Finite Element Modelling of Residual Stresses in Flexible Pipe Pressure Armor C Profiles
Bibliographic record
Abstract
Abstract The pressure armor is one of the structural metallic layers of a flexible pipe for offshore application. Its primary function is to resist radial loads, internal to prevent burst, and external to avoid crushing. It is made by a metallic wire wound around the pipe nucleus in a helical shape. That wire can have several shapes, like Z-profiles and C-profiles. During the manufacturing process of flexible pipes, the pressure armor wires are subjected to successive steps of folding and unfolding to achieve the desired final form, which results in residual stresses in the wire. The pipe is submitted to the so-called Factory Acceptance Test (FAT) to alleviate the residual stress, where a substantial internal pressure is applied and removed. The final stress field then must be considered in further mechanical analysis. This paper is a sequence of previously published work on the conforming process for Z-shaped pressure armors and presents the conforming process of C-shaped profile armors. Some differences in the process are highlighted throughout the text. The paper focuses on a developed finite element model to simulate all the necessary conforming process, besides the internal pressure application and removal during the FAT, for a C-shaped pressure armor profile. Throughout the article, details of the modeling, the applied boundary conditions, and loads are shown, as well as the achieved results.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".