Dynamic mesh technology based on support vector regression

GAO Xiang; LIAO Haixiang; XU Chuanfu

doi:10.7638/kqdlxxb-2021.0317

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Dynamic mesh technology based on support vector regression

更新时间：2026-05-28

- Dynamic mesh technology based on support vector regression
- Vol. 40, Issue 5, Pages: 146-157(2022)
- 作者机构：
  
  国防科技大学计算机学院，量子信息研究所兼高性能计算国家重点实验室,长沙,410073
- 作者简介：
- 基金信息：
- DOI：10.7638/kqdlxxb-2021.0317
  CLC： V211.3
- Published：2022
- 稿件说明：
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高翔, 廖海翔, 徐传福. 基于支持向量回归的动网格技术研究[J]. 空气动力学学报, 2022, 40(5): 146−157.

GAO Xiang, LIAO Haixiang, XU Chuanfu. Dynamic mesh technology based on support vector regression[J]. 2022, 40(5): 146-157.
高翔, 廖海翔, 徐传福. 基于支持向量回归的动网格技术研究[J]. 空气动力学学报, 2022, 40(5): 146−157. DOI： 10.7638/kqdlxxb-2021.0317

GAO Xiang, LIAO Haixiang, XU Chuanfu. Dynamic mesh technology based on support vector regression[J]. 2022, 40(5): 146-157. DOI： 10.7638/kqdlxxb-2021.0317.

摘要

为了提高动网格生成的计算效率，深入分析了广泛使用的径向基函数插值动网格方法，进一步放宽其贪心选点的约束条件，提出并完善了一种基于支持向量回归的高效动网格技术，并给出了该机器学习算法针对网格运动的适配方案。基于基准案例的三套疏密网格和四类运动形式，对不同径向基核函数的拟合性能进行了全面测试分析。以前期采用的高斯核函数方法为基准，进一步通过典型动网格案例，量化对比了筛选出的核函数在网格变形质量、计算效率和参数设置等方面的能力。结果表明基于CP

和IMQB核函数支持向量回归的动网格方法具有良好的变形能力和计算效率。

Abstract

Dynamic mesh generation is one of the key technologies for solving moving boundary problems. In order to improve the computation efficiency of dynamic mesh generation

the widely used dynamic mesh method based on radial basis functions is analyzed in-depth

and an efficient approach based on support vector regression is proposed to further relax the constraints of the greedy choice of points. Moreover

an adaptation scheme for this machine learning algorithm applying to mesh motion is given. According to three different grids and four types of motions in the benchmark cases

a comprehensive analysis of the fitting performance of different radial basis kernel functions is carried out. Using previous Gaussian kernel based method as the benchmark

the s

elected kernel functions are compared through typical dynamic grid cases

for their performance in mesh deformation quality

computational efficiency and parameter setting. The results show that based on the CP

and IMQB kernel functions

the proposed dynamic mesh method has good deformability and computational efficiency.

关键词

Keywords

references

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