NUMERICAL INVESTIGATION OF HVAF-SPRAYED Fe-BASED AMORPHOUS COATINGS
Bibliographic record
Abstract
A numerical analysis was performed to predict the effect of the convergent section geometry of a gun nozzle on the high-velocity air-fuel (HVAF) thermal spray Fe-based amorphous coating (AC) process. A computational fluid dynamics model was applied to investigate the gas-flow field and the behavior of in-flight particles at nozzle entrance convergent section length ranging from 28 mm to 56.8 mm and different shapes of the Laval nozzle convergent section (a straight line and Vitosinski convergence curve). On the one hand, the change in the gas-flame flow characteristics for the Vitosinski curve shows a uniform and stable flame compared with the straight-line curve in the convergent section. The straight-line curve shape of the Laval nozzle convergent section has a higher particle temperature compared with the Vitosinski-curve shape of the Laval nozzle convergent section. The particle dwell time for the straight-line curve shape of the Laval nozzle convergent section is longer than that for the Vitosinski curve shape of the Laval nozzle convergent section. On the other hand, the nozzle entrance convergent section length obviously affects the particle temperature, and the particle dwell time increases with the increasing nozzle entrance convergent section length. By analyzing both the melt status of the particles and particle velocity, the optimal gun configuration (0.7 V) producing low-porosity coatings was predicted. These calculations were experimentally verified by producing a low-porosity (1.37 %) Fe-based AC, fabricated with HVAF using the predicted optimal gun configuration.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".