Sedimentation in particle-laden flows with and without velocity shear
Bibliographic record
Abstract
The vertical transport of sediment from particle-laden flows in marine settings can be enhanced by a settling-driven convective instability. The presence of a horizontal velocity shear can further influence this vertical transport. We conduct numerical simulations to investigate the vertical sediment transport in the presence and absence of shear. We show how this transport is determined by a competition between the growth of the settling-driven convective instability (Rayleigh–Taylor) and the stratified shear instability (Kelvin–Helmholtz). In the absence of shear, the Rayleigh–Taylor instability drives enhanced vertical sediment transport; this effect increases with the Stokes settling velocity of the particles and decreases with the stratification strength. In the presence of shear, there are two regimes of effective settling. When the Kelvin–Helmholtz instability grows rapidly and suppresses the Rayleigh–Taylor instability, the effective settling velocity is significantly reduced. On the other hand, if the Rayleigh–Taylor instability dominates and completely inhibits the Kelvin–Helmholtz instability, the effective settling velocity is enhanced due to the additional energy input by shear. We explore the parameter space of these regimes and interpret their physics.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".