Targeted turbulent structure control in wall-bounded flows via localized heating
Bibliographic record
Abstract
A targeted turbulent flow control strategy, based on selective heating of streamwise-aligned heat strips, is assessed for drag reduction using direct numerical simulations of variable viscosity and compressible turbulent channel flows. As increasing the temperature of a gas increases its viscosity, heating is generally an unfavorable drag mitigation approach. However, through a selective spatial arrangement of the heating array, the slight increase in viscosity and decrease in density can serve to modify the organization of the streamwise-aligned structures and the likelihood of the ejection and sweep events near the wall. This can, under specific conditions, lead to a very modest drag reduction. The optimal spatial arrangement is identified using a bidimensional empirical mode decomposition and targets the near-wall, large-scale turbulent motion. The drag coefficient, at constant mass flow rate, remains unchanged with heating despite up to an 11% increase in the local viscosity above the heating strips. When accounting for the viscosity variation in the drag reduction calculation, an effective drag reduction of 6% is observed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".