# The parameterized preconditioner for the generalized saddle point problems from the incompressible Navier–Stokes equations

## Abstract

A parameterized preconditioner is proposed for the generalized saddle point problems arising from the incompressible Navier–Stokes equations. The eigenvalues and eigenvectors of the preconditioned matrix are analyzed. Numerical results show that the proposed preconditioner is efficient to accelerate the convergence rate of Krylov subspace methods, such as GMRES method.

- Authors:

- Fujian Normal University, College of Mathematics and Informatics and FJKLMAA (China)

- Publication Date:

- OSTI Identifier:
- 22769274

- Resource Type:
- Journal Article

- Journal Name:
- Computational and Applied Mathematics

- Additional Journal Information:
- Journal Volume: 37; Journal Issue: 3; Other Information: Copyright (c) 2018 SBMAC - Sociedade Brasileira de Matemática Aplicada e Computacional; Country of input: International Atomic Energy Agency (IAEA); Journal ID: ISSN 0101-8205

- Country of Publication:
- United States

- Language:
- English

- Subject:
- 97 MATHEMATICAL METHODS AND COMPUTING; CONVERGENCE; EIGENVALUES; EIGENVECTORS; EQUATIONS; MATRICES

### Citation Formats

```
Ke, Yi-Fen, and Ma, Chang-Feng.
```*The parameterized preconditioner for the generalized saddle point problems from the incompressible Navier–Stokes equations*. United States: N. p., 2018.
Web. doi:10.1007/S40314-017-0518-X.

```
Ke, Yi-Fen, & Ma, Chang-Feng.
```*The parameterized preconditioner for the generalized saddle point problems from the incompressible Navier–Stokes equations*. United States. doi:10.1007/S40314-017-0518-X.

```
Ke, Yi-Fen, and Ma, Chang-Feng. Sun .
"The parameterized preconditioner for the generalized saddle point problems from the incompressible Navier–Stokes equations". United States. doi:10.1007/S40314-017-0518-X.
```

```
@article{osti_22769274,
```

title = {The parameterized preconditioner for the generalized saddle point problems from the incompressible Navier–Stokes equations},

author = {Ke, Yi-Fen and Ma, Chang-Feng},

abstractNote = {A parameterized preconditioner is proposed for the generalized saddle point problems arising from the incompressible Navier–Stokes equations. The eigenvalues and eigenvectors of the preconditioned matrix are analyzed. Numerical results show that the proposed preconditioner is efficient to accelerate the convergence rate of Krylov subspace methods, such as GMRES method.},

doi = {10.1007/S40314-017-0518-X},

journal = {Computational and Applied Mathematics},

issn = {0101-8205},

number = 3,

volume = 37,

place = {United States},

year = {2018},

month = {7}

}

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