Combined effect of M/A constituent and grain boundary on the impact toughness of CGHAZ and ICCGHAZ of E550 grade offshore engineering steel
Bibliographic record
Abstract
The present paper investigated the relationship between low temperature impact toughness and microstructure of bainite in coarse-grained heat affected zone (CGHAZ) and intercritically rehazed CGHAZ (ICCGHAZ) of an offshore engineering steel from both the microstructure morphological and crystallographic aspects. In this work, six groups of samples simulated CGHAZ and ICCGHAZ were designated at three different cooling rates. The Charpy test results showed that the toughness in CGHAZ decreases dramatically with decrease of cooling rate, which was attributed to the microstructural evolution from lath bainite to granular bainite, accompanying with the size increase of Bain zone and the change of M/A morphology from film to block. The increase in hardenability by cooling rate promotes more crystallographic variants from different Bain groups. Meanwhile, the combination with controlled inter-spacing of block boundaries by self-accommodation below the critical Griffith crack length, micro-crack can be arrested by these high angle grain boundaries thereby suppressed brittle fracture initiation and increased fracture properties. However, the variation in toughness of ICCGHAZ is not a concern, since obtaining excellent toughness is scarcely accessible even if the matrix microstructure is analogous to CGHAZ. It was due to the formation of coarse M/A constituents (~2 μm) necklacing at the prior austenite grain boundary. The visualized crystallography suggested that the impact toughness was partially correlated to the configuration manner and the size of Bain zones as well via promoting highly misoriented angle (>45°) boundaries, which in turn effectively deflected or arrested the brittle crack propagation.
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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".