Numerical Simulations of Coupled Vapor, Water, and Heat Flow in Unsaturated Deformable Soils During Freezing and Thawing
Bibliographic record
Abstract
Freezing and thawing cycles significantly affect the mechanical and hydraulic behavior of soils, posing detrimental challenges for infrastructures in cold climates. This study develops and validates a coupled Thermal–Hydraulic–Mechanical (THM) model using COMSOL Multiphysics (Version 6.3) to demonstrate the complexities of vapor and water flux, heat transport, frost heave, and vertical stress build-up in unsaturated soils. The analysis focuses on fine sand, sandy clay, and silty clay by examining their varying susceptibilities to frost action. Silty clay generated the highest amount of frost heave and steepest vertical stress gradients due to its high-water retention and strong capillary forces. Fine sand, on the other hand, produced a minimal amount of frost heave and a polarized vertical stress distribution. The study also revealed that vapor flux is more noticeable in freezing fine sand, while silty clay produces the greatest water flux between the frozen and unfrozen zones. The study also assesses the impact of soil properties including the saturated hydraulic conductivity, the particle thermal conductivity, and particle heat capacity on the frost-induced phenomena. Findings show that reducing the saturated hydraulic conductivity has a greater impact on mitigating frost heave than other variations in thermal properties. Silty clay is most affected by these changes, particularly near the soil surface, while fine sand shows less noticeable responses.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".