Advanced Transportation Equipment

Effect of RANS Turbulence Model on Aerodynamic Behavior of Trains in Crosswind

  • Tian Li ,
  • Deng Qin ,
  • Jiye Zhang
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  • State Key Laboratory of Traction Power, Southwest Jiaotong University, Chengdu 610031, China

收稿日期: 2018-09-22

  修回日期: 2019-10-13

  网络出版日期: 2019-12-25

基金资助

Supported by National Natural Science Foundation of China (Grant No. 51605397), Sichuan Provincial Science and Technology Program of China (Grant No. 2019YJ0227), and Self-determined Project of State Key Laboratory of Traction Power (Grant No. 2019TPL_T02)

Effect of RANS Turbulence Model on Aerodynamic Behavior of Trains in Crosswind

  • Tian Li ,
  • Deng Qin ,
  • Jiye Zhang
Expand
  • State Key Laboratory of Traction Power, Southwest Jiaotong University, Chengdu 610031, China

Received date: 2018-09-22

  Revised date: 2019-10-13

  Online published: 2019-12-25

Supported by

Supported by National Natural Science Foundation of China (Grant No. 51605397), Sichuan Provincial Science and Technology Program of China (Grant No. 2019YJ0227), and Self-determined Project of State Key Laboratory of Traction Power (Grant No. 2019TPL_T02)

摘要

The numerical simulation based on Reynolds time-averaged equation is one of the approved methods to evaluate the aerodynamic performance of trains in crosswind. However, there are several turbulence models, trains may present different aerodynamic performances in crosswind using different turbulence models. In order to select the most suitable turbulence model, the inter-city express 2 (ICE2) model is chosen as a research object, 6 different turbulence models are used to simulate the flow characteristics, surface pressure and aerodynamic forces of the train in crosswind, respectively. 6 turbulence models are the standard k-ε, Renormalization Group (RNG) k-ε, Realizable k-ε, Shear Stress Transport (SST) k-ω, standard k-ω and Spalart–Allmaras (SPA), respectively. The numerical results and the wind tunnel experimental data are compared. The results show that the most accurate model for predicting the surface pressure of the train is SST k-ω, followed by Realizable k-ε. Compared with the experimental result, the error of the side force coefficient obtained by SST k-ω and Realizable k-ε turbulence model is less than 1 %. The most accurate prediction for the lift force coefficient is achieved by SST k-ω, followed by RNG k-ε. By comparing 6 different turbulence models, the SST k-ω model is most suitable for the numerical simulation of the aerodynamic behavior of trains in crosswind.

本文引用格式

Tian Li , Deng Qin , Jiye Zhang . Effect of RANS Turbulence Model on Aerodynamic Behavior of Trains in Crosswind[J]. Chinese Journal of Mechanical Engineering, 2019 , 32(5) : 85 -85 . DOI: 10.1186/s10033-019-0402-2

Abstract

The numerical simulation based on Reynolds time-averaged equation is one of the approved methods to evaluate the aerodynamic performance of trains in crosswind. However, there are several turbulence models, trains may present different aerodynamic performances in crosswind using different turbulence models. In order to select the most suitable turbulence model, the inter-city express 2 (ICE2) model is chosen as a research object, 6 different turbulence models are used to simulate the flow characteristics, surface pressure and aerodynamic forces of the train in crosswind, respectively. 6 turbulence models are the standard k-ε, Renormalization Group (RNG) k-ε, Realizable k-ε, Shear Stress Transport (SST) k-ω, standard k-ω and Spalart–Allmaras (SPA), respectively. The numerical results and the wind tunnel experimental data are compared. The results show that the most accurate model for predicting the surface pressure of the train is SST k-ω, followed by Realizable k-ε. Compared with the experimental result, the error of the side force coefficient obtained by SST k-ω and Realizable k-ε turbulence model is less than 1 %. The most accurate prediction for the lift force coefficient is achieved by SST k-ω, followed by RNG k-ε. By comparing 6 different turbulence models, the SST k-ω model is most suitable for the numerical simulation of the aerodynamic behavior of trains in crosswind.

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