Numerical simulation on movement behaviours of cylindrical particles in a circulating fluidized bed
Bibliographic record
Abstract
The movement behaviours of cylindrical particles in a circulating fluidized bed were studied with a three‐dimensional multi‐way coupled model of cylindrical particle flow. In this model, the translation and rotation of individual cylindrical particles were solved directly by Newton‐Euler dynamics. The interaction between cylindrical particles was handled in line with rigid impact dynamics and the modified Nanbu collision probability method. The coupling algorithm between the motion of cylindrical particles and turbulent flow was disposed using the correlation between Lagrangian time scales and the closure model. Numerical simulation indicates that cylindrical particles in the near‐wall region reach the exit of the riser faster than those in other regions. The majority of collisions between cylindrical particles occur in the annular region between the central and near‐wall regions. In the horizontal direction, the horizontal velocity components of cylindrical particles vary slightly and distribute randomly, whilst the vertical velocity component exhibits produced variation from the near‐wall region to the central region. Further, the rotation of a cylindrical particle around its axis is shown to be significantly weaker than those around the two other orthometric axes. The collisions of cylindrical particles affect the distribution of horizontal velocity components of cylindrical particles more evidently.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".