Sikorsky Seal Leakage Criteria and Prevention Methods
Bibliographic record
Abstract
Helicopter gearbox seals typically exhibit a zero-leakage condition, especially on new helicopters. Improved lip seal materials and molding techniques, special attention to grinding seal liners, application of break-in grease, and smooth lead-in chamfers to prevent assembly damage have all contributed to excellent seal performance. Operational leakage criteria, especially for military aircraft is established for completion of missions and exceeds what is expected by operators of new helicopters or by crew chiefs and pilots who are accustomed to zero leakage or minor seal wetness. There are, on occasion, conditions where wetness or drips occur that are questioned by operators because a norm has been established. There are also occurrences where miniscule scratches in seal liners barely visible by the naked eye or microscopic nicks in seal rubber can allow minor seepage. Seal replacement can result in removal of rotors or shafting, requiring reservicing with all new lubricants and serviceability inspections, which can cause mission or delivery delays and put an extra burden on maintenance crews. This paper describes methods to eliminate leakage and provides recommended leakage criteria for safe and reliable operation.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".