Numerical Modelling of Pipeline Lateral Resistance in Rock Berms
Bibliographic record
Abstract
Abstract Rock berms are used for many different offshore pipeline applications such as protection from anchors and trawlers, mitigation against pipeline global buckling and improvement of pipelines on-bottom stability. Understanding the lateral resistance provided by rock berms to pipelines is essential for all the above applications. This paper presents insights into lateral resistance of rock berms restraining pipelines by finite element analyses. Pipelines of various diameters (0.2 m-1.5 m) within typical rock berm geometries were modelled in PLAXIS 2D to evaluate the peak lateral resistance provided by the rock berm to the pipe. The finite element model was validated against available full-scale test data. The results of the numerical analyses demonstrate that the peak lateral resistance of a pipeline in rock berm depends mainly on the unit weight and the frictional properties of the rock, while the mobilization to reach the peak resistance is dependent on the rock berm stiffness. Based on the results from this study, a simplified design chart is presented which provides the lower bound peak lateral resistance for a given pipe diameter under typical rock berm with cover to top of pipe in the range of 0.3 m to 1 m. This design chart could be used by engineers undertaking preliminary design assessment of pipelines in rock berms.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".