Assessment of the Complexity of Stress/Strain Conditions of X100 Steel Pipeline and the Effect on the Steel Corrosion and Failure Pressure Prediction
Bibliographic record
Abstract
In this work, a finite element (FE) model was developed to simulate the complex stress/strain conditions potentially exerted on the northern pipelines due to the synergism of internal pressure, soil strain and local stress/strain concentration at corrosion defects. The effects of pre-strain on corrosion of the steel and the pipeline failure pressure were investigated. Results demonstrated that a high intensity stress/strain field generates preferentially at the bottom of corrosion defect. The increase of operating pressure would increase the stress concentration at defect and the plastically deformed area. Both tensile and compressive soil strains increase the stress intensity and plastic deformation. Thus, a pipe containing corrosion defects or mechanical dents is susceptible to hoop cracking or local bulking under the tensile and compressive soil strains, respectively. Moreover, while an elastic strain enhances slightly the steel corrosion, the effect of plastic strain is much remarkable. In optimal pipeline design, the reliable risk assessment of high-strength steel pipelines should consider the corrosion enhancement and defect propagation under the complex stress/strain conditions.
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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) | 0.001 | 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 | 0.001 | 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".