
Analytical modelling techniques for efficient broadband noise prediction of high-speed trains
Analytical modelling techniques are presented for broadband noise prediction of high-speed trains. For interior noise problems, train body structures are modelled exactly by the dynamic stiffness method (DSM); whereas the interior acoustic cavities of the train body are modelled by
the SDSM where the boundary conditions are described by modified Fourier series with a rapid convergence rate. Finally, the vibro-acoustic coupling model of the train body structures is constructed. For exterior noise problems, exterior train noise models are first formed by experimental data
considering the Doppler effect; then both the DSM and theoretical attenuation formulas are used to build noise radiation models for different external environment conditions. The performance of the method is evaluated by predicting the interior sound field distribution of typical cross sections
of the train body and the external radiated noise in a tunnel, or in an environment where the acoustic barrier or buildings along railways exist. Numerical results are in good agreement with the those obtained by the finite element method. Thus, the proposed methods can achieve broadband noise
prediction highly accurately and efficiently, which can also serve as the benchmark for predicting the radiated noise generated by high‐speed trains.
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Document Type: Research Article
Affiliations: Central South University
Publication date: 04 October 2024
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