Finite element modeling of partially embedded pipelines in clay seabed using Coupled Eulerian–Lagrangian method
Bibliographic record
Abstract
Vertical seabed penetration and lateral movement of deep-water offshore pipelines are simulated using the Coupled Eulerian–Lagrangian (CEL) approach in Abaqus finite element (FE) software. Abaqus CEL has been used in some previous studies to simulate large-deformation behavior of offshore pipelines; however, the effects of strain rate and strain-softening on undrained shear strength (su) have not been considered. In this study, the effects of these factors are critically examined. The available built-in models in Abaqus CEL cannot account for these factors directly, especially the strain rate; therefore, the development of user subroutines is required. In the present study, a simple but realistic soil constitutive model (published by Zhou and Randolph in 2007) that considers the effects of strain rate and strain-softening on su is implemented in Abaqus CEL. The effects of FE mesh size and shear band formation on penetration resistance are discussed based on a comprehensive FE simulation. Lateral analyses are performed for “light” and “heavy” pipes in clay seabed having a linearly increasing undrained shear strength profile for smooth and rough pipe–soil interface conditions. The FE results are compared with previous theoretical, numerical, and centrifuge test results. Based on the present FE analyses, it is shown that, similar to the remeshing and interpolation techniques with small strain (RITSS) technique developed at the The University of Western Australia, the Abaqus CEL can successfully simulate the response of partially embedded pipelines in deep-water clay seabed, provided strain rate and softening dependent clay models are implemented. A methodology to implement such a model using Abaqus user subroutine is also presented.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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) | 0.002 | 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".