Performance Analysis of Error-Control B-spline Gaussian Collocation Software for PDEs

Pre-printB-spline Gaussian collocation software has been widely used in the numerical solution of boundary value ordinary differential equations (BVODEs) and partial differential equations (PDEs) in one space dimension (1D) for many years. The software package, BACOL, developed over a decade ago, was one of the first 1D PDE packages to provide both temporal and spatial error control. A new package, BACOLI, improves upon the efficiency of BACOL through the use of new types of spatial error estimation and control. The complexity of the interactions among the component numerical algorithms used by these packages implies that extensive testing and analysis of the test results is an essential factor in their development. In this paper, we investigate the performance of the BACOL and BACOLI packages with respect to several important machine independent algorithmic measures and examine the effectiveness of the new error estimation and error control strategies. We also investigate the influence of the choice of the degree of the B-splines on the efficiency and reliability of the solvers. These results will provide new insights into how to improve BACOLI, lead to improvements in the Gaussian collocation BVODE solvers, COLSYS and COLNEW, and guide the further development of B-spline Gaussian collocation software with error control for 2D PDEs

IGA-based Multi-Index Stochastic Collocation for random PDEs on arbitrary domains

This paper proposes an extension of the Multi-Index Stochastic Collocation (MISC) method for forward uncertainty quantification (UQ) problems in computational domains of shape other than a square or cube, by exploiting isogeometric analysis (IGA) techniques. Introducing IGA solvers to the MISC algorithm is very natural since they are tensor-based PDE solvers, which are precisely what is required by the MISC machinery. Moreover, the combination-technique formulation of MISC allows the straight-forward reuse of existing implementations of IGA solvers. We present numerical results to showcase the effectiveness of the proposed approach.Comment: version 3, version after revisio

Almost Block Diagonal Linear Systems: Sequential and Parallel Solution Techniques, and Applications

Almost block diagonal (ABD) linear systems arise in a variety of contexts, specifically in numerical methods for two-point boundary value problems for ordinary differential equations and in related partial differential equation problems. The stable, efficient sequential solution of ABDs has received much attention over the last fifteen years and the parallel solution more recently. We survey the fields of application with emphasis on how ABDs and bordered ABDs (BABDs) arise. We outline most known direct solution techniques, both sequential and parallel, and discuss the comparative efficiency of the parallel methods. Finally, we examine parallel iterative methods for solving BABD systems. Copyright (C) 2000 John Wiley & Sons, Ltd

Extending BACOLI to solve multi-scale problems

The BACOLI package is a numerical software package for solving parabolic partial differential equations in one spatial dimension. It implements a B-spline collocation method for the spatial discretization of a system of partial differential equations. The resultant ordinary differential equations together with the boundary conditions form a system of differential-algebraic equations. The differential-algebraic equations are then solved using the DASSL solver. The BACOLI software package features adaptive error control in the temporal and spatial domains. The estimate of the temporal error is controlled through the DASSL solver. The estimate of the spatial error is controlled based on the difference between two solutions computed in the BACOLI software package. This difference gives an estimation of the error. If this error estimate does not meet the user-supplied tolerance, then the spatial mesh is changed. The BACOLI software package can only solve parabolic partial differential equations that depend on spatial derivatives. In this thesis, the BACOLI software package is modified to solve a broader spectrum of problems. In fact, after some modifications, the extended BACOLI software package can solve systems of parabolic partial differential equations and time-dependent equations that do not depend on spatial derivatives. We apply this extended software package to solve the monodomain model of cardiac electrophysiology. The monodomain model is a multi-scale mathematical model for the evolution of the electrical potential in cardiac tissue that couples the ionic currents at the cellular scale with their propagation at the tissue scale. Because of their local nature, the mathematical models of a single cell have no dependency on spatial derivatives whereas the models at the tissue level do. The heart models considered in our numerical experiments use various cardiac cell models. We find that solving the heart models through the extended BACOLI software package, in some cases, leads to a speed-up in comparison with the Chaste software package, which is a powerful, widely used, and well-respected software package for heart simulation

B-spline collocation for two dimensional, time-dependent, parabolic PDEs

vi, 177 leaves : ill. ; 29 cm.Includes abstract and appendices.Includes bibliographical references (leaves 82-88).In this thesis, we consider B-spline collocation algorithms for solving two-dimensional in space, time-dependent parabolic partial differential equations (PDEs), defined over a rectangular region. We propose two ways to solve the problem: (i) The Method of Surfaces: Discretizing the problem in one of the spatial domains, we obtain a system of one-dimensional parabolic PDEs, which is then solved using a one-dimensional PDE system solver. (ii) Two-dimensional B-spline collocation: The numerical solution is represented as a bi-variate piecewise polynomial with unknown time-dependent coefficients. These coefficients are determined by requiring the numerical solution to satisfy the PDE at a number of points within the spatial domain, i.e., we collocate simultaneously in both spatial dimensions. This leads to an approximation of the PDE by a large system of time-dependent differential algebraic equations (DAEs), which we then solve using a high quality DAE solver