Parametric identification of a transmission line model for<i>in situ</i>damage characterization in lap joints
Bibliographic record
Abstract
This paper presents an in situ damage identification method to characterize the thickness and location of a notch in a one-dimensional lap joint. The approach uses the propagation of flexural waves generated by a piezoceramic (PZT) to evaluate the global reflection coefficient of a complex structure such as a lap joint. A transmission line model (TLM) is used to describe the theoretical reflection coefficient from healthy and damaged lap joints. Parameters from the lap joint are identified in two steps from the experimental measurement of the reflection coefficient. The first step is a calibration step which gives, for the healthy lap joint, the length of the lap joint and distance between the measurement point and the lap joint. The identification of these parameters is performed by minimizing a cost function evaluated for different combinations of parameters. The second step allows us to obtain the parameters associated with the notch, which are its location and thickness. Several cases of healthy and damaged lap joints are conducted and very good results are achieved for the identification of the parameters.
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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) | 0.001 | 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 | 0.001 | 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".