论文标题
基于级别的基于粒子方法的预处理算法
Level-set based pre-processing algorithm for particle-based methods
论文作者
论文摘要
在预处理中获得代表清洁几何形状的高质量颗粒分布对于基于粒子方法的仿真精度至关重要。在本文中，提出了几种基于级别的基于级别的技术，用于自动清理“肮脏”几何形状并产生均匀的粒子分布。首先，采用了基于级别集合场的非分辨结构识别方法来检测在给定分辨率下几何“肮脏”的微小片段。其次，提出了一种重新距离算法，以去除微小的片段并重建清洁和光滑的几何形状。第三，在粒子弛豫过程中发展了“静态限制”边界条件。通过补充对几何表面附近颗粒的内核支持，边界条件在狭窄区域上以高曲率的形式获得了更好的身体构成颗粒分布。几个数值示例包括2D机翼30p30n，3D Sphinxsys符号，带有旗杆的摩天大楼和下腔静脉表明，目前的方法不仅可以有效地清理“脏”几何形状，而且还为复杂的几何形式提供了更好的身体均匀粒子分布。
Obtaining high quality particle distribution representing clean geometry in pre-processing is essential for the simulation accuracy of the particle-based methods. In this paper, several level-set based techniques for cleaning up `dirty' geometries automatically and generating homogeneous particle distributions are presented. First, a non-resolved structure identifying method based on level-set field is employed to detect the tiny fragments which make the geometry `dirty' under a given resolutions. Second, a re-distance algorithm is proposed to remove the tiny fragments and reconstruct clean and smooth geometries. Third, a `static confinement' boundary condition is developed in the particle relaxation process. By complementing the kernel support for the particles near the geometric surface, the boundary condition achieves better body-fitted particle distribution on the narrow region with high curvature. Several numerical examples include a 2D airfoil 30P30N, 3D SPHinXsys symbol, a skyscraper with a flagpole and an inferior vena cava demonstrate that the present method not only cleans up the `dirty' geometries efficiently, but also provides better body-fitted homogeneous particle distribution for complex geometry.
