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A platform for research: civil engineering, architecture and urbanism
Assessing frost heave susceptibility of gravelly soils based on multivariate adaptive regression splines model
Abstract Frost heave of railway roadbed leads to track geometry degradation during the cold season, seriously threatening the safety of high-speed trains. An accurate estimation of freezing-induced deformation in subgrade aggregates is thus critical to construction and maintenance of transportation infrastructure in seasonally frozen regions. This paper proposes a practical approach to assessing the frost heave susceptibility of gravelly soils under unidirectional freezing conditions. Typical frost heave tests are first performed on gravel columns in closed and open systems. The multivariate adaptive regression splines algorithm is subsequently applied to develop a predictive model for the normalized heave of a specimen. Experimental data of freezing tests were collected from this study and available literature to compile a dataset. A randomly selected subset is used for training, while the complement of the subset is intended for testing. Relative importance analysis and analysis of variance are finally performed to examine the general and coupling effects of initial moisture content, fines, relative compaction, and stress level on the frost heave susceptibility of compacted soil. Hopefully, the developed model and comprehensive analysis of coarse fills could assist railway agencies in understanding the appropriate characterization of frost heave and provide an evaluation guideline for optimized railway roadbed.
Highlights A multivariate adaptive regression splines-based model was developed to predict frost heave ratio of gravelly soils. The general and coupling effects of four influential factors on frost heave susceptibility of coarse fills were examined. Difference of frost heave response between closed and open systems was investigated.
Assessing frost heave susceptibility of gravelly soils based on multivariate adaptive regression splines model
Abstract Frost heave of railway roadbed leads to track geometry degradation during the cold season, seriously threatening the safety of high-speed trains. An accurate estimation of freezing-induced deformation in subgrade aggregates is thus critical to construction and maintenance of transportation infrastructure in seasonally frozen regions. This paper proposes a practical approach to assessing the frost heave susceptibility of gravelly soils under unidirectional freezing conditions. Typical frost heave tests are first performed on gravel columns in closed and open systems. The multivariate adaptive regression splines algorithm is subsequently applied to develop a predictive model for the normalized heave of a specimen. Experimental data of freezing tests were collected from this study and available literature to compile a dataset. A randomly selected subset is used for training, while the complement of the subset is intended for testing. Relative importance analysis and analysis of variance are finally performed to examine the general and coupling effects of initial moisture content, fines, relative compaction, and stress level on the frost heave susceptibility of compacted soil. Hopefully, the developed model and comprehensive analysis of coarse fills could assist railway agencies in understanding the appropriate characterization of frost heave and provide an evaluation guideline for optimized railway roadbed.
Highlights A multivariate adaptive regression splines-based model was developed to predict frost heave ratio of gravelly soils. The general and coupling effects of four influential factors on frost heave susceptibility of coarse fills were examined. Difference of frost heave response between closed and open systems was investigated.
Assessing frost heave susceptibility of gravelly soils based on multivariate adaptive regression splines model
Wang, Tengfei (author) / Ma, Hongfei (author) / Liu, Jiankun (author) / Luo, Qiang (author) / Wang, Qingzhi (author) / Zhan, You (author)
2020-10-07
Article (Journal)
Electronic Resource
English
A novel criterion for assessing frost heave susceptibility of soils
| Springer Verlag | 2024
A novel criterion for assessing frost heave susceptibility of soils
| Springer Verlag | 2024
Frost heave prediction for clayey soils
| Elsevier | 1988