Simulation and experimental research on coarse coal slime particles’ separation in inclined tapered diameter separation bed
Bibliographic record
Abstract
A novel inclined tapered diameter separation bed (ITDSB) was designed for the beneficiation of coarse coal slime. Computational fluid dynamics (CFD) coupled with the discrete element method (DEM) was explored to study particle separation and the effect of underscreen water on particle movements over time. Results show that coal particles and gangue particles have disparate movements. Coal particles are drifted by the force of water flow and have the analogous trend of movements as water flow, while gangue particles sink towards the lower part of the bed under the effect of the gravity. Secondary separation was achieved through forcing particles to bounce back into the flow field and benefited from the invention and application of underscreen holes. The three factor orthogonal experiments of separating coarse coal slime (3–0.5 mm) have been performed. The obtained clean coals and tailings were tested and further analyzed with an X‐ray fluorescence spectrometer (XRF) and scanning electron microscope (SEM). XRF and SEM results show that gangue minerals were discarded significantly after the separation. Orthogonal experimental results reveal that with reasonable combination of various levels of factors, the average combustible recovery is approximately 60 %, which shows that the inclined tapered diameter separation bed is efficient equipment for coarse coal slime beneficiation. Secondary separation and the effect of underscreen water were simultaneously verified as efficient methods in particle separation processes.
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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 | 0.000 |
| 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 | 0.001 | 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".