Parameter-robust Braess-Sarazin-type smoothers for linear elasticity problems

TL;DR

This paper introduces three new multigrid relaxation schemes for linear elasticity problems that are robust to material parameters, analyzing their efficiency through local Fourier analysis and validating with numerical experiments.

Contribution

The paper develops three Braess-Sarazin-type multigrid relaxation schemes for linear elasticity, including inexact versions, with proven robustness and efficiency via local Fourier analysis.

Findings

All schemes achieve parameter-robust convergence.

Inexact schemes perform comparably to exact ones.

Vanka-Braess-Sarazin is the most efficient relaxation method.

Abstract

In this work, we propose three Braess-Sarazin-type multigrid relaxation schemes for solving linear elasticity problems, where the marker and cell scheme, a finite difference method, is used for the discretization. The three relaxation schemes are Jacobi-Braess-Sarazin, Mass-Braess-Sarazin, and Vanka-Braess-Sarazin. A local Fourier analysis (LFA) for the block-structured relaxation schemes is presented to study multigrid convergence behavior. From LFA, we derive optimal LFA smoothing factor for each case. We obtain highly efficient smoothing factors, which are independent of Lam\'{e} constants. Vanka-Braess-Sarazin relaxation scheme leads to the most efficient one. In each relaxation, a Schur complement system needs to be solved. Due to the fact that direct solve is often expensive, an inexact version is developed, where we simply use at most three weighted Jacobi iterations on the Schur complement system. Finally, two-grid and V-cycle multigrid performances are presented to validate our theoretical results. Our numerical results show that inexact versions can achieve the same performance as that of exact versions and our methods are robust to the Lam\'{e} constants.