Effects of Loading Spectra on High pH Crack Growth Behavior of X65 Pipeline Steel
Bibliographic record
Abstract
The effects of mechanical factors on crack growth behavior during the second stage of high pH stress corrosion cracking in pipeline steel were investigated by applying several loading scenarios on compact tension (CT) specimens. The main mechanism for stage 2 of intergranular crack propagation is anodic dissolution ahead of the crack tip which is highly dependent on crack-tip strain rate. The maximum and minimum crack growth rates were 3 × 10−7 mm/s and 1 × 10−7 mm/s, respectively. It was observed that several factors such as mean stress intensity factor, amplitude, and frequency of loading cycles determine the crack-tip strain rate. Low R-ratio cycles, particularly high-frequency ones, enhance secondary crack initiation, and crack coalescence on the free surface. This mechanism accelerates crack advance on the free surface which is accompanied with an increase in mechanical driving force for crack propagation in the thickness direction. These findings have implications for pipeline operators and could be used to increase the lifespan of the cracked pipelines at stage 2. For those pipelines, any loading condition that increases the strain rate ahead of the crack tip enhances anodic dissolution and is detrimental. Additionally, secondary crack initiation and coalescence could be minimized by avoiding internal pressure fluctuation, particularly rapid large pressure fluctuations.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".