Modelling evaporation of paste tailings from the Bulyanhulu mine
Bibliographic record
Abstract
Accurate predictions of drying rates are desirable to optimize surface deposition of thickened or paste tailings. A series of laboratory and field trials were implemented to study evaporation from tailings at the Bulyanhulu gold mine and were compared with numerical simulations using the unsaturated flow model SoilCover. The laboratory tests included two “large-scale” experiments on 10 cm thick layers of tailings 2 m by 1 m in plan, and a smaller column test on a 20 cm thick and 20 cm diameter sample. Data monitored during these tests included albedo, volume change, degree of cracking, matric suction, water content, and drying rate. Field data included gravimetric water contents and albedo values. The model could reasonably simulate the laboratory experiments when adjustments were made to account for self-weight consolidation and the effect of volume change on the relative permeability function. The model could simulate drying in the field for up to 3 weeks after deposition before the accumulation of gypsum and magnesium sulphate salts began to affect evaporation. Cracking and salt accumulation were observed both in the laboratory and in the field. A general model for simulating drying from paste tailings should incorporate the effects of cracking and salts.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".