In this study, we present an $hp$-multigrid preconditioner for a divergence-conforming HDG scheme for the generalized Stokes and the Navier-Stokes equations using an augmented Lagrangian formulation. Our method relies on conforming simplicial meshes in two- and three-dimensions. The $hp$-multigrid algorithm is a multiplicative auxiliary space preconditioner that employs the lowest-order space as the auxiliary space, and we developed a geometric multigrid method as the auxiliary space solver. For the generalized Stokes problem, the crucial ingredient of the geometric multigrid method is the equivalence between the condensed lowest-order divergence-conforming HDG scheme and a Crouzeix-Raviart discretization with a pressure-robust treatment as introduced in Linke and Merdon (Comput. Methods Appl. Mech. Engrg., 311 (2016)), which allows for the direct application of geometric multigrid theory on the Crouzeix-Raviart discretization. The numerical experiments demonstrate the robustness of the proposed $hp$-multigrid preconditioner with respect to mesh size and augmented Lagrangian parameter, with iteration counts insensitivity to polynomial order increase. Inspired by the works by Benzi & Olshanskii (SIAM J. Sci. Comput., 28(6) (2006)) and Farrell et al. (SIAM J. Sci. Comput., 41(5) (2019)), we further test the proposed preconditioner on the divergence-conforming HDG scheme for the Navier-Stokes equations. Numerical experiments show a mild increase in the iteration counts of the preconditioned GMRes solver with the rise in Reynolds number up to $10^3$.
翻译:在此研究中,我们为通用的Stokes 和 Navier-Stokes 方程式展示了一个以$hp$(5)-muldgrid 配制的差异化 HDG 方案,用于使用扩大的Lagranger 配方方。我们的方法依赖于在二和三维二对二和三对立中符合简化的模子。$hp$-mulgrid 算法是一个多倍复制的辅助空间先决条件,将最低级空间用作辅助空间,我们开发了作为辅助空间解算器的几何数多格方法。对于普遍化的Stokes 问题, 几何数多格方法的关键成分是精密的J- Navier-Stokes 方格方程式- Navier- Stokes 方程式的比对等值。我们的方法是:在Linke和Merdondondond(方法Appl. Mech. Engrgrg.) 中直接应用了数解数性多格理论,用于Crouprealalalalalalalalal-revalalalalalal exalalal suder Sqlationalationalational) 和Squaldationaldationaldationaldaldaldal 的比重的比重。</s>