Numerical Analysis of Aerodynamic Resistance for High-Speed Trains Passing Through the Most Unfavorable Tunnel

WEI Mengjie; LIU Feng; DI Juan; YANG Sihan; MA Jianbin; CHEN Dawei

doi:10.7652/xjtuxb202401016

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Numerical Analysis of Aerodynamic Resistance for High-Speed Trains Passing Through the Most Unfavorable Tunnel

更新时间：2025-05-13

- Numerical Analysis of Aerodynamic Resistance for High-Speed Trains Passing Through the Most Unfavorable Tunnel
- Vol. 58, Issue 1, Pages: 167-177(2024)
- 作者机构：
  
  1. 太原理工大学机械与运载工程学院,太原,030024
  2. 中车青岛四方机车车辆股份有限公司,山东,青岛,266111
  3. 太原科技大学车辆与交通工程学院,太原,030024
- 作者简介：
- 基金信息：
- DOI：10.7652/xjtuxb202401016
  CLC： U260
- Online First：10 January 2024，
  
  Published：2024
- 稿件说明：
移动端阅览
WEI Mengjie, LIU Feng, DI Juan, et al. Numerical Analysis of Aerodynamic Resistance for High-Speed Trains Passing Through the Most Unfavorable Tunnel[J]. 2024, 58(1): 167-177.
DOI：

WEI Mengjie, LIU Feng, DI Juan, et al. Numerical Analysis of Aerodynamic Resistance for High-Speed Trains Passing Through the Most Unfavorable Tunnel[J]. 2024, 58(1): 167-177. DOI： 10.7652/xjtuxb202401016.

摘要

为了探明高速列车与最不利长度隧道耦合作用下列车气动阻力变化规律

以某动车组为计算模型

基于滑移网格技术和计算流体动力学(CFD)理论

采用k-ε两方程湍流模型对最不利隧道内8辆编组单车穿越和双车等速交会时的气动效应进行了三维数值模拟

并结合遂渝线上二岩隧道实测数据对计算方法的可靠性进行了验证。结果表明:①列车所受气动阻力变化与列车头尾部的压差变化有直接关系

压差的升高和降低会引起阻力的增大和减小。②在隧道内以时速300 km单车穿越和双车交会过程中

整车最大气动阻力分别发生在列车入隧道后3.1 s和2.8 s时刻

阻力系数分别达到1.37和1.49

且此时头车阻力在整车中占比最大

分别为34.67%和36.57%。③当列车头头交会和头尾交会时

尾车阻力占比最大

分别为56.79%和37.33%; 当列车尾尾交会时

头车阻力占比最大

为44.62%

而尾车阻力此时接近为0。④列车行驶速度提高会引起气动阻力迅速增大

当列车时速从250 km提升至400 km时

隧道内单车穿越和双车交会整车气动阻力平均值分别增大了132%和150%。研究结果可为车隧设计提供一定的参考。

Abstract

This study aims to analyze the variation in aerodynamic resistance of high-speed trains under the combined effect of train movement and unfavorable tunnel conditions. An EMU(electric multiple units)is chosen as the calculation model to investigate the aerodynamic effects using sliding grid technology and computational dynamics theory(CFD). The k-ε two-equation turbulence model is employed to simulate the aerodynamic behavior of eight different train configurations crossing and intersecting within the most unfavorable tunnel. The proposed calculation method is validated by comparing it with the measured data of the Eryan tunnel on Suiyu line. The findings reveal several important insights: ①The aerodynamic resistance experienced by the train is directly influenced by the pressure difference between the train's head and tail. Changes in this pressure difference will cause corresponding variations in resistance. ②During single-train crossings and double-train intersections at 300 km/h in the tunnel

the maximum aerodynamic resistance occurs at 3.1 s and 2.8 s after the train enters the tunnel respectively. The resistance coefficients reach 1.37 and 1.49

and the head train contributes the largest proportion of resistance

accounting for 34.67% and 36.57% respectively. ③In head-head and head-tail intersections

the resistance exerted by the tail of train is the highest

comprising 56.79% and 37.33%

respectively. Conversely

in tail-tail intersections

the head of the train experiences the most significant resistance(44.62%)

while the tail's resistance ratio is close to 0. ④As the train's speed increases

the aerodynamic resistance rises rapidly. For instance

when the train speed increases from 250 km/h to 400 km/h

the average aerodynamic resistance for single-train crossings and double-train intersections increases by 132% and 150%

respectively. These research outcomes offer valuable insights for the design and engineering considerations involved in train-tunnel configurations.

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