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Modelling the multi-physics of wind-blown sand impacts on high-speed train

  • Zhang, Yani (National Innovation Centre of High-speed Train) ;
  • Jiang, Chen (Key Laboratory of Traffic Safety on Track of Ministry of Education, School of Traffic & Transportation Engineering, Central South University) ;
  • Zhan, Xuhe (National Innovation Centre of High-speed Train)
  • Received : 2020.07.21
  • Accepted : 2021.04.26
  • Published : 2021.05.25

Abstract

The wind-blown sand effect on the high-speed train is investigated. Unsteady RANS equation and the SST k-ω turbulent model coupled with the discrete phase model (DPM) are utilized to simulate the two-phase of air-sand. Sand impact force is calculated based on the Hertzian impact theory. The different cases, including various wind velocity, train speed, sand particle diameter, were simulated. The train's flow field characteristics and the sand impact force were analyzed. The results show that the sand environment makes the pressure increase under different wind velocity and train speed situations. Sand impact force increases with the increasing train speed and sand particle diameter under the same particle mass flow rate. The train aerodynamic force connected with sand impact force when the train running in the wind-sand environment were compared with the aerodynamic force when the train running in the pure wind environment. The results show that the head car longitudinal force increase with wind speed increasing. When the crosswind speed is larger than 35m/s, the effect of the wind- sand environment on the train increases obviously. The longitudinal force of head car increases 23% and lateral force of tail increases 12% comparing to the pure wind environment. The sand concentration in air is the most important factor which influences the sand impact force on the train.

Keywords

Acknowledgement

Authors appreciate the supports from, National Key Research and Development Program of China (Grant No.2020YFA0710901), National Natural Science Foundation of China (Grant No. 1202395), Science Foundation of Hunan Province (Grant No. 2019JJ50790), and Start-up funding of Central South University of China.

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