A review of crack growth models for near-neutral pH stress corrosion cracking on oil and gas pipelines
Bibliographic record
Abstract
This paper presents a review of four existing growth models for near-neutral pH stress corrosion cracking (NNpHSCC) defects on buried oil and gas pipelines: Chen et al.'s model, two models developed at the Southwest Research Institute (SwRI) and Xing et al.'s model. All four models consider corrosion fatigue enhanced by hydrogen embrittlement as the main growth mechanism for NNpHSCC. The predictive accuracy of these growth models is investigated based on 39 crack growth rates obtained from full-scale tests conducted at the CanmetMATERIALS of Natural Resources Canada of pipe specimens that are in contact with NNpH soils and subjected to cyclic internal pressures. The comparison of the observed and predicted crack growth rates indicates that the hydrogen-enhanced decohesion (HEDE) component of Xing et al.'s model leads to on average reasonably accurate predictions with the corresponding mean and coefficient of variation (COV) of the observed-to-predicted ratios being 1.06 and 61.2%, respectively. The predictive accuracy of the other three models are markedly poorer. The analysis results suggest that further research is needed to improve existing growth models or develop new growth models to facilitate the pipeline integrity management practice with respect to NNpHSCC.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".