Numerical simulation of the effects of obstacle deflectors on the aerodynamic performance of stationary high-speed trains at two yaw angles

Abstract

In this study, based on the shear-stress transport-! turbulent model, the improved delayed detached eddy simulation method has been used to simulate the unsteady aerodynamic performance of trains with different obstacle deflectors at two yaw angles (0 and 15). The numerical algorithm is used and some of the numerical results are verified through wind tunnel tests. By comparing and analysing the obtained results, the effects of the obstacle deflectors on the force of the trains as well as the pressure and flow structure around the trains are elucidated. The results show that the obstacle deflectors primarily affect the flow field at the bottom of the head car as well as the wake flow, and that the internal oblique-type obstacle deflector (IOOD) markedly improves the aerodynamic performance of the trains, by decreasing most of the aerodynamic forces of the train cars and minimising their fluctuations. Further, a nonzero yaw angle weakens or even changes the effect of the IOOD on the aerodynamic forces of the train cars. However, the effect of the IOOD is more on the tail car.

Effect of Two Bogie Cavity Configurations on the Underbody Flow and Near Wake Structures of a High-Speed Train

“…Clearly, the train is surrounded by massive vortices, in particular for the head, inter-carriage gaps, bogie regions and the near wake, similar to what has been found in Huang et al (2016), Zhang et al (2016 and2018a) and Niu et al (2017). There are fewer vortices around the upper body of the train as compared to the lower regions close to the ballast and ground, where the complex geometry of the bogies generates strong vortices that rapidly become chaotic, leading to regions of high turbulence at the bottom of the train.…”

“…DES (detached eddy simulation) is a representative hybrid RANS-LES method that was originally proposed by Spalart et al (1997). With fast development in turbulence model, the DES is becoming a promising method in modelling separated flows at high Reynolds numbers, showing a good prediction in the external flow around ground transport vehicles (Favre and Efraimsson, 2011;Guilmineau et al, 2013;Flynn et al, 2014;Morden et al, 2015;Huang et al, 2016;Niu et al, 2017;Zhu et al, 2017;Zhang et al, 2016Zhang et al, , 2017Zhang et al, and 2018a.…”

“…Its pre-processing package SnappyHexMesh provides an efficient and fast method to build the mesh automatically and allows most of cells to locate in the regions close to the train body. Due to those advantages, this grid generation strategy has been widely used in simulating the external flow fields around trains (Flynn et al, 2014;Zhang et al, 2016Zhang et al, , 2017Zhang et al, and 2018aNiu et al, 2017;Morden et al, 2015). Before determined which grid is suitable for the simulations, a grid-independence test should be conducted in the beginning.…”

“…The previous studies (Zhang et al, 2016 and2018a;Niu et al, 2017) have shown that the bottom configuration has little effect on the upper surface pressure of the train, so only the pressure profiles on the train bottom in the vertical midplane are analysed, as shown in Fig. 10.…”

“…Zheng et al (2011) studied the effect of train's bottom shape on the aerodynamic drag of a high-speed train at a speed of 400 km/h, and found the train bottom shape can influence the drag distribution on the entire train, especially on the bottom. Niu et al (2017) conducted simulations using improved delayed detached eddy simulation (IDDES) to understand the obstacle deflectors' effect on the aerodynamic forces of high-speed trains at 0° and 15° yaw angles. They also showed the underneath configurations cause the change of flow structures underneath the train head and in the wake.…”