Retarding Crack Growth by Static Pressure Hold for Pipeline Steel Exposed to a Near-Neutral pH Environment
Bibliographic record
Abstract
From extensive investigations for over 30 years since the discovery of near-neutral pH stress corrosion cracking (NNpHSCC), the physical processes of crack initiation and growth have been determined, despite that some details in various aspects of crack initiation and growth are still to be understood. The growth curve is a function of crack growth by direct dissolution of steels at localized areas on pipe surface during initiation or at the tip of a crack during early stage of crack growth (the dissolution growth curve), and by a process involving the interaction of fatigue and hydrogen embrittlement (corrosion fatigue, the hydrogen enhanced fatigue growth curve) in Stage II after crack initiation and early stage of crack growth. For the latter case, recent research shows that crack growth rate can be substantially enhanced by variable amplitude cyclic loading. One of the most severe scenarios of cyclic loading in terms of crack growth rate is the underload type of pressure fluctuations that is often found within 30 km downstream of a compressor station. This investigation is aimed to evaluate pressure scenarios that could reduce or retard crack growth during pipeline operation. Specifically, the effect of pressure holds was investigated. Different periods of static hold were performed to an X65 pipeline steel exposed to a near-neutral pH solution. It was found that a static hold at the maximum load for one hour immediately after a large depressurization-repressurization cycle (underload cycle) yielded the lowest crack growth rate, which was about one third of that of constant amplitude fatigue without the static hold. Static holds for a period shorter or longer than one hour have yielded higher crack growth rates. This observation can be applied to field pipelines during operations to retard crack propagation.
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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".