Geocellular railway drainage systems: physical and numerical modelling

Tasalloti, Ali; Marshall, Alec M.; Heron, Charles M.; Hashemi, Mir Amid

Abstract

The importance of resilient railway infrastructure is paramount when considering the increased likelihood of extreme weather and flash flood events in coming years. One of the main causes of instability of railway tracks is excess water in the trackbed, particularly when it is at or above the interface of the ballast and subgrade. Conventional drainage systems are susceptible to clogging and deterioration. Resilient track drainage systems should therefore have sufficient capacity to allow water to dissipate quickly, but they should also be designed to ensure long-term operation with minimal or easily performed maintenance. This paper presents results from an investigation of a potential new railway drainage system using geocellular components. In the paper, the development of a large scale physical model is described which represents a full scale unit cell of a sleeper-to-sleeper track substructure. The physical model includes ballast and subgrade layers, under-track and lateral drainage systems, rainfall simulation, and instrumentation. Results demonstrate the relative hydraulic response of the drainage system with and without the geocellular components. The paper also describes the development of a numerical model of the track subgrade and drainage system, which was first calibrated and verified using experimental data from the physical model, then extended to study the effect of certain parameters on the hydraulic response of the railway track. Results indicate that the under-track geocellular drainage system offers potential benefits in terms of maintaining a lower water table level within the subgrade as well as in aiding the migration of fines out of the ballast.

Citation

Tasalloti, A., Marshall, A. M., Heron, C. M., & Hashemi, M. A. (2020). Geocellular railway drainage systems: physical and numerical modelling. Transportation Geotechnics, 22, 1-12

• Journal Article Type: Article
• Acceptance Date: Nov 7, 2019
• Online Publication Date: Nov 13, 2019
• Publication Date: Mar 1, 2020
• Deposit Date: Nov 12, 2019
• Publicly Available Date: Nov 22, 2019
• Electronic ISSN: 2214-3912
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 22
• Article Number: 100299
• Pages: 1-12
• Public URL: https://nottingham-repository.worktribe.com/output/3232226
• Publisher URL: https://www.sciencedirect.com/science/article/pii/S2214391219303927