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Procedia Engineering
Article . 2016 . Peer-reviewed
License: CC BY NC ND
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Procedia Engineering
Article
License: CC BY NC ND
Data sources: UnpayWall
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Procedia Engineering
Article . 2016
License: CC BY NC ND
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Quantifying Degradation of Railway Ballast Using Numerical Simulations of Micro-deval Test and In-situ Conditions

Authors: Deiros, Ivan; Voivret, Charles; Combe, Gaël; Emeriault, Fabrice;

Quantifying Degradation of Railway Ballast Using Numerical Simulations of Micro-deval Test and In-situ Conditions

Abstract

AbstractThroughout the life of the track, ballast grains wear as a result of both the trains passing over the track and the maintenance operations (tamping). The morphology of the grains is changed: they lose angularity and fine particles are produced, causing a gradual loss of track performance. Eventually ballast renewal becomes necessary. In order to predict the evolution of this degradation, a multi-scale study is proposed. A comparison between discrete element method (DEM) simulations of Micro-Deval attrition test and of the passage of trains over a sleeper is performed in order to both detect the different loading and wearing mechanisms involved and quantify the amount of friction work produced, which is directly related to friction wear. The same numerical approach is also used with the simulations of the track to detect families of contacts in order to determine characteristic loading paths at the micro-scale. Loads and displacements of both systems are then compared in order to discuss the relevance of the Micro-Deval test.

Country
France
Keywords

wear, [SPI.GCIV.GEOTECH]Engineering Sciences [physics]/Civil Engineering/Géotechnique, Micro-Deval, ballast grains, 624, Engineering(all), 620, Discrete Elements Method

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    selected citations
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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    19
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
19
Top 10%
Top 10%
Average
gold