Centrifuge modelling of soil slopes reinforced with vegetation
Bibliographic record
Abstract
This paper reports a series of geotechnical centrifuge model tests conducted to investigate the mechanical reinforcement of slopes by vegetation. Some of the model slopes contained young willow trees, which were grown in controlled conditions to provide different root distributions and mechanical properties. Slopes were brought to failure in the centrifuge by increasing water pressures. The failure mechanisms were investigated photographically and using post-test excavation. By measuring the soil properties and pore pressures in each test when failure occurred, slope stability calculations could be performed for each slope failure. These back-calculations of stability suggest that only a small amount of reinforcement was provided by the root system even when it was grown for 290 days before testing. In contrast, the use of the measured root properties and a commonly used root reinforcement model suggests that significant reinforcement should have been provided by the roots. This disparity is probably due to either inappropriate assumptions made in the root reinforcement model or soil alteration produced by root growth. Such disparities may exist in the application of root reinforcement models to full-scale slopes and therefore require additional study. The modelling technique outlined in this paper is suitable for further investigation of root mechanical interactions with slopes.
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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 | 0.001 | 0.000 |
| Open science | 0.001 | 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".