流体力学与飞行力学

基于DMD方法的缝翼低频噪声机理分析

  • 魏佳云 ,
  • 李伟鹏 ,
  • 许思为 ,
  • 赵克良 ,
  • 孙一峰
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  • 1. 上海交通大学 航空航天学院, 上海 200240;
    2. 中国商飞上海飞机设计研究院 总体气动部, 上海 201315

收稿日期: 2017-06-01

  修回日期: 2017-07-11

  网络出版日期: 2017-07-11

基金资助

国家自然科学基金(11202131,11772194);国家"973"计划(2014CB744802);上海市地面交通工具空气动力学与热环境系统模拟重点实验室基金(VATLAB-2016-02)

Analysis of mechanism of slat low frequency noise based on zonal DMD

  • WEI Jiayun ,
  • LI Weipeng ,
  • XU Siwei ,
  • ZHAO Keliang ,
  • SUN Yifeng
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  • 1. School of Aeronautics and Astronautics, Shanghai Jiao Tong University, Shanghai 200240, China;
    2. Department of Overall Aerodynamics, Shanghai Aircraft Design and Research Institute, Shanghai 201315, China

Received date: 2017-06-01

  Revised date: 2017-07-11

  Online published: 2017-07-11

Supported by

National Natural Science Foundation of China (11202131, 11772194); National Basic Research Program of China (2014CB744802); Foundation of Shanghai Key Laboratory of Vehicle Aerodynamic and Vehicle Thermal Management Systems (VATLAB-2016-02)

摘要

认识缝翼低频噪声的产生机理十分重要,可指导先进的主被动噪声控制方法。本文开展了缝翼噪声的大涡模拟(LES),利用动态模态分解(DMD)方法研究了缝翼低频噪声的产生机理。研究结果表明缝翼低频噪声具有显著的偶极子特性,其利用DMD分析揭示了缝翼噪声的产生机理,缝翼低频噪声源于剪切层中的大尺度涡结构与缝翼下壁面的周期性撞击效应,大尺度涡结构与低频噪声之间存在的流-声耦合的闭环反馈机制,根据反馈机制提出并验证了一种预测低频噪声的理论预测模型。

本文引用格式

魏佳云 , 李伟鹏 , 许思为 , 赵克良 , 孙一峰 . 基于DMD方法的缝翼低频噪声机理分析[J]. 航空学报, 2018 , 39(1) : 121469 -121469 . DOI: 10.7527/S1000-6893.2017.121469

Abstract

It is crucial to know the mechanism of low-frequency noise from the leading-edge slat, which can guide an advanced active and passive control of slat noise. According to the highly reliable Large Eddy Simulation (LES), this paper reveals the mechanism of slat noise using the method of Dynamic Mode Decomposition (DMD). The results indicate that the dipole features of slat noise come from the collision between large scale vortexes in the free shear layer and the lower surface of the slat. There is a close loop feedback mechanism of flow-acoustic coupling existing between large scale vortexes and low-frequency acoustic waves from the reattachment point. Based on this mechanism, a theoretical predictive model is also proposed and verified.

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