Semi-implicit Krylov deferred correction algorithms, applications, and parallelization

In this dissertation, we introduce several strategies to improve the efficiency of the Krylov deferred correction (KDC) methods for special structured ordinary and partial differential equations with algebraic constraints. We first study the semi-implicit KDC (SI-KDC) technique which splits stiff differential equation systems into different components and applies different low-order time marching schemes to these components. Compared with the fully implicit KDC (FI-KDC) method, our analysis and preliminary numerical results for differential algebraic equations show that the SI-KDC schemes are more efficient due to the reduced number of operations in each spectral deferred correction (SDC) iteration. Next, we apply the SI-KDC scheme to simulate a two-scale model describing the mass transfer processes in drinking water treatment applications, in which some set of chemical species move from one distinct phase to a second distinct phase. We also present an improved effective model to further advance the efficiency of the multiscale modeling. Finally, we investigate the parareal method to parallelize the KDC techniques, and present some preliminary numerical results to show its potential in large scale simulations

Spatial Manifestations of Order Reduction in Runge-Kutta Methods for Initial Boundary Value Problems

This paper studies the spatial manifestations of order reduction that occur when time-stepping initial-boundary-value problems (IBVPs) with high-order Runge-Kutta methods. For such IBVPs, geometric structures arise that do not have an analog in ODE IVPs: boundary layers appear, induced by a mismatch between the approximation error in the interior and at the boundaries. To understand those boundary layers, an analysis of the modes of the numerical scheme is conducted, which explains under which circumstances boundary layers persist over many time steps. Based on this, two remedies to order reduction are studied: first, a new condition on the Butcher tableau, called weak stage order, that is compatible with diagonally implicit Runge-Kutta schemes; and second, the impact of modified boundary conditions on the boundary layer theory is analyzed.Comment: 41 pages, 9 figure

Performance of explicit and IMEX MRI multirate methods on complex reactive flow problems within modern parallel adaptive structured grid frameworks

Large-scale multiphysics simulations are computationally challenging due to the coupling of multiple processes with widely disparate time scales. The advent of exascale computing systems exacerbates these challenges, since these enable ever increasing size and complexity. Recently, there has been renewed interest in developing multirate methods as a means to handle the large range of time scales, as these methods may afford greater accuracy and efficiency than more traditional approaches of using IMEX and low-order operator splitting schemes. However, there have been few performance studies that compare different classes of multirate integrators on complex application problems. We study the performance of several newly developed multirate infinitesimal (MRI) methods, implemented in the SUNDIALS solver package, on two reacting flow model problems built on structured mesh frameworks. The first model revisits the work of Emmet et al. (2014) on a compressible reacting flow problem with complex chemistry that is implemented using BoxLib but where we now include comparisons between a new explicit MRI scheme with the multirate spectral deferred correction (SDC) methods in the original paper. The second problem uses the same complex chemistry as the first problem, combined with a simplified flow model, but run at a large spatial scale where explicit methods become infeasible due to stability constraints. Two recently developed implicit-explicit MRI multirate methods are tested. These methods rely on advanced features of the AMReX framework on which the model is built, such as multilevel grids and multilevel preconditioners. The results from these two problems show that MRI multirate methods can offer significant performance benefits on complex multiphysics application problems and that these methods may be combined with advanced spatial discretization to compound the advantages of both

SciCADE 95: International conference on scientific computation and differential equations

This report consists of abstracts from the conference. Topics include algorithms, computer codes, and numerical solutions for differential equations. Linear and nonlinear as well as boundary-value and initial-value problems are covered. Various applications of these problems are also included