The Effect of Niobium on Austenite Decomposition in Line Pipe Steels
Bibliographic record
Abstract
Niobium is a common micro-alloying addition in high-strength low-alloy (HSLA) steels primarily to add strength to the final product. Detailed quantification of the various effects of niobium is critical for understanding the microstructure evolution in the heat affected zone (HAZ) of welds. Laser ultrasonics for metallurgy (LUMet) was used to measure austenite grain growth kinetics in two experimental HSLA steels during continuous heating. For higher heating rates that are of relevance for the HAZ, grain growth during heating is negligible and grain size is determined during the brief time at the peak temperature. Thermal histories were designed based on these tests to produce a variety of microstructures relevant for various positions in the HAZ i.e. coarse and fine grain regions. It was found that the dissolution of niobium carbonitrides has a strong effect on austenite decomposition, particularily in the case of large austenite grain sizes. Nb in solution significantly depresses transformation temperatures in refinement of bainitic microstructures, significantly increasing the hardness in the coarse grained HAZ.
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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 | 0.000 | 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) | 0.001 | 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".