Evolution of unfrozen water in coarse-grained frozen soils during thermal thawing: Integrative observations and mechanistic modeling
Bibliographic record
Abstract
• Dual- T 2 cutoffs (frz:1.05/2.25 ms, thw:1.05/2.77 ms) show reversed water transition. • Ultrasonic vel. drops >800% (-3→3°C) indicates ice-soil pts. thawing collapse. • Resist.- θ u model valid for clay/silt/sand, resist. sharply increases at θ u<2.89%. • NMR measures 2355% bound water increase during -5 to 0°C thaw. • Multi-param diagnose builds thermal-thaw alert frmk. for coarse-grained permafrost. Predicting thermal thawing disasters in coarse-grained frozen soil remains an urgent challenge. To address the limitations of traditional frozen soil models and the unclear multi-physics links, this study utilizes nuclear magnetic resonance (NMR), ultrasound, and resistivity tests to investigate the one-sided phase change in coarse frozen soil. Key innovations include: defining a distinct T ₂ cutoff value for coarse-grained soils and quantifying the asynchronous phase transition behavior of bound water, capillary water, and free water in coarse-grained soils. Revealing a sequence diametrically opposed to the progressive phase transition in fine-grained soils (free water freezes before thawing, while bound water does the opposite). Ultrasonic waves reveal a distinctive brittle failure threshold (-3°C) during the thawing process of coarse-grained soils, characterized by a sharp decline in wave velocity (828.85%). This abrupt change contrasts markedly with the gradual variation observed in fine-grained soils, providing a unique precursor to thermal instability caused by ice-cemented collapse. A universally applicable resistivity ρ -unfrozen water model θ u (R² > 0.90) has been established, effectively overcoming the limitations of traditional models in coarse-grained soils. This model accurately captures critical states such as conductive network fractures ( θ u < 2.89%). The multi-parameter diagnostic system provides a framework for thermal thawing hazard warnings in coarse-grained frozen soil engineering. This is significant for monitoring and reducing instability in railways, roads, and pipelines in frozen soil.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".