A parametric study of piezoceramic thickness effect on the generation of fundamental Lamb modes
Bibliographic record
Abstract
Ultrasound damage detection using built-in piezoelectric transducers is a promising technique because it can automatically inspect and interrogate structural damage in hard to access areas. Although numerous efforts have been devoted to the application of the structural health monitoring (SHM) concepts to real world problems; there is a shortage in the modeling tools specifically tailored for rapid computer aided design of SHM applications. This is due to the fact that the finite element method, which is the dominant method in the simulation of the wave propagation problems due to its geometric versatility and the capability to simulate complex boundary conditions as well as coupling effects, lacks the required computational efficiency for the structural health monitoring applications. This is because of the high frequencies usually utilized is SHM, posing a huge burden on the mesh size to minimize the errors. Spectral element method (SEM), a variant of the p/FEM, combines the fast convergence rates associated with the spectral methods with the geometric flexibility of the finite element method, thus allowing for more computationally efficient simulation, leading to fast product design cycle. Recently, these advantages have drawn the attention of the different researchers in the field of the SHM. The advantage of the SEM as a high accuracy solution method enables the refinement and the testing of different concepts of SHM. One of these concepts is the main focus of the current paper. The presented work is a parametric study of the effect of the piezoceramic actuator thickness on the fundamental Lamb waves S 0, and A0 using a tailored SEM solver. In order to illustrate the reduction of the computational costs the running times of the SEM solver were compared with the running times for some of cases solved using commercial FEM solver (ANSYS), as well as the results are compared with analytical results based on a widely accepted model from the literature. Additionally, the cases were validated experimentally, showing a good agreement with the simulation results.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".