Establishing Rotorcraft Component Fatigue Lives using SUMS Data and a Partial Usage Spectrum Approach for the UH-60 L/M Blackhawk
Bibliographic record
Abstract
Lives of fatigue critical components for Army aircraft are typically established based on component strength from ground test, loads for each regime from flight test, and aircraft usage in each regime from engineering and aircrew judgement. This paper documents the updates to the spectrum for the large Army UH-60 fleet based on usage monitored by the Integrated Vehicle Health Management System (IVHMS). IVHMS and subsequent post processing uses aircraft parameters to identify the regime at any given time. The recognized regimes are summed to generate a spectrum of time or occurrences in each regime. The Partial Regime Recognition Spectrum used here identified specific regimes that had a significant effect on part life and concentrated on identifying only those regimes. Time in other ‘unrecognized’ regimes was prorated based on the legacy spectrum. The SUMS system is validated using scripted flights, as well as by cross checking against a spectrum generated via pilot interviews. Six components were addressed with life changes ranging from 80% to 600% of the legacy life.
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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 | 0.001 | 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 | 0.001 | 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".