A simple technique for the visualisation of eddy kinematics in turbulent flows
Bibliographic record
Abstract
We developed and tested a simple technique to predict, for flow visualisation purposes only, the evolution of coherent structures in between two given realisations of a turbulent flow. Classic coherent-structure eduction methods are adopted, such as the Q-criterion, pressure fluctuations and contours of velocity fluctuations. The kinematics of the evolving structures are reconstructed by means of an advection-based reconstruction technique and captured in a movie. The resulting quality of the animations has been assessed via the Structural Similarity Index (SSIM). The sensitivity to increasing spacing in time of the available flow realisations has been tested and several improvements implemented. The abrupt transition from reconstructed frames of the animation to the available realisations results in a noticeable lack of smoothness. The replacement of the available realisations with a similar advection-based average increases the perceived smoothness of the movies. This is confirmed by the reduced total variation of the SSIM index. The residual minor periodic variations of accuracy have been reduced by introducing a stochastic weighting function. The sensitivity of the results to changes in Reynolds number, resolution and structure representation methods has been tested.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".