Environmental Cracking of X-60 Pipeline Steel
Bibliographic record
Abstract
Abstract Environmentally assisted crack (EAC) growth mechanisms affecting the external surface of API X-60 pipeline steel has been investigated. Low frequency cyclic tests at 4.63x10−4 Hz were conducted in simulated groundwater (NS4 solution) under near neutral (pH ≈7) conditions, similar to those for buried natural gas pipelines. The crack morphology and amount of growth were determined for two stress ratios, R (minimum/maximum stress) 0.5 and 0, at Kmax=25.5 MPa√m under both constant and variable amplitude loading conditions. Examination of EAC was carried out using optical, scanning electron, focused ion beam (FIB) and transmission electron microscopy. Transgranular stress corrosion cracking (SCC) occurred at the higher R-ratio of 0.5. The crack was relatively wide, filled with corrosion product. By contrast, corrosion fatigue had taken place at R=0. The crack was also transcrystalline. Its tip was extremely sharp, and the amount of growth was greater. For the sample subjected to variable amplitude loading conditions, the crack was less sharp, but significantly sharper than that of the sample under constant load at R=0.5. The crack was open in many places, and the majority of the crack path was transgranular. Applying the superposition model to the variable amplitude test showed that the SCC growth rate accelerated when a single cycle at R=0 was combined with 159 cycles at R=0.5.
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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".