<i>In situ</i>mechanical characterization of isotropic structures using guided wave propagation
Bibliographic record
Abstract
Guided waves are widely used in structural health monitoring (SHM). Their behaviour is highly sensitive to the mechanical properties of a structure. The performance of damage detection strategies based on guided waves therefore relies on an accurate knowledge of the mechanical properties. This paper presents an integrated characterization technique that identifies the mechanical properties of isotropic structures, namely the elastic modulus and Poisson's ratio. The approach is based on a modified version of an imaging algorithm (Excitelet), where mechanical properties, instead of geometrical scattering features, are set as the variables to be identified. The methodology, accuracy, repeatability, and robustness are assessed, first via a finite element model (FEM) and then experimentally for an aluminum plate with attached piezoceramic (PZT) transducers. The plate is instrumented with two PZTs located 15 cm from each other in a pitch–catch configuration, distant enough to ensure proper mode discrimination. The algorithm accuracy and robustness with respect to slight variations in the geometrical inputs (PZT to PZT distance and thickness of the plate) are validated within ± 1% and ± 2%, respectively, with the FEM. Experimental results are validated within ± 1% of supplier properties, demonstrating the ability of this approach to allow accurate characterization of a structure in situ without the need for complex and expensive devices or ASTM testing.
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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 | 0.000 | 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 | 0.000 |
| 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 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".