Models for Considering the Thermo-Hydro-Mechanical-Chemo Effects on Soil–Water Characteristic Curves
Bibliographic record
Abstract
The soil–water characteristic curve (SWCC) is widely used as a tool in geotechnical, geo-environmental, hydrology, and soil science fields for predicting and interpreting hydro-mechanical behaviors of unsaturated soils. Several previous studies focused on investigating the influence of initial water content, stress history, temperature, and salt content on the SWCC behavior. However, there is still limited understanding to be gained from the literature on how we can systematically incorporate the influence of complex thermo-hydro-mechanical-chemo (THMC) effects into interpreting and predicting the behavior of unsaturated soils. To address that knowledge gap, in this study, the coupled influence of temperature, initial stress state, initial density, soil structure, and chemical solution effects was modeled using established SWCC equations from the literature. The methodology for incorporating the coupled effects of these influential factors is presented herein. Furthermore, we evaluated the SWCC models proposed in this study, enabling us to provide a comprehensive discussion of their strengths and limitations, using the published SWCC data from the literature. The developments outlined in this paper contribute toward facilitating a rigorous approach for analyzing the THMC behaviors of unsaturated soils.
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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".