Modelling of binary fluidization of coal and ash and validation using radioactive particle tracking and densitometry
Bibliographic record
Abstract
Abstract Binary fluidization finds wide application in a variety of gas–solid catalytic and non‐catalytic industrial fluidization systems. In the present study, a three‐dimensional transient computational fluid dynamics (CFD) model was used to model the binary fluidization of coal and ash in a laboratory‐scale cold flow fluidized bed. In parallel, phase velocity measurements using radioactive particle tracking (RPT) and gamma‐ray densitometry were performed, which provided a rich database for validation of the CFD model. RPT being a time‐resolved Lagrangian technique, it was possible to extract velocity fluctuations and their correlations in addition to the mean velocity profiles. The latter provided additional validation for the CFD model, in addition to the typical validation that is done with time‐averaged profiles of phase velocity and volume fraction. The robust validation procedure opens up the possibility of expanding this model to a pilot plant‐scale fluidized bed.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".