Electrokinetic Dewatering of Eneabba West Mine Tailings: A Laboratory Experimental Study
Bibliographic record
Abstract
A mineral sand deposit located at the West Mine, approximately 10 km southwest of Eneabba, Western Australia, was mined using a dredging operation. In order to increase the water recovery and to reduce the volume of the tailings, an experimental study is conducted on electrokinetic dewatering of the West Mine tailings. In this paper, the principle of electrokinetic dewatering is reviewed first, followed by the discussion on the parameters governing the effectiveness and efficiency of electrokinetic dewatering. The procedure and results of the laboratory electrokinetic tests on the West Mine tailings are reported. The discussion includes the mineral, physical, chemical, and electrical properties of the tailings, as well as the electroosmotic permeability, electrokinetic consolidation ratio and coefficient of electrokinetic water transport of the tailings under various void ratios. An example calculation is presented to demonstrate the projected power consumption and consolidation pressure under a simple electric field configuration. It is concluded that the Eneabba West Mine tailings are feasible for electrokinetic dewatering. This is demonstrated by the electroosmotic permeability in the range of 3.2 to 4.7 x 10–9 m2/sV; the electrokinetic consolidation ratio in the range of 0.1 to 20 m/V; and the coefficient of electrokinetic water transport in the range of 5.1 to 6.4 x 10–8 m3/C. The electrokinetic treatment would be able to consolidate the West Mine tailings in the storage cell at relatively low power consumption and thereby allow for more water recovery and reduce the tailings volume.
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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 | 0.000 | 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".