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This content will become publicly available on January 1, 2027

Title: Large strain thaw consolidation model for ice-rich fine-grained permafrost considering adsorptive and capillary unfrozen water and secondary compression
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.  more » « less
Award ID(s):
1927718
PAR ID:
10650585
Author(s) / Creator(s):
;
Publisher / Repository:
Elsevier
Date Published:
Journal Name:
Cold Regions Science and Technology
Volume:
242
Issue:
C
ISSN:
0165-232X
Page Range / eLocation ID:
104714
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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