Abstract
Crosswind action on a train poses a risk of vehicle overturning or derailment. To assess if new train designs fulfill the safety requirements, computational fluid dynamics is commonly used. This article presents a comprehensive wind flow analysis on an example of a TGV high-speed train. Large yaw angle range is studied with the application of widely used Reynolds-averaged Navier–Stokes (RANS) turbulence models. The predictive performance of popular RANS-based models in that regime has not been reported extensively before. The context of simulations is a study of crosswind stability using methodology presented in norm EN 14067-6:2018. It is shown that for yaw angles up to 45 degrees, aerodynamic forces predicted by all the studied RANS-based models are consistent with experimental data. At larger yaw angles, flow structure becomes complicated, separation lines are no longer defined by geometry, and significant discrepancies between turbulence models appear, with relative differences between models up to 30%. A detailed study was performed to investigate differences between turbulence models for specific angles of 40, 60, and 80 degrees, which correspond to distinctive ranges of moment characteristics. Finally, a successful attempt was made to tune a GEKO turbulence model to fit the experimental data. This allowed us to reduce the maximum relative error in comparison to the experiment in the full yaw angles range down to 12.7%, which is in line with the norm requirements.
Subject
Energy (miscellaneous),Energy Engineering and Power Technology,Renewable Energy, Sustainability and the Environment,Electrical and Electronic Engineering,Control and Optimization,Engineering (miscellaneous),Building and Construction
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