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arXiv 1609.04484math.NAcs.NA
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用于多孔介质中二维斯托克斯流快速模拟的高效预条件子

An efficient preconditioner for the fast simulation of a 2D Stokes flow in porous media

Pieter Coulier, Bryan Quaife, Eric Darve

AI总结:

本文提出一种基于H²矩阵的快速近似直接求解器作为GMRES的预条件子,以高效求解多孔介质中二维斯托克斯方程的边界积分方程。

摘要:

我们考虑了用于多孔介质中二维斯托克斯方程边界积分方程(BIE)的高效预条件子。尽管BIE适合解决复杂的多孔几何结构,但会导致稠密线性方程组,对于大问题计算成本很高。当迭代Krylov求解器如GMRES需要大量迭代时,这种成本进一步增加。在本文中,我们应用快速不精确直接求解器,即逆快速多极子方法(IFMM),作为GMRES的高效预条件子。该求解器基于H²矩阵框架,并利用低秩压缩来近似某些矩阵块。它具有可调精度ε和计算成本为O(N log² 1/ε)。我们讨论了各种数值基准,验证了所提方法的准确性和效率。我们通过几种边界条件展示了预条件子在与简单块对角预条件子相比时,能显著加速GMRES的收敛,特别是对于涉及许多孔隙的管道流问题。

英文摘要:

We consider an efficient preconditioner for boundary integral equation (BIE) formulations of the two-dimensional Stokes equations in porous media. While BIEs are well-suited for resolving the complex porous geometry, they lead to a dense linear system of equations that is computationally expensive to solve for large problems. This expense is further amplified when a significant number of iterations is required in an iterative Krylov solver such as GMRES. In this paper, we apply a fast inexact direct solver, the inverse fast multipole method (IFMM), as an efficient preconditioner for GMRES. This solver is based on the framework of $\mathcal{H}^{2}$-matrices and uses low-rank compressions to approximate certain matrix blocks. It has a tunable accuracy $\varepsilon$ and a computational cost that scales as $\mathcal{O} (N \log^2 1/\varepsilon)$. We discuss various numerical benchmarks that validate the accuracy and confirm the efficiency of the proposed method. We demonstrate with several types of boundary conditions that the preconditioner is capable of significantly accelerating the convergence of GMRES when compared to a simple block-diagonal preconditioner, especially for pipe flow problems involving many pores.

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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