Bibliographic record
Abstract
Abstract This paper presents a comprehensive summary of IAR/NRC research on risk assessment of aging aircraft structures in the presence of corrosion and fatigue. Extensive test data, especially for fuselage splices containing corrosion and multiple site fatigue damage (MSD) and coupons cut from service exposed aircraft lap joints, have been generated under previous projects. Based on these test data, an empirical stochastic crack growth model was first developed to analyze the probabilistic fatigue characteristics of the splices. Risk analysis was then performed on the fuselage splices using the computer codes PRISM (Bombardier Aerospace, Inc.) and PROF (United States Air Force). Holistic life assessment methodology (HLAM), which aims to quantify structural integrity in the entire life cycle by addressing the interaction effects of corrosion and fatigue, has advanced considerably during the past five years. Risk analysis based on HLAM was carried out on the fuselage splices. The analytical results, which were obtained at different stages, are compared with the test results. It is shown that corrosion in lap joints, even at the levels less than the typical maintenance limit (i.e., 10 % material loss), could significantly increase the risk level of structural failure.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".