Undrained Shear Strength of Unsaturated Soils under Zero or Low Confining Pressures in the Vadose Zone
Bibliographic record
Abstract
Core Ideas We present a model to estimate the variation of undrained shear strength of unsaturated soils. Environmental factors influenced the undrained shear strength of unsaturated soils. The proposed model can be implemented into a numerical analysis. In geotechnical engineering practice, many projects such as stability analysis of slopes or trenches and pavement design involve soils in vadose zones at shallow depths, where soils are under unsaturated conditions. For these types of projects, undrained shear strength test results obtained under zero or low confining pressure can be effectively used to analyze the behaviors of unsaturated soils. Experimental procedures to determine the undrained shear strength for different soil suction values, however, is time consuming even under low confining pressure. For this reason, we attempted to develop a semi‐empirical model to predict the undrained shear strength of unsaturated soils at a shallow depth assuming zero confining pressure as a function of soil suction. In addition, existing empirical or semi‐empirical models are also presented along with the characteristic behaviors of unsaturated soils under axial forces at low or zero confining pressures. Finally, the advantages and disadvantages of each model are discussed based on the comparison between the measured undrained shear strengths under zero or low confining pressures with those predicted using the existing and proposed models.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 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".