Development of Failure Criteria for Predicting Tearing of Wrinkled Pipe
Bibliographic record
Abstract
Onshore steel pipelines, particularly buried in cold region, often subjected to extreme geo-environmental conditions, where significant inelastic deformation may occur resulting in localized wrinkles. Under continued deformation, there is a possibility of excessive cross-sectional deformation at wrinkle locations, eventually leading to fracture or damage in the pipe wall. A recent field fracture and failed laboratory specimens under monotonic load history address the necessity of conducting a comprehensive research program to better understand this unique failure mode. Initial results have indicated that even under monotonic loading, significant strain reversals can occur at sharp fold of the wrinkle. These strain reversals were identified as one of the key factors to trigger this unique failure mechanism. This paper addresses the development of failure criteria used in the finite element (FE) model of plain pipes subjected to sustained monotonic axial and bending deformation with or without internal pressure. In conjunction with the strain reversal criterion, the critical equivalent plastic strain was used as the fracture or damage initiation limit in the numerical analyses. Results obtained from the full-scale test of an NPS16 pipe were used to calibrate the FE model. Results obtained from the numerical analyses have shown that the proposed criteria predict the onset of fracture at sharp fold of the wrinkle with reasonable accuracy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".