تقرير
Robust multigrid techniques for augmented Lagrangian preconditioning of incompressible Stokes equations with extreme viscosity variations
العنوان: | Robust multigrid techniques for augmented Lagrangian preconditioning of incompressible Stokes equations with extreme viscosity variations |
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المؤلفون: | Shih, Yu-hsuan, Stadler, Georg, Wechsung, Florian |
سنة النشر: | 2021 |
المجموعة: | Computer Science Mathematics |
مصطلحات موضوعية: | Mathematics - Numerical Analysis, Computer Science - Computational Engineering, Finance, and Science, 65F08, 65F10, 65N55, 65Y05, 76D07 |
الوصف: | We present augmented Lagrangian Schur complement preconditioners and robust multigrid methods for incompressible Stokes problems with extreme viscosity variations. Such Stokes systems arise, for instance, upon linearization of nonlinear viscous flow problems, and they can have severely inhomogeneous and anisotropic coefficients. Using an augmented Lagrangian formulation for the incompressibility constraint makes the Schur complement easier to approximate, but results in a nearly singular (1,1)-block in the Stokes system. We present eigenvalue estimates for the quality of the Schur complement approximation. To cope with the near-singularity of the (1,1)-block, we extend a multigrid scheme with a discretization-dependent smoother and transfer operators from triangular/tetrahedral to the quadrilateral/hexahedral finite element discretizations $[\mathbb{Q}_k]^d\times \mathbb{P}_{k-1}^{\text{disc}}$, $k\geq 2$, $d=2,3$. Using numerical examples with scalar and with anisotropic fourth-order tensor viscosity arising from linearization of a viscoplastic constitutive relation, we confirm the robustness of the multigrid scheme and the overall efficiency of the solver. We present scalability results using up to 28,672 parallel tasks for problems with up to 1.6 billion unknowns and a viscosity contrast up to ten orders of magnitude. Comment: 27 pages, 6 figures |
نوع الوثيقة: | Working Paper |
URL الوصول: | http://arxiv.org/abs/2107.00820 |
رقم الأكسشن: | edsarx.2107.00820 |
قاعدة البيانات: | arXiv |
الوصف غير متاح. |