CFD simulation of flow regime maps in a slot‐rectangular spouted bed
Bibliographic record
Abstract
The recognition of flow regimes is very important in the application of spouted beds. In this paper, two‐dimensional computer simulations of a slot‐rectangular spouted bed using FLUENT commercial software were utilised to construct flow regime maps. Two‐phase gas–solid flows in the bed were simulated with computational fluid dynamics (CFD) using the two‐phase Eulerian–Eulerian granular model. The numerical simulations were applied to predict different flow regimes. The constructed flow regime map for a bed containing solid particles with a diameter of 1.44 mm was in good agreement with the experimental map previously reported elsewhere. With this successful numerical mapping, a flow regime map for particles with a diameter of 3.77 mm was constructed for various superficial gas velocities and static bed heights. The map was composed of six distinct flow patterns, that is fixed bed, internal jet, jet‐in‐fluidised‐bed, spouting, incoherent spouting and slugging. The slugging flow regime occurred at large values for the static bed height and air inlet velocity, while the spouting regime arose by increasing the air inlet velocity at low values of static bed height. Unlike the spouting regime, large pressure drop fluctuations were observed in the incoherent spouting regime.
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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 | 0.001 | 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".