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基于半模型的高速列车远场气动噪声计算方法

李田 秦登 张继业 张卫华

李田, 秦登, 张继业, 张卫华. 基于半模型的高速列车远场气动噪声计算方法[J]. 西南交通大学学报, 2023, 58(2): 272-279, 286. doi: 10.3969/j.issn.0258-2724.20210678
引用本文: 李田, 秦登, 张继业, 张卫华. 基于半模型的高速列车远场气动噪声计算方法[J]. 西南交通大学学报, 2023, 58(2): 272-279, 286. doi: 10.3969/j.issn.0258-2724.20210678
LI Tian, QIN Deng, ZHANG Jiye, ZHANG Weihua. Numerical Approach for Far-Field Aerodynamic Noise of High-Speed Trains Based on Half Model[J]. Journal of Southwest Jiaotong University, 2023, 58(2): 272-279, 286. doi: 10.3969/j.issn.0258-2724.20210678
Citation: LI Tian, QIN Deng, ZHANG Jiye, ZHANG Weihua. Numerical Approach for Far-Field Aerodynamic Noise of High-Speed Trains Based on Half Model[J]. Journal of Southwest Jiaotong University, 2023, 58(2): 272-279, 286. doi: 10.3969/j.issn.0258-2724.20210678

基于半模型的高速列车远场气动噪声计算方法

doi: 10.3969/j.issn.0258-2724.20210678
基金项目: 国家重点研发计划(2020YFA0710902);国家自然科学基金(12172308);四川省科技计划(2023JDRC0062)
详细信息
    通讯作者:

    李田(1984—),男,副研究员,研究方向为列车空气动力学,E-mail:litian2008@swjtu.edu.cn

  • 中图分类号: U266.2;TB533.2

Numerical Approach for Far-Field Aerodynamic Noise of High-Speed Trains Based on Half Model

  • 摘要:

    随着高速列车运行速度的提高,其气动噪声问题逐渐凸显,如何准确快速预测高速列车的远场气动噪声成为关键. 利用半自由空间的Green函数求解FW-H方程,推导了考虑半模型时的远场声学积分公式,提出通过半模型的数值计算结果预测全模型高速列车远场气动噪声的方法;建立了全模型和半模型高速列车的气动噪声数值计算模型,应用改进延迟的分离涡模拟方法对不同模型高速列车表面的气动噪声源进行求解;通过风洞试验进行了全模型高速列车的数值仿真计算方法验证;对比分析了全模型和半模型高速列车周围的流场结构、气动噪声源和远场气动噪声特性. 结果表明:半模型高速列车数值计算得到的列车周围流场结构、气动噪声源以及远场气动噪声特性与全模型的一致;采用半模型计算会过高估计列车尾车流线型区域表面压力的波动程度和噪声源的辐射强度,但通过半模型预测整车模型的远场噪声平均声压级误差小于1 dBA;相比于全模型高速列车,半模型计算时的网格总量减少一半.

     

  • 图 1  列车模型

    Figure 1.  Train model

    图 2  计算区域

    Figure 2.  Computation domain

    图 3  计算网格

    Figure 3.  Computation mesh

    图 4  列车表面y + 分布

    Figure 4.  y + distribution on train surface

    图 5  远场噪声测点位置

    Figure 5.  Far-field noise measurement point location

    图 6  风洞试验

    Figure 6.  Wind tunnel test

    图 7  数值仿真与试验结果对比

    Figure 7.  Comparison of results between numerical simulation and experiment

    图 8  尾流区域涡结构分布

    Figure 8.  Vortex structure distribution in wake

    图 9  不同截面处的时均流向涡量分量ωx

    Figure 9.  Time-averaged streamwise vorticity component ωx at different cross-sections

    图 10  列车表面压力测点的时程曲线对比

    Figure 10.  Comparison of time-history curves of train surface pressure measuring points

    图 11  列车表面压力测点的功率谱密度对比

    Figure 11.  Comparison of power spectral density of train surface pressure measuring points

    图 12  列车表面声功率级对比

    Figure 12.  Comparison of sound power levels on the train surface

    图 13  全模型高速列车远场噪声预测

    Figure 13.  Far-field noise prediction of full-model high-speed trains

    表  1  网格独立性验证

    Table  1.   Independence verification for grids

    网格基础
    尺寸/m
    边界层第一
    层高度/mm
    网格
    量/万
    时均气动
    力系数
    误差/%
    12.080.132910.214
    21.920.139440.2192.34
    31.800.146520.2211.84
    41.760.152360.2241.36
    51.600.158780.222−0.89
    下载: 导出CSV

    表  2  表面压力测点对比

    Table  2.   Comparison of surface pressure monitoring points

    测点时均压力系数标准差/× 10−3
    全模型半模型全模型半模型
    P1−0.1019−0.10351.661.77
    P2−0.0487−0.04920.931.37
    下载: 导出CSV

    表  3  远场噪声测点的平均声压级对比

    Table  3.   Comparison of average sound pressure level of far-field noise measurement points

    模型气动噪声源平均声压
    级/dBA
    差值/
    dBA
    全模型整车声源85.76
    半模型半模型声源 + 镜像声源86.640.88
    下载: 导出CSV
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出版历程
  • 收稿日期:  2021-08-24
  • 修回日期:  2021-10-25
  • 网络出版日期:  2022-12-06
  • 刊出日期:  2021-10-27

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