Enhanced truncated-correlation photothermal coherence tomography with application to deep subsurface defect imaging and 3-dimensional reconstructions
Bibliographic record
Abstract
Photothermal diffusion-wave imaging is a promising technique for non-destructive evaluation and medical applications. Several diffusion-wave techniques have been developed to produce depth-resolved planar images of solids and to overcome imaging depth and image blurring limitations imposed by the physics of parabolic diffusion waves. Truncated-Correlation Photothermal Coherence Tomography (TC-PCT) is the most successful class of these methodologies to-date providing 3-D subsurface visualization with maximum depth penetration and high axial and lateral resolution. To extend the depth range and axial and lateral resolution, an in-depth analysis of TC-PCT, a novel imaging system with improved instrumentation, and an optimized reconstruction algorithm over the original TC-PCT technique is developed. Thermal waves produced by a laser chirped pulsed heat source in a finite thickness solid and the image reconstruction algorithm are investigated from the theoretical point of view. 3-D visualization of subsurface defects utilizing the new TC-PCT system is reported. The results demonstrate that this method is able to detect subsurface defects at the depth range of ∼4 mm in a steel sample, which exhibits dynamic range improvement by a factor of 2.6 compared to the original TC-PCT. This depth does not represent the upper limit of the enhanced TC-PCT. Lateral resolution in the steel sample was measured to be ∼31 μm.
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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".