Name
Abstract | ||
|---|---|---|
We present a reduced basis method for parametrized linear elliptic partial differential equations (PDEs) in a least-squares finite element framework. A rigorous and reliable error estimate is developed, and is shown to bound the error with respect to the exact solution of the PDE, in contrast to estimates that measure error with respect to a finite-dimensional (high-fidelity) approximation. It is shown that the first-order formulation of the least-squares finite element is a key ingredient. The method is demonstrated using numerical examples. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1137/20M1323552 | SIAM JOURNAL ON SCIENTIFIC COMPUTING |
Keywords | DocType | Volume |
least-squares, finite elements, reduced basis | Journal | 43 |
Issue | ISSN | Citations |
2 | 1064-8275 | 0 |
PageRank | References | Authors |
0.34 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jehanzeb Hameed Chaudhry | 1 | 13 | 3.42 |
| Luke Olson | 2 | 235 | 21.93 |
| Sentz Peter | 3 | 0 | 0.34 |