Prediction and mitigation of train-induced vibrations of over-track buildings on a metro depot: Field measurement and numerical simulation

Abstract

To predict the vibration transmission of over-track buildings and investigate the effectiveness of countermeasures, a fully coupled three-dimensional vibration prediction model for over-track buildings with consideration of the pile–soil interaction (PSI) was proposed. The accuracy of this prediction model was validated with field data from in-situ vibration monitoring in a metro depot. The consideration of PSI improved prediction accuracy about the vibration of over-track buildings. Then the effectiveness of different mitigation measures (rail damper and ballast mat) was investigated by this prediction model. It was found that the vibration of over-track buildings was dominated by vertical vibration components. Rail dampers significantly reduced the vibration in the high-frequency range above 80 Hz, while the vibration in the low-frequency range below 10 Hz was amplificated. The insertion loss of ballast mats reached 10 dB in the frequency range above 40 Hz except at the resonance frequency of the track, and mitigation effectiveness gradually decreased with increasing story height. This proposed method can predict the vibration level within over-track buildings and is an effective tool to guide the vibration mitigation design of over-track buildings.

Analysis of Vibration Responses Induced by Metro Operations Using a Probabilistic Method

“…Analytical methods are based on the pipe-in-pipe model [6], the transfer matrix method [7], the semi-analytical method [8] or others for modelling soiltunnel coupling in elastic semi-infinite space or full space, which have good computational efficiency. Numerical methods include the finite element model [9], the 2.5-dimensional finite element model [10], the finite element-infinite element model [11] and the boundary element model [12], which allow for more detailed modelling. In some cases, symmetry is used to reduce the model size and then improve computational efficiency.…”