Evaluation of the spray stability on liquid injection in gas–solid fluidized beds by passive vibrometric methods
Bibliographic record
Abstract
Abstract For some operations, such as fluid coking, gas atomised liquid feed must be injected via spray nozzles into gas–solid fluidized beds. A stable or non‐pulsating spray with a controlled droplet size is desired. The spray stability of various gas–liquid pre‐mixer and nozzle combinations was determined in open air conditions through analysis of vibration measurements on the upstream conduit with an accelerometer correlated to physical downstream spray measurements. The open air vibration measurements did not correspond to vibration measurements while spraying into a fluidized bed due to external vibrations from the fluidisation. The vibration measurements, however, can provide a relative ranking of spray stability of various gas–solid pre‐mixer and nozzle combinations for similar fluidisation conditions. In addition, the gas to liquid ratio (GLR) and the gas properties were all found to affect spray stability.
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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 | 0.002 | 0.001 |
| 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 | 0.001 |
| 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 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".