Numerical study of the effect of soil–atmosphere interaction on the stability and serviceability of cut slopes in London clay
Bibliographic record
Abstract
The stability of cut slopes is greatly influenced by seasonal pore-water pressure variations under the combined effect of rainfall and vegetation. However, predicting soil–atmosphere interaction is not straightforward, due to the complexity of both the boundary conditions involved and the hydromechanical behaviour of soils, which is coupled and highly nonlinear, rendering the use of numerical tools, such as finite element analysis, necessary. This paper discusses the numerical modelling of soil–atmosphere interaction and presents the analysis of a slope cut in London clay in a highly vegetated area. The whole life cycle of the slope is considered with phases of low and high water demand vegetation and vegetation clearance. The analysis results indicate that dense vegetation is associated with high factors of safety, but may induce large differential displacements, which are likely to affect the serviceability of the slope. Vegetation clearance, however, may initiate instability, highlighting the need for effective vegetation management to achieve a balance between serviceability and ultimate limit states. Although the case considered is representative of southeast England, it introduces the necessary tools for realistic numerical analysis of soil–atmosphere interaction.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".