Groundwater flow and solute transport in a laboratory-scale analogue of a decommissioned in-pit tailings management facility
Bibliographic record
Abstract
A laboratory-scale analogue of an in-pit tailings management facility (TMF) was constructed using mortar sand, fluorescent-dye-containing ground silica, and filter gravel to represent fractured host rock, tailings, and a pervious surround, respectively. In a series of experiments, the performance of the analogue was observed through collection of hydraulic head, groundwater discharge, and solute concentration data. These data were found to be sufficient to validate numerical simulations of the experiments carried out using FRAC3DVS. The validation exercise indicated that adequate discretization of the tailings' periphery was critical to accurate simulation of early time solute release from the ground silica, while accurate simulation of groundwater flow and hydrodynamic dispersion adjacent to the ground silica was critical to accurate simulation of the down-gradient solute plumes. The validated model was used to predict how the analogue would have performed over its entire "contaminating lifespan." The results of the experiments and subsequent numerical modelling were used to support the argument that, assuming no dissolution of tailings solids, solute mass flux out of a decommissioned in-pit TMF would decrease asymptotically with time from a rate controlled by diffusion at the tailings' periphery towards a steady rate controlled by advection through their core.Key words: tailings, groundwater contamination, in-pit disposal, physical model, numerical model, advection-dispersion.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".