Use of pulsations to enhance the distribution of liquid injected into fluidized particles with commercial‐scale nozzles
Bibliographic record
Abstract
Gas‐atomized liquid injections into fluidized beds are commonly used in industrial processes such as fluid coking, fluid catalytic cracking (FCC), and pharmaceutical granulation, where it is important to optimize the distribution of the injected liquid to prevent the formation of unwanted liquid–solid agglomerates and maximize product yields. This injection is typically a two‐phase, gas‐atomized liquid injection. One issue with such a liquid injection is that most of the liquid is deposited at the end of the jet tip within the reactor. This study proposes introducing artificial fluctuations into the injection flow, which causes the jet penetration to vary, allowing for a more even spread of liquid throughout a fluidized bed reactor. The effect of artificial pulsations in the atomized injection, of various frequency and amplitude, was investigated in this study. Using pulsations, greatly enhanced the liquid distribution on the bed particles. © 2012 American Institute of Chemical Engineers AIChE J, 59: 719–728, 2013
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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 | 0.000 |
| 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".