Validation of a prediction model for tangent rail roughness and noise growth

Jiang, S., Meehan, P. A., Bellette, P. A., Thompson, D. J. and Jones, C. J. C. (2013) Validation of a prediction model for tangent rail roughness and noise growth. Wear, 314 1-2: 261-272. doi:10.1016/j.wear.2013.11.038

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Author Jiang, S.
Meehan, P. A.
Bellette, P. A.
Thompson, D. J.
Jones, C. J. C.
Title Validation of a prediction model for tangent rail roughness and noise growth
Journal name Wear   Check publisher's open access policy
ISSN 0043-1648
Publication date 2013-12-01
Year available 2013
Sub-type Article (original research)
DOI 10.1016/j.wear.2013.11.038
Open Access Status
Volume 314
Issue 1-2
Start page 261
End page 272
Total pages 12
Place of publication Amsterdam, Netherlands
Publisher Elsevier
Language eng
Formatted abstract
• A reliable predictive tool to investigate railway rolling noise growth due to corrugation and rail roughness growth.
• The increased railway rolling noise level is directly determined by the combined wheel/rail roughness levels growth (almost the same in dB).
• Increasing train speed increases railway rolling noise growth as well as overall rail roughness growth.
• Increasing normal load decreases noise levels, but increases rail roughness growth, as well as relevant noise growth.
• The effect of varying ballast vertical stiffness can be ignored.

Railways can inevitably cause railway rolling noise, which is induced by both wheel and rail roughness. Due to the deformation and wear between the wheel/rail at the contact patch, the rail roughness may grow in amplitude after a number of wheelset passages. This results in increasing railway rolling noise. Rail roughness is a common aspect in all transit systems and much research has been pursued to predict and mitigate its growth on track but prediction of resultant noise growth has not been a focus. This paper provides the experimental validation of the modified Railway Rolling Noise Prediction Software (RRNPS) model for the prediction of rail roughness growth and corresponding noise growth. The model is a new framework to enable noise growth predictions due to rail roughness growth mechanics. It is validated by means of several experiments that have been performed along a straight railway line. Through comparisons between predictions and measurements, it is shown that the RRNPS model gives reliable predictions on rail roughness growth and corresponding noise growth. Subsequently this model is used to predict how speed, normal force, wheelset traffic and ballast vertical stiffness affect rail roughness growth and corresponding noise growth.
Keyword Roughness growth
Railway rolling noise
Normal force
Wheelset traffic
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ
Additional Notes Available online 1 December 2013

Document type: Journal Article
Sub-type: Article (original research)
Collections: School of Mechanical & Mining Engineering Publications
Official 2014 Collection
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Citation counts: TR Web of Science Citation Count  Cited 5 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 8 times in Scopus Article | Citations
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Created: Thu, 30 Jan 2014, 23:58:53 EST by Deanna Mahony on behalf of School of Mechanical and Mining Engineering