A thermo-poromechanical model for simulating freeze–thaw actions in unsaturated soils
Bibliographic record
Abstract
This study presents a new fully coupled thermal-hydraulic-mechanical (THM) model for variably saturated freezing soil, which examines the freeze–thaw (F-T) actions. The model is derived based on the general form of continuum mechanics for porous media. The mass balance equations cover the conservations of the total water and dry air, where liquid water, ice, and vapor are involved in the total water balance equation. The effective stress law for the unsaturated frozen soil is included in the model to quantify poromechanical behaviors. The pore pressure contains components from pore water pressure, pore air pressure, and ice pressure. A new model for characterizing the unfrozen water content based on temperature and air-water capillary pressure is proposed. The THM formulation is based on multidimensional derivation, thus is versatile to be extended to cases including warm temperature conditions or large deformation behavior. The model was implemented in a 2D finite element package and validated by a set of published laboratory experimental data. The numerical code is also applied to simulate the freeze–thaw actions in highly unsaturated loess located in the northwest of China, where the quasi-distributed fiber optic sensing data is collected for field-scale validations. Our simulated thermal-hydro-mechanical responses match well with in situ monitored results and confirm that freezing-induced heaving is still significant in such highly unsaturated soil.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".