A Study of a Powder Coating Gun Near Field: Particle Flow in an Isothermal Staggered Concentric Air Jet
Bibliographic record
Abstract
An experimental study of inert particle dispersion in an isothermal concentric air jet near field was conducted for cases of standard non-staggered and alternative staggered jet nozzles, each taken from a polymer powder flame deposition gun. The experimental work consisted of analysis of high speed digital images of the inert two phase isothermal jet flow, illuminated by a laser light sheet along and across the jet axis. The analysis of particle spread in the jet, represented by families of particle density distributions, clearly showed that the staggered nozzles resulted in a better-focused flow, with narrower distributions in the near field, and in the elimination of the recirculation zone that disrupted the particle flow in a non-staggered nozzle arrangement. In all cases, histograms of the cross-sectional particle area density were found to be approximately Gaussian. It was also found that there was a wide variation in the size and shape of the ground polymer particles used and these two characteristics caused a wide variation in the radial and axial velocities of the particles. Despite the differences between single-phase numerical simulations and experimental results, reported in Payne et al. [1], the introduction of particles into a numerical model produced satisfactory agreement with the particle velocities found experimentally.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".