Decay of turbulence generated by a square-fractal-element grid
Bibliographic record
Abstract
Abstract A novel square-fractal-element grid was designed in order to increase the downstream measurement range of fractal grid experiments relative to the largest element of the grid. The grid consists of a series of square fractal elements mounted to a background mesh with spacing $L_0 = 100\, {\rm mm}$ . Measurements were performed in the region $3.5 \le x/L_0 \le 48.5$ , which represents a significant extension to the $x/L_0 < 20$ of previously reported square fractal grid measurements. For the region $x/L_0 \gtrsim 24$ it was found that a power-law decay region following $\langle {q}^2 \rangle \sim (x - x_0)^m$ exists with decay exponents of $m = -1.39$ and $-1.37$ at $\mathit{Re}_{L_0} = 57\, 000$ and $65\, 000$ , respectively. This agrees with decay values previously measured for regular grids ( $-1 \gtrsim m \gtrsim -1.4$ ). The turbulence in the near-grid region, $x/L_0 < 20$ , is shown to be inhomogeneous and anisotropic, in apparent contrast with previous fractal grid measurements. Nonetheless, power-law fits to the decay of turbulent kinetic energy in this region result in $m = -2.79$ , similar to $m \approx -2.5$ recently reported by Valente & Vassilicos ( J. Fluid Mech. , vol. 687, 2011, pp. 300–340) for space-filling square fractals. It was also found that $C_\epsilon $ is approximately constant for $x/L_0 \ge 25$ , while it grows rapidly for $x/L_0 < 20$ . These results reconcile previous fractal-generated turbulence measurements with classical grid turbulence measurements.
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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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".