A 3-Dimensional Continuum ALE Model for Ice Scour: Study of Trench Effects
Bibliographic record
Abstract
A new Arbitrary Lagrangian Eulerian (ALE) Finite Element (FE) model of ice scour was recently developed by the authors. It is based on continuum representation of the soil. It was shown in recent papers that such a model can characterize the mechanics of the ice-soil-pipeline interaction without requiring any of the assumptions that the Winkler models depend on. The model utilizes soil properties obtained by conventional laboratory testing. In a recent paper, this model was used to show that the subscour deformations and ice-soil interaction forces are very sensitive to ice ridge geometries for shallow slope ice features. In this paper, the ALE FE ice scour model is utilized to study the effects of the pipeline trench on the scour process and the forces transmitted to the pipeline. Two different infill soil properties and two different ice ridge geometries are analyzed with a 36 inch diameter pipe buried to in a trench of 1.5 m cover. It is shown that the scour process near and in the trench is significantly different than in the ambient seabed soils and the recognition of this may present some potential advantages for the protection of the pipelines not recognized by the Winkler models. It is also shown that the pipeline loads generated during the scour process are cyclic. They build slowly as the ice moves over the trench and then reverse as the ice ridge moves away from the trench. This is in contrast to monotonic and rapidly growing loads predicted by the Winkler models. The paper shows that the loads transferred to the pipeline depend on the infill soil properties placed in the trench. It is shown that loads experienced by the pipeline are less for the softer infill than stiffer soils.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| 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".