In-situ austenite grain growth measurements in an X80 line pipe steel
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The evolution of austenite grain sizes is investigated by two in-situ techniques; laser ultrasonics for metallurgy (LUMet) and high temperature confocal scanning laser microscopy (HT-LSCM). The real-time evolution of the mean grain size is monitored during the heat treatment by means of LUMet, whereas the evolution of the surface grain structure is captured from in-situ micrographs obtained by the HT-LSCM technique. The mean grain sizes obtained from LUMet agree reasonably well with those determined from HT-LSCM measurements indicating that grain growth at the sample surface is representative for grain growth in the bulk. The evolution of the grain size distribution during heat treatment is obtained by HT-LSCM measurements. As LUMet only allows to determine mean grain sizes, the microstructural information obtained from HT-LSCM measurements complements the LUMet results. In addition, austenite reconstructions from electron backscatter diffraction (EBSD) were conducted and confirmed the results of the in-situ measurements. • High temperature laser scanning confocal microscopy (HT-LSCM) can record the evolution of surface grain size distributions. • Laser ultrasonics (LUMet) probes a volume to get indirect information on a representative mean grain size in the bulk. • By HT-LSCM and LUMet it is shown that the mean grain size evolutions at the surface and in the bulk are consistent. • This result is also confirmed by EBSD reconstruction of austenite grain structures.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 it