Fluidization expansion of novel generation dense medium and flow regime transition in gas-solid separation fluidized bed
Bibliographic record
Abstract
Gas-solid separation fluidized beds are important for coal cleaning through the removal of ash-forming impurities. Homogeneous fluidization is considered as an ideal separation method because it results in fewer pressure fluctuations and smaller bubbles. And Geldart C ultrafine powder could further intensify the fluidization stability of Geldart A particles. Thus, the present work provides a breakthrough in the density adjustment method in the gas-solid separation field, namely, combining Geldart A magnetite particles and Geldart C fine coal particles as a novel dense medium. The results showed that the addition of ultrafine coal effectively increased the overall expansion of the dense phase by the adhesion of the coal particles on the surfaces of the magnetite particles. To comprehensively understand the difference in the dense phase expansion ratio between the Geldart B/D and Geldart A particles, the flow regime was investigated to determine the transition point of homogeneous expansion using various dense media. The propagation velocities of the shock and continuity waves were analyzed using the theory of elastic systems. A quantitative criterion is proposed to identify the transition point. Based on the error analysis, the available data in the literature and the present work gave an overall in 5 × 10−5 error range compared to the prediction data. Overall, this research provides a comprehensive understanding of homogeneous fluidization characteristics using a novel dense medium and a reliable quantitative transition criterion of the flow regime for Geldart B/D and Geldart A particles in a gas-solid separation fluidized bed.
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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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".