Effects of repeated freeze–thaw cycles on physico-mechanical properties of cohesive soils

Viran, Parisa Adeli Ghareh; Binal, Adil

doi:10.1007/s12517-018-3592-5

Cited by 27 publications

(6 citation statements)

References 15 publications

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“…In addition the subpopulation rEM 5 could also be explained as primary or secondary (reworked) aeolian material (Vandenberghe, 2013;Vandenberghe et al, 2018). The disintegration of coarser grains by repeated frost weathering processes (Viran and Binal, 2018) could also contribute to these rEM 4 and 5 fractions. Schwamborn et al (2012) showed that experimental frost weathering of fine sand samples (63-125 µm) by up to 230 freeze-thaw cycles leads to an increase of up to 25 % in the < 63 µm fraction of a sand sample; this process seems likely to occur in ice-rich Yedoma sediments.…”

Section: Yedoma Grain-size Endmembers and Associated Processesmentioning

confidence: 99%

The genesis of Yedoma Ice Complex permafrost – grain-size endmember modeling analysis from Siberia and Alaska

Schirrmeister

Dietze

Matthes

et al. 2020

E&G Quaternary Sci. J.

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Abstract. The late Pleistocene Yedoma Ice Complex is an ice-rich and organic-bearing type of permafrost deposit widely distributed across Beringia and is assumed to be especially prone to deep degradation with warming temperature, which is a potential tipping point of the climate system. To better understand Yedoma formation, its local characteristics, and its regional sedimentological composition, we compiled the grain-size distributions (GSDs) of 771 samples from 23 Yedoma locations across the Arctic; samples from sites located close together were pooled to form 17 study sites. In addition, we studied 160 samples from three non-Yedoma ice-wedge polygon and floodplain sites for the comparison of Yedoma samples with Holocene depositional environments. The multimodal GSDs indicate that a variety of sediment production, transport, and depositional processes were involved in Yedoma formation. To disentangle these processes, a robust endmember modeling analysis (rEMMA) was performed. Nine robust grain-size endmembers (rEMs) characterize Yedoma deposits across Beringia. The study sites of Yedoma deposits were finally classified using cluster analysis. The resulting four clusters consisted of two to five sites that are distributed randomly across northeastern Siberia and Alaska, suggesting that the differences are associated with rather local conditions. In contrast to prior studies suggesting a largely aeolian contribution to Yedoma sedimentation, the wide range of rEMs indicates that aeolian sedimentation processes cannot explain the entire variability found in GSDs of Yedoma deposits. Instead, Yedoma sedimentation is controlled by local conditions such as source rocks and weathering processes, nearby paleotopography, and diverse sediment transport processes. Our findings support the hypothesis of a polygenetic Yedoma origin involving alluvial, fluvial, and niveo-aeolian transport; accumulation in ponding waters; and in situ frost weathering as well as postdepositional processes of solifluction, cryoturbation, and pedogenesis. The characteristic rEM composition of the Yedoma clusters will help to improve how grain-size-dependent parameters in permafrost models and soil carbon budgets are considered. Our results show the characteristic properties of ice-rich Yedoma deposits in the terrestrial Arctic. Characterizing and quantifying site-specific past depositional processes is crucial for elucidating and understanding the trajectories of this unique kind of ice-rich permafrost in a warmer future.

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Section: Yedoma Grain-size Endmembers and Associated Processesmentioning

confidence: 99%

The genesis of Yedoma Ice Complex permafrost – grain-size endmember modeling analysis from Siberia and Alaska

Schirrmeister

Dietze

Matthes

et al. 2020

E&G Quaternary Sci. J.

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“…A study on the physical properties of soils amid freeze-thaw cycles fundamentally emphasized the impact of two variables: the number of freeze-thaw cycles and the initial moisture content on soil shear strength. The studies uncovered that the soil's strength and cohesion declined when subjected to freeze-thaw cycles, while the soil's internal friction angle increased exponentially [8][9][10]. The first freeze-thaw cycle leads the most obvious reduction in the internal friction angle and cohesion during the entire freeze-thaw cycle.…”

