A Study of the Hydrocyclone for the Separation of Light and Heavy Particles in Aqueous Slurry
Bibliographic record
Abstract
This paper describes an experimental and modelling investigation of a hydrocyclone for the separation of light and heavy particles in an aqueous slurry. The effects of overflow pressure, feed flow rate, particle size, vortex finder length, and particle concentration are investigated. A model based on the governing conservation equations for mass and momentum is solved using a commercial software package, Ansys 12 Fluid Dynamics. Turbulence is modelled using the large eddy simulation, and the discrete particle model is used to predict the particle separation. It is shown by experimentation and modelling that increasing the vortex finder length results in an increase in the recovery of light particles in the overflow. The recovery of light particles increases as their size increases. Increasing the feed flow rate and decreasing the solid concentration in the feed also improves light particle recovery. A computational model based on LES gave close agreement with experimental results for low overall particle concentration.
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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 | 0.000 | 0.001 |
| 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 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".