Comparison of the impact of flow pulsations on the performance of various liquid–gas injectors in a gas–solid fluidised bed
Bibliographic record
Abstract
Abstract This article shows that spray nozzles pulsations can greatly improve the distribution of the sprayed liquid on fluidised bed particles, as characterised by a Nozzle Performance Index (NPI). Appropriate pulsations increased the NPI by nearly 100% under several operating conditions. This article compares four pulsating, gas atomised nozzles under various operating conditions. The performance of each nozzle was evaluated by measuring the electric conductance of a bed of silica sand particles fluidised by air, subsequent to liquid injection. Three sets of experiments were conducted to investigate the effect of operating conditions on the performance of the four gas atomised nozzles. The first set determined the effect of the liquid flowrate, the second set measured the effect of a restriction orifice on the atomisation gas line and the third set studied the effect of the atomisation air to liquid ratio. Artificial nozzle spray pulsations were found to have similar beneficial effects with the different types of gas‐atomised nozzles. © 2011 Canadian Society for Chemical Engineering
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".