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A Review and Evaluation of Ballast Settlement Models using Results from the Southampton Railway Testing Facility (SRTF).
- Source :
- Procedia Engineering; 2016, Vol. 143, p999-1006, 8p
- Publication Year :
- 2016
-
Abstract
- Many of the world's railways run on ballasted track, which has for nearly 200 years provided a stable support for train operation. However, with trafficking the geometry of the track deteriorates, mainly as a result of the development of differential settlement of the track-bed (ballast and sub-base). When the geometry defects become too severe, maintenance is needed to realign the track to enable the continued safe running of trains. Maintenance is a major cost associated with ballasted railway track, which usually takes the form of tamping. However, tamping damages the ballast, resulting in a diminishing return period between maintenance interventions until eventually the track-bed requires full renewal. A major component of the differential settlement can be attributed to the ballast layer. However, differential settlement of lengths of track cannot easily be modelled or predicted either computationally or experimentally. Thus the total plastic (permanent) settlement is often used as a proxy for the potential for the development of differential settlement along a length of track in the field. Many empirical models have been developed to predict ballast settlement, usually as a function of the number of train axle passes and/or the cumulative load. However, these models may produce very different results, perhaps indicating that the input variables have not been adequately formulated. This paper describes some current empirical ballast settlement models, and evaluates them using experimental data generated using the Southampton Railway Testing Facility (SRTF). This apparatus represents a section of track consisting of a single sleeper bay 650 mm wide, confined by rigid sides that enforce plane strain conditions. The paper summarises the strengths and weaknesses of the existing models, and suggests variables that could be taken into account to improve them. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 18777058
- Volume :
- 143
- Database :
- Supplemental Index
- Journal :
- Procedia Engineering
- Publication Type :
- Academic Journal
- Accession number :
- 116781319
- Full Text :
- https://doi.org/10.1016/j.proeng.2016.06.089