Bibliographic record
Abstract
Creep curves of Grade 91 and 92 steels were analyzed by applying an exponential law to the temperature, stress, and time parameters to investigate the formation process of the Z-phase, which lowers the long-term rupture strength of high-Cr martensitic steel. The activation energy (Q), activation volume (V), and Larson–Miller constant (C) were obtained as functions of creep strain. At the beginning of creep, sub-grain boundary strengthening occurs because of dislocations that are swept out of the sub-grains, and this is followed by strengthening owing to the rearrangement of M23C6 and the precipitation of the Laves phase. Heterogeneous recovery and subsequent heterogeneous deformation start at an early stage of transient creep near several of the weakest boundaries because of the coarsening of the precipitates; this results in the simultaneous decreases in Q, V, and C even in transient creep. Further, this activity triggers an unexpected degradation in strength because of the accelerated formation of the Z-phase even in transient creep. The stabilization of M23C6 and the Laves phase is important to mitigate the degradation of the long-term rupture strength of high-strength martensitic steel. The stabilization of the Laves phase is especially important for Cr-Mo systems because Fe2Mo is easily coarsened at approximately 600 °C compared to Fe2W in Grade 92 steel.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 teacher head, 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".