Low-rank solution to an optimization problem constrained by the Navier-Stokes equations

Sergey Dolgov, Martin Stoll

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14 Citations (SciVal)
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The numerical solution of PDE-constrained optimization problems subject to the nonstationary Navier-Stokes equation is a challenging task. While space-time approaches often show favorable convergence properties, they often suffer from storage problems. Here we propose to approximate the solution to the optimization problem in a low-rank form, which is similar to the model order reduction (MOR) approach. However, in contrast to classical MOR schemes we do not compress the full solution at the end of the algorithm but start our algorithm with low-rank data and maintain this form throughout the iteration. Numerical experiments indicate that this approach reduces the computational costs by two orders of magnitude.

Original languageEnglish
Pages (from-to)A255-A280
JournalSIAM Journal on Scientific Computing
Issue number1
Early online date8 Feb 2017
Publication statusPublished - 2017


  • Alternating solvers
  • Iterative solvers
  • Low-rank methods
  • Model reduction
  • PDE-constrained optimization
  • Preconditioning


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