摘要
随着高速列车运行速度的不断提高,隧道出口的微气压波噪声污染问题愈发严重。高速列车穿越隧道速度增大到350 km·h^(-1)时近隧道区域形成较强的非线性声源区,其非线性随着高速列车穿越隧道的速度增大而增强。传统CFD方法计算效率较低,难以精确模拟此类现象,且用线性微气压波预测模型误差较大。针对该问题,根据现有线性微气压波预测模型,结合高阶谱差分计算气动声学模型与完全匹配层人工边界,构建非线性范畴的隧道微气压波预测模型,并与实验结果进行对比,论证该模型的准确性。结果表明:在200 km·h^(-1)、250 km·h^(-1)、300 km·h^(-1)、350 km·h^(-1)速度级下,微气压波声压峰值分别与隧道轴向距离r^(-0.87)、r^(-0.86)、r^(-0.85)、r^(-0.83)成正比。
With the continuous increase of the running speed of high-speed trains,the noise pollution problem of the micro-pressure wave at the exit of the tunnel has become more and more serious.When the speed of the high-speed train passing through the tunnel increases to 350km·h^(-1),a strong non-linear sound source area is formed near the tunnel,and its non-linearity increases as the speed of the high-speed train passing through the tunnel increases.Having low computational efficiency,the traditional CFD method is difficult to accurately simulate such phenomena,and the prediction error of the linear micro-pressure wave prediction model is relatively large.To solve this problem,based on the existing linear micro-pressure wave prediction model,this paper combines the high-order spectral difference calculation aeroacoustic model and the fully matched layer artificial boundary to construct a tunnel micro-pressure wave prediction model in the nonlinear category,and compares it with the experimental results to demonstrate the accuracy of the model.The research result shows that for 200 km·h^(-1),250 km·h^(-1),300 km·h^(-1)and 350 km·h^(-1)speed levels,the peak sound pressure of the micro-pressure wave is proportional to the axial distance of the tunnel r^(-0.87),r^(-0.86),r^(-0.85) and r^(-0.83),respectively.
作者
韦斌
唐飞
谭晓明
WEI Bin;TANG Fei;TAN Xiaoming(School of Automotive and Transportation Engineering,Hefei University of Technology,Hefei 230009,China;China Aerodynamics Research and Development Center,Key Laboratory of Pneumatic Noise Control,Mianyang 621000,China;College of Mechanical Engineering,Hunan Institute of Science and Technology,Yueyang 414006,China)
出处
《交通科技与经济》
2022年第4期55-60,共6页
Technology & Economy in Areas of Communications
基金
气动噪声控制重点实验室研究基金项目(ANCL20200302)
中央高校基本科研业务费专项基金项目(JZ2020HGQA0213)。
关键词
微气压波
高阶谱差分
非线性
计算气动声学
隧道轴向距离
micro-pressure wave
high-order spectrum difference
non-linear
computational aeroacoustics
tunnel axial distance
