Coupling effect of urban building clusters and crosswinds on the aerodynamic performance of high-speed maglev trains

The operating speed of high-speed maglev trains in China has reached 430 km/h. The aerodynamic coupling between urban building clusters and crosswinds critically constrains the operational safety of maglev trains. Utilizing the Shanghai maglev line as the prototype, a computational fluid dynamics (CFD) model encompassing the crosswind–urban building clusters–train–bridge system was developed. The large eddy simulation (LES) method was employed to investigate the effects of one to four building cluster layouts and wind direction angles ranging from 45° to 90° on the aerodynamic loads and flow field structures of the train. Using a 1:10 scaled model with constant train speed and uniform crosswind speed, the results showed that: (1) As the train traversed urban roads or open areas under four types of building cluster layouts, the maximum increases in the mean lateral force coefficient C_z, lift coefficient C_y, and overturning moment coefficient C_mx of the head car attained 42.28%, 180.34%, and 37.97%, respectively; (2) During passage through the building gaps of the one building cluster, the peak windward-side surface pressure of the train reached 1.26 times that behind the buildings, while traversal of the urban road in the two building clusters increased this value to 2.87 times; (3) The building gaps of the one building cluster amplified the peak wind speed on the windward side of the bridge to 1.17–1.78 times the incoming wind speed, while urban road of the two building clusters elevated this metric to 1.29 times the incoming wind speed; (4) Traversal of building gaps or urban roads substantially enlarged leeward side vortex structures, thereby augmenting the pressure differential across the car body and associated aerodynamic loads, with these effects intensified as wind direction angles increased. These findings provide a theoretical basis for risk prevention of maglev train operation in urban wind environments. © 2026 Elsevier Ltd.