ANSYS simulation as a feasibility study for high repetition laser ultrasonic non-destructive evaluation (NDE)
Bibliographic record
Abstract
The characterization of delamination in Carbon Fibre Reinforced Plastic (CFRP) composite laminates with laser generated ultrasonic shock waves is presented. This paper reports the understanding of shock-wave prompted free surface vibration which intern can help a user to estimate the frequency range for the material evaluation, wherein the model in the software contains an artificial internal delamination located at the middle in the thickness direction. The propagation characteristics of ultrasonic waves are in accordance with the pulsed laser in the nanosecond regime. The laser can produce a power density optimal enough for ultrasonic evaluation. The pressure deposited on the specimen would importantly be a function of the laser power density, and the acoustic impedance of the specimen. The comparison of free surface velocities and/or the deformation between the two models with and without any delamination, shows the change in the propagation of shock wave due to discontinuity. Also, the analysis is done by varying the location of the delamination in the model. The transducer or an interferometer can be selected based on the magnitude of the velocity and/or the deformation, for the ultrasound detection and evaluation.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.001 |
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".