Reactive control of isolated unsteady streaks in a laminar boundary layer
Bibliographic record
Abstract
This study is motivated by controlling transient growth and subsequent bypass transition of the laminar boundary layer to turbulence. In experiments employing a model problem, an active roughness element is used to introduce steady/unsteady streak disturbances in a Blasius boundary layer. This tractable arrangement enables a systematic investigation of the evolution of the disturbances and of potential methods to control them in real time. The control strategy utilizes wall-shear-stress sensors, upstream and downstream of a plasma actuator, as inputs to a model-based controller. The controller is designed using empirical input/output data to determine the parameters of simple models, approximating the boundary layer dynamics. The models are used to tune feedforward and feedback controllers. The control effect is examined over a range of roughness-element heights, free stream velocities, feedback sensor positions, unsteady disturbance frequencies and control strategies; and is found to nearly completely cancel the steady-state disturbance at the downstream sensor location. The control of unsteady disturbances exhibits a limited bandwidth of less than 1.3 Hz. However, concurrent modelling demonstrates that substantially higher bandwidth is achievable by improving the feedforward controller and/or optimizing the feedback sensor location. Moreover, the model analysis shows that the difference in the convective time delay of the roughness- and actuator-induced disturbances over the control domain must be known with high accuracy for effective feedforward control. This poses a limitation for control effectiveness in a stochastic environment, such as in bypass transition beneath a turbulent free stream; nonetheless, feedback can remedy some of this limitation.
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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 | 0.000 |
| 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 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".