Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4642276 | Journal of Computational and Applied Mathematics | 2008 | 12 Pages |
Abstract
In many applications, partial differential equations depend on parameters which are only approximately known. Using tools from functional analysis and global optimization, methods are presented for obtaining certificates for rigorous and realistic error bounds on the solution of linear elliptic partial differential equations in arbitrary domains, either in an energy norm, or of key functionals of the solutions, given an approximate solution. Uncertainty in the parameters specifying the partial differential equations can be taken into account, either in a worst case setting, or given limited probabilistic information in terms of clouds.
Related Topics
Physical Sciences and Engineering
Mathematics
Applied Mathematics
Authors
Arnold Neumaier,