Fatigue Crack Growth Assessment of Pipeline Steels and Girth Welds
Bibliographic record
Abstract
Abstract Fatigue test specimens were prepared and tested with an API 5L X70 spiral welded pipe steel and girth weld. For a few selected specimens, two unloading compliance techniques (elastic compliance and back-face strain compliance) were applied simultaneously to a single specimen for direct comparisons of in-situ crack size estimation. This paper also includes fatigue crack growth rate (FCGR) data of other pipe steels and welds available in the literature. It was observed that most FCGR curves of pipeline steels (X65∼X100) remained within the BS 7910 mean and upper bound design curves in the Paris region. On the contrary, the fatigue crack growth rate of the X42 pipeline steel from a reference was high — a very steep slope of the FCGR curve, crossing over the BS 7910 design criteria. It was noted that the FCGR of austenitic stainless pipe steel and girth weld obtained from Arora et al. (2014) showed a very excellent fatigue property.
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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 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".