Environmental Effect of Crack Growth Rate of Pipeline Steel in Near-Neutral pH Soil Environments
Bibliographic record
Abstract
The laboratory work reported here was initiated to determine whether different soils can be shown to give rise to different growth rate for a given pipeline steel. Two soil synthetic environments with different near neutral pH value were designed based on various soil chemistries collected near the pipeline in the field where near-neutral pH SCC was found. The crack growth behavior in both the environments were determined using compact tension specimen. The crack growth rate was in situ monitored by the potential drop system. It was found that soil chemistry has a profound effect on crack growth rate. Although it is insensitive to the soil chemistry and cyclic frequency, the crack growth rate in the high ΔK regime has been significantly enhanced in comparison with that in air. In the low ΔK regime, the growth rate is shown to have minor dependence on ΔK value but strong dependence on the testing environments. The observed crack growth behavior in different ΔK regimes and environments was related to the crack tip sharpness and crack crevice wideness as a result of corrosion and room temperature creep deformation. Soil solutions with low general corrosion rate are associated with a blunt crack tip and wide crack crevice, which would result in lower stress intensity at the crack tip and weaker crack closure effect, respectively. Similarly, a loading wave allowing shorter creep time on a given volume of material at the crack tip at high loading stress tends to produce a sharper crack tip and narrow crack crevice. These two factors have opposite effect on crack growth rate, and the observed crack growth rate reflects the combined effect of these two opposite factors.
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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".