Feedback control of slowly-varying transient growth by an array of plasma actuators
Bibliographic record
Abstract
Closed-loop feedback control of boundary layer streaks embedded in a laminar boundary layer and experiencing transient growth, which is inherent to bypass boundary layer transition, is experimentally investigated. Streaky disturbances are introduced by a spanwise array of cylindrical roughness elements, and a counter disturbance is provided by a spanwise array of plasma actuators, which are capable of generating spanwise-periodic counter rotating vortices in the boundary layer. Feedback is provided by a spanwise array of shear stress sensors. An input/output model of the system is obtained from measurements of the boundary layer response to steady forcing, and used to design and analyze a proportional-integral controller, which targets a specific spanwise wavenumber of the disturbance. Attention is directed towards a quasi-steady case in which the controller update is slower than the convective time scale. This choice enables addressing issues pertinent to sensing, actuation, and control strategy that are also relevant to the control of unsteady disturbances but without the full complexity of transient effects. The feedback controller and plasma actuators perform well, attenuating the streamwise streaks both in the vicinity of the sensors and farther downstream. The controller remains effective for a range of off-design flow conditions, such as when the free-stream velocity is varied.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".