Control strategies for a distributed active acoustic skin
Bibliographic record
Abstract
New miniaturization and integration capabilities made available from the emerging MEMS technology allow for the design of artificial linings involving distribution of a large number of elementary cells, that may be composed of loudspeakers and microphones. These smart materials pose the challenge of developing new control strategies to engineer target acoustical impedances, in order to control acoustic fields. This paper investigates the acoustical capabilities of such a distributed active acoustic skin by comparing two control strategies. The first approach is based on local control, where each loudspeaker is current-driven, using a current-pressure transfer function which is designed according to a target acoustic impedance. In the second approach, a distributed control system is implemented such that acoustic waves cannot propagate in a certain direction. Numerical results demonstrate how a well-controlled active skin can substantially modify sound transmission along a waveguide. In this study, each strategy is characterized in terms of efficiency, frequency bandwidth, and robustness. Finally, design parameters for a future prototype are proposed.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".