Quarterly Management Document – FY22, 1st Quarter, Multi-pass Hybrid Laser Arc Welding of Alloy 740H
Bibliographic record
Abstract
This report summarizes the progress made on the project during the first quarter of FY22. The model for deep penetration laser welding continues to be developed to understand and mitigate cracking issues associated with laser welding Alloy 740H. The effects of laser wobble on laser welding of this alloy are also being developed. Additionally, the short-term creep behavior of welds made by various hybrid laser arc parameters has been obtained and the results indicate they are comparable to welds made by conventional gas tungsten arc welding which is a factor 2 slower than the hybrid welds. Additionally, the creep behavior of laser-only welds is also consistent with conventional gas tungsten arc welds as well as the hybrid laser arc welds made under this project. However, the creep rate of the laser-only welds is much higher than that observed in the hybrid laser arc welded specimens. This is most likely due to the narrower weld produced by laser-only welding compared to hybrid laser arc welding and, thus, the higher creep rate of laser-only welded creep specimens is likely a result of the increased fraction of base metal (which exhibits a higher creep rate than weld metal) contained within the gage section of the creep specimen. Creep rupture lifetimes were all about the same for both laser-only and hybrid laser arc welded specimens and consistent with the creep rupture lifetime of conventional gas tungsten arc welded creep specimens.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.045 | 0.017 |
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".