Stability analysis for rainfall-infiltrated unsaturated soil slopes subjected to tensile–shear failure following a nonlinear strength criterion
Bibliographic record
Abstract
Rainfall infiltration is one of the major causes of slope instability. While shear failures were commonly adopted, unsaturated soil slopes are in fact highly susceptible to composite tensile-and-shear failure. To address this problem, a nonlinear Mohr–Coulomb (MC) criterion was modified to capture the time dependent tensile and shear strengths for various soils during rainfall, where the coupled effect between capillary and adsorption pressures in the soils was considered. The results showed that the proportion of adsorption stress in the total suction stress varied greatly across different soil types, with the transitional and saturated gravimetric water contents being the two most sensitive parameters affecting the proportion of adsorption stress. On this basis, energy balance equation was established through a two-stage composite tensile–shear failure mechanism of three-dimensional (3D ) slopes following the modified MC criterion. Based on the upper bound theorem of limit analysis, the factor of safety (FoS) for the slopes was calculated by incorporating the strength reduction technique to systematically investigate the effects of rainfall patterns including intensity and duration and soil types on slope stability. Comparisons by analytical and numerical approaches were conducted to verify the present work. Parametric analysis revealed that a 3D analysis could better reflect the slope stability, and that the falling range of slope FoS was strongly correlated with the rainfall patterns and soil permeability. The present study provides a reference and method for assess the stability of various unsaturated soil slopes under different rainfall conditions.
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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 | 0.001 | 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) | 0.001 | 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".