Modelling environmentally assisted cracking in pipeline steels
Bibliographic record
Abstract
An investigation has been conducted on the environmentally assisted cracking (EAC) of ferritic-pearlitic pipeline steels in contact with simulated groundwater.The loading and environmental conditions were similar to those for buried natural gas pipelines in service.An anaerobic, dilute near-neutral pH solution was used in conjunction with the open-circuit potential for this system.The intent of this work was to determine and model the growth rate of environmentally assisted cracks in the form of transgranular stress corrosion cracks (TGSCC) that have been observed following field investigations.Combinations of low frequency cycling and high stress ratio R (=minimum load/maximum load), can produce transgranular fracture and a quantitative relationship between these two parameters has been developed for the conditions under which TGSCC takes place.The recorded crack growth rates were similar to those in the field and a superposition model was applied to the experimental data, giving good agreement between the observed and predicted single crack growth rates.Applying the superposition model to operating natural gas pipeline data indicated that more realistic predictions of crack growth would result by considering the interaction of multiple cracks, as observed in the field colonies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 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".