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浙江大学学报(工学版)  2026, Vol. 60 Issue (11): 2523-2534    DOI: 10.3785/j.issn.1008-973X.2026.11.021
土木工程、交通工程     
超高速列车隧道气动效应的主动吹/吸气控制策略
李文辉1(),刘忠健1,陆志康2,顾轶凡1,丁芃芃1
1. 苏州大学 轨道交通学院,江苏 苏州 215131
2. 中国科学院大学 渗流流体力学研究所,河北 廊坊 065007
Active blowing/suction control strategy for mitigating aerodynamic effects of ultra-high-speed trains in tunnels
Wenhui LI1(),Zhongjian LIU1,Zhikang LU2,Yifan GU1,Pengpeng DING1
1. School of Rail Transportation, Soochow University, Suzhou 215131, China
2. Institute of Porous Flow and Fluid Mechanics, University of Chinese Academy of Sciences, Langfang 065007, China
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摘要:

为了缓解超高速列车进入隧道时引起的空气动力学效应,提出基于车载吹/吸气的主动流动控制策略. 采用三维、可压缩和非定常雷诺时均纳维-斯托克斯(URANS)数值计算模型,分析前吸后吹、单独前吸和单独后吹3种模式及不同狭缝面积条件下的车隧气动响应规律(压力波和气动载荷). 结果表明:前吸后吹协同控制模式可显著削弱列车表面与隧道壁面瞬变压力,压力峰峰值平均降幅达18%,优于单一控制模式;前吸控制通过削弱车前压缩波及正压区,有效降低初始压力梯度;后吹控制缓解尾部膨胀波及负压区,对尾流稳定性改善明显;吹/吸狭缝面积与压力峰峰值控制效果呈近似线性衰减关系,当狭缝面积为4 m2时,列车与隧道最大压差峰值分别降低16.6%和17.4%. 所提策略通过同步削弱车头压缩波和车尾膨胀波,降低了列车表面压力波动、隧道壁面压力波动及车体气动载荷;增大狭缝面积可进一步增强压力波削弱效果.

关键词: 超高速列车;  铁路隧道;  主动流动控制;  隧道压力波;  气动载荷    
Abstract:

An active flow control strategy based on onboard blowing and suction was proposed to mitigate the aerodynamic effects induced by ultra-high-speed trains entering tunnels. A three-dimensional, compressible, and unsteady Reynolds-averaged Navier-Stokes (URANS) numerical model was established to analyze train-tunnel aerodynamic responses, including pressure waves and aerodynamic loads, under three control modes (front suction with rear blowing, front suction only, and rear blowing only) and different slit areas. Results demonstrate that the combined front suction and rear blowing mode significantly attenuates pressure fluctuations on both the train surface and tunnel wall, with an average peak-to-peak pressure reduction of 18%, outperforming the single modes. Specifically, front suction weakens the head compression wave and suppresses the positive pressure region ahead of the train, thereby effectively reducing the initial pressure gradient. Meanwhile, rear blowing alleviates the tail expansion wave and negative-pressure region, which helps improve flow stability. The peak-to-peak pressure control effect exhibits an approximately linear decay relationship with the blowing/suction slit area: when the slit area is 4 m2, the maximum pressure difference peak-to-peak values on the train and tunnel are reduced by about 16.6% and 17.4%, respectively. The proposed strategy simultaneously weakens the compression wave generated at the train head and the expansion wave generated at the train tail, thereby reducing pressure fluctuations on the train surface and tunnel wall as well as aerodynamic loads on the train body. Moreover, increasing the slit area can further enhance the attenuation of pressure waves.

Key words: ultra-high-speed train    railway tunnel    active flow control    tunnel pressure wave    aerodynamic loads
收稿日期: 2025-09-03 出版日期: 2026-10-16
CLC:  U 25  
基金资助: 江苏省自然科学基金资助项目(BK20240810);江苏省高校面上项目(24KJB580013).
作者简介: 李文辉(1992—),男,讲师,博士,从事轨道交通空气动力学研究. orcid.org/0000-0002-9747-3941. E-mail:lwh@suda.edu.cn
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引用本文:

李文辉,刘忠健,陆志康,顾轶凡,丁芃芃. 超高速列车隧道气动效应的主动吹/吸气控制策略[J]. 浙江大学学报(工学版), 2026, 60(11): 2523-2534.

Wenhui LI,Zhongjian LIU,Zhikang LU,Yifan GU,Pengpeng DING. Active blowing/suction control strategy for mitigating aerodynamic effects of ultra-high-speed trains in tunnels. Journal of ZheJiang University (Engineering Science), 2026, 60(11): 2523-2534.

链接本文:

https://www.zjujournals.com/eng/CN/10.3785/j.issn.1008-973X.2026.11.021    或    https://www.zjujournals.com/eng/CN/Y2026/V60/I11/2523

图 1  车-隧耦合系统几何模型
图 2  列车表面及隧道壁面测点布置
图 3  计算区域与边界条件
图 4  车-隧耦合气动效应的网格分布
参数数值
粗网格中网格细网格
列车表面/m0.040.020.01
隧道轴向区域/m1.00.50.2
隧道径向区域/m0.40.20.1
外部轴向区域/m1.20.80.4
单元数量/1069.617.929.8
隧道内压力相对误差εp/%2.91.2—
表 1  不同网格密度下列车-隧计算域网格尺寸
图 5  不同网格密度下隧道内压力时程曲线
图 6  列车通过隧道时隧道壁面测点压力时程曲线
图 7  不同吹/吸速度下隧道瞬变压力响应
图 8  不同控制模式下列车表面压力时程曲线
图 9  列车表面与隧道壁面不同测点处压力峰峰值
图 10  头车气动载荷时程演化特性
图 11  不同车厢气动载荷对比
图 12  不同狭缝面积下压力峰值分布
图 13  隧道中点壁面压力时程曲线及对应马赫图
图 14  车头和车尾进入隧道时的压力与流线分布
图 15  列车完全在隧道内运行时的压力与流线分布
图 16  隧道和列车不同测点处压力时程曲线
图 17  列车驶入隧道时流线型车鼻部截面瞬态流线和压力云图
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