Unusual Corrosion and Stress Corrosion Cracking on a Pipeline
Bibliographic record
Abstract
Abstract An in-line inspection run uncovered a large number of anomalies in one joint of a pipeline. A subsequent investigative excavation revealed external corrosion with fish-bone/flower shaped morphologies. Grinding of the corrosion in the ditch revealed crack-like features in the steel still resembling flower/fish bones. This was different from corrosion and stress corrosion cracking (SCC) normally observed on the pipe steel during excavation, thus causing difficulties to recognize these types of anomalies. As a result it was labeled as unusual corrosion. The concerned pipes were cut-out and replaced. An investigation was thus conducted to understand the nature and mechanism of the unusual corrosion/cracks on this concerned pipeline. Metallurgical characterization identified the anomalies on the surface to be corrosion along manganese sulfide (MnS) inclusions, and SCC subsequently occurred along the corroded MnS inclusions in the steel. MnS inclusions in this pipe demonstrated fish-bone type morphologies, as a result, corrosion along the MnS inclusions caused fish-bone/flower type damage on the surface. The subsequent SCC thus generated cracks along the corroded inclusions; the primary branches aligned with the axial direction and secondary branches aligned with the circumferential directions. The SCC observed was identified to be near-neutral pH SCC as the cracks were microscopically transgranular. The cracks were very shallow and the upper portion was relatively wide, however, the crack tips were branched and sharp, indicating that SCC was actively propagating.
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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 | 0.001 | 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".