A pipeline transport correlation for slurries with small but dense particles
Bibliographic record
Abstract
Abstract Most correlations/models for minimum transport or critical velocity of slurry were developed for slurries composed of particles greater than ∼100–200 µm diameter with narrow particle‐size distributions which is typical of the minerals industry. Many other process industries handle smaller particles. In particular waste slurries at the U.S. Department of Energy's Hanford Site have broad size distributions and significant fractions of smaller particles. Despite the size of these wastes, recent studies at Pacific Northwest National Laboratory indicate that the small particles might be of sufficient density to pose a significant risk for pipeline deposition and plugging. To allow predictive assessment of deposition of fine dense particles for waste slurry transport at the U.S. DOE Hanford site, a pipeline‐transport correlation for critical velocity was developed using a simple power‐law between two dimensionless numbers important for slurry transport, the deposition Froude and Archimedes numbers. The correlation accords well with experimental data for slurries with Archimedes numbers <80 and is an adequate pipeline design guide for processing Hanford waste slurry.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".