NDE corrosion metrics for life prediction of aircraft structures
Why this work is in the frame
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Bibliographic record
Abstract
have outlined the USAF shift towards an ‘Anticipate-and-manage’ approach to airframe corrosion control. The two approaches are essentially the same and are aimed at significantly reducing aircraft non-availability and at decreasing maintenance costs. The move from a ‘Find-and-fix’ approach requires a careful assessment of the effects of the corrosion on structural integrity of the aircraft. To achieve this, reliable models are needed which can be used to predict the long-term effects of corrosion on properties such as static strength and fatigue life. Significant progress has been made towards this goal through research being conducted in the US, Canada and Australia. Models allowing the effects of pitting and exfoliation corrosion on fatigue life and the role of corrosion on the degradation of lap joints are currently under development. Eventually these will allow the impact of different levels of corrosion on structural integrity to be assessed and will permit the time at which rectification must be carried out to be determined. The ‘Identify-and-manage’ or ‘Anticipate-and-manage’ approaches will only be possible if effective non-destructive evaluation (NDE) methods are available to detect, characterise and monitor the corrosion that is present within the airframe. The aim of the present project is to assess the capabilities of a range of NDE techniques for detecting and quantifying corrosion present in aircraft structures. As part of this programme, the initial step has been to establish the corrosion metrics that need to be determined so that the ‘Identify-and-manage’ approach can be followed. The metrics will depend on the particular models that are being employed to estimate the residual life of the structure. This paper presents the results of a review of the some of the models and tools that are currently under development and the basic corrosion data or corrosion metrics that are employed. The results from an initial feasibility study of pitting corrosion and crevice corrosion coupons are also presented.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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