Cold Spray Processing and Repair Design for Helicopter Components
Bibliographic record
Abstract
The cold spray process is currently being utilized to repair metallic production and field-returned helicopter components. The process is a low, solid-state temperature deposition technology in which fine metallic powder particles are injected into a supersonic velocity gas stream to produce a dense deposit by impact onto the substrate surface. The non-melted metallic particles form cold welded bonds with metal substrates, and additional spray passes can achieve deposition layers up to a few inches in thickness. As a result, the cold spray process can be used to repair and rebuild features on field returned parts with damages such as corrosion or wear and on production parts with non-compliance to the drawings such as casting anomalies or machining issues. The successful repair of components using the cold spray process can require various levels of engineering design, processing expertise and machining knowledge. The degree of evaluation is generally based on the complexity of the repair and/or the intended end use of the component. This paper will focus on developing complex cold spray repairs that require high bond strength and minimum porosity levels in the deposit which are typically achieved using a high pressure cold spray system.
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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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".