Experiments and reduced order modeling of symmetry breaking in Rayleigh-Taylor mixing
Bibliographic record
Abstract
We report the observation of asymmetrical fingering instabilities unfolding across an upward-moving dissolution interface while downward fingers also evolve. We tackled complexities characterized by large viscosity ratios (M) and Rayleigh (Ra) numbers - phenomena often challenging to replicate experimentally and simulate numerically. We present our Rayleigh-Taylor mixing experiments conducted at a substantial viscosity ratio (M$\ensuremath{\approx}5\ifmmode\times\else\texttimes\fi{}{10}^{5}$) and high Rayleigh numbers (Ra~${10}^{5}\ensuremath{-}3\ifmmode\times\else\texttimes\fi{}{10}^{6}$). Our experiments have confirmed the emergence of asymmetric growth in fingering instabilities along an upward-moving interface, accompanied by significant downward finger evolution.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".