Correlation Between Microstructure and Yield Strength in Low-Carbon High-Strength Microalloyed Steels
Bibliographic record
Abstract
Microalloyed pipeline and structural steels are currently graded according to their yield strength. In this work, different microstructural factors that affect the yield strength of the steels are assessed and their contributions to the strength are estimated for several low-carbon microalloyed steels, used in pipeline or structural applications. Emphasis is placed on the relative contribution of grain/sub-grain size, precipitate distribution and dislocation density. Accurate grain/sub-grain size measurements were only possible through electron microscopy imaging. It was found that the increased strength is mainly due to the formation of bainitic structures with fine grain/sub-grain sizes. The contribution from other strengthening sources such as precipitates, dislocations and atoms in solid solution is limited and does not vary much among the several grades examined here. The variation in hardness among the fine-grained heat-affected zone samples (heat input range 0.5–2.5 kJ/mm) of one of the steels was also explained based on the microstructural changes.
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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 | 0.001 |
| 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) | 0.000 | 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 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".