Blunt Crack Initiation and its Transition to Sharp Cracks in Pipeline Steel in Near-Neutral pH Solution
Bibliographic record
Abstract
This paper reviews our research into pipeline stress corrosion cracking (SCC) in near-neutral pH (NNpH) environment to help understand the mechanisms on pit-to-crack transition and early growth to contribute to pipeline integrity management so that the risk of failure can be avoid or reduced. Pitted specimens by using two different techniques (passivation/immersion and electrochemical methods) were cyclically loaded in NNpH environment sparged with 5% CO2 / balance N2 gas mixture at high stress ratios (minimum stress/maximum stress), low strain rates and low frequencies which are close to the operational pipelines in the field. Blunt cracks initiation was seen first and associated with the pit geometry, and most of the blunt cracks were observed to have initiated from the corrosion pits that had the pit depth to surface width aspect ratios greater than 0.5. The blunt crack growth was engendered by anodic dissolution, which was facilitated by stress. So it was called as stress facilitated dissolution crack growth. These blunt cracks had considerably large crack tip width to crack mouth width aspect ratios, and the majority were below 0.5 to 0.6 mm deep, and considered dormant. Once cracks surpassed the critical value, around 0.5 to 0.6 mm, the cracks would be reactivated and the crack tip width to crack mouth width ratios became significantly smaller. Meanwhile, more hydrogen would be trapped in the plastic zones. Thus, hydrogen would play an important role in the crack propagation. So in this stage, cracks tended to become sharp and the mechanism was referred to hydrogen facilitated cracking. The observations from the field can be interpreted very well by using the proposed models. It was proposed that two different mechanisms are responsible for the early-stage crack growth and sharp cracks be removed to reduce the risk of failure in pipelines.
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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".