Finite element model study of the effect of corner rounding on detectability of corner cracks using bolt hole eddy current
Bibliographic record
Abstract
Recent work has shown that the detectability of corner cracks in bolt-holes is compromised when rounding of corners arises, as might occur during bolt-hole removal. Probability of Detection (POD) studies normally require a large number of samples of both fatigue cracks and electric discharge machined notches. In the particular instance of rounding of bolt-hole corners the generation of such a large set of samples representing the full spectrum of potential rounding would be prohibitive. In this paper, the application of Finite Element Method (FEM) modeling is used to supplement the study of detection of cracks forming at the rounded corners of bolt-holes. FEM models show that rounding of the corner of the bolt-hole reduces the size of the response to a corner crack to a greater extent than can be accounted for by loss of crack area. This reduced sensitivity can be ascribed to a lower concentration of eddy currents at the rounded corner surface and greater lift-off of pick-up coils relative to that of a straight-edge corner. A rounding with a radius of 0.4 mm (.016 inch) showed a 20% reduction in the strength of the crack signal. Assuming linearity of the crack signal with crack size, this would suggest an increase in the minimum detectable size by 25%.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".