A Mechanistic Study of Carbon Steel Cracking in 360°C Air and Hydrogen Environments
Bibliographic record
Abstract
Thirty percent cold-worked (CW) carbon steel tensile specimens were exposed to 360°C air and hydrogen environments (2 MPa H2 and 20 MPa H2) under an applied load to produce intergranular creep cracking. In this study, cutting-edge microscopy techniques were applied to characterize cracking on multiple length scales and in three dimensions. The objective was to develop a better mechanistic understanding of creep cracking in carbon steel, and the known deleterious effect of hydrogen (attack) at the micro-to-nanoscale. Amorphous carbon along the fracture path was observed in all experiments, with evidence for nanoscale cavities/methane bubbles in hydrogen exposures, particularly at cementite-ferrite boundaries. Results suggested that creep or residual stress led to breakdown of cementite to amorphous carbon, cavitation, and/or formation of methane (depending on H2 content); it is suggested that the combination of deleterious mechanisms leads to initiation and/or acceleration of creep cracking in CW carbon steel. Comparisons are made between the morphology of creep cracking in these laboratory experiments and recent results from characterization of creep cracking in ex-service carbon steel piping from a CANDU nuclear power plant. Although more subtle, similar morphology and chemistry at crack tips in laboratory and ex-service CW carbon steel suggests that the mechanism(s) of creep cracking is similar.
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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".