基于OPTICS聚类算法的流场结构特征分析方法

王锐; 辛大波; 欧进萍

doi:10.7638/kqdlxxb-2021.0002

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基于OPTICS聚类算法的流场结构特征分析方法

研究论文 | 更新时间：2026-05-28

- 基于OPTICS聚类算法的流场结构特征分析方法
- A modified OPTICS clustering algorithm for analyzing flow characteristics
- 空气动力学学报 2021年39卷第5期页码：27-43
- 作者机构：
  
  1. 哈尔滨工业大学土木工程学院,哈尔滨,150090
  2. 东北林业大学土木工程学院,哈尔滨,150040
- 作者简介：
  
  王锐（1992-），男，河北人，博士研究生，研究方向：桥梁风工程. E-mail：16B933053@stu.hit.edu.cn
  辛大波*（1978-），男，黑龙江人，教授，博士，研究方向：结构风工程和防灾减灾工程等. E-mail：xindabo@nefu.edu.cn
- 基金信息：
  
  国家重点研发计划重点专项项目（2018YFC0809600，2018YFC0809605）;国家自然科学基金面上项目（51878131）
- DOI：10.7638/kqdlxxb-2021.0002
  中图分类号： O302
- 纸质出版：2021
- 稿件说明：
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王锐, 辛大波, 欧进萍. 基于OPTICS聚类算法的流场结构特征分析方法[J]. 空气动力学学报, 2021, 39(5): 27−43.

WANG Rui, XIN Dabo, OU Jinping. A modified OPTICS clustering algorithm for analyzing flow characteristics[J]. 2021, 39(5): 27-43.
王锐, 辛大波, 欧进萍. 基于OPTICS聚类算法的流场结构特征分析方法[J]. 空气动力学学报, 2021, 39(5): 27−43. DOI： 10.7638/kqdlxxb-2021.0002

WANG Rui, XIN Dabo, OU Jinping. A modified OPTICS clustering algorithm for analyzing flow characteristics[J]. 2021, 39(5): 27-43. DOI： 10.7638/kqdlxxb-2021.0002.

摘要

为了改进现有的基于聚类分析的流场结构特征分析方法，使之更加适用于结构风工程领域的风场特征识别与分析，依托聚类分析的思想，结合一种基于密度的OPTICS聚类算法，并引入相关距离的概念替换了原算法中的欧氏距离，提出了采用一种基于相关距离的OPTICS聚类算法进行流场结构特征分析。实例分析利用基于大涡模拟的计算流体动力学数值模拟，对低雷诺数下经典圆柱绕流问题进行了瞬态求解，获取了2000个圆柱尾流中顺流向涡的瞬态涡量场样本。然后，以识别圆柱尾流中的顺流向涡旋涡脱落状态和顺流向涡A模式展向分布为目标，对比了

-means、原始的OPTICS算法和基于相关距离的OPTICS聚类算法等流场结构特征分析方法。分析实例的结果表明，基于相关距离的OPTICS算法能够在合适的初始参数设置下有效识别顺流向涡脱落状态和其A模式展向分布间距，相对

-means算法降低了对初始参数的敏感度，聚类结果稳定且唯一。

Abstract

Current clustering-based methods still need improvement for the flow features identifying and analysis in the field of wind engineering. Therefore

this paper proposed a modified OPTICS (Ordering Points to Identify the Clustering Structure) algorithm to extract flow features. It is a density-based clustering method with the Euclidean distance replaced by the correlation distance. It is employed to study the streamwise vortex shedding and the spanwise distribution of the A-mode in a low-Reynolds-number circular cylinder wake flow obtained by Large Eddy Simulation. Its performance is further compared with the

-means

and the original OPTICS method. The results indicated that the OPTICS algorithm based on the correlation distance can identify the streamwise vortex shedding and the spanwise distribution of the A-mode effectively with reasonable initial parameters. Compared with the

-means

this method is insensitive to the initialization parameters and its results are consequently more stable and well-determined.

关键词

Keywords

references

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