The Effect of Microstructure on Pit-to-Crack Transition and Crack Growth in an X-52 Pipeline Steel in Near-Neutral pH Environment
Bibliographic record
Abstract
X-52 pipeline steel specimens that had been pitted using a passivation/immersion technique were cyclically loaded in a near-neutral pH solution sparged with 5% CO2/balance N2 gas mixture at a peak normal stress of 109% of the yield strength (YS), a stress ratio, R, of 0.8, and a frequency of 0.0001 Hz. Blunt cracks were seen to have initiated from the corrosion pits. There were many more cracks on the radial transverse (R-T) surface than on the axial transverse (A-T) surface. On the R-T surface, there were a lot of non-metallic inclusions particularly at mid-wall in this steel and these resulted in the nucleation of large pits that were particularly prone to pit-to-blunt-crack transition. At higher peak normal stress, 109% of YS, compared to previous studies at a little lower stresses, there was more rapid crack formation on the R-T surface. In the end, the cracks along the large elongated inclusions penetrated into the steel samples and led to failure. The crack path was transgranular in nature and the fracture surface displayed quasi-cleavage features. Analysis revealed that the pit depth to width ratio for individual pits was a little higher than that for linked pits, however, the ratio of crack depth to crack mouth width was observed to be much larger than the ratio for the linked pits. Strong preferential dissolution was believed to be responsible for the pit nucleation from these non-metallic inclusions, with the plastically deformed regions at the pits acting as the anodic phases.
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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".