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Enumeration	Reference	Cover	Find
1.	Kabo, Elena, 1972, et al. (author) Characterisation of track buckling resistance 2024 In: Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit. - 0954-4097 .- 2041-3017. ; in Press Journal article (peer-reviewed)abstract This study sets out with a network-wide analysis of the risk for track buckling that concludes that track buckling relates to a few “weak points” along the track. To identify these, a numerical model to predict track buckling resistance is developed. The influences of key track parameters are evaluated and quantified using the innovative concept of an equivalent temperature. This allows to quantify the large influence of for example, curves and hanging sleepers in terms of an equivalent increase in temperature. Influence of less well-defined track parameters such as nearby fixed points or recent track work is estimated through statistical assessment of track buckling reports. Predicted influence generally agrees with empirical knowledge with some exceptions that are discussed in the report. Developed models and produced results should be valuable in identifying track sections at risk of track buckling and in assessing effectiveness of mitigating actions.

Kabo, Elena, 1972, et al. (author)
Characterisation of track buckling resistance
2024
In: Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit. - 0954-4097 .- 2041-3017. ; in Press
Journal article (peer-reviewed)abstract
- This study sets out with a network-wide analysis of the risk for track buckling that concludes that track buckling relates to a few “weak points” along the track. To identify these, a numerical model to predict track buckling resistance is developed. The influences of key track parameters are evaluated and quantified using the innovative concept of an equivalent temperature. This allows to quantify the large influence of for example, curves and hanging sleepers in terms of an equivalent increase in temperature. Influence of less well-defined track parameters such as nearby fixed points or recent track work is estimated through statistical assessment of track buckling reports. Predicted influence generally agrees with empirical knowledge with some exceptions that are discussed in the report. Developed models and produced results should be valuable in identifying track sections at risk of track buckling and in assessing effectiveness of mitigating actions.

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