The influence of particle morphology on the long-term strength of sandy soil under freeze-thaw cycles
Source abstract
Abstract
Freeze-thaw weathering can fragment sand and gravel materials, altering their mechanical properties. This study aims to simulate the effects of freeze-thaw weathering by subjecting sand and gravel materials to cycling tests. The tests were conducted in the monsoonal freeze zone, and the long-term strength and morphological indices of the sub-materials were measured after 0, 5, 10, 50, and 100 freeze-thaw cycles (FTCs) using a spherical template indenter and a particle image analyzer. The morphological indicators that were selected for this study – equivalent diameter and fractal dimension showed a strong correlation with long-term strength. The coefficients of determination (R) were 0.685 and 0.597, respectively. However, the roundness, aspect ratio, and ellipticity of the materials showed a weak correlation with long-term strength, with coefficients of determination less than 0.5. The freeze-thaw cycling process altered the degree of fragmentation of the sand and gravel materials, producing unique particle shape properties. This subsequently influences the alterations in the frictional resistance of the frozen soil, ultimately impacting the changes in its long-term strength. Improving the morphological characteristics of sand and gravel materials before use could be an effective way to enhance their resistance to freeze-thaw damage in engineering applications. In summary, our study demonstrates the importance of considering the effects of freeze-thaw weathering on the mechanical properties of sand and gravel materials. By improving their morphological characteristics, engineers can better protect these materials from damage caused by freeze-thaw cycling.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Climate change and permafrost · Cryospheric studies and observations · Arctic and Antarctic ice dynamics
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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