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arXiv 2409.02652math.NAcs.NA
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基于增广拉格朗日和全局技术求解离散 Stokes 问题的新方法:在不可压缩流鞍点线性系统中的应用

Novel Approach for solving the discrete Stokes problems based on Augmented Lagrangian and Global Techniques: Application to Saddle-Point Linear Systems from Incompressible flow

A. Badahmane, A. Ratnani, H. Sadok

AI总结:

针对不可压缩 Stokes 离散产生的鞍点线性系统,提出基于全局 Arnoldi 的增广拉格朗日预条件子,并通过谱分析与计算时间数值实验验证其高效性与稳健性。

摘要:

本文提出一种基于全局 Arnoldi 的新型增广拉格朗日预条件子,用于加速应用于具有 3×3 块结构线性方程组的 Krylov 子空间方法的收敛;这类系统通常产生于使用混合有限元方法对 Stokes 方程进行离散化。在实践中,速度的各个分量总是使用单一有限元空间来逼近。更确切地说,在二维情形下,作者的新方法基于标量有限元基函数的标准空间来离散速度空间。可以证明,这种按分量分解会自然产生一种 3×3 块结构。文中对这些预条件子的精确版本建立了谱分析。最后,所得数值结果表明,该新方法在求解离散 Stokes 问题时更高效、更稳健;新方法的效率通过计算时间来评估。

英文摘要:

In this paper, a novel augmented Lagrangian preconditioner based on global Arnoldi for accelerating the convergence of Krylov subspace methods applied to linear systems of equations with a block three-by-three structure, these systems typically arise from discretizing the Stokes equations using mixed-finite element methods. In practice, the components of velocity are always approximated using a single finite element space. More precisely, in two dimensions, our new approach based on standard space of scalar finite element basis functions to discretize the velocity space. This componentwise splitting can be shown to induce a natural block three-by-three structure. Spectral analyses is established for the exact versions of these preconditioners. Finally, the obtained numerical results claim that our novel approach is more efficient and robust for solving the discrete Stokes problems. The efficiency of our new approach is evaluated by measuring computational time.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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