An Augmented Lagrangian Preconditioner for the Control of the Navier–Stokes Equations

We address the solution of the distributed control problem for the steady, incompressible Navier–Stokes equations. We propose an inexact Newton linearization of the optimality conditions. Upon discretization by a finite element scheme, we obtain a sequence of large symmetric linear systems of saddle-point type. We use an augmented Lagrangian-based block triangular preconditioner in combination with the flexible GMRES method at each Newton step. The preconditioner is applied inexactly via a suitable multigrid solver. Numerical experiments indicate that the resulting method appears to be fairly robust with respect to viscosity, mesh size, and the choice of regularization parameter when applied to 2D problems.

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Publication Details

Journal
SIAM Journal on Scientific Computing
Published
2025-09-12
DOI
https://doi.org/10.1137/24m1683354
Primary Topic
Advanced Numerical Methods in Computational Mathematics
Type
article
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article

An Augmented Lagrangian Preconditioner for the Control of the Navier–Stokes Equations

Michele Benzi, Santolo Leveque, Patrick E. Farrell
SIAM Journal on Scientific Computing
Advanced Numerical Methods in Computational Mathematics
article

An Augmented Lagrangian Preconditioner for the Control of the Navier–Stokes Equations

Michele Benzi, Santolo Leveque, Patrick E. Farrell
article en

Abstract

We address the solution of the distributed control problem for the steady, incompressible Navier–Stokes equations. We propose an inexact Newton linearization of the optimality conditions. Upon discretization by a finite element scheme, we obtain a sequence of large symmetric linear systems of saddle-point type. We use an augmented Lagrangian-based block triangular preconditioner in combination with the flexible GMRES method at each Newton step. The preconditioner is applied inexactly via a suitable multigrid solver. Numerical experiments indicate that the resulting method appears to be fairly robust with respect to viscosity, mesh size, and the choice of regularization parameter when applied to 2D problems.

SIAM Journal on Scientific ComputingVol. 47(5)
Scuola Normale Superiore (IT), University of Oxford (GB)
Openalex Percentile: Top 73%
Advanced Numerical Methods in Computational Mathematics
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An Augmented Lagrangian Preconditioner for the Control of the Navier–Stokes Equations — Michele Benzi, Santolo Leveque, et al. · SIAM Journal on Scientific Computing (2025) | TGRS Research Map | TGRS