动态大气环境下高速飞行器气动噪声不确定性量化研究

郑伶华1,2,陈强1,2,李彦斌1,2,方芳3,费庆国1,2

振动与冲击 ›› 2023, Vol. 42 ›› Issue (14) : 306-313.

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PDF(1637 KB)
振动与冲击 ›› 2023, Vol. 42 ›› Issue (14) : 306-313.
论文

动态大气环境下高速飞行器气动噪声不确定性量化研究

  • 郑伶华1,2,陈强1,2,李彦斌1,2,方芳3,费庆国1,2
作者信息 +

Uncertainty quantification for the aerodynamic noise of high-speed aircrafts in dynamic atmospheric environment

  • ZHENG Linghua1,2, CHEN Qiang1,2, LI Yanbin1,2,FANG Fang3, FEI Qingguo1,2
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摘要

临近空间内大气参数的动态变化会导致高速飞行器气动噪声具有显著的不确定性特征,准确量化气动噪声不确定性特征对飞行器结构设计具有重要意义。本文针对高速飞行器机翼结构,首先通过本征正交分解和代理模型技术建立气动噪声的降阶分析模型,提升气动噪声的分析效率;然后,基于降阶分析模型和大气参数的随机分布特性,高效量化动态大气环境下高速飞行器气动噪声的不确定性特征;最后,通过敏感性分析研究大气参数对气动噪声的影响程度。研究结果表明:本文所构建的降阶模型具有较高的分析效率和预示精度,能够准确高效地量化动态大气环境下飞行器气动噪声的不确定性特征;大气参数和气动噪声之间存在非线性关系,激波及激波后边界层分离非线性是造成气动噪声剧烈波动的重要原因;大气密度变化对气动噪声不确定度贡献较大。

Abstract

Due to the dynamic variation of atmospheric parameters in near space, the aerodynamic noise of high-speed aircrafts presents significant uncertain characteristics, which is useful for structural design. In this paper, a typical wing of high-speed aircraft is taken as research model. First, the reduced order model for aerodynamic noise prediction is established, by using proper orthogonal decomposition and surrogate model, to improve the aerodynamic noise analysis efficiency. Then, based on the reduced order model and random distribution characteristics of the atmospheric parameters, the aerodynamic noise uncertainty characteristics are efficiently quantified. Finally, the influence of atmospheric parameters on aerodynamic noise is studied by sensitivity analysis. Results show that the uncertainty characteristics of aerodynamic noise could be accurately and efficiently quantified using the reduced order model. A nonlinear relationship between the atmospheric parameters and the aerodynamic noise can be observed. Shock wave and boundary layer separation behind shock wave are the important reasons for the aerodynamic noise violent fluctuation. The density variation contributes greatly to the uncertainty of aerodynamic noise.

关键词

动态大气环境 / 气动噪声 / 模型降阶 / 神经网络 / 敏感性分析

Key words

dynamic atmosphere / aerodynamic noise / reduced order model / neural network / sensitivity analysis

引用本文

导出引用
郑伶华1,2,陈强1,2,李彦斌1,2,方芳3,费庆国1,2. 动态大气环境下高速飞行器气动噪声不确定性量化研究[J]. 振动与冲击, 2023, 42(14): 306-313
ZHENG Linghua1,2, CHEN Qiang1,2, LI Yanbin1,2,FANG Fang3, FEI Qingguo1,2 . Uncertainty quantification for the aerodynamic noise of high-speed aircrafts in dynamic atmospheric environment[J]. Journal of Vibration and Shock, 2023, 42(14): 306-313

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