Probabilistic risk analysis for aircraft structures with limited in-service damages
Bibliographic record
Abstract
This paper presents some recent results of NRC research on risk assessment for aircraft structures. First, this paper briefly reviews the Canadian Forces (CF) risk assessment requirements related to aircraft structural life assessment. Because the single flight probability of failure (SFPOF) (instantaneous failure rate) is an important parameter used in aircraft risk assessment, a critical review of different SFPOF definitions and calculations is presented. As the size of the CF aircraft fleet is relatively small, one common issue encountered during risk assessment is that only a limited number of inservice damage findings are available. Several methods are discussed for preparing input data, especially the initial crack size distribution (ICSD), from small samples for structural risk analysis. To demonstrate one of the in-service damage based methods, a risk analysis case study is presented, in which limited in-service damage findings were used to calculate the SFPOF at a wing location, in support of the CF risk-based decision-making on maintenance actions and the operational life limit.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".