A Re-Baseline Design Usage Methodology for Vibration and Acoustic Environments Using the F-22A Air Vehicle Operational Spectra
Bibliographic record
Abstract
The F-22 baseline usage definition used for establishing design and certification criteria for high cycle and sonic fatigue assessment of the air vehicle structure and subsystems is derived from two sets of mission profiles composed of eleven peace-time mission profiles and 3 combat mission profiles. These profiles were established in the early 1990s and are the foundation of the derived design and certification environments. These vibration and acoustics environments are documented in the F-22 Environmental Criteria Document and the F-22 Acoustic Loads for Sonic Fatigue Design Document. Both documents have undergone numerous revisions since they were first published, however, the aircraft usage defined by exposure time, aircraft state, aircraft configuration and other aircraft aerodynamic parameters has remained constant except for granularity. This paper presents the methodology employed for re-baselining the F-22 air vehicle usage based on fleet operational spectra and discusses the approach for future air vehicle life tracking. In this paper the analysis approach for establishing the new usage spectrum is discussed in detail. Specifically the protocol for integration of data obtained from the Individual Aircraft Tracking (IAT) program and the Integrity Data Analysis & Reporting System (IDARS) is presented. The results are new usage spectra for vibration and acoustic life assessments which are representative of an F-22 fleet-wide operational spectrum. Comparison of the new re-baselined usage spectrum with the baseline EMD certification spectrum is presented as well as a process under development for tracking air vehicle life. Initial impact assessments for both vibration and acoustic environments are also 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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".