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MINISYMPOSIA |
Spatial
Error Estimation and Grid Refinement Techniques
for the Numerical Solution of PDEs
organized by
Ronald Haynes, Memorial University of Newfoundland
Paul Muir, Saint Mary's University
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The Method-Of-Lines is an important approach for the numerical solution
of partial differential equations (PDEs). Based on a given spatial grid,
the PDE is discretized, leading to a system of time dependent ordinary
differential equations (ODEs) or differential-algebraic equations (DAEs).
For PDEs in one spatial dimension, standard techniques for discretization,
error estimation, and grid refinement for boundary value ODEs are also
relevant. This mini-symposium will bring together researchers who will
discuss recent work in the method-of-lines approach for the numerical
solution of PDEs, with a focus on spatial error estimation and grid refinement
techniques
SPEAKERS |
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Ronald
Haynes
Memorial University of Newfoundland |
Domain
Decomposition approaches for grid generation via the Equidistribution
Principle (slides
of talk)
Adaptively choosing an underlying grid for computation has proven
to be a useful, if not essential, tool for the solution of boundary
value problems and partial differential equations. One way of generating
adaptive meshes is through the so-called equidistribution principle
(EP). In one spatial dimension the required mesh can be obtained
through the solution of a nonlinear BVP. In this talk I will review
the idea of EP and consider the solution of the resulting BVP via
domain decomposition including classical, optimized and optimal
Schwarz iterations. |
Felix
Kwok
University of Geneva |
Accuracy
and Stability of a Predictor-Corrector Crank-Nicolson Method with
Many Subdomains
(slides of talk)
Many
techniques for parallelizing the solution of time-dependent PDEs
using domain decomposition ideas have been developed over the
past 20 years. One such class of methods uses a predictor-corrector
strategy, where variables along subdomain interfaces are first
predicted using an explicit method, and the remaining variables
are solved implicitly in parallel, using the predicted interface
values as boundary conditions. In this talk, we analyze the truncation
error and the stability of a predictor-corrector Crank-Nicolson
method proposed by Rempe and Chopp (SISC 2006), which formally
has second-order accuracy in time for a fixed spatial grid.
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Paul
Muir
Saint Mary's University
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Efficient
Interpolant-based Spatial Error Estimation for B-Spline Collocation
Solutions of PDEs (slides
of talk)
BACOL, recently developed collocation software for 1D parabolic
PDEs, has been shown to be efficient, reliable and robust, especially
for problems with solutions exhibiting sharp layers. It features
adaptive control of estimates of the spatial and temporal error.
While the BACOL spatial error estimate is generally quite reliable,
it involves the expensive computation of two collocation solutions
of orders p and p+1. This talk will discuss recent work investigating
more efficient spatial error estimation algorithms based on (i)
an order p+1 (superconvergent) interpolant and (ii) an order p interpolant
whose error agrees asymptotically with the order p collocation solution
error.
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Natesan
Srinivasan
Indian Institute of Technology Guwahati |
Second-Order
Uniformly Convergent Hybrid Numerical Scheme for Singularly Perturbed
Problems of Mixed Parabolic-Elliptic Type
Here,
we propose a uniformly convergent numerical scheme for a class
of singularly perturbed mixed parabolic-elliptic problems exhibiting
both boundary and interior layers. The domain under consideration
is partitioned into two subdomains. In the first subdomain, the
given problem takes the form of parabolic reaction-diffusion type,
and in the second subdomain, it takes an elliptic convection-diffusion-reaction
type. The numerical scheme consists of the backward-Euler method
for the time derivative, and a hybrid scheme for the spatial derivatives.
The numerical method is analyzed on a layer resolving piecewise-uniform
Shishkin mesh, and parameter-uniform error estimate is obtained.
Numerical examples are carried out to validate the theoretical
results.
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