Integration of a hybrid vibration prediction model for railways into noise mapping software: methodology, assumptions and demonstration

Abstract

Within the SILVARSTAR project, a user-friendly frequency-based hybrid prediction tool has been developed to assess the environmental impact of railway-induced vibration. This tool is integrated in existing noise mapping software. Following modern vibration standards and guidelines, the vibration velocity level in a building in each frequency band is expressed as the sum of a force density (source term), line source transfer mobility (propagation term) and building correction factor (receiver term). A hybrid approach is used that allows for a combination of experimental data and numerical predictions, providing increased flexibility and applicability. The train and track properties can be selected from a database or entered as numerical values. The user can select soil impedance and transfer functions from a database, pre-computed for a wide range of parameters with state-of-the-art models. An experimental database of force densities, transfer functions, free field vibration and input parameters is also provided. The building response is estimated by means of building correction factors. Assumptions within the modelling approach are made to reduce computation time but these can influence prediction accuracy; this is quantified for the case of a nominal intercity train running at different speeds on a ballasted track supported by homogeneous soil of varying stiffness. The paper focuses on the influence of these parameters on the compliance of the track–soil system and the free field response. We also demonstrate the use and discuss the validation of the vibration prediction tool for the case of a high-speed train running on a ballasted track in Lincent (Belgium).

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Funding

Horizon 2020(101015442)