Bibliographic record
Abstract
The classical gravitational instability of a layer of denser fluid overlying a layer of less dense fluid, commonly known as the Rayleigh-Taylor instability, has been studied for well over a hundred years. In this article, we present the results of numerical simulations of a variant of this instability in which a plug of dense fluid is released from rest in a thin channel between two flat, vertical walls, causing a downward acceleration of the entire fluid column and formation of boundary layers near the walls. The plug of dense fluid undergoes distinctly different evolution near the walls and in the fluid interior. The instability in the interior, which we label the “hammerhead” instability based on its shape, is robust over a range of physical parameters, but disappears below a threshold Schmidt number. Fluid near the wall is slowed, and thin tendrils that link the near wall fluid to the main body of the fluid plug form, and in some cases undergo their own instability. We characterize the fully three-dimensionalized state, finding that while bulk measures of kinetic energy three-dimensionalization do not discriminate between low and high Schmidt number cases, the geometric distributions of the dynamical parameters Q and R from the turbulence literature are profoundly different in the high Schmidt number case. Finally, we consider the role of shear in situations in which the two plates are not exactly vertical, demonstrating that shear diminishes the importance of three-dimensionalization, while the hammerhead instability remains relevant.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.199 | 0.492 |
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".