Strength and critical state characteristics of lime-stabilised mine tailings
Bibliographic record
Abstract
This study examines the influence of molding conditions and curing time on the mechanical characteristics of lime-stabilized mine tailings. Consolidated drained and undrained triaxial tests were conducted on reconstituted specimens with varying molding conditions and curing times, with 6% lime content, under confining pressures ranging from 48 to 200 kPa. Multi-stage oedometric tests and constant head permeability tests were also performed under these varying conditions. Scanning electron microscopy, energy dispersive spectroscopy, and X-ray fluorescence were employed to analyze changes in particle morphology and chemical composition. The results suggest that the observed changes can be mainly attributed to two mechanisms: flocculation–agglomeration and pozzolanic reactions. The former occurs shortly after lime addition and appears responsible for increases in compressibility, permeability, and the slopes of the critical state lines (CSLs) in both the compression and p′– q planes. The latter mechanism progresses over time and is responsible for an increase in yield stress, the upward shift of the CSL in the compression plane, and enhanced shear strength due to cementation. However, this latter effect is only significant when the material is reconstituted to relatively high densities. The results provide valuable insights into the effects of lime stabilization on the mechanical characteristics of mine tailing materials.
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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 | 0.000 | 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".