Drained and undrained weakening and post-reconsolidation strength recovery
Bibliographic record
Abstract
The effect of clay fraction on drained and undrained strain-weakening and subsequent recovery in strength through reconsolidation was investigated using a series of constant volume direct simple shear (DSS) tests and drained ring shear (DRS) tests. This study examined three different materials with a range of plasticity index and fines content values: a mixture of 80% silica fine sand and 20% kaolin by dry weight (20K80SFS), iron ore tailings (IOT), and kaolin. The specimens were monotonically sheared in multiple stages or alternatively cyclically sheared under stress-controlled conditions to various values of shear strain in DSS tests. After the completion of initial shearing, the specimens were reconsolidated to three different vertical effective stresses, and monotonic shearing was recommenced. The lowest fines content 20K80SFS mixture exhibited strength recovery post undrained shearing. The initial degree of shear strain and reconsolidated vertical effective stress was found to influence the post-reconsolidation undrained strength of soils with a higher plasticity index (IOT and kaolin). The shear strength of kaolin specimens after significant undrained shearing showed a reduction that was consistent with that seen in the DRS tests at high shear strain, suggesting a similitude between the process of undrained and drained strain-weakening in predominantly clay soils. This study highlights (i) the potential for undrained strength recovery for pre-sheared specimens and (ii) the undrained frictional-weakening process depending on the clay fraction of the material, consistent with previous studies of drained frictional weakening.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".