Frost heave behavior of coarse-grained materials for high-speed railways subgrade: experimental analysis and machine learning predictive modeling

Abstract Coarse-grained subgrade fill has traditionally been considered frost-heave-insensitive. However, uneven frost heave in such materials has become a critical constraint for high-speed railways (HSRs) in cold regions. Short-wavelength uneven frost heave induces poor sleeper-ballast contact, le...

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Detalhes bibliográficos

Principais autores:	Shanzhen Li, Ke Wang, Shuang Tian, Wenqiang Xing, Xianzhang Ling, Liang Tang, Guoyu Li, Wenjian Zhao
Formato:	Artigo
Idioma:	Inglês
Publicado em:	Nature Portfolio 2025-11-01
coleção:	Scientific Reports
Assuntos:	Frost heave ratio Prediction model Machine learning Frost heave test Coarse-grained materials
Acesso em linha:	https://doi.org/10.1038/s41598-025-26177-9
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