Numerical ultrasonic full waveform inversion (FWI) for complex structures in coupled 2D solid/fluid media
Bibliographic record
Abstract
Abstract Undetected inclusions in engineering components cause tremendous industrial expenses in maintenance and repairs each year, with additional risks of catastrophic failures. This paper introduces a powerful method for inclusion imaging and reconstruction in irregularly-shaped components, based on a cutting-edge imaging technique—full waveform inversion (FWI). We propose an ultrasonic scanning setup for nondestructive evaluation (NDE) that fits a variety of components with different shapes and sizes. The FWI theoretical expressions are summarized, aiming for creating clear explanations for the NDE and material characterization communities. Systematic analysis of the FWI performance using different setups has been conducted, and a variety of case studies show different aspects of complexity that the FWI technique can address. Multiple inclusions have been successfully reconstructed in gears, exhibiting the potential of applying the proposed technique in overcoming various NDE challenges related to the rapidly growing structural and material complexity nowadays.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".