Study of the Applicability of the Vyalov Long-Term Strength Prediction Equation under Freezing and Thawing Conditions

Junsong Fu, Ze Zhang (), Chunguang Xu, Jinbang Zhai, Linzhen Yang and Xiangxi Meng
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Junsong Fu: School of Civil Engineering and Transportation, Institute of Cold Regions Science and Engineering, Permafrost Institute, Northeast-China Observatory and Research-Station of Permafrost Geo-Environment of the Ministry of Education, Northeast Forestry University, Harbin 150040, China
Ze Zhang: School of Civil Engineering and Transportation, Institute of Cold Regions Science and Engineering, Permafrost Institute, Northeast-China Observatory and Research-Station of Permafrost Geo-Environment of the Ministry of Education, Northeast Forestry University, Harbin 150040, China
Chunguang Xu: School of Civil Engineering and Transportation, Institute of Cold Regions Science and Engineering, Permafrost Institute, Northeast-China Observatory and Research-Station of Permafrost Geo-Environment of the Ministry of Education, Northeast Forestry University, Harbin 150040, China
Jinbang Zhai: School of Civil Engineering and Transportation, Institute of Cold Regions Science and Engineering, Permafrost Institute, Northeast-China Observatory and Research-Station of Permafrost Geo-Environment of the Ministry of Education, Northeast Forestry University, Harbin 150040, China
Linzhen Yang: School of Civil Engineering and Transportation, Institute of Cold Regions Science and Engineering, Permafrost Institute, Northeast-China Observatory and Research-Station of Permafrost Geo-Environment of the Ministry of Education, Northeast Forestry University, Harbin 150040, China
Xiangxi Meng: School of Civil Engineering and Transportation, Institute of Cold Regions Science and Engineering, Permafrost Institute, Northeast-China Observatory and Research-Station of Permafrost Geo-Environment of the Ministry of Education, Northeast Forestry University, Harbin 150040, China

Sustainability, 2023, vol. 15, issue 13, 1-19

Abstract: In order to determine the appropriate utilization conditions of the Vyalov long-term strength prediction equation, this study selected three soil samples from the loess region. These samples were subjected to varying numbers of freeze–thaw cycles, namely 0, 4, 6, 8, 10, 50, and 100 cycles. Subsequently, post-test soil samples underwent spherical template indenter press-in tests and grain size determinations. The experimental outcomes demonstrated that the Vyalov long-term strength prediction equation accurately reflected the long-term strength variations of frozen loess after 10 freeze–thaw cycles. A further analysis revealed that the stability of the soil samples’ grain composition played a vital role in ensuring the accuracy of the prediction equation. Notably, a highly significant positive correlation was observed between the silt content of the soil samples and the prediction equation parameter β . Moreover, employing the Vyalov long-term strength prediction equation after 10 freeze–thaw cycles yielded prediction results consistent with the freeze–thaw cycles–time analogy method for durations of 10, 20, and 30 years. This study is beneficial for the construction and operation of projects in loess areas.

Keywords: Vyalov long-term strength prediction equation; freeze–thaw cycles; frozen loess; grain composition; parameter; freeze–thaw cycles–time analogy method (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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