Ultrasonic guided wave inspection of Inconel 625 brazed lap joints
Bibliographic record
Abstract
The aerospace industry has been investigating the use of brazing for structural joints, as a mean of reducing cost and weight. There therefore is a need for a rapid, robust, and cost-effective non-destructive testing method for evaluating the structural integrity of the joints. The mechanical strength of brazed joints depends mainly on the amount of brittle phases in their microstructure. Ultrasonic guided waves offer the possibility of detecting brittle phases in joints using spatio-temporal measurements. Moreover, they offer the opportunity to inspect complex shape joints. This study focused on the development of a technique based on ultrasonic guided waves for the inspection of Inconel 625 lap joints brazed with BNi-2 filler metal. A finite element model of a lap joint was used to optimize the inspection parameters and assess the feasibility of detecting the amount of brittle phases in the joint. A finite element parametric study simulating the input signal shape, the center frequency, and the excitation direction was performed. The simulations showed that the ultrasonic guided wave energy transmitted through, and reflected from, the joints was proportional to the amount of brittle phases in the joint.
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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 | 0.001 |
| 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 | 0.000 | 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".