Moving Surface Actuation, Effects of Frequency-based Shear Layer Excitation on the Response of a Bluff Body Wake
Bibliographic record
Abstract
The effect of actuation frequency, using moving surface actuation, is investigated for a square cylinder bluff body wake. Pressure sensor data are used to optimize actuation characteristics through the implementation of an NSGA-II evolutionary algorithm. Velocity field data are obtained using Particle Image Velocimetry (PIV) for baseline and optimized actuation cases. A Proper Orthogonal Decomposition (POD) analysis shows that the vortex shedding frequency shifts between frequencies associated with the actuation, moving between regions of lock-on and quasi-periodicity. Additionally, the POD shows that the energy contained in the coherent shedding motion is reduced through actuation, while the total energy in the velocity field stays relatively constant. A reconstruction of the first 10 POD modes indicates that the coherent contribution to the Reynolds stresses significantly decreases compared to the non-actuated case. The mechanism for drag reduction is investigated using the shed circulation flux and Kochin’s drag formulation model. The drag obtained using PIV measurements and Kochin’s formulation is consistent with trends observed for the base pressure as a function of actuation frequency.
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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".