Stability and Accuracy of a Meshless Finite Difference Method for the Stokes Equations

IF 2.7 3区 工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY
Alexander Westermann, Oleg Davydov, Andriy Sokolov, Stefan Turek
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引用次数: 0

Abstract

We study the behavior of the meshless finite difference method based on radial basis functions applied to the stationary incompressible Stokes equations in two spatial dimensions, with the velocity and the pressure discretized on their own node sets. We demonstrate that the main condition for the stability of the numerical solution is that the distribution of the pressure nodes has to be coarser than that of the velocity both globally and locally in the domain, and there is no need for any more complex assumptions similar to the Ladyzhenskaya-Babuška-Brezzi condition in the finite element method. Optimal stability is achieved when the relative local density of the velocity to pressure nodes is about 4:1. The convergence rates of the method correspond to the convergence rates of numerical differentiation for both low and higher order discretizations. The method works well on both mesh-based and irregular nodes, such as those generated by random or quasi-random numbers and on nodes with varying density. There is no need for special staggered arrangements, which suggests that node generation algorithms may produce just one node set and obtain the other by either refinement or coarsening. Numerical results for the benchmark Driven Cavity Problem confirm the robustness and high accuracy of the method, in particular resolving a cascade of multiple Moffatt Eddies at the tip of the wedge by using nodes obtained from the quasi-random Halton sequence.

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斯托克斯方程无网格有限差分法的稳定性和准确性
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来源期刊
CiteScore
5.70
自引率
6.90%
发文量
276
审稿时长
5.3 months
期刊介绍: The International Journal for Numerical Methods in Engineering publishes original papers describing significant, novel developments in numerical methods that are applicable to engineering problems. The Journal is known for welcoming contributions in a wide range of areas in computational engineering, including computational issues in model reduction, uncertainty quantification, verification and validation, inverse analysis and stochastic methods, optimisation, element technology, solution techniques and parallel computing, damage and fracture, mechanics at micro and nano-scales, low-speed fluid dynamics, fluid-structure interaction, electromagnetics, coupled diffusion phenomena, and error estimation and mesh generation. It is emphasized that this is by no means an exhaustive list, and particularly papers on multi-scale, multi-physics or multi-disciplinary problems, and on new, emerging topics are welcome.
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