Numerical Investigation of Pressure-Cycling-Induced Fatigue Failure of Wrinkled Energy Pipelines
Bibliographic record
Abstract
Abstract Wrinkle defects can be complex pipeline deformities to assess and can present the potential to initiate a pipeline release incident as a result of fatigue failure due to pressure cycling, if not dealt with accordingly. Specifically, the stress distribution arising due to applied loads such as internal pressure can vary rapidly due to the complex shape along the wrinkle profile, which may introduce complexities in subsequent assessments such as fatigue life analysis. This paper presents a methodology using numerical simulation for evaluating stress concentration factors of wrinkle defects of varying geometries. A nonlinear finite element model is developed to evaluate stress concentration factors induced by wrinkle defects within steel pipelines subjected to internal pressure. Afterward, data from full-scale laboratory tests for the wrinkled pipe specimens subjected to cyclic pressure fatigue loading are analyzed to evaluate stress concentration factors for comparable wrinkle profiles. Lastly, a comparison between the results of the stress concentration factors evaluated using the finite element method and test data is provided, followed by a brief discussion of potential sources of discrepancies between results obtained from these methods.
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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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".