A Review of Numerical Models for Slab-Asphalt Track Railways

Atalan, Mucahit; Prendergast, Luke J.; Grizi, Athina; Thom, Nick

Abstract

Higher train speeds and heavier axle loads trigger elevated stresses and vibrations in the track, potentially increasing track deterioration rates and maintenance costs. Alternative track forms made of combinations of reinforced concrete and asphalt layers have been developed. A thorough understanding of the slab and asphalt tracks is needed to investigate track performance. Thus, analytical and numerical models have been developed and validated by many researchers. This paper reviews numerical models developed to investigate railway track performance. The synthesis of major finite element models is described in detail, highlighting the main components and their outputs. For slab track models, the use of a structural asphalt layer within the railway track remains an active research topic and firm conclusions on its efficacy are not yet available. It can be expected that slab track structures will also be affected by train-induced ground vibrations. There is thus a gap in the literature regarding the measurement of dynamic effects on high-speed railway lines, and further research is needed to investigate the dynamic behaviour of slab–asphalt track systems. In this review, novel solutions for mitigating the vibrations in high-speed rail are discussed and compared. The use of asphalt material in railways appears to have beneficial effects, such as increasing the bearing capacity and stiffness of the structure and improving its dynamic performance and responses, particularly under high-speed train loads.

Citation

Atalan, M., Prendergast, L. J., Grizi, A., & Thom, N. (2022). A Review of Numerical Models for Slab-Asphalt Track Railways. Infrastructures, 7(4), Article 59. https://doi.org/10.3390/infrastructures7040059

• Journal Article Type: Article
• Acceptance Date: Apr 14, 2022
• Online Publication Date: Apr 18, 2022
• Publication Date: Apr 1, 2022
• Deposit Date: Apr 20, 2022
• Publicly Available Date: Apr 21, 2022
• Journal: Infrastructures
• Print ISSN: 2412-3811
• Electronic ISSN: 2412-3811
• Publisher: MDPI
• Peer Reviewed: Peer Reviewed
• Volume: 7
• Issue: 4
• Article Number: 59
• DOI: https://doi.org/10.3390/infrastructures7040059
• Keywords: Computer Science Applications; Geotechnical Engineering and Engineering Geology; General Materials Science; Building and Construction; Civil and Structural Engineering
• Public URL: https://nottingham-repository.worktribe.com/output/7782464