Bibliographic record
Abstract
The purpose of this study is to examine the strongly rotating limit of a turbulent flow theoretically and numerically. The goal is to verify the predictions of asymptotic theories. Given the limitations of experimental and dissipative numerical approaches to this problem, we use classical equilibrium statistical mechanics. We apply the statistical mechanics approach to the inviscid truncated model of strongly rotating turbulence (in the small Rossby number range) and derive the theoretical spectra of the decoupled model. We use numerical simulations to complement these derivations and examine the relaxation to equilibrium of the inviscid unforced truncated rotating turbulent system for different sets of initial conditions. We separate our discussion into two time domains: the discussion of the decoupled phase with time below a threshold time t⋆, for which a new set of invariants S are identified, and the coupled phase with a time beyond t⋆, for which the quantities S are no longer invariants. We obtain a numerical evaluation of t⋆ which is coherent with the theoretical asymptotic expansions. We examine if the quantities S play a constraining role on the coupled dynamics beyond t>t⋆. We find that the theoretical statistical predictions in the decoupled phase capture the horizontal dynamics of the flow. In the coupled phase, the invariants S are found to still play a constraining role on the short-timescale horizontal dynamics of the flow. These results are discussed in the larger context of previous rotating turbulence studies.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".