Particle image velocimetry of the underfloor flow for generic high-speed train models in a water towing tank

Author:

Jönsson Mattias1,Wagner Claus1,Loose Sigfried1

Affiliation:

1. Institute of Aerodynamics and Flow Technology, German Aerospace Center, Germany

Abstract

The underfloor flow field of three different 1:50 generic high-speed train models hauled through a water towing tank at a speed of 4 m/s (Reynolds number = 0.24 × 106) over smooth ground, rough ground, and ground with sleepers is measured by means of two-component particle image velocimetry. The reference train model, consisting of four cars, features inter-car gaps and two bogies per car. These features are removed and all gaps are closed to create the smooth train configuration whereas the rough train configuration has all the gaps but no bogies. The lowest underfloor flow velocities and velocity gradients at the ground are observed for the smooth train model on the ground with sleepers. Furthermore, the measurements reveal that any additional irregularity of the underbody leads to regions characterised by flow acceleration in the otherwise Couette-like flow and this increases the possibility of ballast flight. Therefore, it is concluded that a smooth underbody can lower the risk of ballast flight. The results obtained for the reference train model are compared with those of a full-scale measurement. It is shown that the results of the water towing tank experiments with the scaled train model reflect the main characteristics of the underfloor flow of the full-scale measurements.

Publisher

SAGE Publications

Subject

Mechanical Engineering

Cited by 23 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3