Handling dewatered tailings: the three root causes of poor material discharge and bin hang-ups
Bibliographic record
Abstract
Dewatered tailings can be among the most difficult flowing bulks solids found in the mining industry. Understanding the scientific principles that guide good bin and feeder design for difficult flowing cohesive materials, such as dewatered tailings, is key to knowing how to design an appropriate storage and feed system capable of reliably handling these materials. In the late 1970s, Kamengo launched a 15-year research programme to understand and resolve the root causes of bin plugging, including for handling difficult flowing cohesive bulk solids such as dewatered tailings. The research showed that good bin design centres on choosing the correct geometry for the storage bin using the flow properties of the stored material. The standard for a correctly designed storage bin is that with the feeder removed, it should self-empty with only the aid of gravity. The research also showed that the feeder can be a significant culprit in creating plugging problems in a storage bin – including storage bins with correct geometry. First, conventional feeders have a tendency to compact the stored material. With many cohesive bulk solids, when you compact them, they gain strength very quickly. And the more shear strength a bulk solid has, the wider the opening it can bridge over. When compacted enough, a cohesive bulk solid will develop the strength to bridge over the feeder. Second, conventional feeders have a tendency to withdraw material selectively from the storage bin’s discharge outlet. Uneven discharge promotes a first-in, last-out discharge pattern. This is problematic because most cohesive bulk solids, including dewatered tailings, will not reliably discharge in a first-in, last-out discharge pattern. In summary, the research demonstrated that a reliable storage and feed system handling cohesive bulk solids requires both: a) a storage bin with correct bin geometry; and, b) a feeder that withdraws material evenly from the entire discharge opening of the storage bin.
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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 | 0.000 |
| 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".