Abstract

A novel experimental/numerical hybrid methodology for the assessment of railway-induced ground-borne vibration in buildings based on experimental measurements in the soil surface is proposed in this paper. This methodology has been specifically designed for the prediction of railway-induced vibration in buildings to be constructed close to an operative railway infrastructure, although it can be applied for other types of vibration sources. The model of the incident wave field induced by the railway infrastructure consists of a set of virtual forces applied in the soil, which would be obtained from vibration experimental measurements in the surface of the ground where the building will be constructed. These virtual forces can be subsequently applied to a model of the building-soil system to obtain a prediction of the vibration levels that will be induced by the existing railway infrastructure to the studied building. In the present work, this methodology is theoretically defined and it is numerically validated for two-dimensional and two-and-a-half-dimensional cases. To numerically test the methodology, the measured ground surface responses are replaced by simulated ones obtained in a set of points called collocation points. In this context, a parametric study has been developed with the aim of finding out a robust criterion for the application of the present methodology with respect to the amount and location of the collocation points (representing vibration sensors) and virtual forces. It is found that the distance between virtual sources should be smaller than the S-wave wavelength of the upper soil layer corresponding to the highest frequency of the frequency range of interest to ensure the reliability of the methodology. Moreover, the proposed method is found to be insignificantly affected by the building-tunnel dynamic coupling for building-tunnel distances above 20 m. The proposed hybrid model would simplify the usual numerical prediction approach commonly adopted for dealing in detail with these problems, since a model of the railway infrastructure is no longer required. Moreover, it would reduce the uncertainty of the prediction due to the use of experimental measurements of the particular site to be studied. In addition, it would provide a higher accuracy and flexibility than empirical models based on experimental transmissibility functions between the soil surface and the building.

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