A SHANSEP approach to quantifying the behaviour of clayey soils on a constant shear drained stress path
Bibliographic record
Abstract
Assessing the risk of slope failures of earth structures comprising loose, saturated soils has seen increased focus recently owing to a series of prominent tailings and water dam failures. The potential for the triggering of slope instability by a rising phreatic surface—commonly referred to as the constant shear drained (CSD) stress path—has been well documented over the past few decades for sands and sandy soils under a wide range of loading modes. Alternatively, there has been limited CSD element testing of more clayey soils, with the available data rather showing a dilative tendency through the CSD stress path and mobilised strengths greater than the critical friction ratio, even for specimens commencing CSD shearing from an initially loose state. The current study expands on the CSD data of clayey soils by testing an iron ore tailings and kaolin clay in both triaxial and direct simple shear (DSS) devices, with an emphasis on the DSS. Owing to the tendency for the CSD stress path to result in an overconsolidated condition (i.e., unloading), the tests in the current study were interpreted in the SHANSEP framework given its frequent use to analyse clay behaviour. The results indicated that the SHANSEP framework can reasonably characterise some aspects of CSD behaviour of clays in DSS loading, with some caveats.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".