Relationship Between Yield Strength and Near-Neutral pH Stress Corrosion Cracking Resistance of Pipeline Steels—An Effect of Microstructure
Bibliographic record
Abstract
In this paper the relationship between the near-neutral pH stress corrosion cracking (SCC) resistance and the yield strength of pipeline steels was investigated and an attempt was made to understand the microstructural effect on such a relationship. Pipeline steels ranging from X52 to X100 steels and the weldments of X70 and X65 were adopted as the test materials and various heat treatments were used to achieve different microstructures and strength levels. The results indicate that the near-neutral pH SCC resistance of pipeline steel is reduced, generally, with an increase in the strength level, but the strength dependence of SCC resistance is heavily affected by the microstructures of the pipeline steels. The steels with a fine-grained, bainite-ferrite structure possess a much better combination of strength and SCC resistance than those with a ferrite + pearlite structure. However, the introduction of the welding process will significantly degrade SCC resistance in the steels containing a bainitic ferrite structure. This degradation effect is caused mainly by the decomposition of the bainitic ferrite structure into a separate microstructural entity. On the other hand, an increase in the pearlite content in the microstructure has a detrimental effect on the SCC resistance of pipeline steels with a ferrite + pearlite structure. The experimental results indicate that the SCC resistance of the pipeline steels in the near-neutral pH environment can be approximately correlated to the polarization resistance with a linear relation. This relationship is used to evaluate the microstructure effect of weldments on the SCC resistance. The applicability of this method is discussed briefly.
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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 | 0.000 | 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".