Identifying unstable modes in stratified shear layers
Bibliographic record
Abstract
One interpretation of the mechanism of instability in stratified shear flows is based on the idea that two independently propagating waves may interact to cause mutual growth in one another. This theory is used in the present study to develop a diagnostic that can be used to identify different types of unstable modes. We focus on stratified shear layers that are susceptible to both the Kelvin–Helmholtz (KH) and Holmboe (H) modes of instability—though the formulation is more general. The diagnostic is found to be useful in differentiating between KH and H modes in the symmetric stratified shear layer (where the center of the shear layer and the density interface coincide). The asymmetric stratified shear layer is also examined since there is no clear distinction between KH- and H-type modes in this flow. The KH mechanism of growth is predicted to extend to stronger stratifications (i.e., larger bulk Richardson numbers) than in the symmetric case, in qualitative agreement with nonlinear numerical results. However, the transition is found to be a gradual one in which the KH mechanism gives way to the H as the bulk Richardson number is increased. In order to demonstrate the utility of the method, we apply it to instability observed in the Fraser River estuary.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".