Decoupled Analysis of a Multi-Layer Flexible Pipeline Buried in Clay Subjected to Large Lateral Soil Displacement
Bibliographic record
Abstract
Multilayered flexible subsea pipelines may experience significant lateral movements due to manmade and environmental geohazards. These pipelines incorporate several structural and protective layers to resist different loads, and may require additional protection such as trenching, rock placement, or burial. In practice, simplifications are considered due to the complexities and uncertainties involved in the multi-layer pipe structure and the surrounding soil, compromising the pipe structure or the soil behavior. These simplifications are applied either on the pipe by assuming a rigid section or on the soil by representing it as elastic springs, which may result in inaccuracies. This study proposes a decoupled methodology combining the Coupled Eulerian–Lagrangian (CEL) model for soil displacement with a small-strain finite element analysis of the flexible pipe. This approach aims to accurately capture cross-sectional deformations and local stresses due to soil movement while maintaining reasonable computational effort. A parametric analysis was conducted to assess the impact of several variables on failure risk. The deformed cross-section was then used for a collapse analysis to determine critical loads at maximum operational depth. The study showed that modeling parameters such as soil strength and internal diameter might significantly influence pipe failure and the risk of collapse.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".