Quantitative non-destructive single-frequency thermal-wave-radar imaging of case depths in hardened steels
Bibliographic record
Abstract
Single-frequency thermal-wave radar (SF-TWR) imaging was used to produce dynamic images of effective case depths from phase image frequency scans in AISI 9310 and Pyrowear 53 steels. SF-TWR, as a fast non-destructive testing technique, was also compared with conventional photothermal radiometry measurements in these two types of steel samples using a three-layer theoretical thermal-wave model. In this paper, a novel approach of SF-TWR imaging, combining a three-distinct-layer thermal-wave model and radial phase profiles to image mean value case depths and their lateral non-uniform distributions, yielded quantitative images of case depths in the two hardened steels and exhibited very good correlation with standard Vickers measurements. The SF-TWR images further revealed strong inhomogeneities in the case depth thickness profiles to be used as important feedback to the heat treating manufacturing industry toward the optimization of their case depth hardening process.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".