Cyclic shear response of fine-grained mine tailings
Bibliographic record
Abstract
The mechanical response of three different types of fine-grained mine tailings is examined using data from constant-volume cyclic direct simple shear (DSS) tests. Under cyclic DSS loading, fine-grained tailings typically exhibit a cumulative decrease in effective stress along with progressive degradation of shear stiffness. The observed shear strain development due to cyclic mobility is similar in form to that of the previously observed cyclic shear response for natural silts. The cyclic resistance ratio (CRR) of laterite tailings is observed to increase with an increase in the initial effective confining stress (σ′vc). For this material, the dilative tendency due to stress densification seems to have overridden the contractive tendency due to the increase in confining stress. In contrast, the CRR of coppergoldzinc tailings is insensitive to the initial effective confining stress, suggesting a response similar to that of normally consolidated clay. The postcyclic maximum shear strength ratio (Su-PC/σ′vc) obtained from constant-volume monotonic DSS tests is noted to increase with a decrease in the void ratio. For the fine-grained tailings considered in this study, the liquefaction susceptibility predicted using commonly used empirical criteria is not always in agreement with the liquefaction triggering determined from cyclic DSS tests.Key words: tailings, liquefaction, cyclic stress ratio, postcyclic shear strength, direct simple shear testing.
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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 | 0.001 | 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".