A First Step Towards the Development of a Pipeline Wrinkle Material Ultimate Limit State
Bibliographic record
Abstract
While the formation of a wrinkle in an onshore pipeline is an undesirable event, in many instances this event does not have immediate pipeline integrity implications. The magnitude or severity of a wrinkle formed due to displacement controlled loading processes (e.g. slope movement, fault displacement, frost heave and thaw settlement) may increase with time, eventually causing serviceability concerns (e.g. fluid flow or inspection restrictions). Pipe wall damage leading to cracking and eventually a loss of containment involves contributions from the wrinkle formation and growth processes, as well as, wrinkle deformations promoted by in-service line pressure, temperature and seasonal soil displacements. The objective of this paper is to provide an overview of the ongoing research efforts, sponsored by TransCanada PipeLines Ltd. and Tokyo Gas Co. Ltd., towards the development of a mechanics based wrinkle ultimate limits state that may be used in future to evaluate the long term integrity of wrinkled pipeline segments. The research efforts include non-linear finite element modeling to demonstrate the ability of experimentally derived material properties to predict the formation of through wall cracking induced by high and low frequency load effects. This paper outlines the material testing program used to support the development of failure criteria capable of considering the contributions of monotonic deformation, as well as, high and low cycle cyclic loading.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".