Hydrogen Effects on High Strength Pipeline Steels
Bibliographic record
Abstract
Abstract High strength pipeline steels are currently being considered for new construction and line extensions for economic reasons. These steels are designed for high strength and high toughness for fracture resistance. In this investigation, the electrochemical behavior, hydrogen permeation and hydrogen effect on mechanical properties were investigated. The testing was designed to simulate corrosion and hydrogen generation around the high strength steel (X100) under permafrost condition, with the comparison to the regular pipeline steel (X65 steel). Temperature is found to be an important parameter influencing the polarization resistance, solution resistance, hydrogen generation and the effect of hydrogen on the mechanical properties. For both X100 and X65 steels, polarization resistance is low and similar in values at temperatures above the freezing point, while increasing more than ten (10) times with only 4°C difference from 1°C to -3°C. In general these two steels behave similarly in terms of electrochemical properties for all the temperature spectra. Under freely corroding conditions, the generation rate of hydrogen is small. The application of cathodic protection increases the generation of hydrogen, especially at temperatures above the freezing point. As a result, both steels became less ductile with increasing cathodic polarization. However for the condition of permafrost or temperature lower than 20°C, the ductility loss of X100 steel due to hydrogen permeation is comparable to that of X65 steel. This suggests that the use of X100 steel pipe should not result in additional problems associated with hydrogen embrittlement or cracking as a result of cathodic protection application.
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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".