CFD Modeling and Validation of Bubble Properties for a Bubbling Fluidized Bed
Bibliographic record
Abstract
Simulation using Computational Fluid Dynamics (CFD, FLUENT 6.0.20) and experiments were conducted on a scaled-down cold flow model of a gas−solid fluidized bed reactor used for the production of polyethylene. Using a Eulerian−Eulerian multiphase model based on the two-phase model of Anderson and Jackson ( Ind. Eng. Chem. Fundam. 1967, 6, 527−538) and Jackson ( Chem. Eng. Sci . 1997, 52, 2457−2469; The Dynamics of Fluidized Bed Particles; Cambridge University Press: New York, 2000) simulations were conducted to determine the effect of several parameters; time step, differencing scheme, frictional stress, and closing equations on the bubble properties (predominantly bubble diameter). Once the model flexibility was accessed, the next step was to compare these result with those from experiments conducted using X-ray fluoroscopy. X-ray fluoroscopy was used to create a statistically significant data set. Preliminary experiments comparing the bubble diameter and axial bubble velocity were conducted using glass beads. The results demonstrated that, for glass beads, the average bubble diameters were comparable for CFD and experiments.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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) | 0.001 | 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".