A method of fundamental solutions for large-scale 3D elastance and mobility problems

IF 2.1 3区 数学 Q2 MATHEMATICS, APPLIED
Anna Broms, Alex H. Barnett, Anna-Karin Tornberg
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引用次数: 0

Abstract

The method of fundamental solutions (MFS) is known to be effective for solving 3D Laplace and Stokes Dirichlet boundary value problems in the exterior of a large collection of simple smooth objects. Here, we present new scalable MFS formulations for the corresponding elastance and mobility problems. The elastance problem computes the potentials of conductors with given net charges, while the mobility problem—crucial to rheology and complex fluid applications—computes rigid body velocities given net forces and torques on the particles. The key idea is orthogonal projection of the net charge (or forces and torques) in a rectangular variant of a “completion flow.” The proposal is compatible with one-body preconditioning, resulting in well-conditioned square linear systems amenable to fast multipole accelerated iterative solution, thus a cost linear in the particle number. For large suspensions with moderate lubrication forces, MFS sources on inner proxy-surfaces give accuracy on par with a well-resolved boundary integral formulation. Our several numerical tests include a suspension of 10,000 nearby ellipsoids, using \(2.6\times 10^7\) total preconditioned degrees of freedom, where GMRES converges to five digits of accuracy in under two hours on one workstation.

一种大规模三维弹性和流动性问题的基本解方法
基本解方法(MFS)对于求解大量简单光滑物体外部的三维拉普拉斯和斯托克斯狄利克雷边值问题是有效的。在这里,我们提出了新的可扩展的MFS公式,以解决相应的弹性和迁移问题。弹性问题计算给定净电荷时导体的势,而迁移率问题——对流变学和复杂流体应用至关重要——计算给定粒子上的净力和扭矩时的刚体速度。关键思想是净电荷(或力和扭矩)在“完井流”的矩形变体中的正交投影。该方法与单体预处理相兼容,得到了条件良好的平方线性系统,可适应快速多极加速迭代解,因此粒子数的代价为线性。对于具有中等润滑力的大型悬架,内部代理表面上的MFS源提供与良好分辨的边界积分公式相当的精度。我们的几个数值测试包括在10,000个附近的椭球上悬挂,使用\(2.6\times 10^7\)总预置自由度,其中GMRES在一个工作站在两小时内收敛到五位数的精度。
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来源期刊
CiteScore
3.00
自引率
5.90%
发文量
68
审稿时长
3 months
期刊介绍: Advances in Computational Mathematics publishes high quality, accessible and original articles at the forefront of computational and applied mathematics, with a clear potential for impact across the sciences. The journal emphasizes three core areas: approximation theory and computational geometry; numerical analysis, modelling and simulation; imaging, signal processing and data analysis. This journal welcomes papers that are accessible to a broad audience in the mathematical sciences and that show either an advance in computational methodology or a novel scientific application area, or both. Methods papers should rely on rigorous analysis and/or convincing numerical studies.
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