<scp>CFD‐DEM</scp> analysis of the spouted fluidized bed with non‐spherical particles
Bibliographic record
Abstract
Abstract Hydrodynamics of spouted fluidized beds of spherical and elongated sphero‐cylindrical particles with an aspect ratio (AR) of 4 were studied by the CFD‐DEM technique. The multi‐sphere method was adopted to present the sphero‐cylindrical particles. Simulations were validated with the experimental data for both particle types. Bubble equivalent diameter, bubble shape factor, and leakage fraction were obtained in the simulations. Time‐averaged particle velocity and porosity profiles, solids circulation rate, particle exchange distribution at the spout‐annulus interface, were investigated in the beds filled with spherical and sphero‐cylindrical particles at gas mass flow rates of 0.005, 0.007, and 0.009 kg/s. The equivalent bubble diameter was found to be lower for spherical particles compared to sphero‐cylindrical particles. The leakage fraction of the bubble was lower for sphero‐cylindrical particles. Solid circulation rate and spout diameter were larger for the bed of spherical particles. A higher probability of particles transition into the spout was observed for spherical particles. Investigating the orientation showed that sphero‐cylindrical particles tend to orient almost vertically against the gas flow in the spout region, which lowers the exerted drag force, whereas the particles align nearly horizontally in the annulus region. The results revealed that the CFD‐DEM approach is a promising method for investigating the fluid and both spherical and non‐spherical particle behaviours in spouted fluidized beds.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".