CFD simulation of flyash fluidized-bed pulverization with superheated steam
Bibliographic record
Abstract
Abstract The supersonic pulverization technology uses superheated steam generated by the boiler to generate supersonic airflow through the Laval nozzle, and accelerates the flyash fed into the crushing chamber by the screw feeder, and then the flyash can be crushed in mutual collision and friction process. The present paper conducted CFD simulation of fluidized-bed pulverization with superheated steam, and both the velocity filed and the particle tracks are obtained. Convergence test was performed firstly to verify the numerical results, and three different meshes and several different numbers of particles are employed here to show the average velocity of the particles through a certain horizontal plane. The effect of some key parameters, such as distance between the two opposite nozzles and feeding locations of the flyash to the velocity filed and the particle velocity are also numerically investigated. Results show that, the best distance between the two opposite nozzles of the four-nozzle case is 142 mm and the average particle velocity distribution varies little with the flyash feeding position for the present jet mill model.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".