Centrifuge modeling of rainfall-induced instability in sandy slopes
Bibliographic record
Abstract
This study examines the mechanisms of rainfall-induced slope instability through centrifuge model tests on silica sand slopes conducted at the Western Geotechnical Drum Centrifuge. A custom-designed rainfall simulation system was developed and calibrated to provide uniform infiltration under elevated gravity. High-resolution image analysis (GeoPIV) and real-time pore pressure monitoring were employed to capture the coupled hydraulic–mechanical behaviour of slopes under controlled conditions. Tests were performed on slopes with varying inclination, initial water content, and gravitational acceleration, under both dry and rainfall scenarios. Results showed that rainfall infiltration rapidly reduced matric suction in unsaturated zones and generated positive pore water pressures, leading to decreased effective stress and a significant loss of shear strength. Compared with dry slopes of identical geometry and density, rainfall-exposed slopes experienced faster and more extensive deformation, with failure occurring earlier and progressing more severely under higher inclination or greater initial water content. The observed relationships between infiltration dynamics, suction loss, pore pressure evolution, and deformation progression provide essential physical insights for physics-based modeling. By elucidating these trends under controlled conditions, the study enhances understanding of rainfall-induced slope failure mechanisms and supports the development of improved hazard assessment and mitigation strategies.
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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) | 0.000 | 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 | 0.001 | 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".