Pipeline Circumferential Cracking in Near-Neutral pH Environment Under the Influence of Residual Stress: Dormancy and Crack Initiation
Bibliographic record
Abstract
Abstract The purpose of this study is to identify the integrity challenges encountered by buried pipeline steels, specifically to address Circumferential Near-Neutral pH Corrosion Fatigue (C-NNpH-CF). Damage to the pipeline’s protective coating and corrosion conditions increase the risk of service failures caused by C-NNpH-CF. (Note that this mechanism has previously been termed near-neutral pH stress corrosion cracking.) Unlike axial cracking, circumferential cracking is primarily influenced by residual stress from pipeline bending, geohazards, and girth welds. External corrosion pits often lead to dormant cracks, with growth ceasing around 1 mm depth due to reduced dissolution rates. Investigating the impact of bending residual stress (an appropriate source of axial residual stress) and cyclic loading (simulated pipeline pressure fluctuation), the study employs the digital image correlation (DIC) method for stress distribution analysis. Factors like applied loading, initial notch depth, and bending conditions influence crack initiation and recovery from the dormancy stage by affecting stress distribution, stress cells, and stress concentration. Cross-sectional and fractographic images reveal time/stress-dependent mechanisms governing crack initiation, including dissolution rate and hydrogen-enhanced corrosion fatigue. The study emphasizes the role of various residual stress types and their interactions with axial cyclic loading in determining the threshold conditions for crack initiation.
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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".