A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Serviceability of railway slab track foundations with retaining walls under train loading
Railway retaining wall designs tend to disregard vehicle-induced trackbed deformation control, despite its potential impact on infrastructure serviceability. To fill this gap, this study seeks to develop an improved method to assess the performance of railway gravity retaining walls, specifically focusing on managing slab trackbed deformation. Utilizing a validated 3D numerical model, the research examines the impact of five parameters – wall width, location, inclination, embankment height, and ground-bearing capacity – on trackbed surface displacement (ω) arising from train loading. The multivariate adaptive regression splines (MARS) approach is applied to establish the mathematical relationship between these factors and an assessment indicator for evaluating track foundation serviceability. This indicator is the trackbed surface displacement index (R ω), signifying the ratio of the maximum allowable to the practical ω value. Results highlight the necessity for comprehensive retaining wall design to ensure R ω ≥1.0, particularly when the wall is near the track, steeply inclined, or supporting a tall embankment.
Serviceability of railway slab track foundations with retaining walls under train loading
Railway retaining wall designs tend to disregard vehicle-induced trackbed deformation control, despite its potential impact on infrastructure serviceability. To fill this gap, this study seeks to develop an improved method to assess the performance of railway gravity retaining walls, specifically focusing on managing slab trackbed deformation. Utilizing a validated 3D numerical model, the research examines the impact of five parameters – wall width, location, inclination, embankment height, and ground-bearing capacity – on trackbed surface displacement (ω) arising from train loading. The multivariate adaptive regression splines (MARS) approach is applied to establish the mathematical relationship between these factors and an assessment indicator for evaluating track foundation serviceability. This indicator is the trackbed surface displacement index (R ω), signifying the ratio of the maximum allowable to the practical ω value. Results highlight the necessity for comprehensive retaining wall design to ensure R ω ≥1.0, particularly when the wall is near the track, steeply inclined, or supporting a tall embankment.
Serviceability of railway slab track foundations with retaining walls under train loading
Lyu, Pengju (author) / Luo, Qiang (author) / Wang, Tengfei (author) / Connolly, David P. (author) / Ye, Qingzhi (author)
International Journal of Rail Transportation ; 13 ; 23-48
2025-01-02
26 pages
Article (Journal)
Electronic Resource
English
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