Particle Image Velocimetry And Scaling Of Mach 0.3 And 1.25 Axisymmetric Turbulent Jets
Bibliographic record
Abstract
The influence of compressibility on the scaling of the Reynolds stress transport (RST) budgets is investigated for Mach 0.3 and Mach 1.25 free axisymmetric turbulent jets using particle image velocimetry (PIV). It is proposed that the RST equations can be shown in self-preserving form scaled by the local streamwise evolving spreading rate, b’. It is shown that b’ is a function of the local convective Mach number, M_c. Compressibility effects on the suppression of the Reynolds stresses and higher turbulence moments are detailed. From self-preservation principles, the budgets scaled by powers of b’. In this form, most terms in the budgets are scaled appropriately indicating self-preservation. Terms which are not properly scaled are isolated then which allows for insight on effects of compressibility on turbulence.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".