Non-destructive inspection of welding defects in friction stir welds and prediction of their fatigue life
Bibliographic record
Abstract
The welding defects in friction stir welds (FSW) such as kissing bond and wormhole were inspected by non-destructive techniques based on X-ray inspection and ultrasonic testing with phased-array probe. Although the X-ray inspection could detect wormhole defects, kissing bonds were recognized only by the ultrasonic testing. The sizes of kissing bonds were estimated based on the maximum echo height of the ultrasonic testing, while the estimated sizes were smaller than the actual ones observed on the fatigue fracture surfaces. Fatigue tests were performed using welds with defects, revealing that the fatigue strengths were significantly reduced due to the early fatigue crack initiation from defects. The prediction of fatigue life of weld was conducted based on the Paris law of fatigue crack propagation rate. The predicted lives of the welds with defects correlated with the actual ones. The ultrasonic testing led to the linear relationship between the estimated and actual sizes of kissing bond, thus it would be possible to predict the fatigue life of the weld with defects by non-destructive inspection.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| 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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".