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This paper presents a second-order, implicit numerical model for one-dimensional, large strain thaw consolidation of ice-rich, fine-grained permafrost. The phase composition of permafrost at sub-freezing temperatures is determined using an unfrozen water content model that accounts for both capillary and adsorptive unfrozen water. The model incorporates secondary compression to improve the accuracy of long-term thaw consolidation simulations. The algorithm incorporates conduction, advection, and phase change in heat transfer and simultaneous occurrence of primary consolidation and secondary compression. Benchmarking and verification of the model show good agreement with existing numerical models. The proposed model is validated against experimental observations. The model indicates that adsorbed unfrozen water dominates over a wide range of sub-freezing temperatures, while capillary unfrozen water freezes at temperatures just below the freezing point. Numerical simulations suggest that ignoring secondary compression can lead to underestimation of excess pore pressure and settlement during both thaw and post-thaw consolidation. Void ratio and average degree of consolidation are overestimated when secondary compression is not considered. The effect of secondary compression on excess pore pressure and void ratio during thawing becomes more pronounced in thicker, field-scale permafrost layers. Results from this study highlight the importance of considering adsorptive and capillary unfrozen water to determine permafrost composition and incorporating secondary compression in thaw consolidation modeling and thaw settlement estimation for long-term civil infrastructure planning in cold regions. The proposed model provides a comprehensive framework for simulating thaw consolidation processes in permafrost regions. 

This dataset provides distributed acoustic sensing (DAS)-derived axial strains of a ~2 km (kilometer) fiber-optic cable in permafrost terrain near Utqiaġvik, Alaska, during October 2021 to September 2022. The dataset establishes a baseline for assessing cryoseismic activity and dynamic near-surface vibration in Arctic permafrost and supports broader investigations of geophysical and geomechanical processes in Arctic permafrost environments using distributed fiber-optic sensing. 

We first survey historical and recent developments concerning Lu’s uniformization theorem of the Bergman metric. We then establish a new generalization of Lu’s theo rem. 

Thermodynamic characteristics and constitutive relationships are used to predict frozen soil’s behaviors in cold regions. Physical models typically require robust thermodynamic constitutive relationships; however, estimating these relationships of frozen soils is challenging and often requires time-consuming and expensive field and laboratory testing. This study introduces a novel differentiable modeling for frozen soil to obtain its thermodynamic characteristics, termed as the DMFS model. DMFS infers key constitutive relationships that govern heat transfer in frozen soils using observed soil temperature data. In this model, three key thermodynamic constitutive relationships, i.e., the soil freezing characteristic curve, thermal conductivity curve, and heat capacity curve, are represented by physically constrained neural networks (PCNNs). These PCNN-represented constitutive relationships are embedded in heat transfer equations for forward modeling and yield temperature predictions, which are compared against observations to construct a loss function. The forward modeling was implemented via a differentiable numerical solver, which enables backpropagation of loss gradient to PCNNs. By minimizing the loss function with gradient backpropagation, PCNNs are optimized to accurately capture the unknown constitutive relationships. Results from both numerical experiments and in situ borehole experiments demonstrated that the DMFS model could effectively infer constitutive relationships, even with sparse and noisy data. These findings indicate that DMFS holds a significant promise for characterizing frozen soil’s thermodynamic properties in cold regions. 

The degradation of permafrost alters deformation and long-term strength, posing challenges to existing and future civil infrastructure in Northern Alaska. Long-term strength is a critical parameter in the design of civil projects; yet, to our best knowledge, data on the creep deformation and long-term strength of undisturbed permafrost in Northern Alaska remain limited. Soil particle fraction, unfrozen water content, temperature, and salinity may interactively affect creep deformation and long-term strength of permafrost; however, their interactive effects are not well understood. In this study, field samples of relatively undisturbed permafrost from the upper 1.5 m of the Arctic Coastal Plain near Utqiaġvik, Alaska, were first retrieved and analyzed. The permafrost was characterized as saline ice-rich silty sand and nonuniformly distributed ice. We conducted constant stress creep tests, unconfined compression strength tests, and unfrozen water content tests to assess the mechanical and physical properties of the permafrost cores. The results indicated that the long-term strength of the permafrost decreased by nearly 90% from −10°C to −2°C. At −10°C, the long-term strength increased by approximately 120% as the soil particle fraction rose from 0.14 to 0.26. The strengthening effect of soil particles diminished at higher temperatures and higher salinity due to the influence of unfrozen water. A quantitative tool has been developed to predict the long-term strength of ice-rich permafrost, incorporating the effects of soil particle fraction and temperature. The findings of this study can potentially support infrastructure design and planning in Northern Alaska in the context of a warming climate. 

The Arctic is experiencing accelerated warming at up to four times the rate of temperate regions, driving permafrost thawing and ground ice melting, which, in turn lead to coastal bluff failure and accelerated erosion. The primary mechanisms behind Arctic coastal bluff failures include the formation of thermoerosional niches at the bluff’s toe and warming-induced reductions in ground strength, making Arctic coastal bluff failure a complex thermal-mechanical coupling process. Most existing studies have focused on coastal bluff failures in temperate regions, but the unique failure mechanism in the Arctic remain underexplored. This study addresses this gap by developing a thermalmechanical coupling model to study the failure mechanism of a permafrost bluff failure that occurred in 2023–2024 in Utqia˙gvik, Alaska. The model incorporates pore ice phase change, thaw-induced reductions in permafrost stiffness and strength, and the effects of thermoerosional niches, cracks, and ice wedges. Stability analysis is conducted via the local factor of safety (LFS) method to account for spatial variations in permafrost strength and stiffness. Ground-penetrating radar (GPR) data from the August 2024 site survey were employed to characterize site conditions, and ground temperature data were used to validate the model. The results revealed two primary failure zones: one near the ground surface and another at the bluff’s toe. The total area of these two failure zones expanded with ongoing thaw. Besides, the results indicated that the increase in thaw thickness, the growth in niche length, and the presence of cracks exacerbate bluff instability, and bluff failure is likely to initiate along the ice wedge–permafrost interface.