Experimental Study on Low Cycle Fatigue Behaviours of Wrinkled Pipes
Bibliographic record
Abstract
Buried pipelines can be locally buckled (wrinkled) by a load combination of axial deformations and rotations. Previous test results show that those wrinkled pipes do not lose their safety and integrity if they possess sufficient ductility. However, if those wrinkled pipes are going to continue operating under the condition of cyclic loading, their low cycle fatigue (LCF) behaviours have to be thoroughly investigated. This paper presents LCF tests for two full-scale pipes and the relevant results. Those two pipes were tested under a complicated loading procedure. The entire loading consisted of two stages: the monotonic loading stage and the cyclic loading stage. The monotonic loading was designed to form an enclosed wrinkle around the pipe under a locked curvature, and the cyclic loading was planned to fracture the wrinkled pipe. Firstly, the loading procedure was demonstrated by viewing the spectra of MTS load, MTS stroke, jack load, internal pressure, as well as pipe end average rotation. Secondly, the global behaviour was investigated by examining the relation between bending moment and global curvature, the relation between pivot axial load and relative axial deformation (RAD) between pivots, and the relation between internal pressure and RAD between pivots. Thirdly, the phenomenon of ‘deformation localization’ was studied by investigating the relation between the global RAD and the local RAD, and it was found that the global deformation was totally localized into the wrinkle area. Fourthly, the failure modes were discussed and it was found that the seam weld was more liable to be fractured under the condition of cyclic axial deformation. At last, the failure mechanism was investigated by macroscopically examining fracture surfaces. It found out that the cracks initiated from multi-locations on surfaces, then those cracks propagated from surfaces into the interior and finally fractured the pipe wall. Moreover, it found out that more damage was generated from the inside surface than from the outside surface.
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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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".