CFD study on the flow distribution of an annular multi‐hole nozzle
Bibliographic record
Abstract
Abstract Annular multi‐hole nozzles are commonly used to disperse one or more types of material in chemical processing, agricultural irrigation, firefighting, and so on. In this study, the LES (large eddy simulation) method combined with the VOF (volume of fluid) model was employed to investigate the impacts of inlet volume flow rate, hole diameter, and distance downstream of nozzle on the flow distribution of the nozzle. To quantify the uniformity of the flow distribution, the non‐uniformity parameter, wetted area, and uniformity index were introduced. The sprays ejected from the nozzle are separated into two modes in accordance with their structure, namely partially impinging sprays (PIS) and fully impinging sprays (FIS). Compared with the three other types of nozzles investigated in this study, the nozzles with a 400 μm hole diameter can achieve the most uniform flow distribution of the nozzle outlet. In addition, the nozzle with larger holes and a higher inlet volume flow rate can easily achieve a large wetted area. However, the nozzle with smaller holes and a relatively low inlet volume flow rate is more inclined to achieve a uniform flow distribution. The larger the inlet volume flow rate, the larger the holes that should be adopted to achieve a relatively uniform flow distribution.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".