Section: Introductionmentioning

confidence: 99%

Effect of Freeze–Thaw Cycles on the Shear Strength of Root-Soil Composite

Liu,

Huang,

Zhang

et al. 2024

Materials

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A large alpine meadow in a seasonal permafrost zone exists in the west of Sichuan, which belongs to a part of the Qinghai–Tibet Plateau, China. Due to the extreme climates and repeated freeze–thaw cycling, resulting in a diminishment in soil shear strength, disasters occur frequently. Plant roots increase the complexity of the soil freeze–thaw strength problem. This study applied the freeze–thaw cycle and direct shear tests to investigate the change in the shear strength of root-soil composite under freeze–thaw cycles. This study examined how freeze–thaw cycles and initial moisture content affect the shear strength of two sorts of soil: uncovered soil and root-soil composite. By analyzing the test information, the analysts created numerical conditions to foresee the shear quality of both sorts of soil under shifting freeze–thaw times and starting moisture levels. The results showed that: (1) Compared to the bare soil, the root-soil composite was less affected by freeze–thaw cycles in the early stage, and the shear strength of both sorts of soil was stabilized after 3–5 freeze–thaw cycles. (2) The cohesion of bare soil decreased more than that of root-soil composite with increasing moisture content. However, freeze–thaw cycles primarily influence soil cohesion more than the internal friction angle. The cohesion modification leads to changes in shear quality for both uncovered soil and root-soil composite. (3) The fitting equations obtained via experiments were used to simulate direct shear tests. The numerical results are compared with the experimental data. The difference in the soil cohesion and root-soil composite cohesion between the experiment data and the simulated result is 8.2% and 17.2%, respectively, which indicates the feasibility of the fitting equations applied to the numerical simulation of the soil and root-soil composite under the freeze–thaw process. The findings give potential applications on engineering and disaster prevention in alpine regions.

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“…Seasonally frozen soil refers to soil that freezes in winter and completely melts in summer, usually within a few metres from the ground 1 . Regions where there is seasonally frozen soil cover are referred to as seasonally frozen areas.…”

Section: Introductionmentioning

confidence: 99%

“…During the last few decades, scholars have conducted extensive investigations on the mechanical properties of frozen–thawed soils and summarized the variation rules of different soil mechanical properties under varying conditions. The results show that the compressive strength 7 , cohesion 1 , friction angle 8 and other soil properties are greatly changed after freezing and thawing and that the variations in soil characteristics are affected by many factors, such as the freezing temperature 9 , strain rate 10 and number of freeze‒thaw cycles 11 – 13 . However, these experiments are costly and time-consuming, especially when the number of freeze‒thaw cycles is large.…”

Section: Introductionmentioning

confidence: 99%

Principal component analysis–artificial neural network-based model for predicting the static strength of seasonally frozen soils

Sun,

Zhou,

Meng

et al. 2023

Sci Rep

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Seasonally frozen soils are exposed to freeze‒thaw cycles every year, leading to mechanical property deterioration. To reasonably describe the deterioration of soil under different conditions, machine learning (ML) technology is used to establish a prediction model for soil static strength. Six key influencing factors (moisture content, compaction degree, confining pressure, freezing temperature, number of freeze‒thaw cycles and thawing duration) are included in the modelling database. The accuracy of three typical ML algorithms (support vector machine (SVM), random forest (RF) and artificial neural network (ANN)) is compared. The results show that the ANN outperforms the SVM and RF. Principal component analysis (PCA) is combined with the ANN, and the PCA–ANN algorithm is proposed, which further improves the prediction accuracy. The deterioration of soil static strength is systematically researched using the PCA–ANN algorithm. The results show that the soil static strength decreased considerably after the first several freeze‒thaw cycles before the strength plateau occurred, and the strength reduction increased significantly with increasing moisture content and compaction degree. The PCA–ANN model can generate a reasonable prediction for the static strength or other soil properties of seasonally frozen soil, which will provide a scientific reference for practical engineering.

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Effects of repeated freeze–thaw cycles on physico-mechanical properties of cohesive soils

Cited by 27 publications

References 15 publications

The genesis of Yedoma Ice Complex permafrost – grain-size endmember modeling analysis from Siberia and Alaska

The genesis of Yedoma Ice Complex permafrost – grain-size endmember modeling analysis from Siberia and Alaska

Effect of Freeze–Thaw Cycles on the Shear Strength of Root-Soil Composite

Principal component analysis–artificial neural network-based model for predicting the static strength of seasonally frozen soils

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