Update of Understanding of Near-Neutral pH SCC Crack Growth Mechanisms and Development of Pipe-Online Software for Pipeline Integrity Management
Bibliographic record
Abstract
This paper is aimed to introduce Pipe-Online Software that has been developed recently for crack growth and remaining service life prediction for pipelines experiencing near-neutral pH stress corrosion cracking and corrosion fatigue. The software was developed based on the latest understanding of the physical, chemical and mechanical processes involved during crack initiation, early crack growth and coalescence, and stage II crack growth. In each stage of cracking, governing equations were established based on extensive experimental simulations under realistic conditions found during pipeline operation in the field and vast amounts of field data collected, which include pipeline steel properties, crack geometries, field environmental conditions, Supervisory Control and Data Acquisition (SCADA) data of oil and gas pipelines. The model has considered a wide range of conditions that could lead to the crack initiation, crack dormancy and crack transition from a dormant state to active growth. It is concluded that the premature rupture caused by stress cracking at a service life of about 20–30 years commonly found during field operation could take place only when all the worst conditions responsible for crack initiation and growth have been realized concurrently at the site of rupture. This also explains the reason why over 95% of near-neutral pH cracks remain harmless, while about 1% of them become a threat to the integrity of pipeline steels. It has been found that crack initiation and early stage crack growth are primarily caused by the direct dissolution of steels at constrained areas. The rate of dissolution can be high at the pipe surface because of various galvanic effects, but decreases to a low value as the cracks approach a depth of ∼ 1.0 mm, leading to a state of dormancy as generally observed in the field. In stage II crack growth, the software has considered loading interactions occurring during oil and gas pipeline operations with underload-type variable pressure fluctuations. The software has provided predicted lifetimes that are comparable to the actual service lives found in the field. This forms a sharp contrast with the predictions made by existing methods that are generally conservative or inconsistent with the field observations.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".