Certification of the F-22 Advanced Tactical Fighter for High Cycle and Sonic Fatigue
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper presents the methods and approach employed for certification of the F-22 air vehicle for high cycle and sonic fatigue design. To this end the approach employed on the F22 utilizes a four step process. This paper presents and discusses each step of the certification process in detail, beginning with Step 1, the development of design-to criteria for vibration and acoustics. In this step, the details of the derivation of the F-22 design specification and usage are presented. The various ground, wind tunnel, and prototype flight tests conducted to establish a baseline environmental definition are also discussed. With the establishment of a baseline design-to criterion, Step 2 follows with the development of a detailed design-to criterion. In this Step, the ground and laboratory tests conducted to develop design allowables and establish design margins are discussed. The analysis approach for establishing vibration and acoustic environments for design and qualification test are also presented. Step 3 in the certification process is verification of the vibroacoustic environments for design. Verification of the vibroacoustic environments is accomplished through engineering and manufacturing development (EMD) flight test. In Step 3, the requirements, execution and results of the F-22 EMD flight test program for vibroacoustics are discussed. Finally Step 4 presents the processes employed to validate the aircraft structure and air vehicle systems using the verified vibroacoustic environments determined in Step 3. The vibration and acoustic data reduction process is discussed and high cycle and sonic fatigue analyses methods are presented.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 it