Characteristics of Near-Neutral-pH Stress Corrosion Cracks in an X-65 Pipeline
Bibliographic record
Abstract
Two patches of near-neutral-pH stress corrosion cracks (SCC), as developed on a pipeline steel during service, have been characterized. The two patches can be characterized as containing either dense cracks or sparse cracks, based on their spatial separation. Cracks from both patches were categorized as either linked cracks or independent cracks; the former were distinguished by multiple peaks in the depth direction, considered to be a result of crack coalescence, while the latter had a single peak and a smooth depth profile. The linked cracks were usually <500 μm in depth with little increase in depth as the crack length extended beyond ~2 mm. In contrast, the independent cracks exhibited a linear relationship between crack length and crack depth. The linked cracks, although dormant in the depth direction, appeared to be actively corroding in the width direction near the crack root and possibly at the overlapped region between two joined cracks. For the independent cracks, corrosion in the width direction became faster as the crack deepened, implying that the growing cracks were evolving toward a pit. This also suggests that alternative mechanisms (e.g., possibly hydrogen embrittlement, as evidenced in this study) must become operative in the process of rupture following the initial dissolution mechanism for crack initiation and initial growth.
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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".