Tolerance Relief on Transmissions Castings for Producibility
Bibliographic record
Abstract
Helicopter gearbox transmission castings must be designed for adequate strength, adequate stiffness for gear meshes and flight loads, clean-up of all machined surfaces, adequate edge distance for all clamped connections and minimum weight. Castings manufacturers generally request relatively large tolerances due to the nature of the casting processes in the order of +/- 0.100 inch while designers will require casting tolerances in the order of +/- 0.030 inch for cast surfaces. Excess casting material can lead to assembly interferences and excess weight while insufficient material can lead to thin wall conditions, lack of damage repair capability and potential performance issues. This paper describes how skewed (unilateral or unequally disposed) casting tolerances can eliminate casting rejections, eliminate Material Review Board (MRB) delays, eliminate reworks, ensure proper performance, and have negligible impact on weight.
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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 | 0.000 |
| 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) | 0.000 | 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".