Stochastic stability analysis of a test excavation involving spatially variable subsoil
Bibliographic record
Abstract
A stochastic slope stability analysis method is proposed to investigate the short-term stability of unsupported excavation works in a soft clay deposit having spatially variable properties. Spatial variability of undrained shear strength is modelled by a stochastic model that is the sum of a trend component and a fluctuation component. The undrained shear strength trend, which is also spatially variable, is modelled by kriging or a random function. Slope stability analyses are performed on the stochastic soft clay model to investigate the contribution of spatial variability of undrained shear strength to a disagreement among high factors of safety computed from deterministic methods for slopes that have failed. Probabilities of failure as computed from the stochastic analyses give a better assessment of failure potential. Probability of failure values also correlate with time delay before failure. This phenomenon may be related to progressive failure or creep and to pore pressure dissipation with time.Key words: slope stability analysis, failure probability, spatial variability, stochastic modelling, geostatistics, vane tests, sensitive clay.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".