Keywords: railway noise mitigation, finite element modelling, modal basis reduction, viscoelastic materials, computational efficiency, open-source.

Switzerland has reduced railway noise exposure for 80% of affected residents since 2000, but challenges persist for the remaining 20%. To support this goal, the Rail Track Modelling Toolbox, developed with the Swiss Federal Office for the Environment (FOEN) and Swiss Federal Railways (SBB), provides open-source 3D finite element models to optimize vibration and noise mitigation. However, high computational costs (hours to days per simulation) limit scalability. This study addresses this challenge by introducing two key innovations: a phi-filter that prioritizes eigenvector components alongside modal mass to improve high-frequency accuracy and multiple modal bases to adapt to frequency-dependent material properties, reducing memory usage and simulation time. Results demonstrate that combining these methods achieves near-reference precision with 25% of the original modal basis, cutting memory requirements from 90 GB to 11 GB and simulation time from 4 days to 5 hours. These advancements enable high-fidelity simulations for soft track systems (e.g., polyurethane rail pads) up to 5000 Hz, facilitating cost-effective noise reduction strategies.

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