Pumping Performance Increase Through the Addition of Turbulent Drag-Reducing Polymers to Pulp Fibre Suspensions
Bibliographic record
Abstract
The addition of a small amount of long chain polymers to a turbulent fluid is known to reduce the wall shear stress and drag. Similarly, the addition of pulp fibres to a turbulent suspension is also turbulent-drag reducing despite pulp fibres having a length scale that is 1000 times larger than polymer molecules. The mechanism of drag reduction and its impact on centrifugal pump performance is poorly understood, especially when there is a combination of polymer and fibres in suspension. Centrifugal (slurry) pump performance was measured as a function of pulp fibre and PAM polymer concentration. Both the pump best efficiency and maximum head rise were greater when pumping modest concentrations of polymer solutions and low consistency pulp fibre than pure water. We measured an efficiency increase of 22 percent and a maximum head increase of 4.3 percent with the addition of 150 ppm PAM polymer relative to pure water. We measured an increase of 8 percent and 2.3 percent in pump efficiency and maximum head coefficient, respectively, with 2 percent pulp fibres over that of water alone. With both 1 percent consistency pulp fibres and 100 ppm of PAM polymers, we measured a 12 percent increase in efficiency over that of pulp suspension alone. With both 2 percent consistency pulp fibres and 100 ppm of PAM polymers, we measured an 8 percent increase in efficiency over that of pulp fibre suspension alone. The reasons for the increased pump efficiency with addition of additives is not known but are thought to be due to the turbulent-drag-reducing properties associated with flow of these suspensions.
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 | 0.000 |
| 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 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".