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Monolithic Algebraic Multigrid Preconditioners for the Stokes Equations
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abstract
We investigate a novel monolithic algebraic multigrid (AMG) preconditioner for the Taylor-Hood ($\pmb{\mathbb{P}}_2/\mathbb{P}_1$) and Scott-Vogelius ($\pmb{\mathbb{P}}_2/\mathbb{P}_1^{disc}$) discretizations of the Stokes equations. The algorithm is based on the use of the lower-order $\pmb{\mathbb{P}}_1\text{iso}\kern1pt\pmb{\mathbb{P}}_2/\mathbb{P}_1$ operator within a defect-correction setting, in combination with AMG construction of interpolation operators for velocities and pressures. The preconditioning framework is primarily algebraic, though the $\pmb{\mathbb{P}}_1\text{iso}\kern1pt\pmb{\mathbb{P}}_2/\mathbb{P}_1$ operator must be provided. We investigate two relaxation strategies in this setting. Specifically, a novel block factorization approach is devised for Vanka patch systems, which significantly reduces storage requirements and computational overhead, and a Chebyshev adaptation of the LSC-DGS relaxation is developed to improve parallelism. The preconditioner demonstrates robust performance across a variety of 2D and 3D Stokes problems, often matching or exceeding the effectiveness of an inexact block-triangular (or Uzawa) preconditioner, especially in challenging scenarios such as elongated-domain problems.
Forward citations
Cited by 2 Pith papers
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Nodal AMG Coarsening and Interpolation for PDE Systems
A new algebraic multigrid algorithm coarsens PDE systems by coarsening a nodal dual problem and constructing orientation-aware averages along paths, yielding near-kernel-preserving interpolation for curl-curl, grad-di...
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Generalized Optimal AMG Convergence Theory for Stokes Equations Using Smooth Aggregation and Vanka Relaxation Strategies
The generalized AMG lower bound |1 - λ_{nc+1}| consistently underestimates the observed two-grid convergence rate of monolithic SA-AMG with Vanka relaxation for Stokes equations.
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