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Aerodynamic scaling of a maglev train: Unsteady flow structures and aerodynamic loads

Taihang Zhu, Guanda Cheng, Xianying Zhang, Jiabin Pang, Jianyue Zhu

2025Physics of Fluids9 citationsDOIOpen Access PDF

Abstract

The high operating speed of the 600 km/h maglev train provides a solution for reducing railway transportation time, while the scaling law of its aerodynamic loads and turbulent flow structures traveling at different speeds up to the compressible flow regime remains to be investigated. In this study, employing improved delayed detached eddy simulation, the aerodynamic properties of a generic three-car-body maglev train operating at 600/400/200 km/h (Ma=0.49/0.33/0.16) are studied and compared. In the near wake region, four kinds of motion are identified, and the corresponding spatial structures and timescale are further analyzed by a combination of the proper orthogonal decomposition and spectral proper orthogonal decomposition, revealing large-scale vortex shedding above the track at StH∼1.2, small scaled helix vortices underneath the track at StH∼0.8, spatial symmetry-breaking modes mainly at StH∼1.6, and secondary vortices beside the track expanding downstream. The bulk of aerodynamic drag originates from skin friction, and the drag coefficient remains constant as the Mach number increases. The lift force is dominated by the pressure difference between the lower and the upper surface, with the lift coefficient exhibiting linear growth with Ma. The compressibilities of the flow indicated by the density field illustrate that a compressible simulation is necessary for accurate prediction at a high speed of 600 km/h. These results provide aerodynamic references for the development of the 600 km/h maglev train and flow control methods.

Topics & Concepts

AerodynamicsMaglevPhysicsMach numberVortexMechanicsVortex sheddingDrag coefficientLift coefficientAerodynamic dragLift (data mining)DragDetached eddy simulationAerospace engineeringCompressible flowCompressibilityParasitic dragTurbulenceEngineeringReynolds-averaged Navier–Stokes equationsReynolds numberQuantum mechanicsData miningComputer scienceAerodynamics and Fluid Dynamics ResearchFluid Dynamics and Vibration AnalysisWind and Air Flow Studies
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