The effects of near-bottom stratification on internal wave induced instabilities in the boundary layer
Bibliographic record
Abstract
Large amplitude internal waves in naturally occurring stratified fluids induce currents throughout the water column and hence have the potential to drive instability, and turbulent transition within, and hence material exchange across the bottom boundary layer. In the presence of broad, small amplitude topography, waves of depression have been shown to induce a vortex roll-up instability that has the potential for cross-bottom boundary layer transport through the generation of coherent vortices. At the same time, the three-dimensionalization associated with the instability is weak. We demonstrate that the presence of a near-bottom stratification provides a means for an enhanced rate of three-dimensionalization. For solitary waves of elevation, which do not yield a coherent response in the absence of a near-bottom stratification, the presence of a near-bottom stratification leads to a local hydraulic response, or a gravity-current-like intrusion, as the wave passes over the topography. This feature forms on the lee slope of the topography, propagates with the wave for some time, and provides a coherent pathway for material to be transported a distance of 1.5 times the topography amplitude into the water column in laboratory-scale simulations. Evidence of coherent structures in the turbulent flow in this region is presented.
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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) | 0.000 | 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 | 0.001 |
| 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".