Influence of Chemical Composition and Heat Treatment on Long-term Creep Strength of Grade 91 Steel
Bibliographic record
Abstract
Long-term creep strength of ASTM/ASME Grade 91 steels was investigated. Two heats of Grade 91 steels indicated lower creep rupture strength than the other four heats from short-term to long-term, and presence of delta ferrite phase was observed. In the short-term, no difference in creep rupture strength was observed among four heats of Grade 91 steels, however, the large heat-to-heat variation of creep rupture strength was observed in the long-term at 600 °C. The higher nickel containing heat indicates lower creep rupture strength in the long-term at 600 °C, although nickel concentration was 0.28mass% in maximum. Homogeneously recovered subgrain structure was observed on the specimens creep ruptured after about 80,000 h at 600 °C for both high nickel low strength heat and low nickel high strength one. Only a small number of fine MX carbonitride particles with a large number of coarse Z-phase were observed on the creep ruptured specimen of high nickel low strength heat, in contrast to low nickel high strength heat in which many MX particles were still observed and Z- phase formation was not pronounced. The difference in stability of fine MX carbonitride particles during creep exposure at the elevated temperatures is a cause of heat-to-heat variation of long-term creep strength of the steels. Decrease in phase transformation temperature of Ac1 with increase in nickel content may reduce stability of the precipitates at the elevated temperatures. Nickel content should be reduced in order to suppress a large drop in long-term creep strength of Grade 91 steel.
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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".