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Assessment and enhancement of soil freezing characteristic curve estimation models
被引:5
|作者:
Bi, Jun
[1
,2
]
Li, Laifu
[1
,2
]
Liu, Zhenyu
[1
]
Wu, Zhijian
[1
,2
]
Wang, Guoxu
[1
,2
]
机构:
[1] Nanjing Tech Univ, Coll Transportat Engn, Nanjing 211816, Peoples R China
[2] Jiangsu Provience Engn Res Ctr Transportat Infrast, Nanjing 211816, Peoples R China
基金:
中国国家自然科学基金;
关键词:
Soil freezing characteristic curve;
Estimation model;
One-point measurement method;
Fine-grained soils;
Coarse-grained soils;
UNFROZEN WATER-CONTENT;
CONDUCTIVITY;
D O I:
10.1016/j.coldregions.2023.104090
中图分类号:
X [环境科学、安全科学];
学科分类号:
08 ;
0830 ;
摘要:
The soil freezing characteristic curve (SFCC) represents a vital parameter in cold regions. Special instruments and highly trained personnel must measure the SFCC experimentally, a process that is both cumbersome and labor-intensive. Consequently, several estimation models have emerged to indirectly gauge the SFCC, yet the effectiveness of these models has rarely been examined. This study scrutinized three SFCC estimation models and enhanced them by employing a one-point measurement method. A total of 65 fine-grained soils and 25 coarse grained soils were used to evaluate six SFCC estimation models. Findings reveal that the one-point measurement method markedly enhances the efficiency of the SFCC estimation models. In addition, when compared with three traditional SFCC estimation models, the extended SFCC estimation models were assessed, revealing that the extended Xin et al. SFCC estimation model ranks highest in performance among the SFCC estimation models considered. The research contributes a novel approach to developing SFCC estimation models in cold regions.
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页数:12
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