A numerical assessment of variable saturation of the upper layers on the ground borne vibrations from underground trains: A case history

Pontani, Nicola; Martinelli, L.; Acquati, Marco; Jommi, Cristina

doi:10.1016/j.trgeo.2023.100981

Cited by 1 publication

(1 citation statement)

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“…Assuming the process to be random and stationary [8], from the estimation of the power spectral density function associated to Eqn. (3) a possible temporal realization can be derived [9]. As the train is supposed to cross the section at a speed of 50.0 km/h, the signal is cut at a length of 7.7 s. Finally, two ramps of arbitrary length of 1.025 s are added to simulate the arrival and the removal of the train from the section, providing a non-stationary shape to the process.…”

Section: Numerical Modelmentioning

confidence: 99%

Numerical evaluation of the temporal variation of vibrations induced by underground trains

Acquati,

Pontani,

Martinelli

et al. 2022

Proceedings of the 10th Convention of the European Acoustics Association Forum Acusticum 2023

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The change in the dynamic response of shallow soils as caught by two geophysical test campaigns is exploited to numerically predict the variation in the ground borne vibrations induced by the passage of underground trains. Multiple causes may lead to a variation in the perception of vibrations over time: from an increase in the train load to the roughness of the railway track, from the increase of the train speed to the modification of the dynamic response of the surrounding soil. In the present study, special attention is devoted to the effect of the hydrological regime on the latter. Two scenarios were calibrated on the results of repeated geodynamic tests on the same site in Milano but at two different times. The two investigations revealed differences in the dynamic response of above-ground soils which can be related to different saturation profiles. The passage of a typical convoy is simulated in the time domain. Differences between the two scenarios are highlighted together with the role played by the static axle load of the train. Furthermore, comparisons with recorded accelerations are provided to validate the model.

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Section: Numerical Modelmentioning

confidence: 99%