Strength parameter selection framework for evaluating the design life of clay cut slopes
Bibliographic record
Abstract
The design of engineered earthworks is predominantly conducted through limit equilibrium analysis, requiring strain-independent strength criteria. Previous studies on deep-seated first-time failures within over-consolidated clay cut slopes have proposed the use of fully softened strength parameters for design. A study investigating shallow first-time failures in clay cut slopes due to seasonal stress cycles was undertaken using a validated numerical model capable of capturing seasonal ratcheting and progressive failure. It was found that fully softened strength criteria are inappropriate for the assessment of shallow first-time failures due to seasonal ratcheting and slopes at angles between the material's fully softened and residual friction angle may be at risk of failure in the future due to this behaviour. However, adopting residual strength parameters will likely result in overly conservative solutions considering the required design life of geotechnical assets. It was found that the strain-softening behaviour of clay defines the rate of strength deterioration and the operational life of engineered slopes. While general guidelines for analysis considering shallow first-time failures in clay cut slopes are provided, detailed understanding of a material's strain-softening behaviour, the magnitude and rate of strength reduction with strains, is needed to establish strength criteria for limit equilibrium analysis.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".