Issue |
Acta Acust.
Volume 8, 2024
|
|
---|---|---|
Article Number | 61 | |
Number of page(s) | 13 | |
Section | Structural Acoustics | |
DOI | https://doi.org/10.1051/aacus/2024058 | |
Published online | 18 November 2024 |
Scientific Article
Acoustic optimisation of the rail track by targeted variation of continuous superstructure parameters along the track
Department of Engineering Acoustics, Institute of Fluid Dynamics and Technical Acoustics, Technische Universität Berlin, Einsteinufer 25, 10587 Berlin, Germany
* Corresponding author: maximilian.mantel@tu-berlin.de
Received:
8
April
2024
Accepted:
27
August
2024
Rolling noise is the dominant source for railway vehicles at medium train speeds. In order to reduce the contribution radiated by the rail, this paper investigates how structural irregularities affect sound propagation by varying the superstructure properties along a ballasted track. The so-called disorder is therefore used to optimise the track decay rate (TDR) and thus achieve a lower mean square velocity of the rail. Track parameters included in the analysis are the pad stiffness, the sleeper mass and the sleeper spacing. Structure-borne sound propagation in the rail is computed using a fast finite-difference method. Both periodically repeating and stochastically distributed variations are considered for parameter variation along the track, with up to three parameters being varied simultaneously. The most promising variation schemes are identified with the help of parameter optimisation using the brute-force method. It has been shown that a high TDR over a wider frequency range and a lower TDR drop in the pinned-pinned frequency range can be achieved due to the presence of disorder. The study indicates that variations of the superstructure parameters along the track are a promising method in order to reduce track vibration levels.
Key words: Time-domain finite-difference method / Railway superstructure variation / Railway superstructure optimisation / Disorder
© The Author(s), Published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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