In this paper we propose an accurate, and computationally efficient method for incorporating adaptive spatial resolution into weakly-compressible Smoothed Particle Hydrodynamics (SPH) schemes. Particles are adaptively split and merged in an accurate manner while ensuring that the number of particles is not large for a given resolution. Critically, the method ensures that the number of neighbors of each particle is optimal, leading to an efficient algorithm. A set of background particles is used to specify either geometry-based spatial resolution or solution-based adaptive resolution. This allows us to simulate problems using particles having length variations of the order of 1:250 with much fewer particles than currently reported with other techniques. The method is designed to automatically adapt when any solid bodies move. The algorithms employed are fully parallel. We consider a suite of benchmark problems to demonstrate the accuracy of the approach. We then consider the classic problem of the flow past a circular cylinder at a range of Reynolds numbers and show that the proposed method produces accurate results with a significantly reduced number of particles. We provide an open source implementation and a fully reproducible manuscript.
翻译:在本文中,我们提出了一个精确和计算高效的方法,将适应性空间分辨率纳入低压平流流流体动力学(SPH)系统。粒子是适应性地分割和以精确的方式合并的,同时确保某一分辨率的粒子数量不会很大。关键的是,该方法确保了每个粒子的近邻数量是最佳的,导致一种高效的算法。一组背景粒子被用于指定基于几何的空间分辨率或基于溶液的适应性分辨率。这使我们能够模拟问题,利用粒子的长度变化为1:250,其粒子比目前报告的其他技术要少得多。该方法旨在在任何固体体移动时自动适应。所使用的算法是完全平行的。我们考虑了一系列基准问题,以显示该方法的准确性。我们然后考虑一个圆圆柱子流的典型问题,以一系列的Reynolds数字为基础,并表明拟议的方法产生精确的结果,粒子数量大大减少。我们提供开放源实施和完全复制手稿。