Ground-borne noise and vibration: classification of railway vehicles based on a track-independent vehicle indicator
Ground-borne noise and vibration: classification of railway vehicles based on a track-independent vehicle indicator
Within the SILVARSTAR project, a track-independent vehicle indicator (TVI) is proposed that can be used to identify railway vehicles which generate low ground-borne vibration and noise levels. The proposed TVI is based on applying a frequency weighting to the force density, which may be obtained at a site from the measured ground vibration velocity levels due to train passages and the measured line source transfer mobility. Two different formulations of TVI are proposed; one related to ground-borne vibration and the other to ground-borne noise. Each TVI is a single number quantity, defined as a sum over all frequency bands of the frequency-weighted force density levels. The proposed performance classification of different vehicles can be achieved by comparing the relative differences of their TVIs. A series of test cases is used to demonstrate the calculation of the TVIs and the TVI-based classification of different vehicles at the same site. Although the values of the TVIs for each vehicle may vary due to the different modelling approaches and detail, or due to the limited knowledge of the input parameters used for the target site, the TVI-based classification of different vehicles is found to be insensitive to this model and parameter uncertainty.
ground-borne noise and vibration, railway vehicle classification, force density, hybrid modelling
1-10
Ntotsios, Evangelos
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Thompson, David
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Reumers, Pieter
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Nélain, Brice
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Degrande, Geert
a09a6d7f-7c2a-4afd-831d-121479197948
Bouvet, Pascal
1c215149-9fd3-4604-a39d-b27d6ee9f6f4
Ntotsios, Evangelos
877c3350-0497-4471-aa97-c101df72e05e
Thompson, David
bca37fd3-d692-4779-b663-5916b01edae5
Reumers, Pieter
4c542eed-6b2b-4581-886a-a31a6cee2885
Nélain, Brice
80e2f0e0-3745-43bf-aa96-b14b7010c0b1
Degrande, Geert
a09a6d7f-7c2a-4afd-831d-121479197948
Bouvet, Pascal
1c215149-9fd3-4604-a39d-b27d6ee9f6f4
Ntotsios, Evangelos, Thompson, David, Reumers, Pieter, Nélain, Brice, Degrande, Geert and Bouvet, Pascal
(2023)
Ground-borne noise and vibration: classification of railway vehicles based on a track-independent vehicle indicator.
In Journal of Physics: Conference Series: XII International Conference on Structural Dynamics, 2-5 July, Delft Netherlands (EURODYN2023).
IOP Publishing.
.
(In Press)
Record type:
Conference or Workshop Item
(Paper)
Abstract
Within the SILVARSTAR project, a track-independent vehicle indicator (TVI) is proposed that can be used to identify railway vehicles which generate low ground-borne vibration and noise levels. The proposed TVI is based on applying a frequency weighting to the force density, which may be obtained at a site from the measured ground vibration velocity levels due to train passages and the measured line source transfer mobility. Two different formulations of TVI are proposed; one related to ground-borne vibration and the other to ground-borne noise. Each TVI is a single number quantity, defined as a sum over all frequency bands of the frequency-weighted force density levels. The proposed performance classification of different vehicles can be achieved by comparing the relative differences of their TVIs. A series of test cases is used to demonstrate the calculation of the TVIs and the TVI-based classification of different vehicles at the same site. Although the values of the TVIs for each vehicle may vary due to the different modelling approaches and detail, or due to the limited knowledge of the input parameters used for the target site, the TVI-based classification of different vehicles is found to be insensitive to this model and parameter uncertainty.
Text
Eurodyn2023_SILVARSTAR_TVI_fullpaper_pure_version
More information
Submitted date: 31 March 2023
Accepted/In Press date: 14 June 2023
Keywords:
ground-borne noise and vibration, railway vehicle classification, force density, hybrid modelling
Identifiers
Local EPrints ID: 479480
URI: http://eprints.soton.ac.uk/id/eprint/479480
PURE UUID: 8cd9e000-7501-4c74-9811-5e1bbd177c9f
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Date deposited: 25 Jul 2023 16:35
Last modified: 18 Mar 2024 02:43
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Contributors
Author:
Pieter Reumers
Author:
Brice Nélain
Author:
Geert Degrande
Author:
Pascal Bouvet
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