Models for Minimum Liquid Fluidization Velocity of Gas-Liquid Fluidized Beds.
Bibliographic record
Abstract
The gas-perturbed liquid model of Zhang et al. (1995) is modified in an effort to improve its prediction of the minimum liquid velocity of fluidization, Ulmf, of a bed of solid particles in the presence of a low or moderate cocurrent flow of gas. Variants of the model are considered where the buoyancy term is based on the gas-liquid mixture, instead of the liquid alone, and with the frictional pressure gradient given by several alternative equations to the Ergun equation employed in the original gas-perturbed liquid model. All versions of the model provide similar dependence on such factors as gas velocity, particle diameter, particle density and liquid viscosity as those seen experimentally. The mixture buoyed equation with the drag based on an equation suggested by Foscolo et al. (1983) gives improved predictions over the original Zhang et al. (1995) model, but the best overall agreement is with buoyancy based on the liquid alone and the first term in the drag equation with the Carman (1937) constant of 180 instead of Ergun's 150. The predictions are sensitive to the minimum fluidization voidage, which is measured, assumed, or estimated. Further work is required to investigate minimum liquid fluidization velocities experimentally for particles of density closer to that of the liquid, and for high-viscosity liquids.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".