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.
Original language | English (US) |
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Pages (from-to) | A1081-A1107 |
Journal | SIAM Journal on Scientific Computing |
Volume | 43 |
Issue number | 2 |
DOIs | |
State | Published - 2021 |
Keywords
- Finite elements
- Least-squares
- Reduced basis
ASJC Scopus subject areas
- Computational Mathematics
- Applied Mathematics