Geometrical and hydrodynamical study of gas jets in packed and fluidized beds using magnetic resonance
Bibliographic record
Abstract
Abstract Magnetic resonance (MR) was used to image the motion of particles and gas just above the distributor of 3D beds of particles fluidized by air. Three different distributors were used: (i) a single‐orifice distributor, with orifice diameters 1.0–4.0 mm, (ii) a plate, drilled with a triangular array of 79 holes, each of 0.35 mm diameter, with a central nozzle containing a single hole of diameter 1.0, 2.5, or 9.0 mm, (iii) distributors with two or three orifices and diameters of 1.0 or 2.5 mm. It proved possible to extract geometrical information, such as the length of a jet, from MR images, each averaged over ∼5 min. Also, light was shed on the question of why is there such a discrepancy between reported jet‐lengths. The fluidization state, the “start‐up” procedure and also the number of holes all play a significant role in determining the measured distance a jet penetrates into a bed. The question as to whether the observed voids represent permanent jets or streams of bubbles was considered. The evidence from ultra‐fast MR measurements strongly suggests that only the lower part of a jet from an orifice in a multi‐orifice distributor is permanent; bubbles form at the top of the jet. Consequently, the top of each jet is transient. However, most of the jet from a single orifice is a permanent cavity when the bed of particles is not fluidized. The length of a jet was successfully correlated with operating variables using dimensional analysis. Finally, the flow of particles around a single jet was measured with high resolution MR.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 teacher head, 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".