A New Way in HVOF Technology—CFD Optimized TopGun AirJet for Powder and Wire
Bibliographic record
Abstract
Abstract The thermal spray industry requires universal and economical HVOF systems for the production of high-quality coatings with high deposition efficiencies. In the last years classic HVOF guns have been adapted insufficiently to these requirements. This paper shows how modern numeric simulation and new inventions in gas safety engineering enable the development of a spray system for powder and wire feedstock that is optimized especially for the needs of the market. The new IBEDA TopGunAirJet is equipped with an air-cooled ‘de Laval’-like nozzle. The optimized expansion of the gas leads to high gas and particle velocities as well as to moderate flame and particle temperatures. Advantages of the TopGunAirJet are the achievable high coating quality, the low energy consumption (propane, ethene), the utilization of powder or wire and the efficient air cooling of the thermally loaded nozzle parts. Additionally, as a result of the axial powder injection, the free jet divergence and the nozzle wear are minimized. By varying the powder gas flow, the dwell time of the particles inside the flame can be influenced in order to avoid fusing of hard phases. As an example, WC-Co 88-12 coatings are presented and compared to coatings sprayed with a standard HVOF system of the 3rd generation. Different 316L coatings are produced and tested in comparison to standard HVCW coatings to show the workability of solid and cored wires. Finally, extensive LDA measurements are used for in-flight particle analysis, and investigations concerning the achievable deposition efficiencies are carried out.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".