Application of high resolution jet-miniaturized HVOF spray systems for the development of bond coats for TBCs
Bibliographic record
Abstract
In the context of high temperature protection of hot sections of gas turbine engines, recently developed miniaturized thermal spray torches offer new capabilities in creating protective thermal barrier coatings (TBCs) in space restricted components at normal spray angles. In this work, novel miniaturized HVOF systems of hydrogen fueled SprayWerx ID-Nova and liquid fueled Praxair JPid, with high resolution spray jets of few millimeters width, were employed for the deposition of NiCoCrAlX (X=Y,HfSi) bond coats. The coatings were applied at short standoff distances on both external and internal surfaces of cylinders with ≥140 mm diameter. Inert gas was added to the spray jet to reduce the flame temperature and increase in-flight particles’ kinetic energy, thus minimizing oxidation while improving coating density. Spray parameters and feedstock powders were selected to overcome challenges imposed by the compact torch designs. Yttria-stabilized zirconia top coats were subsequently applied by air plasma spraying, and the resulting TBC systems were evaluated by high frequency furnace cycle testing (50 min dwell time at high temperature / 10 min cooling) at 1150°C in air. Oxidation behavior and thermal cycle performance of these newly developed TBCs for space restricted applications will be discussed.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".