Particle separator with vortex claw: an efficient and new technology
Bibliographic record
Abstract
Despite facing many challenges, the exploration of using natural forces and mechanisms besides gravity to enhance particle settling has never ceased. A novel particle separator design, which utilizes multiple vortexes to enhance particle settling, was proposed in this study. The basic principle is using the fluid's energy to generate small swirling currents in a specially designed vortex claw generator. These currents bring suspended particles from the rapid and turbulent inflow to relatively quiet water regions, separating them from the main flows and reducing their travel distance to the wall. To verify the new separator design's performance, comparison studies were carried out in the laboratory using physical models. The results showed that the new design had much higher particle capture rates for the same inflow rates and tested particle sizes. Most importantly, it was able to effectively remove small particles, and particle capture rates were much less affected by fluctuations in inflow rates. Since most existing particle separators failed to perform well under large inflow rates, these characteristics make the new design stand out from other separators. Due to its special structure, its treatment capacity can also be easily increased without changing its horizontal separator size.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".