Ground vibration induced by maglev trains running inside tunnel: Numerical modelling and experimental validation

Vibration induced by urban rail transit has been a growing public concern worldwide. In this context, medium-low speed maglev trains gradually stand out due to their environmentally-friendly advantages in vibration and noise control. However, few studies have investigated maglev train-induced vibration, and much uncertainty still exists about the environmental vibration caused by underground medium-low speed maglev trains. This paper presents a numerical study of train-induced vibration and proposes a hybrid prediction model based on vehicle-track spatially coupled dynamics in the 2.5D FE framework. This method could consider the nonlinear behaviour of the vehicle-track system in more detail, and the application of Green's function makes this method more efficient when dealing with multiple conditions. Moreover, field measurements are carried out on maglev train-track-embankment system, and measured data show good agreement with the prediction results in the time and frequency domain, verifying the accuracy of the proposed model. Numerical analysis is conducted for the vibration response of the vehicle-track-tunnel-soil system, which reveals the transmission behaviour of the maglev train-induced vibration in layered soils, along with the possible causes of vibration amplification phenomena disclosed. Finally, the vibration levels caused by the maglev and subway trains are compared to quantify their differences. Related results provide insights for unveiling the mechanism of impact brought by daily maglev trains on the neighbouring environment and the quality of residents living alongside.

Automated summary

This paper investigates the vibration induced by medium-low speed maglev trains through numerical study and proposes a hybrid prediction model. The research reveals the transmission behavior of maglev train-induced vibration in layered soils and possible causes of vibration amplification phenomena, providing insights for understanding the impact of daily maglev trains on the neighboring environment.