Finite element simulation of seismically induced retrogressive failure of submarine slopes
Bibliographic record
Abstract
Retrogressive failures have been reported for both offshore and onshore slopes subjected to various triggering mechanisms. As a result of large spatial extension of the failure, the retrogression phenomenon leads to significantly increasing damage and may affect facilities located far away from the original slope. The mechanisms of such failures are not fully understood, and reports of analyses are rather scarce. To simulate earthquake-induced retrogressive submarine slope failures and to better understand the mechanisms involved, the element removal capabilities of a finite element program are used to model a soil mass that fails and then flows away, causing upper parts of the slope to fail retrogressively, as a result of the loss of support. It is explained how an initial failure leads to subsequent failures of a flat seafloor. Effects of a shallow silt layer and of a gently sloping seafloor on the extension of retrogression in a sandy seabed are also studied. It is found that the extension of failure increases significantly because of a gentle seafloor slope and (or) the presence of a silt layer.Key words: retrogressive submarine failure, seismic liquefaction, finite elements.
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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) | 0.001 | 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 | 0.001 |
| 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".