signal Via Transition Through Power/Ground Layers

Signal transitioning through layers on vias are very common in multi-layer printed circuit board (PCB) design. For a signal via transitioning through the internal power and ground planes, the return current must switch from one reference plane to another reference plane. The discontinuity of the return current at the via excites the power and ground planes, and results in noise on the power bus that can lead to signal integrity, as well as EMI problems. Numerical methods, such as the finite-difference time-domain (FDTD), Moment of Methods (MoM), and partial element equivalent circuit (PEEC) method, were employed herein to study this problem. The modeled results are supported by measurements. In addition, a common EMI mitigation approach of adding a decoupling capacitor was investigated with the FDTD method

Experimental and numerical description of rapid granular flows and some baseline constraints for simulating 3-dimensional granular flow dynamics

Accurate prediction of rapid granular flow behavior is essential to optimize protection measures from hazardous natural granular flows like snow avalanches and landslides and to design efficient production facilities for granulate processing industries. So far, most successful models for rapid granular flow descriptions employ depth-averaging, assuming an essentially constant velocity over depth. This assumption greatly reduces calculation power but can lead to incorrect predictions in regions of strong velocity shearing in the flow depth direction, e.g., during the impact on an obstacle. To overcome these limitations, this study introduces a novel type of non-depth-averaged fluid dynamics simulations for rapid granular flows of cohesionless material. A series of small scale experiments with industrial (polyvinyl chloride (PVC)) and natural (sand) granular material was performed (i) to select and refine the appropriate rheological model, (ii) to yield a better insight into velocity profiles and (iii) to obtain parameters for comparison with numerical simulations. Based on these experiments, Coulomb-type friction was selected as rheological model. A Poly(methyl methacrylate) channel set-up with variable inclination angle in combination with high-speed image recording and an open source particle image velocimetry (PIV) software developed in this study allowed detailed observation of velocity profiles during flow inception, undisturbed flows, flows encountering obstacles, and shock scenarios. The PIV measurements revealed considerable changes in velocity between layers of the granular flow and thus underpin the necessity to perform non-depth-averaged simulations in order to accurately describe the flow behavior in all aspects. Comparison of the depth-averaged simulation model of the Savage-Hutter type and the non-depth-averaged simulation method introduced here with the experiments revealed that certain quantities, like the flow height and shape could only be accurately predicted using the non-depth-averaged simulations. Furthermore, the non-depth-averaged simulations were well capable of predicting the observed velocity profiles and produce accurate predictions of associated quantities like strain rates and slip velocities for both materials in most experiments. Nevertheless, this study also revealed cases where both depth-averaged and non-depth-averaged methods generate similar predictions, e.g., the height of an undisturbed flow and deposition shapes. A detailed summary of parameters and dynamic variables in different experiments, and their predictability by both methods is provided. This serves as a guideline to decide when to employ the reduced but faster depth-averaged methods and when more calculation power intensive, but more accurate, non-depth-averaged methods must be employed. The non-depth-averaged method developed in this study was further validated to measure its predictive power in three dimensional experiments with obstacles. Also here, accurate predictions were observed. Furthermore, a method for the introduction of complex topographies into the simulation process was developed, allowing the direct integration of real mountain topographies. As pilot tests, simulations of granular flows on a complex experimental topography and a real case snow avalanche described in the literature were performed. The results demonstrated that the new method can be transferred to complex topographies and yields good predictions. These findings can serve as a basis for further refinement of the model and its expansions to describe more complex events, e.g., the entrainment of snow mass. Taken together, the novel, non-depth-averaged model and simulation technique build in this study based on the experimental observation are a suitable tool to predict important flow dynamical quantities in non-cohesive granular flows of both natural and industrial origins. Furthermore, it can serve as a basis for the development of a non-depth-averaged predictive model for real scale hazardous granular flows and is thus an important step towards the correct prediction of granular flow behavior for risk assessment in endangered regions