A least-squares finite element reduced basis method

JEHANZEB H. CHAUDHRY, LUKE N. OLSON, PETER SENTZ

Research output: Contribution to journalArticlepeer-review

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 languageEnglish (US)
Pages (from-to)A1081-A1107
JournalSIAM Journal on Scientific Computing
Volume43
Issue number2
DOIs
StatePublished - 2021

Keywords

  • Finite elements
  • Least-squares
  • Reduced basis

ASJC Scopus subject areas

  • Computational Mathematics
  • Applied Mathematics

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