Applications of Voronoi Diagram in the Moving Particle Semi-Implicit Method

ZHOU Ziqi; SUN Yijie; SUN Zhongguo; XI Guang

doi:10.7652/xjtuxb202605011

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Applications of Voronoi Diagram in the Moving Particle Semi-Implicit Method

更新时间：2026-04-27

- Applications of Voronoi Diagram in the Moving Particle Semi-Implicit Method
- Journal of Xi'an Jiaotong University Vol. 60, Issue 5, Pages: 111-119(2026)
- 作者机构：
  
  西安交通大学能源与动力工程学院，710049，西安
- 作者简介：
- 基金信息：
- DOI：10.7652/xjtuxb202605011
  CLC： O242;TP301.6
- Received：14 August 2025，
  
  Published：10 May 2026
- 稿件说明：
移动端阅览
ZHOU Ziqi, SUN Yijie, SUN Zhongguo, et al. Applications of Voronoi Diagram in the Moving Particle Semi-Implicit Method[J]. Journal of Xi'an Jiaotong University, 2026, 60(5): 111-119.
DOI：

ZHOU Ziqi, SUN Yijie, SUN Zhongguo, et al. Applications of Voronoi Diagram in the Moving Particle Semi-Implicit Method[J]. Journal of Xi'an Jiaotong University, 2026, 60(5): 111-119. DOI： 10.7652/xjtuxb202605011.

摘要

为了优化移动粒子半隐式法的空间拓扑关系相关算法，将Voronoi图应用于移动粒子半隐式法（MPS）的邻居粒子搜索、表面粒子判定及粒子迁移3个关键环节。通过构建粒子Voronoi图并利用其拓扑关系层级进行邻居粒子搜索；针对表面粒子识别问题，提出了基于Voronoi图单元结构的判别方法；结合Lloyd松弛法与格林-高斯公式，推导出基于Voronoi图的粒子迁移方法。结果表明：相较于传统全配对方法，基于Voronoi图的粒子搜索可使效率提升159倍以上；相较于传统数密度方法，基于Voronoi图的粒子判断方法更准确，计算效率是几何判别法的43.3倍；相较于传统粒子迁移方式，基于Voronoi图的粒子迁移能够有效减小系统扰动，在保持自由液面的光滑性与无重叠特性的同时，计算效率可达6倍以上。综上所述，Voronoi图良好的空间分割特性在移动粒子半隐式法中具有良好的应用前景。

Abstract

To optimize the algorithms for establishing and analyzing spatial topology in the moving particle semi-implicit (MPS) method

the Voronoi diagram to three key components is applied：neighbor particle search

surface particle detection

and particle shifting. The specific approaches are as follows：a particle Voronoi diagram is constructed to facilitate neighbor particle search by leveraging its inherent topological relationships；a novel method based on Voronoi cell structure is proposed to address the challenge of surface particle detection；and a particle shifting scheme derived from the Voronoi diagram is developed by integrating the Lloyd relaxation algorithm with the Green-Gauss formula. The results demonstrate that： the Voronoi-based particle search achieves an efficiency improvement of over 159 times compared to the traditional all-pair search method；the Voronoi-based surface particle detection is more accurate than the conventional particle number density method and computes 43.3 times faster than the geometric method；furthermore

the Voronoi-based particle shifting effectively reduces system disturbance while preserving the smoothness and non-overlapping characteristics of the free surface

also yielding a computational efficiency advantage exceeding 6 times compared to traditional shifting approaches. In conclusion

the proficient spatial partitioning properties of the Voronoi diagram present promising potential for its application within the MPS framework.

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references

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