### Abstract

Iterative substructuring methods are introduced and analyzed for saddle point problems with a penalty term. Two examples of saddle point problems are considered: The mixed formulation of the linear elasticity system and the generalized Stokes system in three dimensions. These problems are discretized with spectral element methods. The resulting stiffness matrices are symmetric and indefinite. The interior unknowns of each element are first implicitly eliminated by using exact local solvers. The resulting saddle point Schur complement is solved with a Krylov space method with block preconditioners. The velocity block can be approximated by a domain decomposition method, e.g., of wire basket type, which is constructed from a local solver for each face of the elements, and a coarse solver related to the wire basket of the elements. The condition number of the preconditioned operator is independent of the number of spectral elements and is bounded from above by the product of the square of the logarithm of the spectral degree and the inverse of the discrete inf-sup constant of the problem.

Original language | English (US) |
---|---|

Pages (from-to) | 375-402 |

Number of pages | 28 |

Journal | SIAM Journal on Numerical Analysis |

Volume | 37 |

Issue number | 2 |

State | Published - 2000 |

### Fingerprint

### Keywords

- Gauss-Lobatto-Legendre quadrature
- Linear elasticity
- Mixed methods
- Preconditioned iterative methods
- Spectral element methods
- Stokes problem
- Substructuring

### ASJC Scopus subject areas

- Mathematics(all)
- Applied Mathematics
- Computational Mathematics

### Cite this

*SIAM Journal on Numerical Analysis*,

*37*(2), 375-402.

**Iterative substructuring methods for spectral element discretizations of elliptic systems. II : Mixed methods for linear elasticity and stokes flow.** / Pavarino, Luca F.; Widlund, Olof B.

Research output: Contribution to journal › Article

*SIAM Journal on Numerical Analysis*, vol. 37, no. 2, pp. 375-402.

}

TY - JOUR

T1 - Iterative substructuring methods for spectral element discretizations of elliptic systems. II

T2 - Mixed methods for linear elasticity and stokes flow

AU - Pavarino, Luca F.

AU - Widlund, Olof B.

PY - 2000

Y1 - 2000

N2 - Iterative substructuring methods are introduced and analyzed for saddle point problems with a penalty term. Two examples of saddle point problems are considered: The mixed formulation of the linear elasticity system and the generalized Stokes system in three dimensions. These problems are discretized with spectral element methods. The resulting stiffness matrices are symmetric and indefinite. The interior unknowns of each element are first implicitly eliminated by using exact local solvers. The resulting saddle point Schur complement is solved with a Krylov space method with block preconditioners. The velocity block can be approximated by a domain decomposition method, e.g., of wire basket type, which is constructed from a local solver for each face of the elements, and a coarse solver related to the wire basket of the elements. The condition number of the preconditioned operator is independent of the number of spectral elements and is bounded from above by the product of the square of the logarithm of the spectral degree and the inverse of the discrete inf-sup constant of the problem.

AB - Iterative substructuring methods are introduced and analyzed for saddle point problems with a penalty term. Two examples of saddle point problems are considered: The mixed formulation of the linear elasticity system and the generalized Stokes system in three dimensions. These problems are discretized with spectral element methods. The resulting stiffness matrices are symmetric and indefinite. The interior unknowns of each element are first implicitly eliminated by using exact local solvers. The resulting saddle point Schur complement is solved with a Krylov space method with block preconditioners. The velocity block can be approximated by a domain decomposition method, e.g., of wire basket type, which is constructed from a local solver for each face of the elements, and a coarse solver related to the wire basket of the elements. The condition number of the preconditioned operator is independent of the number of spectral elements and is bounded from above by the product of the square of the logarithm of the spectral degree and the inverse of the discrete inf-sup constant of the problem.

KW - Gauss-Lobatto-Legendre quadrature

KW - Linear elasticity

KW - Mixed methods

KW - Preconditioned iterative methods

KW - Spectral element methods

KW - Stokes problem

KW - Substructuring

UR - http://www.scopus.com/inward/record.url?scp=0009269387&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0009269387&partnerID=8YFLogxK

M3 - Article

AN - SCOPUS:0009269387

VL - 37

SP - 375

EP - 402

JO - SIAM Journal on Numerical Analysis

JF - SIAM Journal on Numerical Analysis

SN - 0036-1429

IS - 2

ER -