|
Error estimation and adaptive computation for
elliptic problems with randomly perturbed coefficients
Axel M\aa lqvist
Department of Mathematics
UCSD
Joint with Donald Estep and Simon Tavener
Abstract
We develop and analyze an efficient numerical method for computing
the response of the solution of an elliptic problem with randomly
perturbed coefficients. We use a variational analysis based on the adjoint
operator to deal with the perturbations in data. To deal with
perturbations in the diffusion coefficient, we construct a piecewise
constant approximation to the random perturbation then use domain
decomposition to decompose the problem into sub-problems on which
the diffusion coefficient is constant. To compute local solutions of
the sub-problems, we use the infinite series for the inverse of a
perturbation of an invertible matrix to devise a fast way to compute
the effects of variation in the parameter. Finally, we derive a
posteriori error estimates that take into account all the sources
of error and derive a new adaptive algorithm that provides a
quantitative way to distribute computational resources between all
of the sources.
|











