Liquid Dispersion and Gas‐Liquid Mass Transfer in Three‐Phase Inverse Fluidized Beds
Bibliographic record
Abstract
Abstract Axial dispersion of continuous liquid phase and gas‐liquid mass transfer characteristics were investigated in a three‐phase inverse fluidized bed with viscous liquid medium. The axial dispersion coefficient of liquid phase(Dz) increased with increasing gas(UG) or liquid velocity(UL), but decreased with an increase in the viscosity of continuous liquid medium(µL). The volumetric gas‐liquid mass transfer coefficient(kLa) increased with increasing UG but decreased with increasing µL, while it did not change considerably with increasing UL : The effects of UG were dominant in three phase inverse fluidized beds. In the beds of polyethylene particle(relatively heavier particle), the values of Dz and kLa exhibited higher values than those in the beds of polypropylene particles(lighter particle). The values of Dz and kLa were well correlated in terms of operating variables.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".