Centrifugal pump performance when handling highly non‐Newtonian clays and tailings slurries
Bibliographic record
Abstract
Abstract Recent loop testing performed at the GIW Hydraulic Lab[1,2] has provided pump performance data for two highly non‐Newtonian slurries with significantly different characteristics: a high clay content slurry with minimal coarse solids; and a typical, low clay content, two‐component tailings slurry. The importance of air removal in the sump and pipe loop was demonstrated using a simple, yet novel de‐aeration system. In addition to the measurement of performance losses, determination of the upper limit of “pumpability” for these slurries relative to their concentration and associated yield stress was investigated. However, once the slurry was de‐aerated, no limits could be found, other than those dictated by suction side losses (NPSHA) or excessive pipeline friction gradients, indicating that the only true limit in practice is one of system economics, i.e. pump operating and capital cost. Experimentally measured pump head and efficiency were compared against corresponding predictions from two different models: the Walker and Goulas technique[3] and the Graham et al. technique,[4] with special focus given to the dependence of the losses on pump rotary speed.
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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 | 0.001 | 0.004 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".