Experimental characterization of effervescent atomization
Bibliographic record
Abstract
The atomization is a process widely used in aerospace, combustion, or thermal spray coating, and is controllable by adopting different fluids as well as by retrofitting nozzle geometry. Desired characteristics of atomized fluid radically depend on the application of the spraying process which could be achieved by the appropriate selection of the nozzle, as well as changing the operating conditions. The objective of this study is experimental investigation of the atomization process by an effervescent nozzle for a variety of fluids where there is a lack of experimental knowledge. \nFour different liquids were taken: distilled water, pure glycerol, water-glycerol aqueous solution and suspensions. The suspension is prepared by an optimized proportion for each case in order to mitigate the sedimentation and clogging of suspended beads. We determined the properties of the atomized fluids in accordance to the commonly used quantities in practical applications. Beside the rheology analyses of the fluids, three types of characterization experiments such as shadowgraphs, PIV and PDPA were conducted. Firstly, shadowgraphs were captured and the overall structures of spraying regions were observed. Accordingly, PIV and PDPA data were provided, consisting of a velocity profile in different operating conditions as well as distributions of a droplets’ diameter. \nThe main characteristics of atomized fluids are velocity profiles, droplet size distributions, spray cone angle, and breakup lengths. These characteristics with dimensionless variables, namely Gas to Liquid Ratios (GLRs), are calculated and compared. It was found that varied values of dynamic viscosities and surface tension values have effects on the atomization affecting breakup lengths and droplet size distributions. Various recommendations were provided regarding the experimental results and future works.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".