Geotechnical Properties Determination of Thickened Fluid Fine Tailings
Bibliographic record
Abstract
Abstract Fluid fine tailings (FFT) comprising clayey-silt solids pose environmental and financial challenges. Currently, mining operators are depositing thickened FFT in deep-pits counting on self-weight consolidation to form stable ground. The motivation of this study is to model the long-term prospects of such deposits utilizing consolidation and direct shear strength measurements. The tests were conducted using scroll decanter centrifuge separated FFT sediment referred to as cake. Drained direct shear tests of the cake gave a linear Mohr–Coulomb failure envelope of 1.2 kPa cohesion intercept and 9° internal friction angle for normal stresses up to 1 MPa. Hydraulic conductivity of the cake was non-linear with normal stress decreasing to 1.7 × 10 –11 m/s at 300 kPa. Consolidation results confirmed that the cake exhibits properties similar to those of active clay minerals. The cake compression index is governed by the same relationship as for active clays. The coefficient of consolidation for the cake was nearly constant and had a mean value of 2.25 × 10 –3 m 2 /y, also similar to that of active clays. The void ratio—effective stress—hydraulic conductivity power law empirical relations were used to simulate settlement with a finite-strain model. Numerical results show that the top portion of an FFT deep-pit deposit remains in the liquid state while the lower portion whose maximum solids content converges to 74% is in plastic state. These mean that options that improve hydraulic conductivity and increase the shear strength of the thickened FFT should be integrated prior to final placement in order to create stable ground.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".