The Peak Impact Force of Landslide-Induced Turbidity Current on Pipelines Above the Seabed
Bibliographic record
Abstract
Abstract Submarine landslides pose significant risks to undersea pipelines and cables due to the intense impact forces generated by gravity-driven currents. This study examines the forces exerted by non-Boussinesq gravity currents generated by the sudden release of mudflow with a large density difference from its ambient to simulate the typical landslide conditions. Large-eddy simulations (LES) are performed for various landslide scenarios. The gravity current is produced by the sudden removal of a dam of height H and reservoir length L. The simulations determine the transient variations of the drag, lift, and total force coefficients on a cylinder above the seabed for reservoir length-to-height ratios L/H ranging from 0.125 to 5.93 and a density difference of (ρs - ρa)/ρa = 0.5 and 1. The results show the advancing front is a gravity current head connecting to the body of the current through a neck region where the velocity is greater than the frontal velocity. The impact force rises sharply upon the arrival of the gravity-current head, with a secondary peak observed in certain scenarios due to the passage of the greater velocity through the neck. For the release from a small reservoir, the peak impact force depends critically on the cylinder position associated with the maximum current through the neck. Conversely, with a sufficiently large volume of release, the impact force becomes insensitive to the cylinder’s position. We have determined the peak drag and lift coefficients, normalizing the forces by the gravity-driven pressure and correlated the coefficients’ values with the volume of the releases. These correlations of the impact force to the gravity-driven pressure and the size of the submarine landslide have provided a more precise evaluation of the landslides’ impact on the design and safety assessment of undersea pipelines and cables exposed to the gravity current.
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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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".